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Impact of Critical Success Factors on Project Success Through the Mediation of Knowledge Creation

Saira naseer, kashif abbass, muhammad asif, hammad bin azam hashmi, sidra naseer, monica violeta achim.

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Edited by: Yenchun Jim Wu, National Taiwan Normal University, Taiwan

Reviewed by: Umair Ahmed, Arab Open University, Bahrain; Muhammad Shamrooz Aslam, Guangxi University of Science and Technology, China; Syed Ahmed, Harbin Institute of Technology, China

*Correspondence: Monica Violeta Achim [email protected]

This article was submitted to Organizational Psychology, a section of the journal Frontiers in Psychology

Received 2022 Mar 14; Accepted 2022 May 2; Collection date 2022.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Several factors affect health project success. This research aims to examine the impact of critical success factors on health project success and show how the essential factors of success interact with knowledge creation to impact health project success. The self-administered questionnaire was distributed to collect data from 246 managers, supervisors and zonal supervisors of DHQ hospital Attock and PIMS hospital Islamabad. The analysis was done using Smart PLS to understand the effect of exogenous variables over endogenous variables and the impact of mediating variables between two constructs. The results show that all critical success factors (MGTRF, DRF, CRF, PMRF, CLRF) are significantly affecting project success, in addition, tacit knowledge creation mediate the association between critical success factors and project success. In contrast, explicit knowledge creation does not mediate the relationship between critical success factors and project success. This study intends to expand the theoretical understanding of process improvement by providing practical insights into the impact of strategies used by project managers to develop new knowledge by capturing explicit and implicit information. This study also reinforces past findings and increases awareness about using knowledge creation to gain a competitive advantage in the health sector.

Keywords: health project success, critical success factors, knowledge creation, project, success

Introduction

According to a Pakistan economic review (2017–18), the government spends 0.35% of its total GDP on health care. There are currently 5,382 clinics, 1,207 hospitals, 5,404 basic health care units, and 696 child care and maternity units in Pakistan. However, Pakistan faces major health concerns due to poor and unfavorable health circumstances. According to Khan and Van Den Heuvel ( 2006 ), numerous governments in Pakistan have worked on health programmes, but the benchmark has not yet been set due to various internal factors. Pakistan also announced the “National Health Policy” last year, aiming to improve society's better health conditions. Policymakers and top management may not take health project success seriously, limiting health development in Pakistan. To resolve the above issues, the government needs to consciously take part in health issues and look at every step to complete the health services. Sheikh and Jensen ( 2019 ) results indicate that due to the poor health conditions in Pakistan, it has to suffer from various diseases in routine life. The population appears as a genetic problem on the international level; the global world focuses on genetic disorders due to health issues, how can reduce genetic diseases, and what measures are required to cope with them. According to Habib et al. ( 2017 ), polio teams are attacked by terrorists due to security concerns; thus, hospitals must take sufficient precautions for such treatments. Good planning is only possible when top management is fully aware of the issue, and knowledge gained from experience.

Knowledge has played an important role in the success of projects and is the key to innovation and competitiveness for an organization (Canonico et al., 2019 ; Yang et al., 2021 ). Studies have shown that employees working on a project acquire new knowledge (both explicit and tacit) from their encounters (Todorović et al., 2015 ). Excellent performance and greater project success could be achieved after creating and utilizing knowledge in the product, business process, and services. Knowledge, both explicit and tacit about the previous project leads to project success. Tactic knowledge is created through discussions with stakeholders, office colleagues, project partners, consultants, and experts. Values, beliefs, assumptions, and mental models comprise tacit knowledge. While explicit knowledge is codified, implicit knowledge is not.

A database, web pages, emails, and documents store explicit knowledge (Boon Sin et al., 2015 ). Whenever a problem arises in the project, it is necessary to schedule sessions with a professional. Professionals and experts share ideas with employees. Professionals acquire insights from documented information and use that knowledge for problem resolution (Canonico et al., 2019 ). Similarly, Japanese car manufacturing creates competitive advantage and innovation dynamically by using Nonaka et al. ( 2000 ) SECI model (Allal-Chérif and Makhlouf, 2016 ). We can also use this theoretical framework in health projects to analyze knowledge creation practices because health project has an important and huge impact on the nation (Sheikh and Jensen, 2019 ). This study is based on Nonaka theory. This study also expands the model of Todorović et al. ( 2015 ) by introducing knowledge creation as a mediator and project success (customer happiness) as a dependent variable. The project's effectiveness has been extensively discussed in the literature, but more research is needed to uncover the most influential CSFs that influence health project success (Kiani Mavi and Standing, 2018b ; Maqbool and Sudong, 2018 ). The study investigates “the impact of CSFs on project success via knowledge creation mediation” (Todorović et al., 2015 ).

This study intends to achieve the following objective;

To determine the effect of critical success factors on project success.

To determine the effect of knowledge creation on project success.

To determine the mediating role of tacit knowledge creation between the critical success factors and project success.

To determine the mediating role of explicit knowledge creation between the critical success factors and project success.

To achieve the above objectives, this study focuses on the following issues.

Is the critical success factors having an impact on project success?

Is knowledge creation significantly related to project success?

Does tacit knowledge creation mediate the effect of critical success factors on project success?

Does explicit knowledge creation mediate the effect of critical success factors on project success?

Significance of the Study

In this research we will find all those critical success factors that are leading project toward success. CSFs are those few area of activity that is actually causing the success of the project. These CSFs have been used in many industries before, like manufacturing industry, construction industry, information system and financial service, etc. the intensity and magnitude of different factors have been identified by different researchers, but in this study we will examine that how many and in which degree these factors are influencing a project's success. According to their importance we will also take an order of these factors. We will also examine that how the tacit and explicit dimension of knowledge creation positively influence between CSFs (MGT, Procurement, Manager, Contractor, and Stakeholder related factors) of project success. In the concluding part of the study a clearer picture has been developed that highlights the factors and their relationship with project success in accordance with the local industry view points. Through this research manager come to know about CSFs factors which affect the project success. And when these factors efficiently manage then many projects could reach the desired success. The study is significant because the top management will get awareness that their strong coordination with their subordinate are the main reason for project success. It makes the authorities realize that how they can use different strategies to handle the critical success factors in the project so that the work environment will be more friendly and its lead project toward success. It helps the policy maker to understand the impact of critical success factors on project success, so that the different policies can be made to handle these critical success factors which may affect project success badly.

This study is organized into six sections. In the first section, we shall discuss the study's context. The second section will present a high-level summary of the research, theories, and models related to project success, critical success factors, and knowledge creation. The third part will give a conceptual framework and operational definition of the variables. The fourth section discusses research methodologies, such as data gathering and the construction of metrics. The fifth portion contains the analysis, discussion of the results, study limitations, managerial implications, recommendations for future work, and study conclusion. In the study's conclusion, a clearer picture of the components and their link with project performance has been produced.

Literature Review

Customer satisfaction.

Customer satisfaction has been mentioned in the project management literature (Kerzner, 2002 ), but it has rarely been included in the formal assessment of success. The client is the one that spends the majority of their time on developed facilities, are actually working and live with the final products. It is critical to ensure that the finished project satisfies the client's/customer's expectation. As per Liu and Walker ( 1998 ), satisfaction should be regarded a success criterion. Customer functional performance, expectations, and technical specifications, as demanded by clients, are critical in project business. This rationale is that “the client is the king/boss of every business/organization/project.” As a result, client happiness is the primary goal of any firm.

A company must first meet its customers' expectations to ensure customer satisfaction. If the project satisfied the end-user (Torbica and Stroh, 2001 ), it could be considered effectively completed in the long run. De Wit ( 1986 ) defines project success as determining whether the aim and goal are met. Customer happiness is more vital to success than reaching any specific project objectives. Project deliverables are also critical to achieving the customer's satisfaction level. If the customer is pleased with the result/product, the project has been deemed successful.

Critical Success Factor

Several research conducted over the last few decades has demonstrated the significance of critical success factors. Denial was the first to introduce the concept of critical success criteria in 1961. In 1982, Rock art used the term Critical Success Factors for the first time. These are “factors that contribute to an organization's success and are important for the achievement of an organization's mission,” according to Haleem et al. ( 2012 ). Rubin and Seelig ( 1967 ) pioneered the critical success factor in project management, assessing the influence of the project manager's experience on project success. A critical success factor is a business strategy. Essential success factors are related to a specific attribute or condition of the industry.

Because each country has its own set of rules and regulations, legal constraints, and operational environment, Critical Success Factors differ when we travel from one country to another and from one project to the next. Several dimensions of critical success factor have been specified in detail by several authors (Ashley et al., 1987 ; Pinto and Slevin, 1987 ; Belassi and Tukel, 1996 ; Eriksson, 2008 ; Yang et al., 2009 ; Ibbs et al., 2010 ; Ahmadabadi and Heravi, 2019 ). According to Saqib et al. ( 2008 ), seven critical success factor influence project success. These dimensions include design-related factors, project management-related factors, contractor related factors, economic and business environment-related factors, client related factors, procurement related factors, and program manager related factors.

In his study, the most important factors were project managers' skills, contractors' experience, contractors' cash flow, site management, prompt decisions by clients, prior management experience, solving and decision-making efficacy, supervision, and clients' decision-making capacity. The findings show a positive association between design-related factors, project management-related factors, contracting related factors, business and work environment-related factors, client-related factors, procurement related factors, project manager related factors, and project success. Many project managers may find this study valuable in analyzing the success of their current project. A project manager can evaluate the present value of their program and compare actual and projected values for considered successful elements in a knowledge management activity. It is a useful hint to encourage us to investigate these aspects in the health sector.

Dimensions of Critical Success Factors

According to Saqib et al. ( 2008 ), the Critical Success Factor has seven dimensions.

Design related factors

Project Management related factors

Contractor related factors

Business and Work Environment related factors

Client related factors

Procurement related factors

Project Managers related factors.

Management Related Factors

One technique to ensure project success is to meet the criteria of Hubbard's project management actions (Hubbard, 1990 ; Misztal-Okońska et al., 2020 ). Shen and Liu ( 2003 ) identified management-related critical issues. The findings highlight two important aspects of project success: “coordination among the management team and collaborative efforts by the client, contractor, and consultant.” Kiani Mavi and Standing ( 2018a ) defined critical success factors (CSFs) in project management and classified them into five criteria groups: external environment, organization, project management, project, and sustainability. Data were collected from 26 Australian project managers in the construction industry for this study to establish the dependency and weight of the CSFs.

According to Mavi and Standing's findings, the biggest weights are allocated to top management and sponsor support, end-user imposed constraints and stakeholder expectation. Previous studies have not adequately addressed these issues. To complete the project, the project manager would organize and enforce it utilizing management tools (Jaselskis and Ashley, 1991 ). These elements (control mechanism, decision-making efficacy, feedback capabilities, adequate communication, risk identification and allocation, plan and schedule of project followed, and previous project management experience of related projects) are extremely important in health projects; if these factors are handled effectively, then it will ensure project accomplishment.

In a health project, project management-related factors such as “feedback capability, communication system, planning effort, organizational structure, control mechanism, control of subcontractors, safety and quality assurance programme, and finally the overall managerial actions” will impact. According to Pinto and Slevin ( 1987 ), communication and troubleshooting, monitoring and feedback, senior management support, and a timeline must all be present at all stages of the implementation process. Top management support has been identified as a critical success factor in several studies (Belassi and Tukel, 1996 ; Young and Jordan, 2008 ; Dikic et al., 2020 ). Another study found that top management related factors had a positive relationship with project success (Shenhar et al., 1997 ; Jugdev et al., 2001 ; Saqib et al., 2008 ).

H1a: Top management related factors is positively and significantly related to project success .

Client Related Factors

The project leader, advisors, consumer, vendor, operator, contractor, and manufacturers are significant project participants (Chua et al., 1999 ). The “client” could be either public or private. Client-related aspects include “client type and experience, project organization expertise, client characteristics, project funding, owner construction sophistication, client confidence, well-defined scope, client project management, and owner risk aversion” (Chan and Kumaraswamy, 1997 ; Songer and Molenaar, 1997 ; Dissanayaka and Kumaraswamy, 1999 ). The project was completed under the client's specifications. As a result, there is a need to effectively engage with the client, keep them updated frequently, and make changes to the project to be completed successfully.

Client experience, the client's capability to brief the project, the client's ability to make appropriate decisions, and the client's ability to clearly define roles are all important elements to consider in the project's completion.

It is a useful hint to encourage us to investigate these aspects in the health sector. Another study found that client-related factors were positively connected to project success (Walker, 1995 ; Saqib et al., 2008 ).

H1b: Client related factors are positively and significantly associated with project success .

Design Related Factors

According to Salmeron ( 2009 ), a project design phase is one way to satisfy the owner's requirements economically and optimally. The project's design phase can be depicted structurally. According to Chalabi and Camp ( 1984 ), adequate planning at the beginning of a project can reduce the likelihood of cost overruns and delays. As a result, the project will be completed within the time-frame indicated, and the project will be delivered to the customer as promised. Designers play an important role in a project because their work continues from completion to inception.

According to Chan and Kumaraswamy ( 1997 ), design team-related factors include project design complexity, design team experience, and mistakes and delays in providing project design documents. According to Chan and Kumaraswamy ( 1997 ), the primary cause of project delays was the consultant's lack of design experience. Inexperienced design consultants do not adequately design a project, resulting in time and cost overruns and project delays. Another study discovered that design related factors had a positive link with project success (Chalabi and Camp, 1984 ; Saqib et al., 2008 ).

H1c: Design related factors are positively and significantly associated with project success .

Contractor Related Factors

Contractors and subcontractors begin their primary responsibilities once a project is completed. A lack of relevant contractor planning and monitoring experience and a lack of design experience on the part of consultants would result in a project time overrun. The variables include: “management of the project site, subcontracting involvement and supervision, experiences of a contractor, cash flows of contractor, speed of information flow, and cost control system effectiveness” (Chan and Kumaraswamy, 1997 ; Dissanayaka and Kumaraswamy, 1999 ). Lu et al. ( 2008 ) described contractor related critical success factors; it's mainly include, insufficient contractor expertise, labor productivity, owner intervention, financing and payment, inappropriate planning, slow decision making, and subcontractors. According to Odeh and Battaineh ( 2002 ), consultants and contractors agreed that the top 10 most critical success factors are bad contractor experience, labor productivity, owner intervention, financing and payment, inappropriate planning, slow decision making, and subcontractors. When an organization can deal with these factors efficiently, it can complete a project on time, at a low cost, and with high quality for its clients. As a result, the project undertaken by the project organization is successful. Another study found that contractor-related factors (particularly cash flow and contractor experience) positively correlated with project success (Saqib et al., 2008 ).

H1d: Contractor's related factors are positively and significantly related to project success .

Project Manager Related Factors

The project manager is another significant stakeholder in projects. Project manager skills impact scheduling, project planning, and communication (Belassi and Tukel, 1996 ). The engagement and devotion of project managers are crucial for project completion and will replicate this if the project manager is overseeing many projects simultaneously. The project manager's skill and qualities, competency, devotion to the project, experience, and project authority are all project manager-related factors (Chua et al., 1999 ). The project manager is in charge of ensuring that the project is managed effectively and efficiently.

As a result, the project manager must be proficient in project management. Project management competency/skill, project-related experience, leadership ability, technical capabilities (with contractor and subcontractor), and reporting abilities are critical to project success. Another study revealed that project manager-related factors (especially project manager expertise) has a positive association with project success (Saqib et al., 2008 ).

H1e: Project manager related factors are positively and significantly associated with project success .

Previous research concentrated solely on the proposed idea of success analysis. For example, determining CSFs and success criteria, followed by linking CSFs and success criteria (Bhatti, 2005 ; Hyvari, 2006 ; Saqib et al., 2008 ). This study will look at the impact of critical success factors on project success via the mediation of knowledge creation. According to the extant literature, none considered the relationship between critical success criteria and project success in health sectors. Different studies were carried out in past years, and they mainly focus on the construction sectors. It has been noticed that the researcher has neglected the health sector. That is the purpose that encourages the researcher to carry out this research. The present study adds value to the extended body of literature by covering health sectors.

Knowledge Creation

An organization's competitive advantage is derived from its knowledge resource, which is valuable, rare, and non-replaceable. In the hope of improving performance through better management of what they know, organizations have been proactively engaged in knowledge management. Knowledge management is generally defined as the ability to leverage knowledge to achieve organizational goals, although theories tend to focus either on people or on technology (Miković et al., 2020 ). According to Hu et al. ( 2019 ), knowledge management in a project environment is an understudied topic in project management. Knowledge is the most precious asset in the context of project management. According to Awad and Ghaziri ( 2004 ), knowledge is ”everything that can learn via the process of experience or suitable studies.” It is crucial to emphasize that data, information, and knowledge have always been significant in the industrial, information, or agrarian ages. Many issues confront the nation and organization; to gain a competitive advantage, the government and organization must deal with knowledge assets (Ali, 2008 ).

As a result, to be more competitive, inventive, and productive, organizations must manage their knowledge resources effectively and strategically. However, the dilemma of attaining the organization's goal through utilizing and producing new information arises. The knowledge managed by organization's includes both explicit and implicit information. The organization's leadership may supply all required information related to identifying, sharing, and developing knowledge. An organization requires a mechanism for knowledge generation, information sharing, and organizational learning (Rowley et al., 2000 ; Reich et al., 2012 ). Knowledge play important in the project. Knowledge of previous projects propels us to project success.

It might be either explicit or implicit. Tactic knowledge is created through discussions with stakeholders, office colleagues, project partners, consultants, and experts. It is extremely difficult to express tacit knowledge. Tactic knowledge is acquired via study and experience. Interaction with other individuals fosters the development of tacit knowledge. Tacit knowledge is unintentional and generally restricted to a particular region. Because it is not found in many books or manuals. Tactic knowledge comprises values, attitudes, assumptions, and mental models since it is cognitive and technical. When people use a variety of technical abilities, their tacit understanding of the technological base is articulated. Perception and implicit mental models are exhibited when tacit cognitive knowledge is employed (Sternberg, 1997 ).

Tacit knowledge is easier to remember than explicit knowledge (Wah, 1999 ). Face-to-face interaction, such as informal talk, internships, and storytelling, transforms two-thirds of work-related information. Whenever an issue arises in the project, it is necessary to arrange a meeting with an expert because project-related professionals and experts share their perspectives with employees. When tacit information is expressed, relevant decisions may resolve the problem. The project will be completed on schedule and under budget, resulting in project success. Social contact is nonetheless a requirement for tacit awareness. Social contact and replication of life and work skills can provide a platform for the production, sharing, and transmission of information (Ibrahim et al., 2021 ). Observations also show that social interaction can occur, especially in aggregated cultures, where people of various ethnic backgrounds and backgrounds share their feelings, perceptions, and ideas. Organizational cultures provide a system of learning, adapting and creating a strong environment for people to share valuable insights, which create added value to the organization. Organizational culture, for example, aims to control its members' actions through information sharing. In addition, organizations can create an atmosphere in which employees can make use of their cognitive skills to develop knowledge and share creative ideas. Tacit knowledge has a favorable impact on project success. So, tacit knowledge plays a mediating role between project success and success factors (Arumugam et al., 2013 ; Dalkir, 2013 ).

H2a: Tacit Knowledge creation mediates the relationship between management-related factors and project success .

H2b: Tacit Knowledge creation mediates the relationship between contractor related factors and project success .

H2c: Tacit Knowledge creation mediates the relationship between design-related factors and project success .

H2d: Tacit Knowledge creation mediates the relationship between project manager related factors and project success .

