1 Introduction
With the advent of the knowledge economy era, project teams have gradually realized the importance of knowledge resources in enhancing core competitiveness and innovation capabilities (
Hanisch et al., 2009;
Zhang and Huang, 2020). Projects are temporary work to create a unique product, service, or outcome (
Li et al., 2020;
He et al., 2021). The role of knowledge in projects is reflected in its sharing and flow, which means that knowledge is more valuable when it is owned by more individuals (
Jafari Navimipour and Charband, 2016). A large amount of knowledge is created during a project’s lifetime, but knowledge is easily lost with the dissolution of the project (
Schindler and Eppler, 2003;
Ren et al., 2019). If effective knowledge exchange and transfer between different individuals, projects, and organizations can be realized, the possible loss of knowledge can be greatly reduced, thus avoiding the waste of time and resources (
Buvik and Tvedt, 2017;
Zhou et al., 2022b). Knowledge transfer (KT) exists between project members, different participating organizations of the project, and different projects. However, a project has the characteristics of one-off and goal-oriented, which makes KT challenging (
Kivrak et al., 2008). KT is usually interdisciplinary and multi-functional, which demonstrates the complexity of the transfer process and outcomes (
Dip, 2021). Therefore, better managing KT within and outside a project is worth pondering (
Bakker et al., 2011;
Schröpfer et al., 2017).
KT in the project environment refers to the process in which organizations, projects, or individuals transmit knowledge through various means in an environment with the project as the production or operation unit, and then the recipients accept the transferred knowledge and apply it (
Aerts et al., 2017;
Zhou et al., 2020). KT embodies the multi-faceted nature of the subject, boundary, and process, which indicates that it must be summarized at multiple levels (
Szulanski, 1996;
Cacciatori, 2008;
Martinkenaite, 2011). The existing research concentrates on three levels: Intra-project KT (IPKT), cross-project KT (CPKT), and cross-organizational KT (COKT). IPKT is KT between different members of the project team; CPKT, different projects; and COKT, different organizations participating in the project.
In recent years, scholars have focused on the elements of KT and the corresponding transfer outcomes (
Martinkenaite, 2011; Teo and Bhattacherjee, 2014). KT elements can be divided into five dimensions: The knowledge sender and receiver, the relationship between the sender and receiver, knowledge characteristics, transfer media, and transfer context, which are the decisive factors of the difficulty, quantity, and quality of KT (
Shahbaznezhad et al., 2019). KT outcomes include two dimensions, namely, the amount of knowledge transferred and the extent to which the receiver applies knowledge (
Martinkenaite, 2011;
Teo and Bhattacherjee, 2014). Although these studies provide significant insights, they suffer from (1) the fragmentation between three research levels of IPKT, CPKT, and COKT; (2) lack of completeness and clarity regarding the elements and outcomes of KT in the project environment; and (3) limited efforts on the relationship between the elements and outcomes of KT, which make the influence path between them unclear. Given the diversity of concepts and methods and the fragmentation of related research, a holistic perspective is needed to express the corresponding relationship between the elements and outcomes of KT in the project environment. This study supplements existing research efforts by conducting a systematic literature review of KT in the project environment and analyzing the transfer elements and outcomes of IPKT, CPKT, and COKT. Specifically, the following research questions require great attention: (1) How are three levels of KT (IPKT, CPKT, and COKT) defined, and what are their scopes? (2) What are the elements and outcomes of KT in the project environment, and how can they be linked? (3) What are the knowledge gaps and research directions for the current research on the KT in the project environment?
This study aims to establish an integrated framework that determines and links the elements and outcomes of KT in the project environment through a comprehensive analysis of the existing literature. It provides an overall assessment of the existing literature and an overview of knowledge gaps. This study is organized as follows. Section 2 introduces the main theoretical background, which becomes the basis of this study. Section 3 describes the methodology and research framework. Section 4 analyzes the results, including the elements and outcomes of KT from three levels. Section 5 conducts an in-depth analysis of the results and discusses knowledge gaps and future directions. Section 6 concludes the work.