H2e: Tacit Knowledge creation mediates the relationship between client-related factors and project success .

Implicit information is not codified, but explicit knowledge is. May find Detailed expertise in databases, the internet, email, and papers. Everyone can easily get access to explicit knowledge and can easily share (Hansen et al., 1999 ). To overcome many similar problems, we use codified and recorded explicit knowledge. We urge project team members to preserve a written record of working ability, a regulated technique for keeping a record of working knowledge, and a working knowledge record in the information system.

When an employee encountered a problem on the project, project-related internal documents and data files were freely accessible/available. The employee derived ideas and used that information to solve the problem (Smith, 2001 ). As a result, explicit information contributes to project success. As a result, explicit knowledge plays a mediating role between project success and success factors (Arumugam et al., 2013 ; Dalkir, 2013 ; Todorović et al., 2015 ).

H3a: Explicit Knowledge creation mediates the relationship between management-related factors and project success .

H3b: Explicit Knowledge creation mediates the relationship between contractor related factors and project success .

H3c: Explicit Knowledge creation mediates the relationship between design-related factors and project success .

H3d: Explicit Knowledge creation mediates the relationship between project manager related factors and project success .

H3e: Explicit Knowledge creation mediates the relationship between client-related factors and project success .

Conceptual Framework of the Study

Institutions that use their tacit knowledge to handle various problems and achieve their goals have a major competitive advantage (Smith, 2001 ). As previously stated, after examining specific projects, some writers believe that gathering of information on project results might be a great strategy to develop a knowledge base that can use to manage future projects (Hanisch et al., 2009 ; Yun et al., 2011 ). None of the above review studies has considered the relationship between knowledge creation and project success based on the existing literature. The purpose of this study is to give a framework for analyzing project success that will allow others to gather information on project results achieved in various segments and investigate the impact of the proposed idea of knowledge creation in a project environment. The research model of this current study is given in Figure 1 .

Conceptual framework. Source: Author's constructed.

Research Methodology

The current study employed a quantitative methodology and a deductive approach. It is explanatory because it explains the variable's causal link. This study uses the deductive method, also known as testing theory, which formed the hypothesis based on theory. A cross-sectional study is employed because it is less expensive, saves time, and is the most commonly used survey approach. The current study's population was the health project of DHQ Hospital Attock and PIMS Hospital Islamabad. Due to time constraints and limited resources, the study only choose two hospitals as a population. The current study's respondents were “Manager, Supervisor, Zonal Supervisor, and LHS.”

The Manager, Supervisor, Zonal Supervisor, and LHS were chosen because they are in charge of the key functions of the health project and review various stages of health projects such as Polio, EPI, Mother-Child health care, Measles, T.B. dot programme, and so on. Furthermore, depending on their project experience, these individuals provide reliable information. The current study employs non-probability sampling, which means that every unit of the population is unknown and does not have an equal chance of being selected for the sample. There are alternative non-probability sampling procedures, but convenience sampling was used in the current investigation. It is made up of people who are easy to reach. The benefit of using this technique is that it saves time, money, and it is useful in the pilot study. For that reason this type of sampling preferred for that study. The current study's sample was selected using Morgan and Krejcie ( 1970 ) criterion, and the sample size for <800 populations is around 246.

See Table 1 , the current study's data is gathered via a questionnaire because there is a lot of information to be collected in a short period. The questionnaire is based on a literature review and prior studies on this topic. The question was broken down into four sections. A pilot study was conducted to evaluate the instruments in the current study. According to Galloway ( 1997 ), the pilot research should be between 5 and 10% of the final sample size, and 10% of 246 equals 25.

Distribution and collection of questionnaire.

The questionnaire was given to 30 people in the current study. Cronbach's alpha was used to determine the internal consistency of the scale. A figure in the range of 0.7 to 0.95, according to Nunnally and Bernstein ( 1994 ), is suitable. Cronbach's alpha was estimated using PLS (Partial Least Square) software for the current study. The Cronbach's alpha value of the instruments and individual constructions is shown in the table below (see Table 2 ), proving that the instrument is reliable. The component would be assessed using a five-point Likert scale ranging from 1 (very un important) to 5 (very important).

Pilot testing results.

In this section of the study, construct of the questionnaire is briefly discussed. Following are the table, which provides detailed information about the constructs of the study (see Tables 3 , 4 ) .

Construct and items.

Sources of reflective constructs.

Management-related factors are coded as MGTRF, design-related factors as DRF, customer-related factors as CRF, project manager-related factors as PMRF, client-related factors as CLRF, tacit knowledge creation as TKC, explicit knowledge creation as EKC, and customer satisfaction as CSRF. In data screening stage, outliers and missing values were identified to ensure that there are no missing values and data has been entered accurately.

Reasons for Using the Smart PLS

In the current study Smart PLS has been used for several characteristics.

As it indicates the maximum variation of latent variable and indicators.

Another reason of using PLS path modeling is that; it had been widely used in the marketing literature and widely accepted (Lim, 2008 ; Voola and O'Cass, 2010 ). As Smart PLS very popular because of it free availability to researchers and academics, user friendly interface and highly developed reporting features.

As it is less restricted and do not require the normally distributed data (Fornell and Cha, 1994 ).

As well as compared to other path technique PLS requires the minimum demand on measurement scale, sample size and residual distribution.

PLS approach is useful for analyzing the causal relationship, as well as PLS path modeling is useful for theory confirmation, as well as the for theory development (Sarkar et al., 2001 ; Urbach and Ahlemann, 2010 ; Umrani et al., 2020 ).

Another benefit of PLS specifically the Smart PLS as they allow us to estimate the measurement model as well as the structural model at the same time (Ringle et al., 2005 ).

Results and Discussion

Demographic study.

The demographic study is conducted using the SPSS Statistical Package for Social Science software. The demographic research provides details about the education level of the respondents, the Designation of the respondents, and the highest results according to different categories. The demographic study results are summarized (see Table 5 ).

Respondent profile.

Statistical Technique: An Introduction to SEM

SEM is a multivariate strategy and second-generation tool for examining the relationship between many variables. The sample descriptive analysis, reliability analysis using the statistical package for social sciences (SPSS) by Arkkelin ( 2014 ), and additional partial least square technique (Smart PLS 3.2.7) by Götz et al. ( 2010 ) were employed in the statistical analysis to assess the suggested model or for hypothesis testing.

Model Validation

The first step evaluated the measurement model, which checks the reliability and validity, the primary criteria for determining the measure's goodness. The second stage examined the structural model to determine the relationship between the latent variables. The model is also known as the outside model. As in the current study, the Cranach alpha ranged from 0 to 1 (see Table 6 ), and the composite reliability ranged from 0.6 to 0.9 (see Table 6 ), both of which met Hair et al. ( 2012 ) criterion or threshold of reliability requirements of at least 0.6 and 0.7.

Internal consistency of the final instrument.

According to Chin ( 1998 ), the indicator reliability is measured by item loading, which should be >0.7; however, according to Hair et al. ( 2012 ), the indicator loading must be 0.50 or greater.

The current study's results are displayed in the figure below (see Figure 2 and Table 7 ), and they show that item loading is satisfactory and meets the criteria, with values ranging from 0.437 to 0.969. According to Fornell and Larcker [61], convergent validity in Smart PLS 3.2.7 can be determined by the value of (AVE) average variance extracted, and the cut-off value for this measure is 0.50. The current study results for the (AVE) average variance extracted are provided in the table (see Table 8 ), with values ranging from 0.5 to 0.8.

Measurement model indicating only indicators reliability. Source: Author's constructed.

Factors loading.

Convergent validity.

The last component that needs to be assessed is the discriminate validity, which the Fornell–Larcker criterion can be evaluated. Reason behind using this method is that, Fornell and Larcker criterion is the most widely used method for assessing the discriminate validity (Ab Hamid et al., 2017 ).

According to Fornell and Larcker ( 1981 ), the square root of AVE is used to test discriminative validity, and diagonal elements must be greater than the square root of AVE, as diagonal elements are the square root of AVE. The diagonal elements in the table below are greater than the diagonal elements (see Table 9 ).

Fornell and Larcker criterion.

Following the evaluation of the measurement model, the structural model, also known as the inner model, is evaluated in the following stage. The first criterion in the SmartPLS 3.2.7 is to assesses each latent variable's coefficient of determination. The R square reflects how much the independent variable explains variance in the dependent variable.

Chin ( 1998 ) defines the R-square, stating that a value of 0.67 is considered significant, 0.20–0.33 is deemed to be average, and a value of 0.19 or lower is considered weak or indicates a poor relationship. The R-square values that met the Chin ( 1998 ) criteria are shown in the table (see Table 10 ).

Coefficient of determination.

Normality Probability Plots of Variables

Furthermore, as illustrated in Figure 3 , a normal probability plot (Q-Q plot) is utilized to assess the data's normality. As the instances go closer to the straight line, the normality plot for all variables shows an almost normal distribution.

Normality probability plots of variables. Source: Author's constructed.

Multicollinearity

In SPSS, multicollinearity is calculated via Tolerance and VIF (Variance Inflation Factors). According to Arkkelin ( 2014 ), the cut-off value for tolerance is >0.10 and for VIF is <5. The values below indicate no multicollinearity issues (see Table 11 ).

Multicollinearity.

Hypothesis Testing

T-values or significant levels are examined via bootstrapping. First, as shown in the table below, the direct relationship between the dependent and independent is examined (see Table 12 ). The findings show that the connections between CSFs, namely, management-related factors, design-related factors, contractor-related factors, project manager-related factors, client-related factors, and project success are positive, therefore supporting H1a, H1b, H1c, H1d, and H1e (see Table 12 ).

Direct analysis (result after boostrapping).

Mediating Analysis

Finally, the mediation effects were investigated using Smart PLS software. The current study's model predicts project success through critical success factors; nevertheless, the impacts manifested separately through different mediators, namely tacit and explicit knowledge creation.

According to Memon et al. ( 2018 ), when investigating models with several mediators, scholars must evaluate individual indirect effects rather than overall indirect effects. Nonetheless, current Smart PLS software updates feature a new option for examining multiple mediators known as ‘multiple specific indirect effects (mediation).' This function automatically calculates the indirect effect of each mediator, which can be mediation via implicit knowledge creation, explicit knowledge creation, or any variety of mediators.

As a result, evaluating models with many mediators is simplified by Memon et al. ( 2018 ). One of this study's contributions is the investigation of mediated interactions. The specific in-direct effect for the mediating variable is shown in Table 13 .

Mediating analysis (tacit and explicit knowledge creation) (result after boostrapping).

The findings of the mediation test revealed that tacit knowledge creation mediated the association between critical success factors and project success, hence supporting H2a, H2b, H2c, H2d, and H2e. On the other hand, explicit knowledge creation does not mediate the relationship between critical success factors and project success; thus, H3a, H3b, H3c, H3d, and H3e were not supported.

Previous research (Dalkir, 2013 ; Todorović et al., 2015 ) found a gap that the current work covers. It demonstrates that knowledge creation acts as a bridge between critical success factors and project success. The present study further expands on the research paradigm that Todorović et al. ( 2015 ) developed by including knowledge creation as a mediator and project success as a dependent variable. Critical success factors exist in today's research arena concerning project success; however, the notion is still unclear on how these factors are associated with project success. The world has changed tremendously in the previous decade, and these changes are continuing at an accelerating rate. As a result of this project's ongoing challenges, we have failed to meet the needs and expectations of our customers. This study choose customer satisfaction as a project success dimension because their behavior directly impacts project success. The current studies concentrate on the critical success factors of health projects. Because the knowledgeable sector has previously gotten little attention. However, the collective data analysis results demonstrate a significant relationship between critical success factors and project success, found in previous literature (Pinto and Slevin, 1987 ; Odeh and Battaineh, 2002 ; Saqib et al., 2008 ).

In terms of tacit mediation, the findings showed a significant relationship between critical success factors and project success and that tacit knowledge creation had been positively influenced, supported by prior research. Tacit knowledge creation contributes to project success. As a result, tacit knowledge links success variables and project outcomes (Dalkir, 2013 ). According to Al-Hakim and Hassan ( 2014 ), mid-level managers impact knowledge creation execution. This tacit knowledge creation has been implemented successfully. It also boosts innovation and improves organizational/project performance. As a result, tacit knowledge creation mediate the relationship between mid-level management and project success.

According to the findings of this study, tacit knowledge creation mediates the relationship between critical success factors (management-related factors, design-related elements, contractor-related factors, project manager-related factors, and client-related factors) and project success. Hypothesis H2a, H2b, H2c, H2d, and H2e shows significant relationship. Because ours is a collectivist society. Our lives and jobs are belong to a collectivist society. Whenever an issue arises during project execution, we all interact, exchange our perspectives and thoughts, and work together to find the best solution. Throughout the process, tacit knowledge is articulating, no one seeks explicit knowledge. As a result, tacit knowledge creation mediates the relationship between CSFs and project success.

The findings revealed that explicit knowledge creation does not affect project success in explicit mediation. It does not mediates the relationship between critical success factors and project success. Previous studies in developed nations have shown that explicit knowledge creation considerably moderates the link between CSFs and project success. However, Pakistan is a developing country that prefers a collectivist approach. In a collectivist society, we typically utilize “We” instead of “I,” according to Hofstede's 5-dimension approach. Project team members embraced common responsibility rather than personal duty in the collectivist method. The organization's benefit is important for the people living in collective culture places.

They are unconcerned about their interests. When a project team member encounters an issue during project execution in a collectivist culture. A team member discusses their problem with the rest of the team. They called a formal meeting, and everyone shared their opinions and points of view based on their experiences. They can only conclude and solve the problem through this formal meeting.

As a result of this formal gathering, tacit knowledge is expressed, and no one seeks explicit information. Hypotheses H3a, H3b, H3c, H3d, and H3e are rejected since they do not demonstrate a significant association with project success.

In project management, project success is an intriguing and essential topic. As in any competitive environment, project managers are motivated to maximize project success, and to that end, they employ various strategies to distinguish themselves from their competition. The current research examines impact of critical success criteria on project success. All of the variables in the research model were derived from past research. Data were acquired from the health programmes at DHQ hospital Attock and PIMS hospital Islamabad. After verifying the reliability and validity of research scales, the hypothesis was evaluated, revealing that all measurements were reliable.

The current study found that critical success factors (management-related factors, design-related factors, contractor-related factors, project manager-related factors, and client-related factors) strongly correlate with project success (see Table 9 ). It means that critical success factors are important predictors of project success. As a result, to get the most out of the project, managers and subordinates should concentrate on several critical success factors. It was also shown that tacit knowledge production mediates the relationship between critical success elements and project success, whereas explicit knowledge does not.

It is due to Pakistan's status as a developing country. It takes a collectivist approach rather than an individualist one. Individual interest is prioritized over community interest in a collectivist society. As a result, tacit knowledge rather than explicit knowledge is communicated. The current research can be described in two parts: marketing implications and theoretical contribution. The marketing application will investigate the practical applicability of recent study findings in today's project, whilst the theoretical contribution will fill a knowledge gap in the previous literature.

Managerial Implication

This study helps the project manager and subordinates discover essential elements for project success. To combat the severity of these factors, the manager should change their strategies. Managers should instruct their employees on generating tacit and explicit knowledge that may be used efficiently when a team member confronts a challenge.

The research work assists project managers in developing strong team cohesion. The manager should encourage their project team members to speak with and share their ideas. Also, reply fast and supply their team with the essential information, documents, or procedures whenever they meet challenges.

Project managers must also construct a structure within a project that generates both implicit and explicit knowledge. They should announce a reward scheme for their team members in incentives and allowances to accomplish this.

The results suggest that one must gain continuous and sustained top management support before launching any knowledge management project. Leadership developed with transformational leadership traits is the core requirement to make the project successful.

Top management of the organization is required to keep leadership development on top of the agenda for projects. In consultation with all stakeholders, a clear vision and objectives for knowledge management must be formulated and articulated. A well-developed knowledge management framework and knowledge cycle be adopted and communicated to all employees. A strategy about top-down and bottom-up learning and knowledge sharing may also be formulated and widely circulated before practically launching the knowledge management project.

Project managers need to get people involved in Knowledge management processes that require continuous learning and development. Training also needs to be included in the knowledge management program. However, before launching any training program, identify knowledge management related competencies and behaviors through a knowledge audit. It will enable their people to build their knowledge processing capabilities and competencies and will realize the priority of the knowledge management project.

Theoretical Contribution

Previous studies only focused on the proposed concept of success analysis only. For example determination of CSFs and success criteria and then correlating CSFs and success criteria (Bhatti, 2005 ; Hyvari, 2006 ; Saqib et al., 2008 ). This study is going to examine the influence of critical success factors on project success through the mediation of knowledge creation.

The current study also improves the research framework initially designed by [5], after adding the knowledge creation as a mediator and project success as a dependent variable.

Little is known about the antecedents and consequences of critical success factors which can further lead to crucial project outcomes like time overrun and cost overrun, and there is still room for further exploration in this regard (Saqib et al., 2008 ; Todorović et al., 2015 ). So the current research adds to the database existing in project success literature.

Recommendation to Practioner

The health project manager should develop a system that focuses on the generation of implicit and explicit knowledge and the formulation of tacit and explicit knowledge.

Coordination between senior management and project subordinates is lacking. Several staff members in the DHQ Attock hospital complained that upper management does not respond on time and coordinate adequately, causing project operations to be delayed. As a result, senior management must communicate with their subordinates on time and effectively.

Vertical collectivism and centralization underpin the health initiative. We recommend that the health initiative follow horizontal collectivism. In which responsibility is distributed to each individual, each individual can decide on their behalf. Project activities will not be delayed as a result of these timely decisions.

This research educates practitioners on the CSFs characteristics that influence project success in the health sector. And when these difficulties are adequately managed, many projects stand a reasonable chance of succeeding.

This study is significant because top management will gain knowledge from their great coordination with their subordinates, which is the primary reason for project success. It makes the authorities comprehend how they can utilize various tactics to handle the essential success aspects in the project to complete, so that the work environment more comfortable and lead the project to success.

It enables policymakers to understand better the impact of critical success factors on project success in the health sector, allowing new policies to be developed to address these critical success factors that may affect project performance.

Limitation and Future Recommendation

The present study uses cross-sectional and quantitative research methods; thus, different methodologies are being used to predict behavior better. The information was gathered from two hospitals and can be expanded further. Because many other marketing elements may impact project success, but only a few were evaluated in this study, future studies should extend the other variables (project KPIs) to understand better, how and to what extent the project's success occurs. The current study only looks at mediation; thus, future research should look into other mediating variables (knowledge acquisition, knowledge application, knowledge transfer) and moderating variables (such as project experience) to better assess the results.

In the future, cross-sectional studies can address the issue of generalizability, with study samples drawn from various areas of Pakistan, particularly those previously out of reach due to financial restrictions and the risk of terrorist activity. Many other components, such as the industrial sector other than the health sector, might be expanded to broaden the research. Little is known about the causes and effects of critical success variables, leading to important project outcomes such as time and cost overruns. There is still an opportunity for future research in this area (Saqib et al., 2008 ; Todorović et al., 2015 ). As a result, the current study adds to the database of project success literature.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.

Author Contributions

The idea of the original draft belongs to SaN. SaN wrote the introduction, literature review, and empirical outcomes sections. MA, HH, and SiN helped collect and visualize data of observed variables. SaN, MVA, and KA constructed the methodology section in the study. All authors contributed to the article and approved the submitted revised version.

This work was supported by a grant of the Romanian Ministry of Education and Research, CNCS - UEFISCDI, project number PN-III-P4-ID-PCE-2020-2174, within PNCDI III.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

• Ab Hamid M. R., Sami W., Sidek M. M. (2017). Discriminant validity assessment: use of Fornell & Larcker criterion versus HTMT criterion. J. Phys. Confer. Ser. 890, 012163. 10.1088/1742-6596/890/1/012163 [ DOI ] [ Google Scholar ]
• Ahmadabadi A. A., Heravi G. (2019). The effect of critical success factors on project success in Public- Private Partnership projects: a case study of highway projects in Iran. Transport Policy 73, 152–161. 10.1016/j.tranpol.2018.07.004 [ DOI ] [ Google Scholar ]
• Al-Hakim L. A. Y., Hassan S. (2014). Who are the crew members on implementation of knowledge management strategies to enhance innovation and improve organizational performance? J. Resources Dev. Manage. 3, 54–63. [ Google Scholar ]
• Ali B. (2008). Critical success factors for effective knowledge management in corporate sector (Pakistan) (Doctoral dissertation: ). National University of Modern Languages, Islamabad, Pakistan. [ Google Scholar ]
• Allal-Chérif O., Makhlouf M. (2016). Using serious games to manage knowledge: The SECI model perspective. Journal of Business Research, 69, 1539–1543. 10.1016/j.jbusres.2015.10.013 [ DOI ] [ Google Scholar ]
• Arkkelin D. (2014). Using SPSS to Understand Research and Data Analysis. [ Google Scholar ]
• Arumugam V., Antony J., Kumar M. (2013). Linking learning and knowledge creation to project success in Six Sigma projects: an empirical investigation. Int. J. Prod. Econ. 141, 388–402. 10.1016/j.ijpe.2012.09.003 [ DOI ] [ Google Scholar ]
• Ashley D. B., Lurie C. S., Jaselskis E. J. (1987). Determinants of construction project success. Project Manage. J. 18, 69–79. [ Google Scholar ]
• Awad E. M., Ghaziri H. M. (2004). Knowledge Management. [ Google Scholar ]
• Belassi W., Tukel O. I. (1996). A new framework for determining critical success/failure factors in projects. Int. J. Project Manage. 14, 141–151. 10.1016/0263-7863(95)00064-X [ DOI ] [ Google Scholar ]
• Bhatti T. R. (2005). “Critical success factors for the implementation of enterprise resource planning (ERP): empirical validation,” in The Second International Conference on Innovation in Information Technology, 110. [ Google Scholar ]
• Boon Sin A., Zailani S., Iranmanesh M., Ramayah T. (2015). Structural equation modeling on knowledge creation in Six Sigma DMAIC project and its impact on organizational performance. Int. J. Prod. Econ. 168, 105–117. 10.1016/j.ijpe.2015.06.007 [ DOI ] [ Google Scholar ]
• Canonico P., De Nito E., Esposito V., Pezzillo Iacono M., Consiglio S. (2019). Knowledge creation in the automotive industry: analyzing obeya-oriented practices using the SECI model. J. Business Res. 1. 10.1016/j.jbusres.2019.11.047 [ DOI ] [ Google Scholar ]
• Chalabi F. A., Camp D. (1984). Causes of delays and overruns of construction projects in developing countries. CIB Proc. 2, 723–734. [ Google Scholar ]
• Chan D. W., Kumaraswamy M. M. (1997). A comparative study of causes of time overruns in Hong Kong construction projects. Int. J. Project Manage. 15, 55–63. 10.1016/S0263-7863(96)00039-7 [ DOI ] [ Google Scholar ]
• Chin W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods Business Res. 295, 295–336. [ Google Scholar ]
• Chua D. K. H., Kog Y. C., Loh P. K. (1999). Critical success factors for different project objectives. J. Construct. Eng. Manage. 125, 142–150. 10.1061/(ASCE)0733-9364(1999)125:3(142) [ DOI ] [ Google Scholar ]
• Dalkir K. (2013). Knowledge Management in Theory and Practice. Routledge. [ Google Scholar ]
• De Wit A. (1986). “Measuring project success: an illusion,” in Proceedings of the 18th Annual Seminar/Symposium (Montreal, QC: ), 13–21. [ Google Scholar ]
• Dikic M., Nikolic D., Todorovic J., Terzic-Supic Z., Kostadinovic M., Babic U., et al. (2020). Alignment of perceived competencies and perceived job tasks among primary care managers. Healthcare 8, 9. 10.3390/healthcare8010009 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Dissanayaka S. M., Kumaraswamy M. M. (1999). Evaluation of factors affecting time and cost performance in Hong Kong building projects. Eng. Construct. Architect. Manage. 6, 287–298. 10.1108/eb021119 [ DOI ] [ Google Scholar ]
• Doloi H., Iyer K. C., Sawhney A. (2011). Structural equation model for assessing impacts of contractor's performance on project success. Int. J. Project Manage. 29, 687–695. 10.1016/j.ijproman.2010.05.007 [ DOI ] [ Google Scholar ]
• Eriksson P. E. (2008). Procurement effects on coopetition in client-contractor relationships. J. Construct. Eng. Manage. 134, 103–111. 10.1061/(ASCE)0733-9364(2008)134:2(103) [ DOI ] [ Google Scholar ]
• Fornell C., Cha J. (1994). Partial least squares. Adv. Methods Marketing Res. 407, 52–78. [ Google Scholar ]
• Fornell C., Larcker D. F. (1981). Structural equation models with unobservable variables and measurement error: algebra and statistics. J. Market. Res. 382–388. 10.1177/002224378101800313 [ DOI ] [ Google Scholar ]
• Galloway A. (1997). Questionnaire Design and Analysis. [ Google Scholar ]
• Götz O., Liehr-Gobbers K., Krafft M. (2010). Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach Handbook of Partial Least Squares. Springer, 691–711. [ Google Scholar ]
• Habib M. A., Soofi S., Cousens S., Anwar S., Haque N., ul Ahmed I., et al. (2017). Community engagement and integrated health and polio immunization campaigns in conflict-affected areas of Pakistan: a cluster randomized controlled trial. Lancet Global Health 5, e593–e603. 10.1016/S2214-109X(17)30184-5 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hair J. F., Sarstedt M., Ringle C. M., Mena J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Market. Sci. 40, 414–433. 10.1007/s11747-011-0261-6 [ DOI ] [ Google Scholar ]
• Haleem A., Sushil Qadri M. A., Kumar S. (2012). Analysis of critical success factors of world-class manufacturing practices: an application of interpretative structural modelling and interpretative ranking process. Prod. Plann. Control 23, 722–734. 10.1080/09537287.2011.642134 [ DOI ] [ Google Scholar ]
• Hanisch B., Lindner F., Mueller A., Wald A. (2009). Knowledge management in project environments. J. Knowl. Manage. 13, 148–160. 10.1108/13673270910971897 [ DOI ] [ Google Scholar ]
• Hansen M. T., Nohria N., Tierney T. (1999). “What's your strategy for managing knowledge?” in The Knowledge Management Yearbook 2000–2001. [ PubMed ] [ Google Scholar ]
• Hu Y. F., Hou J. L., Chien C. F. (2019). A UNISON framework for university knowledge management- industry collaboration and an illustration. Comput. Indus. Eng. 129, 31–43. 10.1016/j.cie.2018.12.072 [ DOI ] [ Google Scholar ]
• Hubbard D. G. (1990). Successful Utility Project Management From Lessons Learned. Project Management Institute. [ Google Scholar ]
• Hyvari I. (2006). The success of projects in different organizational conditions. Project Manage. J. 37, 31. 10.1177/875697280603700404 [ DOI ] [ Google Scholar ]
• Ibbs W., Nguyen L. D., Simonian L. (2010). Concurrent delays and apportionment of damages. J. Construct. Eng. Manage. 137, 1191126. 10.1061/(ASCE)CO.1943-7862.0000259 [ DOI ] [ Google Scholar ]
• Ibrahim S. B., Ahmed U., Abdullahi M. S. (2021). Testing the prediction of knowledge sharing behavior through the lens of organizational culture and organizational citizenship behavior. Ann. Contemp. Dev. Manage. HR 3, 27–40. 10.33166/ACDMHR.2021.02.003 [ DOI ] [ Google Scholar ]
• Ismail F., Yusuwan N. M., Baharuddin H. E. A. (2012). Management factors for successful IBS projects implementation. Procedia Soc. Behav. Sci. 68, 99–107. 10.1016/j.sbspro.2012.12.210 [ DOI ] [ Google Scholar ]
• Jaselskis E. J., Ashley D. B. (1991). Optimal allocation of project management resources for achieving success. J. Construct. Eng. Manage. 117, 321–340. 10.1061/(ASCE)0733-9364(1991)117:2(321) [ DOI ] [ Google Scholar ]
• Jugdev K., Thomas J., Delisle C. (2001). Rethinking project management: old truths and new insights. Int. Project Manage. J. 7, 36–43. [ Google Scholar ]
• Kerzner H. R. (2002). Strategic Planning for Project Management Using a Project Management Maturity Model. John Wiley & Sons. [ Google Scholar ]
• Khan M. M., Van Den Heuvel W. (2006). Description and content analysis of the national health policy of Pakistan. Asia Pacific J. Public Health. 33–52. [ Google Scholar ]
• Kiani Mavi R., Standing C. (2018a). Critical success factors of sustainable project management in construction: a fuzzy DEMATEL-ANP approach. J. Cleaner Prod. 194, 751–765. 10.1016/j.jclepro.2018.05.120 [ DOI ] [ Google Scholar ]
• Kiani Mavi R., Standing C. (2018b). Critical success factors of sustainable project management in construction: a fuzzy DEMATEL-ANP approach. J. Cleaner Prod. 194, 751–765. 10.1016/j.jclepro.2018.05.120 [ DOI ] [ Google Scholar ]
• Lim Y. W. (2008). Triple endobutton technique in acromioclavicular joint reduction and reconstruction. Ann. Acad. Med. Singapore 37, 294. [ PubMed ] [ Google Scholar ]
• Liu A. M., Walker A. (1998). Evaluation of project outcomes. Construct. Manage. Econ. 16, 209–219. 10.1080/014461998372493 [ DOI ] [ Google Scholar ]
• Lu W., Shen L., Yam M. C. (2008). Critical success factors for the competitiveness of contractors: China study. J. Construct. Eng. Manage. 134, 972–982. 10.1061/(ASCE)0733-9364(2008)134:12(972) [ DOI ] [ Google Scholar ]
• Maqbool R., Sudong Y. (2018). Critical success factors for renewable energy projects; empirical evidence from Pakistan. J. Cleaner Prod. 195, 991–1002. 10.1016/j.jclepro.2018.05.274 [ DOI ] [ Google Scholar ]
• Memon M. A., Cheah J., Ramayah T., Ting H., Chuah F. (2018). Mediation analysis issues and recommendations. J. Appl. Struct. Equation Model. 2, 1–9. 10.47263/JASEM.2(1)01 [ DOI ] [ Google Scholar ]
• Miković R., Petrović D., Mihić M., Obradović V., Todorović M. (2020). The integration of social capital and knowledge management-the key challenge for international development and cooperation projects of nonprofit organizations. Int. J. Project Manage. 38, 515–533. 10.1016/j.ijproman.2020.07.006 [ DOI ] [ Google Scholar ]
• Misztal-Okońska P., Goniewicz K., Hertelendy A. J., Khorram-Manesh A., Al-Wathinani A., Alhazmi R. A., et al. (2020). How medical studies in Poland prepare future healthcare managers for crises and disasters: results of a pilot study. Healthcare 8, 202. 10.3390/healthcare8030202 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Morgan D. W., Krejcie R. V. (1970). Determining sample size for research activities. Educ. Psychol. Measure. 30, 607–610. 10.1177/001316447003000308 [ DOI ] [ Google Scholar ]
• Nonaka I., Toyama R., Nagata A. (2000). A firm as a knowledge-creating entity: a new perspective on the theory of the firm. Indus. Corporate Change 9, 1–20. 10.1093/icc/9.1.1 [ DOI ] [ Google Scholar ]
• Nunnally J. C., Bernstein I. H. (eds.). (1994). Elements of Statistical Description and Estimation. Psychometric Theory 3rd Edn. New York, NY. [ Google Scholar ]
• Odeh A. M., Battaineh H. T. (2002). Causes of construction delay: traditional contracts. Int. J. Project Manage. 20, 67–73. 10.1016/S0263-7863(00)00037-5 [ DOI ] [ Google Scholar ]
• Pinto J. K., Slevin D. P. (1987). Critical factors in successful project implementation. IEEE Trans. Eng. Manage. EM 34, 22–27. 10.1109/TEM.1987.6498856 [ DOI ] [ Google Scholar ]
• Reich B. H., Gemino A., Sauer C. (2012). Knowledge management and project-based knowledge in its projects: a model and preliminary empirical results. Int. J. Project Manage. 30, 663–674. 10.1016/j.ijproman.2011.12.003 [ DOI ] [ Google Scholar ]
• Ringle C. M., Wende S., Will A. (2005). SmartPLS 2.0 (beta). [ Google Scholar ]
• Rowley T., Behrens D., Krackhardt D. (2000). Redundant governance structures: an analysis of structural and relational embeddedness in the steel and semiconductor industries. Strategic Manage. J. 21, 369–386. [ DOI ] [ Google Scholar ]
• Rubin I. M., Seelig W. (1967). Experience as a factor in the selection and performance of project managers. Eng. Manage. IEEE Trans. 131–135. 10.1109/TEM.1967.6448338 [ DOI ] [ Google Scholar ]
• Salmeron J. L. (2009). Augmented fuzzy cognitive maps for modelling LMS critical success factors. Knowl. Based Syst. 22, 275–278. 10.1016/j.knosys.2009.01.002 [ DOI ] [ Google Scholar ]
• Saqib M., Farooqui R. U., Lodi S. H. (2008). “Assessment of critical success factors for construction projects in Pakistan,” in First International Conference on Construction in Developing Countries, 392–404. [ Google Scholar ]
• Sarkar M. B., Echambadi R., Cavusgil S. T., Aulakh P. S. (2001). The influence of complementarity, compatibility, and relationship capital on alliance performance. J. Acad. Market. Sci. 29, 358–373. 10.1177/03079450094216 [ DOI ] [ Google Scholar ]
• Seiler S., Lent B., Pinkowska M., Pinazza M. (2012). An integrated model of factors influencing project managers' motivation - findings from a Swiss Survey. Int. J. Project Manage. 30, 60–72. 10.1016/j.ijproman.2011.03.002 [ DOI ] [ Google Scholar ]
• Sheikh Z. A., Jensen A. M. B. (2019). Channelling hope: an ethnographic study of how research encounters become meaningful for families suffering from genetic disease in Pakistan. Soc. Sci. Med. 228, 103–110. 10.1016/j.socscimed.2019.03.024 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Shen Q., Liu G. (2003). Critical success factors for value management studies in construction. J. Construct. Eng. Manage. 129, 485-491. 10.1061/(ASCE)0733-9364(2003)129:5(485) [ DOI ] [ Google Scholar ]
• Shenhar A. J., Levy O., Dvir D. (1997). Mapping the dimensions of project success. Project Manage. J. 28, 5–9. [ Google Scholar ]
• Smith E. A. (2001). The role of tacit and explicit knowledge in the workplace. J. Knowl. Manage. 5, 311–321. 10.1108/13673270110411733 [ DOI ] [ Google Scholar ]
• Songer A. D., Molenaar K. R. (1997). Project characteristics for successful public-sector design-build. J. Construct. Eng. Manage. 123, 34–40. 10.1061/(ASCE)0733-9364(1997)123:1(34) [ DOI ] [ Google Scholar ]
• Sternberg R. J. (1997). Successful Intelligence. New York, NY: Penguin Putnam. [ Google Scholar ]
• Todorović M. L., Petrović D. T., Mihić M. M., Obradović V. L., Bushuyev S. D. (2015). Project success analysis framework: a knowledge-based approach in project management. Int. J. Project Manage. 33, 772–783. 10.1016/j.ijproman.2014.10.00935291661 [ DOI ] [ Google Scholar ]
• Torbica Z. M., Stroh R. C. (2001). Customer satisfaction in home building. J. Construct. Eng. Manage. 127, 82–86. 10.1061/(ASCE)0733-9364(2001)127:1(82) [ DOI ] [ Google Scholar ]
• Umrani W. A., Channa N. A., Yousaf A., Ahmed U., Pahi M. H., Ramayah T. (2020). Greening the workforce to achieve environmental performance in hotel industry: a serial mediation model. J. Hospitality Tourism Manage. 44, 50–60. 10.1016/j.jhtm.2020.05.007 [ DOI ] [ Google Scholar ]
• Urbach N., Ahlemann F. (2010). Structural equation modeling in information systems research using partial least squares. J. Information Technol. Theory Appl. 11, 5. [ Google Scholar ]
• Verburg R. M., Bosch-Sijtsema P., Vartiainen M. (2013). Getting it done: critical success factors for project managers in virtual work settings. Int. J. Project Manage. 31, 68–79. 10.1016/j.ijproman.2012.04.005 [ DOI ] [ Google Scholar ]
• Voola R., O'Cass A. (2010). Implementing competitive strategies: the role of responsive and proactive market orientations. Euro. J. Market. 44, 245–266. 10.1108/03090561011008691 [ DOI ] [ Google Scholar ]
• Wah L. (1999). ” Making knowledge stick”, Management Review, May , 24–9. [ Google Scholar ]
• Walker D. H. (1995). An investigation into construction time performance. Construct. Manage. Econ. 13, 263–274. 10.1080/01446199500000030 [ DOI ] [ Google Scholar ]
• Yang J., Shen G. Q., Drew D. S., Ho M. (2009). Critical success factors for stakeholder management: construction practitioners' perspectives. J. Construct. Eng. Manage. 136, 778–786. 10.1061/(ASCE)CO.1943-7862.0000180 [ DOI ] [ Google Scholar ]
• Yang M., Lin Q., Maresova P. (2021). Does employee care trigger innovation under a healthy and safe working environment? Evidence from the pharmaceutical industry in China. Healthcare 9, 194. 10.3390/healthcare9020194 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Young R., Jordan E. (2008). Top management support: mantra or necessity?. Int. J. Project Manage. 26, 713–725. 10.1016/j.ijproman.2008.06.001 [ DOI ] [ Google Scholar ]
• Yun G., Shin D., Kim H., Lee S. (2011). Knowledge-mapping model for construction project organizations. J. Knowl. Manage. 15, 528–548. 10.1108/13673271111137475 [ DOI ] [ Google Scholar ]

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Critical success factors in early new product development: a review and a conceptual model

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• Published: 05 July 2017
• Volume 14 , pages 411–427, ( 2018 )

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• Henrik Florén 1 ,
• Johan Frishammar 2 ,
• Vinit Parida 2 &
• Joakim Wincent   ORCID: orcid.org/0000-0002-8770-8874 2 , 3  

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The literature on the front end in the New Product Development (NPD) literature is fragmented with respect to the identification and analysis of the factors that are critical to successful product development. The article has a two-fold purpose. First, it describes, analyses, and synthesizes those factors through a literature review of the research on the front end in NPD. Second, it conceptualizes a framework that features two types of success factors: foundational success factors (common to all the firm’s projects) and project-specific success factors (appropriate for the firm’s individual projects). The article makes recommendations for the management of this important phase of product development, discusses limitations of relevant previous research, and offers suggestions for future research. The article makes a theoretical contribution with its analysis and synthesis of the reasons for success in front-end activities and a practical contribution with its conceptual framework that can be used as an analytical tool by firms and their product managers.