2 Theoretical background
2.1 KT in the project environment
Teece (
1977) first proposed the concept of KT. He indicated that technology transfer can accumulate a large amount of practical knowledge for enterprises. Szulanski (
1996) stated that KT involves knowledge senders and receivers, who need to transfer, acquire, absorb, and apply knowledge in their interaction. Subsequently, scholars put forward that KT means the knowledge source transfers knowledge to potential recipients, and ensuring that the recipients fully absorb the knowledge and can guide actions accordingly is necessary (
Davenport and Prusak, 1998; Skovvang Christensen and Kaasgaard Bang, 2003). KT is an interactive process between the sender and receiver that depends on specific contexts. Therefore, KT that occurs in different contexts should be specifically studied. KT in the project environment has gradually become a hot spot (
Newell et al., 2006;
Ajmal and Koskinen, 2008).
According to the different scenarios in which the transfer occurs, the research on KT in the project environment can be divided into three types. (1) IPKT refers to the sum of KT activities between project members (
Zhou et al., 2022a). In a project team, members who possess specific knowledge send the knowledge to other members. Then, other members receive the knowledge and use it to improve their technical and management levels (
Aerts et al., 2017;
Ni et al., 2018). During continuous KT among project members, useful knowledge is possessed by a growing number of members, thereby increasing the project’s knowledge reserve and improving teamwork ability and work efficiency (
Sang et al., 2019). (2) CPKT is the process by which knowledge is transferred from the source project team to the recipient project team so that knowledge can be received, internalized, and reused by the latter (
Zhao et al., 2015). CPKT includes horizontal KT between projects and vertical KT between the project-based organization (PBO) and projects (
Zhou et al., 2020). Through CPKT, the project team can transfer the knowledge acquired during construction and operation to other projects or the construction enterprise, avoiding knowledge loss caused by the disbandment of the project team. And (3) COKT refers to the KT between different participating organizations involved in the project. Each participating organization transfers and absorbs knowledge while jointly completing the project task to obtain knowledge resources that can enhance their competitive advantages (
Lawson and Potter, 2012;
Lievre and Tang, 2015). Organizations involved in COKT include project owners, design units, contractors, material suppliers (
Sun et al., 2019), and academic research units (
Liu et al., 2020).
2.2 Elements and outcomes of KT
With the development of KT theory, scholars conducted many studies to explore the factors affecting KT. Szulanski (
1996) divided the influencing factors into four dimensions: Knowledge characteristics, the sender, the recipient, and knowledge context. Gupta and Govindarajan (
2000) proposed that transfer channels and their richness should also be considered. Cummings and Teng (
2003) set up a framework including the knowledge sender and receiver, the relationship between the sender and the receiver, knowledge characteristics, and transfer context. Therefore, the elements influencing KT can be divided into five dimensions: The knowledge sender and receiver, the relationship between the sender and receiver, knowledge characteristics, transfer media, and transfer context. The five-dimensional transfer elements have become a generally accepted theoretical framework for research and laid a good foundation for KT in the project environment (
Zhao et al., 2015;
Zhou et al., 2020).
The research on the transfer outcomes starts as the dependent variables when studying the factors influencing KT. Szulanski (1996) defined the results of KT as on time, on budget, and on satisfaction. According to Garavelli et al. (
2002), KT can be divided into two phases: One is the knowledge flow from the knowledge sender to the receiver; the other is the knowledge application of the knowledge recipient. Therefore, scholars proposed that the transfer outcomes also include two dimensions: One is the amount of knowledge transferred and the amount of knowledge accepted by the knowledge receiver (
Milagres and Burcharth, 2019); the other is the extent to which the knowledge receiver applies the transferred knowledge (
Ambos and Ambos, 2009;
Tshuma et al., 2018). In the field of project management, scholars began to pay attention to the results of KT and use different standards to measure the transfer outcomes, such as the effectiveness (
Ciabuschi et al., 2011;
Sun et al., 2019) and successfulness (
Lee and Ram, 2018;
McGowan Poole, 2020) of KT. Although many scholars recognized the significance of KT for projects, comprehensive studies of the transfer elements and outcomes within and outside projects and their parent PBOs are quite rare. Considering the knowledge intensity of the project and the importance of knowledge flow, developing a systematic research framework for the smooth occurrence and effective completion of KT has great theoretical and practical significance.