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Introduction

New product development (NPD) projects tend to fail, either in the last stage of the development process or in the later commercial stage. The underlying causes of failure can often be traced to the beginning stage, in what is often called the front end of NPD. Broadly speaking, this stage is defined as the period between the initial consideration of a new product idea and the decision to begin or to abort development of the product (Kim and Wilemon 2002a ).

Prior research on managing NPD has shown that the front end of NPD often has a dynamic and interactive nature (Akbar and Tzokas 2013 ). This stage is characterized by complex information processing (Khurana and Rosenthal 1997 ; De Brentani and Reid 2012 ), ad hoc decision-making (Montoya-Weiss and O'Driscoll 2000 ), and conflicting organizational pressures caused by, for example, high degrees of complexity and uncertainty (Chang et al. 2007 ). These challenging characteristics frequently result in missteps, time delays, and product failure (Goldenberg et al. 2001 ).

Prior research also shows that ability to manage the front end of NPD, in which robust product definitions are developed, has a significant effect on product success (Cooper and Kleinschmidt 1987 ; Murphy and Kumar 1996 ; Khurana and Rosenthal 1997 , 1998 ). Vague or faulty product definitions may result in high costs and/or failure in subsequent stages of the development process (Bacon et al. 1994 ).

Most research on the front end of NPD concludes that this stage – from a managerial point of view – is different from later product development stages. Therefore, the front end of NPD must be managed following a different logic (Markham 2013 ). However, the extant front-end literature, which relies considerably on anecdotal evidence, lacks a comprehensive conceptual framework that identifies, describes, and synthesizes the key success factors in front-end management.

This article, which reviews the literature on the front end of NPD, focuses on these success factors. The article then uses these factors to create a conceptual framework that firms can use to manage the front end of NPD. Although the literature on the later stages of NPD is well developed (e.g., Brown and Eisenhardt 1995 ; Cooper et al. 2002 ), we still lack a conceptual understanding of how firms that seek to enhance their front-end competence should proceed (e.g., Florén and Frishammar 2012 ; Chang et al. 2007 ; Kim and Wilemon 2002a , 2002b ). Our conceptual framework is intended to provide that assistance.

The article is structured as follows. We begin by describing how we conducted our literature review. Based on the results of this review, we present a discussion of success factors for the front end of NPD, including commentary on robust product definition, open innovation, and on go/no-go decision-making in NPD. We distinguish between foundational success factors and project-specific success factors. We then present our conceptual framework that that is based on these factors. Thereafter we discuss our findings with reference to previous research and describe our practical and theoretical contributions. We conclude with suggestions for future research.

Method and research procedure

Choosing sources for literature review is a process of inclusion and exclusion. We followed several steps to minimize this risk of including the “right” literature and excluding the “wrong” literature.

We searched for articles on the front end in NPD that were published in the last fifteen years in well-known, peer-reviewed technology and innovation management journals. We found that the articles use various terms to refer to the front end of NPD. We identified the following synonyms for “front end”: e arly, discovery, idea, concept , and predevelopment . We also identified three words that refer to the time in which front-end activities are conducted: stage, process, and phase . Last, we identified three terms that describe the work in front-end activities: product development, innovation, and NPD . We used these search words and terms, in various combinations, in selected databases to produce a list of articles for our review.

We searched the following databases: Business Source Elite, Emerald Insight, ABI/Inform, JSTOR, IEEE Xplore, and Blackwell Synergy. These are databases commonly used to review the published work of innovation and entrepreneurship researchers (George et al. 2016 ).

For various reasons, we excluded many of the retrieved articles from our review. For example, we found articles that only briefly addressed the importance of the front end of NPD and did not describe the success factors related to front-end activities. We also excluded articles that focused on sources of ideas for innovation (e.g. McAdam and McClelland, 2002 ; Salter and Gann, 2003 ). The reason for this decision was that most authors conceptualize the front end as beginning when firms already have an idea. We excluded other articles because they dealt only minimally, or not at all, with how to organize and manage the front end of NPD.

Success factors for the front end in the new product development literature

Many studies on the front end of NPD do not define success. However, for purposes of our conceptual framework, a definition of success is required. We agree with Kim and Wilemon ( 2002b ) that the success of front-end activities depends on whether they lead to a robust product definition that, in turn, leads to product development. A robust or corroborated product definition is one that is clear, stable, and unambiguous, and has passed business and feasibility analysis (Florén and Frishammar 2012 ). Product concepts, which are at the core of robust product definitions, are “representations of the goals for the development process” (Seidel 2007 , p. 523).

According to Montoya-Weiss and O'Driscoll ( 2000 ), a product concept requires a definition of the underlying technologies plus statements on customer benefits and evaluations of market opportunities. A product concept also includes analyses of market segments and positioning, competitors, and alignments with existing business and technology plans (Khurana and Rosenthal 1997 ; Montoya-Weiss and Calantone 1994 ; Song and Parry 1996 ; Cooper and Kleinschmidt 1987 ).

Popper ( 1959 , 1972 ) concludes that scientific laws are falsifiable rather than verifiable. We apply this reasoning when we state that robust product definitions derived from front-end activities cannot be verified as completely valid; rather, we argue they only can be evaluated as unflawed. Therefore, relevant actors at a firm (e.g., the development team, the review committee, and other decision-makers) must accept the robust product definition and agree that it has the potential to lead to product development.

We use the robust product definition as a proxy for front-end success. We acknowledge that such a managerial definition of front-end success potentially neglects alternative definitions that other decision-makers, with other NPD interests and perspectives, support. Such definitions typically do not align with the robust product definition that the firm supports. Examples are skunkworks projects that are generally found outside traditional NPD processes.

We claim that the front end of NPD begins when relevant key actors in the firm recognize the potential of an idea to lead to product development. The front end of NPD concludes with the go/no-go decision for a proposed product. The decision to begin or to abort product development is made with reference to the robust product definition. This means that the robust product definition exerts a powerful influence on product development.

Two major reasons explain a no-go decision. First, an idea is “killed” if decision-makers conclude the proposed product has no or low commercial potential. Second, an idea is abandoned if it does not fit with the firm’s current business model even though the idea may, in some respects, have commercial value. The latter reason leads to reflections on the open innovation paradigm,

In promoting the open innovation paradigm, Chesbrough ( 2003 , 2006 ) comments that ideas that do not align with a focal firm’s current business may still be successfully commercialized outside that firm. The implication is that a robust product definition can still lead to product development even if the focal firm chooses not to develop the idea into a product. Hence, we argue that a robust product definition is also a valid measure of the success of front-end activities when it leads to insights relevant to the open innovation paradigm.

Figure 1 presents our conceptual framework. Tables 1 and 2 develop the success factors in the framework. In agreement with Khurana and Rosenthal ( 1997 ), we distinguish between foundational success factors and project-specific success factors. Foundational success factors apply to all of the firm’s front-end projects whereas project-specific success factors apply to the firm’s individual front-end projects. Hence, top management should oversee the foundational success factors, and front-end project managers and teams should oversee the project-specific success factors.

A conceptual framework of success factors in the front end of new product development

Next we describe how these two groups of factors lead to corroborated or robust product definitions. We begin with the foundational success factors followed by the project-specific success factors.

Foundational success factors

Senior management involvement.

Senior management can support managers and teams who work with front-end activities in various situations and in various ways (De Cleyn et al. 2015 ). First, such support is essential when resistance to change is encountered (McAdam and Leonard 2004 ). Second, the momentum behind new product ideas is stronger if senior management is directly involved during the front end of NPD (Murphy and Kumar 1997 ; Lauto et al. 2013 ). Third, senior management’s support in front-end activities promotes greater innovation (Koen et al. 2001 ). Fourth, senior management can provide resources, clarify project objectives (Kim and Wilemon 2002a , 2002b ), and create vision statements (Koen et al. 2014 ). Fifth, senior management can coordinate individual activities that span functional boundaries (Khurana and Rosenthal 1998 ).

Early customer involvement

The value of customer involvement in the front end of NPD is somewhat controversial. For example, some commentators argue that customers rarely provide rich or diverse information to firms (Granovetter 1982 ; Krackhardt 1992 ). Alam ( 2006 ), who warns against asking customers to suggest solutions for product problems, thinks that firms learn more from asking customers about the benefits they seek.

However, other researchers support the positive effects of customer involvement in product development. For example, Bacon et al. ( 1994 ) claims that NPD teams that do not include customer input in their development projects seldom produce successful products. Other researchers agree that firms should explore customer expectations and requirements before product development begins (Kim and Wilemon 2002b ; Smith et al. 1999 ; Verworn 2006 ; Verworn et al. 2008 ). Such information is useful because it clarifies project objectives early in the development stages (Cooper 1988 ; Cooper and Kleinschmidt 1987 ; Zien and Buckler 1997 ; Robbins and O'Gorman 2015 ; Verworn et al. 2008 ; Murphy and Kumar 1997 ). In addition, customers may offer product ideas at the front end of NPD that developers have not yet§ considered (Cooper et al. 2002 ; Kim and Wilemon 2002a ).

External cooperation beyond customers

External actors (e.g., suppliers) can offer assistance in the front end of NPD (Harvey et al. 2015 ). Murmann ( 1994 ) found that partnering with competent suppliers in the front end may reduce technological uncertainty. Effective supplier cooperation has also been found to decrease time-to-market, reduce development costs, and improve product quality (Kim and Wilemon 2002a , 2002b ). Khurana and Rosenthal ( 1997 ) show that some firms take a broad perspective on the value chain in the front end of NPD. Such firms, for example, address their suppliers’ requirements in the front end in order to acquire useful input for concept development.

Alignment between NPD and strateg y

From a more strategic perspective, researchers have identified the firm’s alignment of NPD with its general business strategy as a critical front-end success factor (Koen et al. 2001 ; Schröder and Jetter 2003 ; Trimi and Berbegal-Mirabent 2012 ; Khurana and Rosenthal 1997 ). Some researchers recommend that firms use their core competences in front-end projects to ensure that their business strategy stays in focus (Bacon et al. 1994 ; Smith et al. 1999 ).

Costa et al. ( 2013 ) found that inadequate strategic planning has a negative influence on the front end of NPD. Khurana and Rosenthal ( 1998 ) found that successful firms link business strategy, product strategy, and product-specific decisions. Good alignment between NPD and strategy also highlights the need for firms to engage in product portfolio planning. An example is the need to think strategically when planning an optimal mix of product attributes that meet customers’ wishes and expectations (Kim and Wilemon 2002b ).

Adequate degree of formalization

Several researchers propose that orderly and predictable management that reduces uncertainty in the front end benefits NPD (Khurana and Rosenthal 1998 ; Smith et al. 1999 ; De Brentani 2001 ; Boeddrich 2004 ). Other researchers conclude success is more likely if front-end activities are broken into modules or sub-phases, just as they are in the later stages of NPD (Cooper et al. 2002 ; Flint 2002 ; Verworn et al. 2008 ; Williams et al. 2007 ; Van Der Duin et al. 2014 ). Khurana and Rosenthal ( 1998 ) claim that management should explicitly communicate around NPD, clearly assign decision-making responsibilities, and specifically identify performance measurements. Markham ( 2013 ) corroborates these recommendations.

However, the relationship between formalization and success is not necessarily linear. Rather, the literature suggests the relationship has an inverted u-shape: Too little as well as too much formalization seems to damage the chance of success of front-end activities (Khurana and Rosenthal 1998 ). In particular, too much formalization may lead to rigidity that dampens creativity (Gassmann et al. 2006 ) that – in turn – may risk negative effects, particularly in cases of radical innovation (Florén and Frishammar 2012 ). Furthermore, recent research indicates that a low degree of formalization in the front end, in a climate that promotes psychological safety, is a possible avenue to front-end success (Nienaber et al. 2015 ).

Cooperation among functions and departments

Cross-functional cooperation has been identified as essential to front-end success (Bocken et al. 2014 ; Kim and Wilemon 2002a , 2002b ; Smith and Reinertsen 1992 ; Verganti 1997 ). One explanation may be that cross-functional cooperation benefits task analysis and reduces uncertainty in the front end (Moenaert et al. 1995 ). A second explanation may be that idea selection often takes place in meetings with representatives from different functional areas of the firm (Verworn 2006 ). In such meetings, cross-functional cooperation facilitates screening of ideas. A third explanation may be that cross-functional cooperation is necessary for “keeping an idea alive and active” (Conway and McGuinness 1986 , p. 287) and for creating new knowledge (Heller 2000 ).

Various researchers have examined types of cross-functional cooperation. Kohn ( 2006 ) identifies the R&D and marketing relationship as the most likely cooperative interdependency in the front end of NPD. These two areas take responsibility for product definition and product concept, which is then shared among the firm’s other functions and departments. The areas of manufacturing and process design should also cooperate in the front end of NPD to assure the feasibility of manufacturing proposed products (Bacon et al. 1994 ; Verganti 1997 ).

Creative organization culture

Creativity is clearly essential in the front end of NPD (Koen et al. 2001 ), as good ideas emerge in innovation-friendly cultures that foster the communication and development needed in the front end (Koen et al. 2014 ; Schröder and Jetter 2003 ; Smith et al. 1999 ) . A creative culture encourages a firm’s employees to use their innovative talent to produce and refine a steady stream of ideas (Kim and Wilemon 2002b ; Murphy and Kumar 1997 ). A creative culture also reinforces a firm’s market orientation by promoting consistency, efficiency, and productivity in the front end (Langerak et al. 2004 ).

Project Management capabilities

The project manager has ultimate responsibility for managing a project through its various stages – one of which is the front-end stage, including its sub-phases. A good project manager requests support, lobbies for resources, and manages technical problems and design issues. Khurana and Rosenthal ( 1997 ) found that project managers at successful firms are involved in all these tasks. As far as the front-end tasks, project managers also define goals, prioritize work, and provide leadership (Kim and Wilemon 2002b ). Project managers influence the product definitions, promote teamwork, facilitate strategic alignment, create a sense of joint team mission, and define project objectives (Koufteros et al. 2002 ; Rauniar et al. 2008 ).

Although researchers have not yet extensively investigated the characteristics of successful project management in the front end, the extant research shows that front-end activities may vary greatly as far as sequences, degree of overlap, and relative time duration (Nobelius and Trygg 2002 ; Reinertsen 1999 ). This means that front-end project managers must have many and varied capabilities.

Project-specific success factors

Evaluating-phase success factors, environmental scanning and analysis.

Firms should ensure that relevant external information is made available to projects in the front end of NPD. Bacon et al. ( 1994 ) state that firms should pay close attention to competitors’ current and planned products. They found that successful teams generally make such analyses whereas unsuccessful teams do not. They also found it is essential that firms pay attention to the applicable regulations and standards related to their NPD.

However, information about competitors, regulations, and standards is often firm-specific or industry-specific. Therefore, Börjesson et al. ( 2006 ) warn practitioners against taking too narrow a focus that may lead to ideas for products already available. Hence, it is recommended that firms adopt a scanning process, which includes more experimentation than the strategy literature suggests when they engage in NPD (e.g., Bocken et al. 2014 ).

Idea visioning and product championing

Committed enthusiasts in leadership positions are valuable for overcoming firms’ inertia that tends to support the status quo (Grant 1995 ; Griffiths-Hemans and Grover 2006 ; O’Regan and Ghobadian 2006 ; Markham 2013 ). Such enthusiasts are typically referred to as product champions (Conway and McGuinness 1986 ; Kim and Wilemon 2002b ) or as idea visionaries (Griffiths-Hemans and Grover 2006 ).

The idea originator, the individual who is affected by a specific problem, or the individual with new product responsibilities are possible product champions (Conway and McGuinness 1986 ). Their involvement in front-end activities is essential.

Idea visionaries and product champions are, by definition, highly committed to product ideas. This commitment, which is reflected in their perseverance despite feelings of frustration and uncertainty (Kim and Wilemon 2002a ), contributes to front-end results that add strategic value to the firm. Thus, they exert persistent, forward pressure on their firms (Conway and McGuinness 1986 ). Moreover, in providing the linkage between the project and the firm, they assist in interpreting the strategic meaning of product ideas (Heller 2000 ).

Preliminary technology assessment

A product’s required technology must be determined before product development begins (Cooper and Kleinschmidt 1987 ). This determination, which is mainly aimed at reducing technological uncertainty, is essential before significant resources are invested (Murmann 1994 ; Verworn et al. 2008 ). Cooper ( 1988 ) states that evaluation of technology requirements should address the product’s viability. This means addressing the product’s required technical solutions, its manufacturing feasibility, and its cost. In most successful projects, pre-development technology uncertainty is relatively low when technical requirements are explicitly defined and are shown to be technically feasible (Verworn 2006 ).

Idea refinement

The front end of NPD is frequently said to begin when a firm first spots an opportunity (Khurana and Rosenthal 1997 ; Kim and Wilemon 2002b ). Individuals create ideas (Boeddrich 2004 ; Kijkuit and van den Ende 2007 ). A product idea is a mental image of a solution to a problem (Griffiths-Hemans and Grover 2006 ). The qualities of the initial idea typically “make or break the project” (Cooper et al. 2002 , p. 22).

As ideas are generally nebulous in their early stages, they need refinement so that risks and problems associated with them can be identified (Boeddrich 2004 ; Zien and Buckler 1997 ). As many, if not most, ideas eventually prove unviable, idea refinement is especially important in the front end. Poor idea refinement often results in costly problems in later stages (Cooper 1988 ). Therefore, careful refinement of ideas allows firms to move rapidly from new ideas to assessable concepts (Smith et al. 1999 ).

Defining-phase success factors

Creation of a preliminary product concept.

In the lead-up to the finalization of a robust product definition, a team prepares product specifications (Kalyanaram and Krishnan 1997 ) using different sources (Backman et al. 2007 ). Eventually a preliminary product concept is developed that allows the firm to decide whether further development is warranted. If the decision is to move forward, the preliminary product concept enables the prioritization of activities in the development phase (Khurana and Rosenthal 1997 ; Kohn 2006 ). A preliminary product concept can be visualized as a picture, a drawing, a three-dimensional model, or a mock-up (Dickinson and Wilby 1997 ). Often, however, the concept is only described in text that explains its primary features and its customer benefits (Parish and Moore 1996 ).

Researchers have found that careful concept development is associated with project success (Cooper and Kleinschmidt 1987 ; Kim and Wilemon 2002b ; Song and Parry 1996 ; Verworn et al. 2008 ). In addition, concept development influences the final go/no-go decision on product development (Cooper 1988 ).

Bacon et al. ( 1994 ) found that to create a robust product definition, information, including feedback, from all the firm’s main functions is required. Insufficient information from these functions may explain why firms report severe difficulties in clarifying product concepts (e.g., Khurana and Rosenthal 1997 ).

In sum, a well-defined preliminary product concept allows for a better understanding of many important matters, including development time, costs, technical expertise, market potential, risk, and organizational fit (Kim and Wilemon 2002a ).

Project priorities

According to Khurana and Rosenthal ( 1997 ), project prioritization requires making trade-offs among scope (product functionality), scheduling (timing), and resources (cost). After observing a great deal of confusion about project priorities, they concluded that fuzzy project priorities were the single most important cause of time delays and product over-engineering. Murphy and Kumar ( 1997 ) support this finding in their conclusion that the clarification of project requirements is a key objective in the front end. Bacon et al. ( 1994 ) provide additional support in their finding that a priority list (i.e., a ranking of key product features) is crucial for developing robust product definitions.

Formalizing-phase success factors

Screening of the preliminary product concept.

Deficiencies in screening preliminary product concepts often cause problems in the development phase (Cooper 1988 ). Hence, it is not surprising that effective screening has been found to be an essential activity in the front end (Elmquist and Segrestin 2007 ; Kim and Wilemon 2002a , 2002b ; Kohn 2005 ; Rosenthal and Rosenthal and Capper 2006 ).

The purpose of such screening is to evaluate product concepts. In principle, firms can make two screening mistakes: rejection of “good” product concepts or acceptance of “bad” product concepts (Reinertsen 1999 ). According to Lin and Chen ( 2004 ), abandoning inferior product concepts at an early stage often results in large cost savings since costs increase progressively in the NPD process. However, Cooper ( 1988 ) found that screening was most ineffective when it was used only to screen out obvious no-go projects. Firms should therefore assure that their screening activities are not conducted in a way that risks screening out good ideas and product concepts.

Murphy and Kumar ( 1997 ) found that screening takes place in two related domains: business analysis and feasibility analysis. In business analysis, the firm evaluates the viability of a new product concept as a business proposition. In feasibility analysis, the firm decides if it has the resources to support the development of a product concept.

However, if the screening of preliminary product concepts is too restrictive, potentially valuable ideas may be eliminated. Conway and McGuinness ( 1986 ) found that an overreliance on formal processes in the front end might slow the momentum that the concept acquired in the informal debate. An additional complexity is that research has identified a tendency for tacit rules to act as filters when screening ideas (McAdam and Leonard 2004 ). The conclusion is that firms need to consider both the formal and the informal aspects of concept screening.

Cross-functional executive review committee

Prior research shows that cross-functionality is a success factor at the executive level as well as at the department and functional levels. An executive review committee for the front end adds various competencies and perspectives. Khurana and Rosenthal ( 1997 ) found that product success in the front end is associated with the existence of a cross-functional, executive review committee. They state that the committee members’ roles and decision responsibilities must be well-defined. The review criteria must also be explicit. In addition, they emphasize the importance of the on-going interaction between the committee and the development team.

Discussion and concluding remarks

There are many explanations for the failure of new products. Some explanations relate to problems in the front-end activities of NPD. Complex information may be inadequately processed (Khurana and Rosenthal 1997 ), decisions may be taken on an ad hoc basis (Montoya-Weiss and O'Driscoll 2000 ), and/or conflicting organizational pressures may create unmanageable complexity and uncertainty (Chang et al. 2007 ). In explaining these problem areas, this article helps managers and their teams identify the factors that contribute to the success of front-end activities in NPD.

This article uses a review of the literature on the front end in NPD as the inspiration for the creation of a front-end conceptual framework. The framework is built on two groups of success factors for front-end activities identified in the literature: foundational success factors and project-specific success factors. The framework also highlights the interplay between these success factors that is relevant for firms working with new product ideas and concepts, regardless of firm size.

By visualizing these success factor groups in a conceptual framework, we provide firms and their managers with an analytical tool useful for working with front-end activities in NPD. In tabular and textual presentations, we list the success factors, ask key questions related to these factors, and describe the ideal condition/situation action responses. Product managers and their teams can use our conceptual framework to identify the front-end success factors and thereby better deal with this early stage of NPD. Use of the framework can reduce development time and mitigate the problems associated with rework in front-end activities that are characterized by great complexity and uncertainty.

At present, the theory on the front end in NPD is rather weak when judged by the evaluation criteria for theory development (Bacharach 1989 ; Edmondson and McManus 2007 ; Suddaby 2010 ). About 95% of the articles we reviewed do not address the issue of performance measurement (i.e., the dependent variables) although there are exceptions (e.g., Khurana and Rosenthal 1997 ; Montoya-Weiss and O'Driscoll 2000 ). We were not surprised, however, by our finding that the NPD literature, with the exceptions noted above, is not particularly theoretical. We were not surprised, however, by our finding that the NPD literature, with the exceptions noted above, is not particularly theoretical. As Daft ( 1985 ) explains, research topics behave like product life cycles. When a research field is new, many researchers add new knowledge. Because the front-end literature is relatively new, it is still open to new theoretical observations.

Given the gaps in the literature on front-end success in NPD, it seems worthwhile to address this topic more specifically. This effort requires an understanding of the front end itself. Where, when, and how does the front end begin? What does it look like? Where and how does it end? Khurana and Rosenthal ( 1997 , 1998 ), for example, who do not explicitly examine the creative act of idea generation, conceive of the beginning of the front end as the point when firms “first recognize, in a semi-formal way, an opportunity” (Khurana and Rosenthal 1997 , p. 106). This statement implies that when a firm has recognized an opportunity, that idea, which originates very possibly with a single individual, must be shared collectively among others in the firm. The statement also implies that sources of ideas (e.g., from customers, suppliers, etc.) fall outside the front end. Although relevant, our framework does not capture this view, but instead focuses on the management inside the company.

We found greater agreement among researchers that the front end concludes when firms decide to approve or to abort a NPD project idea (Herstatt et al. 2004 ; Khurana and Rosenthal 1998 ; Verworn 2006 ). Because the front end concludes with a go/no-go decision, the “output” of the front end should be a product definition rather than a product concept . The reason is that a go/no-go decision cannot be made without consideration of available resources, market estimates, and business plans (e.g., Herstatt et al. 2004 ; Verworn 2006 ).

To this background, our position is that the front end begins when the organization recognizes that an idea presents an opportunity, and that the front end concludes with approval or disapproval of the proposed project. Moreover, because the front end concludes with a go/no-go decision (i.e., when a robust product definition exists), we argue that a reasonable evaluation of front-end success depends on two conditions: the quality and status of the product definition when it “leaves” the front end; and the usefulness of the product definition relative to enlightened decision-making about product development (Florén and Frishammar 2012 ).

Our study adds to previous research on the critical success factors for front-end innovation (e.g., Russell and Tippett 2008 ) in that it presents a general synthesis of these factors that previous research has identified. This synthesis can be useful to researchers as they expand on this area of research, especially from a theoretical perspective, and to practitioners who can use our conceptual framework as an analytical tool when working with front-end activities in NPD.

Future research suggestions

We offer several suggestions for future research. We assume some success factors will moderate the relationship between front-end activities and front-end success. Extant research, however, does not clearly address the relationship between foundational success factors and project-specific success factors. For example, a creative organizational culture might moderate the relationship between early customer involvement/active environmental scanning and success in front-end activities. In firms that have a creative culture, idea refinement might advance creatively without early customer involvement/active environmental scanning, especially in the development of radically new products. Conversely, when firms lack a creative culture, early customer involvement/active environmental scanning might substitute for a creative culture. Therefore, we recommend that researchers conduct quantitative studies on the moderating role of foundational success factors in positive relationships between front-end development and front-end performance.

Another opportunity for future research stems from one shortcoming of extant research and of our conceptual framework. Our understanding of the iterative aspects in the front end is insufficient. While prior research emphasizes the importance of probing and learning in the front end (e.g., Verganti 1997 ; Florén and Frishammar 2012 ), it not clear how the success factors in our conceptual framework relate to such activities or how iterations play out as a consequence of such activities. Therefore, we recommend that researchers examine the relationship between the success factors of probing and learning in the front end of NPD.

We admit that our review does not reveal how the context of the front-end activities influences the success factors. Although, the results are developed based on empirical and conceptual studies, further investigation on how well the proposed successful factors holds in different context would be beneficial, for example in the context of new entrepreneurial ventures (George et al. 2016 ). From this follows that our study has certain limitations that should be considered when interpreting the results.

Thus, we encourage researchers from entrepreneurship and innovation management to take our study as a starting point for providing novel insights related to the front end of NPD.

Akbar, H., & Tzokas, N. (2013). An exploration of new product development’s front-end knowledge conceptualization process in discontinuous innovations. British Journal of Management, 24 (2), 248–263.

Article   Google Scholar  

Alam, I. (2006). Removing the fuzziness from the fuzzy front-end of service innovations through customer interactions. Industrial Marketing Management, 35 (4), 468–480.

Bacharach, S. B. (1989). Organizational theories: Some criteria for evaluation. Academy of Management Review, 14 (4), 496–515.

Backman, M., Börjesson, S., & Setterberg, S. (2007). Working with concepts in the fuzzy front end: Exploring the context for innovation for different types of concepts at Volvo cars. R&D Management, 37 (1), 17–28.

Bacon, G., Beckman, S., Mowery, D., & Wilson, E. (1994). Managing product definition in high-technology industries: A pilot study. California Management Review, 36 (3), 32–56.

Bocken, N. M. P., Farracho, M., Bosworth, R., & Kemp, R. (2014). The front-end of eco-innovation for eco-innovative small and medium sized companies. Journal of Engineering and Technology Management, 31 (1), 43–57.

Boeddrich, H.-J. (2004). Ideas in the workplace: A new approach towards organizing the fuzzy front end of the innovation process. Creativity and Innovation Management, 13 (4), 274–285.

Börjesson, S., Dahlsten, F., & Williander, M. (2006). Innovative scanning experiences from an idea generation project at Volvo cars. Technovation, 26 (7), 775–783.

Brown, S. L., & Eisenhardt, K. (1995). Product development: Past research, present findings, and future directions. Academy of Management Review, 20 (2), 343–378.

Chang, S. L., Chen, C. Y., & Wey, S. C. (2007). Conceptualizing, assessing, and managing front-end fuzziness in innovation/NPD projects. R&D Management, 37 (5), 469–478.

Chesbrough, H. (2003). The logic of open innovation: Managing intellectual property. California Management Review, 45 (3), 33–58.

Chesbrough, H. (2006). Open innovation: The new imperative for creating and profiting from technology . Harvard Business Press.

Conway, H. A., & McGuinness, N. W. (1986). Idea generation in technology-based firms. Journal of Product Innovation Management, 3 (4), 276–291.

Cooper, R. G. (1988). Predevelopment activities determine new product success. Industrial Marketing Management, 17 (3), 237–247.

Cooper, R. G., & Kleinschmidt, E. J. (1987). New products: What separates winners from losers? Journal of Product Innovation Management, 4 (4), 169–184.

Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2002). Optimizing the stage-gate process: What best-practice companies do, Part I. Research-Technology Management, 45 (5), 21–27.

Costa, J. M., Rozenfeld, H., Amaral, C. S. T., Marcacinit, R. M., & Rezende, S. O. (2013). Systematization of recurrent new product development management problems. Engineering Management Journal, 25 (1), 19–34.

Daft, R. L. (1985). Why I recommend that your manuscript be rejected and what you can do about it. In L. L. Cummings & P. J. Frost (Eds.), Publishing in the organizational sciences (pp. 193–209). Homewood: Richard D. Irwin, Inc..

Google Scholar  

De Brentani, U. (2001). Innovative versus incremental new business services: Different keys for achieving success. Journal of Product Innovation Management, 18 (3), 169–187.

De Brentani, U., & Reid, S. E. (2012). The fuzzy front-end of discontinuous innovation: Insights for research and management. Journal of Product Innovation Management, 29 (1), 70–87.

De Cleyn, S. H., Braet, J., & Klofsten, M. (2015). How human capital interacts with the early development of academic spin-offs. International Entrepreneurship and Management Journal, 11 (3), 599–621.

Dickinson, J. R., & Wilby, C. P. (1997). Concept testing with and without product trial. Journal of Product Innovation Management, 14 (2), 117–125.

Edmondson, A. C., & McManus, S. E. (2007). Methodological fit in management field research. Academy of Management Review, 32 (4), 1155–1179.

Elmquist, M., & Segrestin, B. (2007). Towards a new logic for front end management: From drug discovery to drug design in pharmaceutical R&D. Creativity and Innovation Management, 16 (2), 106–120.

Flint, D. J. (2002). Compressing new product success-to-success cycle time: Deep customer value understanding and idea generation. Industrial Marketing Management, 31 (4), 305–315.

Florén, H., & Frishammar, J. (2012). From preliminary ideas to corroborated product definitions: Managing the front end of new product development. California Management Review, 54 (4), 20–43.

Gassmann, O., Sandmeier, P., & Wecht, C. H. (2006). Extreme customer innovation in the front-end: Learning from a new software paradigm. International Journal of Technology Management, 33 (1), 46–66.

George, N. M., Parida, V., Lahti, T., & Wincent, J. (2016). A systematic literature review of entrepreneurial opportunity recognition: Insights on influencing factors. International Entrepreneurship and Management Journal, 12 (2), 309–350.

Goldenberg, J., Lehmann, D. R., & Mazursky, D. (2001). The idea itself and the circumstances of its emergence as predictors of new product success. Management Science, 47 (1), 69–84.

Granovetter, M. S. (1982). The strength of weak ties: A network theory revisited. In P. Marsden & N. Lin (Eds.), Social Structure and Network Analysis . Beverly Hills: Sage.

Grant, R. (1995). Contemporary strategy analysis . Cambridge: Blackwell.

Griffiths-Hemans, J., & Grover, R. (2006). Setting the stage for creative new products: Investigating the idea fruition process. Journal of the Academy of Marketing Science, 34 (1), 27–39.

Harvey, J. F., Cohendet, P., Simon, L., & Borzillo, S. (2015). Knowing communities in the front end of innovation. Research-Technology Management, 58 (1), 46–54.

Heller, T. (2000). If only we'd known sooner: Developing knowledge of organizational changes earlier in the product development process. IEEE Transactions on Engineering Management, 47 (3), 335–359.

Herstatt, C., Verworn, B., & Nagahira, A. (2004). Reducing project related uncertainty in the “fuzzy front end” of innovation: A comparison of German and Japanese product innovation projects. International Journal of Product Development, 1 (1), 43–65.

Kalyanaram, G., & Krishnan, V. (1997). Deliberate product fuzzy front end of new product developmentn process. Journal of Marketing Research, 34 (2), 276–285.

Khurana, A., & Rosenthal, S. R. (1997). Integrating the fuzzy front end of new product development. Sloan Management Review, 38 (2), 103–120.

Khurana, A., & Rosenthal, S. R. (1998). Towards holistic "front ends" in new product development. Journal of Product Innovation Management, 15 (1), 57–74.

Kijkuit, B., & van den Ende, J. (2007). The organizational life of an idea: Integrating social networks, creativity and decision-making perspectives. Journal of Management Studies, 44 (6), 863–882.

Kim, J., & Wilemon, D. (2002a). Focusing the fuzzy front-end in new product development. R&D Management, 32 (4), 269–279.

Kim, J., & Wilemon, D. (2002b). Strategic issues in managing innovation’s fuzzy front-end. European Journal of Innovation Management, 5 (1), 27–39.

Koen, P., Ajamian, G., Burkart, R., Clamen, A., Davidson, J., D’Amore, R., Elkins, C., Herald, K., Incorvia, M., Johnson, A., Karol, R., Seibert, R., Slavejkov, A., & Wagner, K. (2001). Providing clarity and a common language to the "fuzzy front end". Research-Technology Management, 44 (2), 46–55.

Koen, P. A., Bertels, H. M. J., & Kleinschmidt, E. (2014). Managing the front end of innovation-part I: Results from a three-year study. Research-Technology Management, 57 (2), 34–43.

Kohn, K. (2005). Idea generation in new product development through business environmental scanning: The case of XCar. Marketing Intelligence & Planning, 23 (6/7), 688–704.

Kohn, K. (2006). Managing the balance of perspectives in the early phase of NPD: A case study from the automotive industry. European Journal of Innovation Management, 9 (1), 44–60.

Koufteros, X. A., Vonderembse, M. A., & Doll, W. J. (2002). Integrated product development practices and competitive capabilities: The effects of uncertainty, equivocality, and platform strategy. Journal of Operations Management, 20 (4), 331–355.

Krackhardt, D. (1992). The strength of strong ties: The importance of philos in organizations. In N. Nohria & R. G. Eccles (Eds.), Networks and organizations: Structure, form and action (pp. 216–239). Boston: HBS Press.

Langerak, F., Hultink, E. J., & Robben, H. S. J. (2004). The role of predevelopment activities in the relationship between market orientation and performance. R&D Management, 34 (3), 295–309.

Lauto, G., Valentin, F., Hatzack, F., & Carlsen, M. (2013). Managing front-end innovation through idea markets at Novozymes: Idea markets stimulate creativity and enable recombination of existing knowledge in large corporations. Research-Technology Management, 56 (4), 17–26.

Lin, C.-T., & Chen, C.-T. (2004). New product go/no-go evaluation at the front end: A fuzzy linguistic approach. IEEE Transactions on Engineering Management, 51 (2), 197–207.

Markham, S. K. (2013). The impact of front-end innovation activities on product performance. Journal of Product Innovation Management, 30 (1), 77–92.

McAdam, R., & McClelland, J. (2002). Sources of new product ideas and creativity practices in the UK textile industry. Technovation, 22 (2), 113–121.

McAdam, R., & Leonard, D. (2004). Reengineering based inquiry into innovation in the front end of new product and service development processes. International Journal of Product Development, 1 (1), 66–91.

Moenaert, R. K., De Meyer, A., Souder, W. E., & Deschoolmeester, D. (1995). R&D/marketing communication during the fuzzy front-end. IEEE Transactions on Engineering Management, 42 (3), 243–258.

Montoya-Weiss, M. M., & Calantone, R. M. (1994). Determinants of new product performance: A review and meta-analysis. Journal of Product Innovation Management, 11 (5), 397–417.

Montoya-Weiss, M. M., & O'Driscoll, T. M. (2000). From experience: Applying performance support technology in the fuzzy front end. Journal of Product Innovation Management, 17 (2), 143–161.

Murmann, P. A. (1994). Expected development time reductions in the German mechanical engineering industry. Journal of Product Innovation Management, 11 (3), 236–252.

Murphy, S. A., & Kumar, V. (1996). The role of predevelopment activities and firm attributes in new product success. Technovation, 16 (8), 431–441.

Murphy, S. A., & Kumar, V. (1997). The front end of new product development: A Canadian survey. R&D Management, 27 (1), 5–15.

Nienaber, A. M. I., Holtorf, V., Leker, J., & Schewe, G. (2015). A climate of psychological safety enhances the success of front end teams. International Journal of Innovation Management, 19 (2), 1–34.

Nobelius, D., & Trygg, L. (2002). Stop chasing the front end process - management of the early phases in product development projects. International Journal of Project Management, 20 (5), 331–340.

O’Regan, N., & Ghobadian, A. (2006). Innovation in NTBFs: Does leadership really matter? International Entrepreneurship and Management Journal, 2 (2), 299–314.

Parish, T. D., & Moore, L. E. (1996). Nonassembled product development. In M. D. Rosenau (Ed.), The PDMA handbook of new product development (pp. 287–296). Hoboken, NJ: John Wiley and Sons.

Popper, K. R. (1959). The logic of scientific discovery . London: Hutchinson.

Popper, K. R. (1972). Objective knowledge: An evolutionary approach . Oxford: Clarendon.

Rauniar, R., Doll, W., Rawski, G., & Hong, P. (2008). The role of heavyweight product manager in new product development. International Journal of Operations & Production Management, 28 (2), 130–154.

Reinertsen, D. G. (1999). Taking the fuzziness out of the fuzzy front end. Research-Technology Management, 42 (6), 25–32.

Robbins, P., & O'Gorman, C. (2015). Innovating the innovation process: An organisational experiment in global pharma pursuing radical innovation. R&D Management, 45 (1), 76–93.

Rosenthal, S. R., & Capper, M. (2006). Ethnographies in the front end: Designing for enhanced customer experiences. Journal of Product Innovation Management, 23 (3), 215–237.

Russell, R. K., & Tippett, D. D. (2008). Critical success factors for the fuzzy front end of innovation in the medical device industry. Engineering Management Journal, 20 (3), 36–43.

Salter, A., & Gann, D. (2003). Sources of ideas for innovation in engineering design. Research policy, 32 (8), 1309–1324.

Schröder, H.-H., & Jetter, A. J. M. (2003). Integrating market and technology knowledge in the fuzzy front end: An FCM-based action support system. International Journal of Technology Management, 26 (5/6), 517–539.

Seidel, V. P. (2007). Concept shifting and the radical product development process. Journal of Product Innovation Management, 24 (6), 522–533.

Smith, P. G., & Reinertsen, D. G. (1992). Shortening the product development cycle. Research-Technology Management, 35 (3), 44–49.

Smith, R., Herbein, C., & Morris, R. C. (1999). Front-end innovation at AlliedSignal and Alcoa. Research-Technology Management, 42 (6), 15–24.

Song, X. M., & Parry, M. E. (1996). What separates Japanese new product winners from losers. Journal of Product Innovation Management, 13 (5), 422–439.

Suddaby, R. (2010). Editor's comments: Construct clarity in theories of management and organization. The Academy of Management Review, 35 (3), 346.

Trimi, S., & Berbegal-Mirabent, J. (2012). Business model innovation in entrepreneurship. International Entrepreneurship and Management Journal, 8 (4), 449–465.

Van Der Duin, P. A., Ortt, J. R., & Aarts, W. T. M. (2014). Contextual innovation management using a stage-gate platform: The case of Philips shaving and beauty. Journal of Product Innovation Management, 31 (3), 489–500.

Verganti, R. (1997). Leveraging on systemic learning to manage the early phases of product innovation projects. R&D Management, 27 (4), 377–392.

Verworn, B. (2006). How German measurement and control firms integrate market and technological knowledge into the front end of new product development. International Journal of Technology Management, 34 (3–4), 379–389.

Verworn, B., Herstatt, C., & Nagahira, A. (2008). The fuzzy front end of Japanese new product development projects: Impact on success and differences between incremental & radical projects. R&D Management, 38 (1), 1–19.

Williams, M. A., Kochhar, A. K., & Tennant, C. (2007). An object-oriented reference model of the fuzzy front end of the new product introduction process. International Journal of Advanced Manufacturing Technology, 34 (7–8), 826–841.

Zien, K. A., & Buckler, S. A. (1997). Dreams to market: Crafting a culture of innovation. Journal of Product Innovation Management, 14 (4), 274–287.

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Florén, H., Frishammar, J., Parida, V. et al. Critical success factors in early new product development: a review and a conceptual model. Int Entrep Manag J 14 , 411–427 (2018). https://doi.org/10.1007/s11365-017-0458-3

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ORIGINAL RESEARCH article

Impact of critical success factors on project success through the mediation of knowledge creation.

• 1 School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China
• 2 Riphah School of Business and Management, Riphah International University, Lahore, Pakistan
• 3 Department of Economics & Business Administration, University of Education Lahore, Multan, Pakistan
• 4 Department of Environment Science, University of Wah, Wah Cantt, Pakistan
• 5 Department of Finance, Babes-Bolyai University, Cluj-Napoca, Romania

Several factors affect health project success. This research aims to examine the impact of critical success factors on health project success and show how the essential factors of success interact with knowledge creation to impact health project success. The self-administered questionnaire was distributed to collect data from 246 managers, supervisors and zonal supervisors of DHQ hospital Attock and PIMS hospital Islamabad. The analysis was done using Smart PLS to understand the effect of exogenous variables over endogenous variables and the impact of mediating variables between two constructs. The results show that all critical success factors (MGTRF, DRF, CRF, PMRF, CLRF) are significantly affecting project success, in addition, tacit knowledge creation mediate the association between critical success factors and project success. In contrast, explicit knowledge creation does not mediate the relationship between critical success factors and project success. This study intends to expand the theoretical understanding of process improvement by providing practical insights into the impact of strategies used by project managers to develop new knowledge by capturing explicit and implicit information. This study also reinforces past findings and increases awareness about using knowledge creation to gain a competitive advantage in the health sector.

Introduction

According to a Pakistan economic review (2017–18), the government spends 0.35% of its total GDP on health care. There are currently 5,382 clinics, 1,207 hospitals, 5,404 basic health care units, and 696 child care and maternity units in Pakistan. However, Pakistan faces major health concerns due to poor and unfavorable health circumstances. According to Khan and Van Den Heuvel (2006) , numerous governments in Pakistan have worked on health programmes, but the benchmark has not yet been set due to various internal factors. Pakistan also announced the “National Health Policy” last year, aiming to improve society's better health conditions. Policymakers and top management may not take health project success seriously, limiting health development in Pakistan. To resolve the above issues, the government needs to consciously take part in health issues and look at every step to complete the health services. Sheikh and Jensen (2019) results indicate that due to the poor health conditions in Pakistan, it has to suffer from various diseases in routine life. The population appears as a genetic problem on the international level; the global world focuses on genetic disorders due to health issues, how can reduce genetic diseases, and what measures are required to cope with them. According to Habib et al. (2017) , polio teams are attacked by terrorists due to security concerns; thus, hospitals must take sufficient precautions for such treatments. Good planning is only possible when top management is fully aware of the issue, and knowledge gained from experience.

Knowledge has played an important role in the success of projects and is the key to innovation and competitiveness for an organization ( Canonico et al., 2019 ; Yang et al., 2021 ). Studies have shown that employees working on a project acquire new knowledge (both explicit and tacit) from their encounters ( Todorović et al., 2015 ). Excellent performance and greater project success could be achieved after creating and utilizing knowledge in the product, business process, and services. Knowledge, both explicit and tacit about the previous project leads to project success. Tactic knowledge is created through discussions with stakeholders, office colleagues, project partners, consultants, and experts. Values, beliefs, assumptions, and mental models comprise tacit knowledge. While explicit knowledge is codified, implicit knowledge is not.

A database, web pages, emails, and documents store explicit knowledge ( Boon Sin et al., 2015 ). Whenever a problem arises in the project, it is necessary to schedule sessions with a professional. Professionals and experts share ideas with employees. Professionals acquire insights from documented information and use that knowledge for problem resolution ( Canonico et al., 2019 ). Similarly, Japanese car manufacturing creates competitive advantage and innovation dynamically by using Nonaka et al. (2000) SECI model ( Allal-Chérif and Makhlouf, 2016 ). We can also use this theoretical framework in health projects to analyze knowledge creation practices because health project has an important and huge impact on the nation ( Sheikh and Jensen, 2019 ). This study is based on Nonaka theory. This study also expands the model of Todorović et al. (2015 ) by introducing knowledge creation as a mediator and project success (customer happiness) as a dependent variable. The project's effectiveness has been extensively discussed in the literature, but more research is needed to uncover the most influential CSFs that influence health project success ( Kiani Mavi and Standing, 2018b ; Maqbool and Sudong, 2018 ). The study investigates “the impact of CSFs on project success via knowledge creation mediation” ( Todorović et al., 2015 ).

This study intends to achieve the following objective;

• To determine the effect of critical success factors on project success.

• To determine the effect of knowledge creation on project success.

• To determine the mediating role of tacit knowledge creation between the critical success factors and project success.

• To determine the mediating role of explicit knowledge creation between the critical success factors and project success.

To achieve the above objectives, this study focuses on the following issues.

• Is the critical success factors having an impact on project success?

• Is knowledge creation significantly related to project success?

• Does tacit knowledge creation mediate the effect of critical success factors on project success?

• Does explicit knowledge creation mediate the effect of critical success factors on project success?

Significance of the Study

In this research we will find all those critical success factors that are leading project toward success. CSFs are those few area of activity that is actually causing the success of the project. These CSFs have been used in many industries before, like manufacturing industry, construction industry, information system and financial service, etc. the intensity and magnitude of different factors have been identified by different researchers, but in this study we will examine that how many and in which degree these factors are influencing a project's success. According to their importance we will also take an order of these factors. We will also examine that how the tacit and explicit dimension of knowledge creation positively influence between CSFs (MGT, Procurement, Manager, Contractor, and Stakeholder related factors) of project success. In the concluding part of the study a clearer picture has been developed that highlights the factors and their relationship with project success in accordance with the local industry view points. Through this research manager come to know about CSFs factors which affect the project success. And when these factors efficiently manage then many projects could reach the desired success. The study is significant because the top management will get awareness that their strong coordination with their subordinate are the main reason for project success. It makes the authorities realize that how they can use different strategies to handle the critical success factors in the project so that the work environment will be more friendly and its lead project toward success. It helps the policy maker to understand the impact of critical success factors on project success, so that the different policies can be made to handle these critical success factors which may affect project success badly.

This study is organized into six sections. In the first section, we shall discuss the study's context. The second section will present a high-level summary of the research, theories, and models related to project success, critical success factors, and knowledge creation. The third part will give a conceptual framework and operational definition of the variables. The fourth section discusses research methodologies, such as data gathering and the construction of metrics. The fifth portion contains the analysis, discussion of the results, study limitations, managerial implications, recommendations for future work, and study conclusion. In the study's conclusion, a clearer picture of the components and their link with project performance has been produced.

Literature Review

Customer satisfaction.

Customer satisfaction has been mentioned in the project management literature ( Kerzner, 2002 ), but it has rarely been included in the formal assessment of success. The client is the one that spends the majority of their time on developed facilities, are actually working and live with the final products. It is critical to ensure that the finished project satisfies the client's/customer's expectation. As per Liu and Walker (1998) , satisfaction should be regarded a success criterion. Customer functional performance, expectations, and technical specifications, as demanded by clients, are critical in project business. This rationale is that “the client is the king/boss of every business/organization/project.” As a result, client happiness is the primary goal of any firm.

A company must first meet its customers' expectations to ensure customer satisfaction. If the project satisfied the end-user ( Torbica and Stroh, 2001 ), it could be considered effectively completed in the long run. De Wit (1986) defines project success as determining whether the aim and goal are met. Customer happiness is more vital to success than reaching any specific project objectives. Project deliverables are also critical to achieving the customer's satisfaction level. If the customer is pleased with the result/product, the project has been deemed successful.

Critical Success Factor

Several research conducted over the last few decades has demonstrated the significance of critical success factors. Denial was the first to introduce the concept of critical success criteria in 1961. In 1982, Rock art used the term Critical Success Factors for the first time. These are “factors that contribute to an organization's success and are important for the achievement of an organization's mission,” according to Haleem et al. (2012) . Rubin and Seelig (1967) pioneered the critical success factor in project management, assessing the influence of the project manager's experience on project success. A critical success factor is a business strategy. Essential success factors are related to a specific attribute or condition of the industry.

Because each country has its own set of rules and regulations, legal constraints, and operational environment, Critical Success Factors differ when we travel from one country to another and from one project to the next. Several dimensions of critical success factor have been specified in detail by several authors ( Ashley et al., 1987 ; Pinto and Slevin, 1987 ; Belassi and Tukel, 1996 ; Eriksson, 2008 ; Yang et al., 2009 ; Ibbs et al., 2010 ; Ahmadabadi and Heravi, 2019 ). According to Saqib et al. (2008) , seven critical success factor influence project success. These dimensions include design-related factors, project management-related factors, contractor related factors, economic and business environment-related factors, client related factors, procurement related factors, and program manager related factors.

In his study, the most important factors were project managers' skills, contractors' experience, contractors' cash flow, site management, prompt decisions by clients, prior management experience, solving and decision-making efficacy, supervision, and clients' decision-making capacity. The findings show a positive association between design-related factors, project management-related factors, contracting related factors, business and work environment-related factors, client-related factors, procurement related factors, project manager related factors, and project success. Many project managers may find this study valuable in analyzing the success of their current project. A project manager can evaluate the present value of their program and compare actual and projected values for considered successful elements in a knowledge management activity. It is a useful hint to encourage us to investigate these aspects in the health sector.

Dimensions of Critical Success Factors

According to Saqib et al. (2008) , the Critical Success Factor has seven dimensions.

• Design related factors

• Project Management related factors

• Contractor related factors

• Business and Work Environment related factors

• Client related factors

• Procurement related factors

• Project Managers related factors.

Management Related Factors

One technique to ensure project success is to meet the criteria of Hubbard's project management actions ( Hubbard, 1990 ; Misztal-Okońska et al., 2020 ). Shen and Liu (2003) identified management-related critical issues. The findings highlight two important aspects of project success: “coordination among the management team and collaborative efforts by the client, contractor, and consultant.” Kiani Mavi and Standing (2018a) defined critical success factors (CSFs) in project management and classified them into five criteria groups: external environment, organization, project management, project, and sustainability. Data were collected from 26 Australian project managers in the construction industry for this study to establish the dependency and weight of the CSFs.

According to Mavi and Standing's findings, the biggest weights are allocated to top management and sponsor support, end-user imposed constraints and stakeholder expectation. Previous studies have not adequately addressed these issues. To complete the project, the project manager would organize and enforce it utilizing management tools ( Jaselskis and Ashley, 1991 ). These elements (control mechanism, decision-making efficacy, feedback capabilities, adequate communication, risk identification and allocation, plan and schedule of project followed, and previous project management experience of related projects) are extremely important in health projects; if these factors are handled effectively, then it will ensure project accomplishment.

In a health project, project management-related factors such as “feedback capability, communication system, planning effort, organizational structure, control mechanism, control of subcontractors, safety and quality assurance programme, and finally the overall managerial actions” will impact. According to Pinto and Slevin (1987) , communication and troubleshooting, monitoring and feedback, senior management support, and a timeline must all be present at all stages of the implementation process. Top management support has been identified as a critical success factor in several studies ( Belassi and Tukel, 1996 ; Young and Jordan, 2008 ; Dikic et al., 2020 ). Another study found that top management related factors had a positive relationship with project success ( Shenhar et al., 1997 ; Jugdev et al., 2001 ; Saqib et al., 2008 ).

H1a: Top management related factors is positively and significantly related to project success .

Client Related Factors

The project leader, advisors, consumer, vendor, operator, contractor, and manufacturers are significant project participants ( Chua et al., 1999 ). The “client” could be either public or private. Client-related aspects include “client type and experience, project organization expertise, client characteristics, project funding, owner construction sophistication, client confidence, well-defined scope, client project management, and owner risk aversion” ( Chan and Kumaraswamy, 1997 ; Songer and Molenaar, 1997 ; Dissanayaka and Kumaraswamy, 1999 ). The project was completed under the client's specifications. As a result, there is a need to effectively engage with the client, keep them updated frequently, and make changes to the project to be completed successfully.

Client experience, the client's capability to brief the project, the client's ability to make appropriate decisions, and the client's ability to clearly define roles are all important elements to consider in the project's completion.

It is a useful hint to encourage us to investigate these aspects in the health sector. Another study found that client-related factors were positively connected to project success ( Walker, 1995 ; Saqib et al., 2008 ).

H1b: Client related factors are positively and significantly associated with project success .

Design Related Factors

According to Salmeron (2009) , a project design phase is one way to satisfy the owner's requirements economically and optimally. The project's design phase can be depicted structurally. According to Chalabi and Camp (1984) , adequate planning at the beginning of a project can reduce the likelihood of cost overruns and delays. As a result, the project will be completed within the time-frame indicated, and the project will be delivered to the customer as promised. Designers play an important role in a project because their work continues from completion to inception.

According to Chan and Kumaraswamy (1997) , design team-related factors include project design complexity, design team experience, and mistakes and delays in providing project design documents. According to Chan and Kumaraswamy (1997) , the primary cause of project delays was the consultant's lack of design experience. Inexperienced design consultants do not adequately design a project, resulting in time and cost overruns and project delays. Another study discovered that design related factors had a positive link with project success ( Chalabi and Camp, 1984 ; Saqib et al., 2008 ).

H1c: Design related factors are positively and significantly associated with project success .

Contractor Related Factors

Contractors and subcontractors begin their primary responsibilities once a project is completed. A lack of relevant contractor planning and monitoring experience and a lack of design experience on the part of consultants would result in a project time overrun. The variables include: “management of the project site, subcontracting involvement and supervision, experiences of a contractor, cash flows of contractor, speed of information flow, and cost control system effectiveness” ( Chan and Kumaraswamy, 1997 ; Dissanayaka and Kumaraswamy, 1999 ). Lu et al. (2008) described contractor related critical success factors; it's mainly include, insufficient contractor expertise, labor productivity, owner intervention, financing and payment, inappropriate planning, slow decision making, and subcontractors. According to Odeh and Battaineh (2002) , consultants and contractors agreed that the top 10 most critical success factors are bad contractor experience, labor productivity, owner intervention, financing and payment, inappropriate planning, slow decision making, and subcontractors. When an organization can deal with these factors efficiently, it can complete a project on time, at a low cost, and with high quality for its clients. As a result, the project undertaken by the project organization is successful. Another study found that contractor-related factors (particularly cash flow and contractor experience) positively correlated with project success ( Saqib et al., 2008 ).

H1d: Contractor's related factors are positively and significantly related to project success .

Project Manager Related Factors

The project manager is another significant stakeholder in projects. Project manager skills impact scheduling, project planning, and communication ( Belassi and Tukel, 1996 ). The engagement and devotion of project managers are crucial for project completion and will replicate this if the project manager is overseeing many projects simultaneously. The project manager's skill and qualities, competency, devotion to the project, experience, and project authority are all project manager-related factors ( Chua et al., 1999 ). The project manager is in charge of ensuring that the project is managed effectively and efficiently.

As a result, the project manager must be proficient in project management. Project management competency/skill, project-related experience, leadership ability, technical capabilities (with contractor and subcontractor), and reporting abilities are critical to project success. Another study revealed that project manager-related factors (especially project manager expertise) has a positive association with project success ( Saqib et al., 2008 ).

H1e: Project manager related factors are positively and significantly associated with project success .

Previous research concentrated solely on the proposed idea of success analysis. For example, determining CSFs and success criteria, followed by linking CSFs and success criteria ( Bhatti, 2005 ; Hyvari, 2006 ; Saqib et al., 2008 ). This study will look at the impact of critical success factors on project success via the mediation of knowledge creation. According to the extant literature, none considered the relationship between critical success criteria and project success in health sectors. Different studies were carried out in past years, and they mainly focus on the construction sectors. It has been noticed that the researcher has neglected the health sector. That is the purpose that encourages the researcher to carry out this research. The present study adds value to the extended body of literature by covering health sectors.

Knowledge Creation

An organization's competitive advantage is derived from its knowledge resource, which is valuable, rare, and non-replaceable. In the hope of improving performance through better management of what they know, organizations have been proactively engaged in knowledge management. Knowledge management is generally defined as the ability to leverage knowledge to achieve organizational goals, although theories tend to focus either on people or on technology ( Miković et al., 2020 ). According to Hu et al. (2019) , knowledge management in a project environment is an understudied topic in project management. Knowledge is the most precious asset in the context of project management. According to Awad and Ghaziri (2004) , knowledge is ”everything that can learn via the process of experience or suitable studies.” It is crucial to emphasize that data, information, and knowledge have always been significant in the industrial, information, or agrarian ages. Many issues confront the nation and organization; to gain a competitive advantage, the government and organization must deal with knowledge assets ( Ali, 2008 ).

As a result, to be more competitive, inventive, and productive, organizations must manage their knowledge resources effectively and strategically. However, the dilemma of attaining the organization's goal through utilizing and producing new information arises. The knowledge managed by organization's includes both explicit and implicit information. The organization's leadership may supply all required information related to identifying, sharing, and developing knowledge. An organization requires a mechanism for knowledge generation, information sharing, and organizational learning ( Rowley et al., 2000 ; Reich et al., 2012 ). Knowledge play important in the project. Knowledge of previous projects propels us to project success.

It might be either explicit or implicit. Tactic knowledge is created through discussions with stakeholders, office colleagues, project partners, consultants, and experts. It is extremely difficult to express tacit knowledge. Tactic knowledge is acquired via study and experience. Interaction with other individuals fosters the development of tacit knowledge. Tacit knowledge is unintentional and generally restricted to a particular region. Because it is not found in many books or manuals. Tactic knowledge comprises values, attitudes, assumptions, and mental models since it is cognitive and technical. When people use a variety of technical abilities, their tacit understanding of the technological base is articulated. Perception and implicit mental models are exhibited when tacit cognitive knowledge is employed ( Sternberg, 1997 ).

Tacit knowledge is easier to remember than explicit knowledge ( Wah, 1999 ). Face-to-face interaction, such as informal talk, internships, and storytelling, transforms two-thirds of work-related information. Whenever an issue arises in the project, it is necessary to arrange a meeting with an expert because project-related professionals and experts share their perspectives with employees. When tacit information is expressed, relevant decisions may resolve the problem. The project will be completed on schedule and under budget, resulting in project success. Social contact is nonetheless a requirement for tacit awareness. Social contact and replication of life and work skills can provide a platform for the production, sharing, and transmission of information ( Ibrahim et al., 2021 ). Observations also show that social interaction can occur, especially in aggregated cultures, where people of various ethnic backgrounds and backgrounds share their feelings, perceptions, and ideas. Organizational cultures provide a system of learning, adapting and creating a strong environment for people to share valuable insights, which create added value to the organization. Organizational culture, for example, aims to control its members' actions through information sharing. In addition, organizations can create an atmosphere in which employees can make use of their cognitive skills to develop knowledge and share creative ideas. Tacit knowledge has a favorable impact on project success. So, tacit knowledge plays a mediating role between project success and success factors ( Arumugam et al., 2013 ; Dalkir, 2013 ).

H2a: Tacit Knowledge creation mediates the relationship between management-related factors and project success .

H2b: Tacit Knowledge creation mediates the relationship between contractor related factors and project success .

H2c: Tacit Knowledge creation mediates the relationship between design-related factors and project success .

H2d: Tacit Knowledge creation mediates the relationship between project manager related factors and project success .

H2e: Tacit Knowledge creation mediates the relationship between client-related factors and project success .

Implicit information is not codified, but explicit knowledge is. May find Detailed expertise in databases, the internet, email, and papers. Everyone can easily get access to explicit knowledge and can easily share ( Hansen et al., 1999 ). To overcome many similar problems, we use codified and recorded explicit knowledge. We urge project team members to preserve a written record of working ability, a regulated technique for keeping a record of working knowledge, and a working knowledge record in the information system.

When an employee encountered a problem on the project, project-related internal documents and data files were freely accessible/available. The employee derived ideas and used that information to solve the problem ( Smith, 2001 ). As a result, explicit information contributes to project success. As a result, explicit knowledge plays a mediating role between project success and success factors ( Arumugam et al., 2013 ; Dalkir, 2013 ; Todorović et al., 2015 ).

H3a: Explicit Knowledge creation mediates the relationship between management-related factors and project success .

H3b: Explicit Knowledge creation mediates the relationship between contractor related factors and project success .

H3c: Explicit Knowledge creation mediates the relationship between design-related factors and project success .

H3d: Explicit Knowledge creation mediates the relationship between project manager related factors and project success .

H3e: Explicit Knowledge creation mediates the relationship between client-related factors and project success .

Conceptual Framework of the Study

Institutions that use their tacit knowledge to handle various problems and achieve their goals have a major competitive advantage ( Smith, 2001 ). As previously stated, after examining specific projects, some writers believe that gathering of information on project results might be a great strategy to develop a knowledge base that can use to manage future projects ( Hanisch et al., 2009 ; Yun et al., 2011 ). None of the above review studies has considered the relationship between knowledge creation and project success based on the existing literature. The purpose of this study is to give a framework for analyzing project success that will allow others to gather information on project results achieved in various segments and investigate the impact of the proposed idea of knowledge creation in a project environment. The research model of this current study is given in Figure 1 .

Figure 1 . Conceptual framework. Source: Author's constructed.

Research Methodology

The current study employed a quantitative methodology and a deductive approach. It is explanatory because it explains the variable's causal link. This study uses the deductive method, also known as testing theory, which formed the hypothesis based on theory. A cross-sectional study is employed because it is less expensive, saves time, and is the most commonly used survey approach. The current study's population was the health project of DHQ Hospital Attock and PIMS Hospital Islamabad. Due to time constraints and limited resources, the study only choose two hospitals as a population. The current study's respondents were “Manager, Supervisor, Zonal Supervisor, and LHS.”

The Manager, Supervisor, Zonal Supervisor, and LHS were chosen because they are in charge of the key functions of the health project and review various stages of health projects such as Polio, EPI, Mother-Child health care, Measles, T.B. dot programme, and so on. Furthermore, depending on their project experience, these individuals provide reliable information. The current study employs non-probability sampling, which means that every unit of the population is unknown and does not have an equal chance of being selected for the sample. There are alternative non-probability sampling procedures, but convenience sampling was used in the current investigation. It is made up of people who are easy to reach. The benefit of using this technique is that it saves time, money, and it is useful in the pilot study. For that reason this type of sampling preferred for that study. The current study's sample was selected using Morgan and Krejcie (1970) criterion, and the sample size for <800 populations is around 246.

See Table 1 , the current study's data is gathered via a questionnaire because there is a lot of information to be collected in a short period. The questionnaire is based on a literature review and prior studies on this topic. The question was broken down into four sections. A pilot study was conducted to evaluate the instruments in the current study. According to Galloway (1997) , the pilot research should be between 5 and 10% of the final sample size, and 10% of 246 equals 25.

Table 1 . Distribution and collection of questionnaire.

The questionnaire was given to 30 people in the current study. Cronbach's alpha was used to determine the internal consistency of the scale. A figure in the range of 0.7 to 0.95, according to Nunnally and Bernstein (1994) , is suitable. Cronbach's alpha was estimated using PLS (Partial Least Square) software for the current study. The Cronbach's alpha value of the instruments and individual constructions is shown in the table below (see Table 2 ), proving that the instrument is reliable. The component would be assessed using a five-point Likert scale ranging from 1 (very un important) to 5 (very important).

Table 2 . Pilot testing results.

Table 3 . Construct and items.

Table 4 . Sources of reflective constructs.

Management-related factors are coded as MGTRF, design-related factors as DRF, customer-related factors as CRF, project manager-related factors as PMRF, client-related factors as CLRF, tacit knowledge creation as TKC, explicit knowledge creation as EKC, and customer satisfaction as CSRF. In data screening stage, outliers and missing values were identified to ensure that there are no missing values and data has been entered accurately.

Reasons for Using the Smart PLS

In the current study Smart PLS has been used for several characteristics.

• As it indicates the maximum variation of latent variable and indicators.

• Another reason of using PLS path modeling is that; it had been widely used in the marketing literature and widely accepted ( Lim, 2008 ; Voola and O'Cass, 2010 ). As Smart PLS very popular because of it free availability to researchers and academics, user friendly interface and highly developed reporting features.

• As it is less restricted and do not require the normally distributed data ( Fornell and Cha, 1994 ).

• As well as compared to other path technique PLS requires the minimum demand on measurement scale, sample size and residual distribution.

• PLS approach is useful for analyzing the causal relationship, as well as PLS path modeling is useful for theory confirmation, as well as the for theory development ( Sarkar et al., 2001 ; Urbach and Ahlemann, 2010 ; Umrani et al., 2020 ).

• Another benefit of PLS specifically the Smart PLS as they allow us to estimate the measurement model as well as the structural model at the same time ( Ringle et al., 2005 ).

Results and Discussion

Demographic study.

The demographic study is conducted using the SPSS Statistical Package for Social Science software. The demographic research provides details about the education level of the respondents, the Designation of the respondents, and the highest results according to different categories. The demographic study results are summarized (see Table 5 ).

Table 5 . Respondent profile.

Statistical Technique: An Introduction to SEM

SEM is a multivariate strategy and second-generation tool for examining the relationship between many variables. The sample descriptive analysis, reliability analysis using the statistical package for social sciences (SPSS) by Arkkelin (2014) , and additional partial least square technique (Smart PLS 3.2.7) by Götz et al. (2010 ) were employed in the statistical analysis to assess the suggested model or for hypothesis testing.

Model Validation

The first step evaluated the measurement model, which checks the reliability and validity, the primary criteria for determining the measure's goodness. The second stage examined the structural model to determine the relationship between the latent variables. The model is also known as the outside model. As in the current study, the Cranach alpha ranged from 0 to 1 (see Table 6 ), and the composite reliability ranged from 0.6 to 0.9 (see Table 6 ), both of which met Hair et al. (2012) criterion or threshold of reliability requirements of at least 0.6 and 0.7.

Table 6 . Internal consistency of the final instrument.

According to Chin (1998) , the indicator reliability is measured by item loading, which should be >0.7; however, according to Hair et al. (2012) , the indicator loading must be 0.50 or greater.

The current study's results are displayed in the figure below (see Figure 2 and Table 7 ), and they show that item loading is satisfactory and meets the criteria, with values ranging from 0.437 to 0.969. According to Fornell and Larcker [61], convergent validity in Smart PLS 3.2.7 can be determined by the value of (AVE) average variance extracted, and the cut-off value for this measure is 0.50. The current study results for the (AVE) average variance extracted are provided in the table (see Table 8 ), with values ranging from 0.5 to 0.8.

Figure 2 . Measurement model indicating only indicators reliability. Source: Author's constructed.

Table 7 . Factors loading.

Table 8 . Convergent validity.

The last component that needs to be assessed is the discriminate validity, which the Fornell–Larcker criterion can be evaluated. Reason behind using this method is that, Fornell and Larcker criterion is the most widely used method for assessing the discriminate validity ( Ab Hamid et al., 2017 ).

According to Fornell and Larcker (1981) , the square root of AVE is used to test discriminative validity, and diagonal elements must be greater than the square root of AVE, as diagonal elements are the square root of AVE. The diagonal elements in the table below are greater than the diagonal elements (see Table 9 ).

Table 9 . Fornell and Larcker criterion.

Following the evaluation of the measurement model, the structural model, also known as the inner model, is evaluated in the following stage. The first criterion in the SmartPLS 3.2.7 is to assesses each latent variable's coefficient of determination. The R square reflects how much the independent variable explains variance in the dependent variable.

Chin (1998) defines the R-square, stating that a value of 0.67 is considered significant, 0.20–0.33 is deemed to be average, and a value of 0.19 or lower is considered weak or indicates a poor relationship. The R-square values that met the Chin (1998) criteria are shown in the table (see Table 10 ).

Table 10 . Coefficient of determination.

Normality Probability Plots of Variables

Furthermore, as illustrated in Figure 3 , a normal probability plot (Q-Q plot) is utilized to assess the data's normality. As the instances go closer to the straight line, the normality plot for all variables shows an almost normal distribution.

Figure 3 . Normality probability plots of variables. Source: Author's constructed.

Multicollinearity

In SPSS, multicollinearity is calculated via Tolerance and VIF (Variance Inflation Factors). According to Arkkelin (2014) , the cut-off value for tolerance is >0.10 and for VIF is <5. The values below indicate no multicollinearity issues (see Table 11 ).

Table 11 . Multicollinearity.

Hypothesis Testing

T-values or significant levels are examined via bootstrapping. First, as shown in the table below, the direct relationship between the dependent and independent is examined (see Table 12 ). The findings show that the connections between CSFs, namely, management-related factors, design-related factors, contractor-related factors, project manager-related factors, client-related factors, and project success are positive, therefore supporting H1a, H1b, H1c, H1d, and H1e (see Table 12 ).

Table 12 . Direct analysis (result after boostrapping).

Mediating Analysis

Finally, the mediation effects were investigated using Smart PLS software. The current study's model predicts project success through critical success factors; nevertheless, the impacts manifested separately through different mediators, namely tacit and explicit knowledge creation.

According to Memon et al. (2018) , when investigating models with several mediators, scholars must evaluate individual indirect effects rather than overall indirect effects. Nonetheless, current Smart PLS software updates feature a new option for examining multiple mediators known as ‘multiple specific indirect effects (mediation).' This function automatically calculates the indirect effect of each mediator, which can be mediation via implicit knowledge creation, explicit knowledge creation, or any variety of mediators.

As a result, evaluating models with many mediators is simplified by Memon et al. (2018) . One of this study's contributions is the investigation of mediated interactions. The specific in-direct effect for the mediating variable is shown in Table 13 .

Table 13 . Mediating analysis (tacit and explicit knowledge creation) (result after boostrapping).

The findings of the mediation test revealed that tacit knowledge creation mediated the association between critical success factors and project success, hence supporting H2a, H2b, H2c, H2d, and H2e. On the other hand, explicit knowledge creation does not mediate the relationship between critical success factors and project success; thus, H3a, H3b, H3c, H3d, and H3e were not supported.

Previous research ( Dalkir, 2013 ; Todorović et al., 2015 ) found a gap that the current work covers. It demonstrates that knowledge creation acts as a bridge between critical success factors and project success. The present study further expands on the research paradigm that Todorović et al. (2015 ) developed by including knowledge creation as a mediator and project success as a dependent variable. Critical success factors exist in today's research arena concerning project success; however, the notion is still unclear on how these factors are associated with project success. The world has changed tremendously in the previous decade, and these changes are continuing at an accelerating rate. As a result of this project's ongoing challenges, we have failed to meet the needs and expectations of our customers. This study choose customer satisfaction as a project success dimension because their behavior directly impacts project success. The current studies concentrate on the critical success factors of health projects. Because the knowledgeable sector has previously gotten little attention. However, the collective data analysis results demonstrate a significant relationship between critical success factors and project success, found in previous literature ( Pinto and Slevin, 1987 ; Odeh and Battaineh, 2002 ; Saqib et al., 2008 ).

In terms of tacit mediation, the findings showed a significant relationship between critical success factors and project success and that tacit knowledge creation had been positively influenced, supported by prior research. Tacit knowledge creation contributes to project success. As a result, tacit knowledge links success variables and project outcomes ( Dalkir, 2013 ). According to Al-Hakim and Hassan (2014) , mid-level managers impact knowledge creation execution. This tacit knowledge creation has been implemented successfully. It also boosts innovation and improves organizational/project performance. As a result, tacit knowledge creation mediate the relationship between mid-level management and project success.

According to the findings of this study, tacit knowledge creation mediates the relationship between critical success factors (management-related factors, design-related elements, contractor-related factors, project manager-related factors, and client-related factors) and project success. Hypothesis H2a, H2b, H2c, H2d, and H2e shows significant relationship. Because ours is a collectivist society. Our lives and jobs are belong to a collectivist society. Whenever an issue arises during project execution, we all interact, exchange our perspectives and thoughts, and work together to find the best solution. Throughout the process, tacit knowledge is articulating, no one seeks explicit knowledge. As a result, tacit knowledge creation mediates the relationship between CSFs and project success.

The findings revealed that explicit knowledge creation does not affect project success in explicit mediation. It does not mediates the relationship between critical success factors and project success. Previous studies in developed nations have shown that explicit knowledge creation considerably moderates the link between CSFs and project success. However, Pakistan is a developing country that prefers a collectivist approach. In a collectivist society, we typically utilize “We” instead of “I,” according to Hofstede's 5-dimension approach. Project team members embraced common responsibility rather than personal duty in the collectivist method. The organization's benefit is important for the people living in collective culture places.

They are unconcerned about their interests. When a project team member encounters an issue during project execution in a collectivist culture. A team member discusses their problem with the rest of the team. They called a formal meeting, and everyone shared their opinions and points of view based on their experiences. They can only conclude and solve the problem through this formal meeting.

As a result of this formal gathering, tacit knowledge is expressed, and no one seeks explicit information. Hypotheses H3a, H3b, H3c, H3d, and H3e are rejected since they do not demonstrate a significant association with project success.

In project management, project success is an intriguing and essential topic. As in any competitive environment, project managers are motivated to maximize project success, and to that end, they employ various strategies to distinguish themselves from their competition. The current research examines impact of critical success criteria on project success. All of the variables in the research model were derived from past research. Data were acquired from the health programmes at DHQ hospital Attock and PIMS hospital Islamabad. After verifying the reliability and validity of research scales, the hypothesis was evaluated, revealing that all measurements were reliable.

The current study found that critical success factors (management-related factors, design-related factors, contractor-related factors, project manager-related factors, and client-related factors) strongly correlate with project success (see Table 9 ). It means that critical success factors are important predictors of project success. As a result, to get the most out of the project, managers and subordinates should concentrate on several critical success factors. It was also shown that tacit knowledge production mediates the relationship between critical success elements and project success, whereas explicit knowledge does not.

It is due to Pakistan's status as a developing country. It takes a collectivist approach rather than an individualist one. Individual interest is prioritized over community interest in a collectivist society. As a result, tacit knowledge rather than explicit knowledge is communicated. The current research can be described in two parts: marketing implications and theoretical contribution. The marketing application will investigate the practical applicability of recent study findings in today's project, whilst the theoretical contribution will fill a knowledge gap in the previous literature.

Managerial Implication

• This study helps the project manager and subordinates discover essential elements for project success. To combat the severity of these factors, the manager should change their strategies. Managers should instruct their employees on generating tacit and explicit knowledge that may be used efficiently when a team member confronts a challenge.

• The research work assists project managers in developing strong team cohesion. The manager should encourage their project team members to speak with and share their ideas. Also, reply fast and supply their team with the essential information, documents, or procedures whenever they meet challenges.

• Project managers must also construct a structure within a project that generates both implicit and explicit knowledge. They should announce a reward scheme for their team members in incentives and allowances to accomplish this.

• The results suggest that one must gain continuous and sustained top management support before launching any knowledge management project. Leadership developed with transformational leadership traits is the core requirement to make the project successful.

• Top management of the organization is required to keep leadership development on top of the agenda for projects. In consultation with all stakeholders, a clear vision and objectives for knowledge management must be formulated and articulated. A well-developed knowledge management framework and knowledge cycle be adopted and communicated to all employees. A strategy about top-down and bottom-up learning and knowledge sharing may also be formulated and widely circulated before practically launching the knowledge management project.

• Project managers need to get people involved in Knowledge management processes that require continuous learning and development. Training also needs to be included in the knowledge management program. However, before launching any training program, identify knowledge management related competencies and behaviors through a knowledge audit. It will enable their people to build their knowledge processing capabilities and competencies and will realize the priority of the knowledge management project.

Theoretical Contribution

• Previous studies only focused on the proposed concept of success analysis only. For example determination of CSFs and success criteria and then correlating CSFs and success criteria ( Bhatti, 2005 ; Hyvari, 2006 ; Saqib et al., 2008 ). This study is going to examine the influence of critical success factors on project success through the mediation of knowledge creation.

• The current study also improves the research framework initially designed by [5], after adding the knowledge creation as a mediator and project success as a dependent variable.

• Little is known about the antecedents and consequences of critical success factors which can further lead to crucial project outcomes like time overrun and cost overrun, and there is still room for further exploration in this regard ( Saqib et al., 2008 ; Todorović et al., 2015 ). So the current research adds to the database existing in project success literature.

Recommendation to Practioner

• The health project manager should develop a system that focuses on the generation of implicit and explicit knowledge and the formulation of tacit and explicit knowledge.

• Coordination between senior management and project subordinates is lacking. Several staff members in the DHQ Attock hospital complained that upper management does not respond on time and coordinate adequately, causing project operations to be delayed. As a result, senior management must communicate with their subordinates on time and effectively.

• Vertical collectivism and centralization underpin the health initiative. We recommend that the health initiative follow horizontal collectivism. In which responsibility is distributed to each individual, each individual can decide on their behalf. Project activities will not be delayed as a result of these timely decisions.

• This research educates practitioners on the CSFs characteristics that influence project success in the health sector. And when these difficulties are adequately managed, many projects stand a reasonable chance of succeeding.

• This study is significant because top management will gain knowledge from their great coordination with their subordinates, which is the primary reason for project success. It makes the authorities comprehend how they can utilize various tactics to handle the essential success aspects in the project to complete, so that the work environment more comfortable and lead the project to success.

• It enables policymakers to understand better the impact of critical success factors on project success in the health sector, allowing new policies to be developed to address these critical success factors that may affect project performance.

Limitation and Future Recommendation

The present study uses cross-sectional and quantitative research methods; thus, different methodologies are being used to predict behavior better. The information was gathered from two hospitals and can be expanded further. Because many other marketing elements may impact project success, but only a few were evaluated in this study, future studies should extend the other variables (project KPIs) to understand better, how and to what extent the project's success occurs. The current study only looks at mediation; thus, future research should look into other mediating variables (knowledge acquisition, knowledge application, knowledge transfer) and moderating variables (such as project experience) to better assess the results.

In the future, cross-sectional studies can address the issue of generalizability, with study samples drawn from various areas of Pakistan, particularly those previously out of reach due to financial restrictions and the risk of terrorist activity. Many other components, such as the industrial sector other than the health sector, might be expanded to broaden the research. Little is known about the causes and effects of critical success variables, leading to important project outcomes such as time and cost overruns. There is still an opportunity for future research in this area ( Saqib et al., 2008 ; Todorović et al., 2015 ). As a result, the current study adds to the database of project success literature.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.

Author Contributions

The idea of the original draft belongs to SaN. SaN wrote the introduction, literature review, and empirical outcomes sections. MA, HH, and SiN helped collect and visualize data of observed variables. SaN, MVA, and KA constructed the methodology section in the study. All authors contributed to the article and approved the submitted revised version.

This work was supported by a grant of the Romanian Ministry of Education and Research, CNCS - UEFISCDI, project number PN-III-P4-ID-PCE-2020-2174, within PNCDI III.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Ab Hamid, M. R., Sami, W., and Sidek, M. M. (2017). Discriminant validity assessment: use of Fornell & Larcker criterion versus HTMT criterion. J. Phys. Confer. Ser. 890, 012163. doi: 10.1088/1742-6596/890/1/012163

CrossRef Full Text | Google Scholar

Ahmadabadi, A. A., and Heravi, G. (2019). The effect of critical success factors on project success in Public- Private Partnership projects: a case study of highway projects in Iran. Transport Policy 73, 152–161. doi: 10.1016/j.tranpol.2018.07.004

Al-Hakim, L. A. Y., and Hassan, S. (2014). Who are the crew members on implementation of knowledge management strategies to enhance innovation and improve organizational performance? J. Resources Dev. Manage. 3, 54–63.

Google Scholar

Ali, B (2008). Critical success factors for effective knowledge management in corporate sector (Pakistan) (Doctoral dissertation). National University of Modern Languages, Islamabad, Pakistan.

Allal-Chérif, O., and Makhlouf, M. (2016). Using serious games to manage knowledge: The SECI model perspective. Journal of Business Research , 69, 1539–1543. doi: 10.1016/j.jbusres.2015.10.013

Arkkelin, D (2014). Using SPSS to Understand Research and Data Analysis .

Arumugam, V., Antony, J., and Kumar, M. (2013). Linking learning and knowledge creation to project success in Six Sigma projects: an empirical investigation. Int. J. Prod. Econ. 141, 388–402. doi: 10.1016/j.ijpe.2012.09.003

Ashley, D. B., Lurie, C. S., and Jaselskis, E. J. (1987). Determinants of construction project success. Project Manage. J. 18, 69–79.

Awad, E. M., and Ghaziri, H. M. (2004). Knowledge Management .

Belassi, W., and Tukel, O. I. (1996). A new framework for determining critical success/failure factors in projects. Int. J. Project Manage. 14, 141–151. doi: 10.1016/0263-7863(95)00064-X

Bhatti, T. R (2005). “Critical success factors for the implementation of enterprise resource planning (ERP): empirical validation,” in The Second International Conference on Innovation in Information Technology , 110.

Boon Sin, A., Zailani, S., Iranmanesh, M., and Ramayah, T. (2015). Structural equation modeling on knowledge creation in Six Sigma DMAIC project and its impact on organizational performance. Int. J. Prod. Econ. 168, 105–117. doi: 10.1016/j.ijpe.2015.06.007

Canonico, P., De Nito, E., Esposito, V., Pezzillo Iacono, M., and Consiglio, S. (2019). Knowledge creation in the automotive industry: analyzing obeya-oriented practices using the SECI model. J. Business Res. 1. doi: 10.1016/j.jbusres.2019.11.047

Chalabi, F. A., and Camp, D. (1984). Causes of delays and overruns of construction projects in developing countries. CIB Proc. 2, 723–734.

Chan, D. W., and Kumaraswamy, M. M. (1997). A comparative study of causes of time overruns in Hong Kong construction projects. Int. J. Project Manage. 15, 55–63. doi: 10.1016/S0263-7863(96)00039-7

Chin, W. W (1998). The partial least squares approach to structural equation modeling. Modern Methods Business Res. 295, 295–336.

Chua, D. K. H., Kog, Y. C., and Loh, P. K. (1999). Critical success factors for different project objectives. J. Construct. Eng. Manage. 125, 142–150. doi: 10.1061/(ASCE)0733-9364(1999)125:3(142)

Dalkir, K (2013). Knowledge Management in Theory and Practice . Routledge.

De Wit, A (1986). “Measuring project success: an illusion,” in Proceedings of the 18th Annual Seminar/Symposium (Montreal, QC), 13–21.

PubMed Abstract | Google Scholar

Dikic, M., Nikolic, D., Todorovic, J., Terzic-Supic, Z., Kostadinovic, M., Babic, U., et al. (2020). Alignment of perceived competencies and perceived job tasks among primary care managers. Healthcare 8, 9. doi: 10.3390/healthcare8010009

PubMed Abstract | CrossRef Full Text | Google Scholar

Dissanayaka, S. M., and Kumaraswamy, M. M. (1999). Evaluation of factors affecting time and cost performance in Hong Kong building projects. Eng. Construct. Architect. Manage. 6, 287–298. doi: 10.1108/eb021119

Doloi, H., Iyer, K. C., and Sawhney, A. (2011). Structural equation model for assessing impacts of contractor's performance on project success. Int. J. Project Manage. 29, 687–695. doi: 10.1016/j.ijproman.2010.05.007

Eriksson, P. E (2008). Procurement effects on coopetition in client-contractor relationships. J. Construct. Eng. Manage. 134, 103–111. doi: 10.1061/(ASCE)0733-9364(2008)134:2(103)

Fornell, C., and Cha, J. (1994). Partial least squares. Adv. Methods Marketing Res. 407, 52–78.

Fornell, C., and Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: algebra and statistics. J. Market. Res. 382–388. doi: 10.1177/002224378101800313

Galloway, A (1997). Questionnaire Design and Analysis .

Götz, O., Liehr-Gobbers, K., and Krafft, M. (2010). Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach Handbook of Partial Least Squares . Springer, 691–711.

Habib, M. A., Soofi, S., Cousens, S., Anwar, S., Haque, N., ul Ahmed, I., et al. (2017). Community engagement and integrated health and polio immunization campaigns in conflict-affected areas of Pakistan: a cluster randomized controlled trial. Lancet Global Health 5, e593–e603. doi: 10.1016/S2214-109X(17)30184-5

Hair, J. F., Sarstedt, M., Ringle, C. M., and Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Market. Sci. 40, 414–433. doi: 10.1007/s11747-011-0261-6

Haleem, A., Sushil Qadri, M. A., and Kumar, S. (2012). Analysis of critical success factors of world-class manufacturing practices: an application of interpretative structural modelling and interpretative ranking process. Prod. Plann. Control 23, 722–734. doi: 10.1080/09537287.2011.642134

Hanisch, B., Lindner, F., Mueller, A., and Wald, A. (2009). Knowledge management in project environments. J. Knowl. Manage. 13, 148–160. doi: 10.1108/13673270910971897

Hansen, M. T., Nohria, N., and Tierney, T. (1999). “What's your strategy for managing knowledge?” in The Knowledge Management Yearbook 2000–2001 .

Hu, Y. F., Hou, J. L., and Chien, C. F. (2019). A UNISON framework for university knowledge management- industry collaboration and an illustration. Comput. Indus. Eng. 129, 31–43. doi: 10.1016/j.cie.2018.12.072

Hubbard, D. G (1990). Successful Utility Project Management From Lessons Learned . Project Management Institute.

Hyvari, I (2006). The success of projects in different organizational conditions. Project Manage. J. 37, 31. doi: 10.1177/875697280603700404

Ibbs, W., Nguyen, L. D., and Simonian, L. (2010). Concurrent delays and apportionment of damages. J. Construct. Eng. Manage. 137, 1191126. doi: 10.1061/(ASCE)CO.1943-7862.0000259

Ibrahim, S. B., Ahmed, U., and Abdullahi, M. S. (2021). Testing the prediction of knowledge sharing behavior through the lens of organizational culture and organizational citizenship behavior. Ann. Contemp. Dev. Manage. HR 3, 27–40. doi: 10.33166/ACDMHR.2021.02.003

Ismail, F., Yusuwan, N. M., and Baharuddin, H. E. A. (2012). Management factors for successful IBS projects implementation. Procedia Soc. Behav. Sci. 68, 99–107. doi: 10.1016/j.sbspro.2012.12.210

Jaselskis, E. J., and Ashley, D. B. (1991). Optimal allocation of project management resources for achieving success. J. Construct. Eng. Manage. 117, 321–340. doi: 10.1061/(ASCE)0733-9364(1991)117:2(321)

Jugdev, K., Thomas, J., and Delisle, C. (2001). Rethinking project management: old truths and new insights. Int. Project Manage. J. 7, 36–43.

Kerzner, H. R (2002). Strategic Planning for Project Management Using a Project Management Maturity Model . John Wiley & Sons.

Khan, M. M., and Van Den Heuvel, W. (2006). Description and content analysis of the national health policy of Pakistan. Asia Pacific J. Public Health. 33–52.

Kiani Mavi, R., and Standing, C. (2018a). Critical success factors of sustainable project management in construction: a fuzzy DEMATEL-ANP approach. J. Cleaner Prod. 194, 751–765. doi: 10.1016/j.jclepro.2018.05.120

Kiani Mavi, R., and Standing, C. (2018b). Critical success factors of sustainable project management in construction: a fuzzy DEMATEL-ANP approach. J. Cleaner Prod. 194, 751–765. doi: 10.1016/j.jclepro.2018.05.120

Lim, Y. W (2008). Triple endobutton technique in acromioclavicular joint reduction and reconstruction. Ann. Acad. Med. Singapore 37, 294.

Liu, A. M., and Walker, A. (1998). Evaluation of project outcomes. Construct. Manage. Econ. 16, 209–219. doi: 10.1080/014461998372493

Lu, W., Shen, L., and Yam, M. C. (2008). Critical success factors for the competitiveness of contractors: China study. J. Construct. Eng. Manage. 134, 972–982. doi: 10.1061/(ASCE)0733-9364(2008)134:12(972)

Maqbool, R., and Sudong, Y. (2018). Critical success factors for renewable energy projects; empirical evidence from Pakistan. J. Cleaner Prod. 195, 991–1002. doi: 10.1016/j.jclepro.2018.05.274

Memon, M. A., Cheah, J., Ramayah, T., Ting, H., and Chuah, F. (2018). Mediation analysis issues and recommendations. J. Appl. Struct. Equation Model. 2, 1–9. doi: 10.47263/JASEM.2(1)01

Miković, R., Petrović, D., Mihić, M., Obradović, V., and Todorović, M. (2020). The integration of social capital and knowledge management-the key challenge for international development and cooperation projects of nonprofit organizations. Int. J. Project Manage. 38, 515–533. doi: 10.1016/j.ijproman.2020.07.006

Misztal-Okońska, P., Goniewicz, K., Hertelendy, A. J., Khorram-Manesh, A., Al-Wathinani, A., Alhazmi, R. A., et al. (2020). How medical studies in Poland prepare future healthcare managers for crises and disasters: results of a pilot study. Healthcare 8, 202. doi: 10.3390/healthcare8030202

Morgan, D. W., and Krejcie, R. V. (1970). Determining sample size for research activities. Educ. Psychol. Measure. 30, 607–610. doi: 10.1177/001316447003000308

Nonaka, I., Toyama, R., and Nagata, A. (2000). A firm as a knowledge-creating entity: a new perspective on the theory of the firm. Indus. Corporate Change 9, 1–20. doi: 10.1093/icc/9.1.1

Nunnally, J. C., and Bernstein, I. H., (eds.). (1994). Elements of Statistical Description and Estimation. Psychometric Theory 3rd Edn . New York, NY.

Odeh, A. M., and Battaineh, H. T. (2002). Causes of construction delay: traditional contracts. Int. J. Project Manage. 20, 67–73. doi: 10.1016/S0263-7863(00)00037-5

Pinto, J. K., and Slevin, D. P. (1987). Critical factors in successful project implementation. IEEE Trans. Eng. Manage. EM 34, 22–27. doi: 10.1109/TEM.1987.6498856

Reich, B. H., Gemino, A., and Sauer, C. (2012). Knowledge management and project-based knowledge in its projects: a model and preliminary empirical results. Int. J. Project Manage. 30, 663–674. doi: 10.1016/j.ijproman.2011.12.003

Ringle, C. M., Wende, S., and Will, A. (2005). SmartPLS 2.0 (beta) .

Rowley, T., Behrens, D., and Krackhardt, D. (2000). Redundant governance structures: an analysis of structural and relational embeddedness in the steel and semiconductor industries. Strategic Manage. J. 21, 369–386. doi: 10.1002/(SICI)1097-0266(200003)21:3<369::AID-SMJ93>3.0.CO;2-M

Rubin, I. M., and Seelig, W. (1967). Experience as a factor in the selection and performance of project managers. Eng. Manage. IEEE Trans. 131–135. doi: 10.1109/TEM.1967.6448338

Salmeron, J. L (2009). Augmented fuzzy cognitive maps for modelling LMS critical success factors. Knowl. Based Syst. 22, 275–278. doi: 10.1016/j.knosys.2009.01.002

Saqib, M., Farooqui, R. U., and Lodi, S. H. (2008). “Assessment of critical success factors for construction projects in Pakistan,” in First International Conference on Construction in Developing Countries , 392–404.

Sarkar, M. B., Echambadi, R., Cavusgil, S. T., and Aulakh, P. S. (2001). The influence of complementarity, compatibility, and relationship capital on alliance performance. J. Acad. Market. Sci. 29, 358–373. doi: 10.1177/03079450094216

Seiler, S., Lent, B., Pinkowska, M., and Pinazza, M. (2012). An integrated model of factors influencing project managers' motivation - findings from a Swiss Survey. Int. J. Project Manage. 30, 60–72. doi: 10.1016/j.ijproman.2011.03.002

Sheikh, Z. A., and Jensen, A. M. B. (2019). Channelling hope: an ethnographic study of how research encounters become meaningful for families suffering from genetic disease in Pakistan. Soc. Sci. Med. 228, 103–110. doi: 10.1016/j.socscimed.2019.03.024

Shen, Q., and Liu, G. (2003). Critical success factors for value management studies in construction. J. Construct. Eng. Manage. 129, 485-491. doi: 10.1061/(ASCE)0733-9364(2003)129:5(485)

Shenhar, A. J., Levy, O., and Dvir, D. (1997). Mapping the dimensions of project success. Project Manage. J. 28, 5–9.

Smith, E. A (2001). The role of tacit and explicit knowledge in the workplace. J. Knowl. Manage. 5, 311–321. doi: 10.1108/13673270110411733

Songer, A. D., and Molenaar, K. R. (1997). Project characteristics for successful public-sector design-build. J. Construct. Eng. Manage. 123, 34–40. doi: 10.1061/(ASCE)0733-9364(1997)123:1(34)

Sternberg, R. J (1997). Successful Intelligence. New York, NY: Penguin Putnam.

Todorović, M. L., Petrović, D. T., Mihić, M. M., Obradović, V. L., and Bushuyev, S. D. (2015). Project success analysis framework: a knowledge-based approach in project management. Int. J. Project Manage. 33, 772–783. doi: 10.1016/j.ijproman.2014.10.009

Torbica, Z. M., and Stroh, R. C. (2001). Customer satisfaction in home building. J. Construct. Eng. Manage. 127, 82–86. doi: 10.1061/(ASCE)0733-9364(2001)127:1(82)

Umrani, W. A., Channa, N. A., Yousaf, A., Ahmed, U., Pahi, M. H., and Ramayah, T. (2020). Greening the workforce to achieve environmental performance in hotel industry: a serial mediation model. J. Hospitality Tourism Manage. 44, 50–60. doi: 10.1016/j.jhtm.2020.05.007

Urbach, N., and Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. J. Information Technol. Theory Appl. 11, 5.

Verburg, R. M., Bosch-Sijtsema, P., and Vartiainen, M. (2013). Getting it done: critical success factors for project managers in virtual work settings. Int. J. Project Manage. 31, 68–79. doi: 10.1016/j.ijproman.2012.04.005

Voola, R., and O'Cass, A. (2010). Implementing competitive strategies: the role of responsive and proactive market orientations. Euro. J. Market. 44, 245–266. doi: 10.1108/03090561011008691

Wah, L (1999). ” Making knowledge stick”, Management Review, May , 24–9.

Walker, D. H (1995). An investigation into construction time performance. Construct. Manage. Econ. 13, 263–274. doi: 10.1080/01446199500000030

Yang, J., Shen, G. Q., Drew, D. S., and Ho, M. (2009). Critical success factors for stakeholder management: construction practitioners' perspectives. J. Construct. Eng. Manage. 136, 778–786. doi: 10.1061/(ASCE)CO.1943-7862.0000180

Yang, M., Lin, Q., and Maresova, P. (2021). Does employee care trigger innovation under a healthy and safe working environment? Evidence from the pharmaceutical industry in China. Healthcare 9, 194. doi: 10.3390/healthcare9020194

Young, R., and Jordan, E. (2008). Top management support: mantra or necessity?. Int. J. Project Manage. 26, 713–725. doi: 10.1016/j.ijproman.2008.06.001

Yun, G., Shin, D., Kim, H., and Lee, S. (2011). Knowledge-mapping model for construction project organizations. J. Knowl. Manage. 15, 528–548. doi: 10.1108/13673271111137475

Keywords: health project success, critical success factors, knowledge creation, project, success

Citation: Naseer S, Abbass K, Asif M, Hashmi HBA, Naseer S and Achim MV (2022) Impact of Critical Success Factors on Project Success Through the Mediation of Knowledge Creation. Front. Psychol. 13:892488. doi: 10.3389/fpsyg.2022.892488

Received: 14 March 2022; Accepted: 02 May 2022; Published: 07 June 2022.

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Copyright © 2022 Naseer, Abbass, Asif, Hashmi, Naseer and Achim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Monica Violeta Achim, monica.achim@econ.ubbcluj.ro

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