3 Methodology
Literature review is a scientific method that mainly solves specific problems by identifying, evaluating, and synthesizing all relevant studies (
Milagres and Burcharth, 2019;
Xu and Zou, 2021). To ensure the rigor and objectivity of the research method, the authors selected and analyzed papers on KT in the project environment following the PRISMA statement method (
Moher et al., 2010). PRISMA means “preferred reporting items for systematic reviews and meta-analyses”. It uses systematic and clear methods to discover, select, and evaluate related literature and then analyze collected data from the publications. As shown in Fig.1, the whole process includes four stages: Identification, screening, eligibility, and content analysis.
Phase I: Identification refers to a comprehensive search and identification of relevant articles, including the two sub-phases of searching and filtering. At first, the samples in this study were collected from Web of Science, Scopus, and SpringerLink, the main databases of global scientific articles. The publication time was from January 2000 to June 2021. The search terms used were “project” AND (“KT” OR “knowledge sharing” OR “knowledge exchange” OR “knowledge flow”). After removing duplicates, a total of 865 papers were gathered, including journal articles, conference papers, thesis dissertations, and book chapters. Subsequently, the search scope was limited to full-text published articles in English academic journals. After checking the source, authors, and language, the papers that are not journal papers, not written in English, or not available in full-text version are removed. After this series of operations, 329 papers remained.
In Phase II, the title, authors, source, keywords, and abstract of the papers were screened. At this phase, the authors of this work assessed whether the paper is relevant to “project” and “KT”. Papers that do not explore the influencing factors and outcomes of KT in the project environment were excluded. In Phase III, eligibility means reading the full text version of the selected 85 articles after phase II. Articles would be excluded if they did not focus on KT in the project environment but only used KT as a background for other activities. Following the above standards, 64 articles were included in the scope of this literature review.
Lastly, in Phase IV, the authors conducted content analysis on the selected papers, including descriptive and conceptual results. The former mainly conducts statistical and quantitative analysis on publication year, journal, method, and research level, while the latter summarizes the five-dimensional KT elements, the transfer outcomes, and the relationship between the elements and outcomes in the project environment.
4 Results
4.1 Descriptive results
This section mainly provides the statistics and overview of the articles’ publication year, related journal, method, and research level.
4.1.1 Year and journal distributions
Fig.2 demonstrates the yearly numbers of publications since 2000, with an overall trend of growth. From 2001 to 2007, except in 2002 and 2003, one related paper was published every year. From 2008 to 2013, the number of publications fluctuated, ranging from 0 to 4. Except that only three related papers published in 2016, five to seven papers were published each year from 2014 to 2020. This result shows that KT in the project environment has attracted ever-increasing attention from scholars, and the research in this field has been significantly developed. These 64 papers were published in more than 30 different journals related to project management, knowledge management, and organizational management. Among them, ten journals has published two or more related papers, namely, Research Policy, Journal of Knowledge Management, International Journal of Project Management, Automation in Construction, Journal of Management in Engineering, Journal of Construction Engineering and Management, Project Management Journal, Knowledge Management Research & Practice, Engineering Construction & Architectural Management, and Management Learning.
4.1.2 Research methods
Afterward, the authors carefully read the selected 64 papers, coded them, and conducted a comprehensive analysis in the form of data. The data included author information, analysis levels, research background, keywords, methods, and results. At this stage, preliminary tables, graphs, and reports were used to facilitate comprehensive surveys and statistics. In terms of methods, over half of the 64 articles (35 articles) used quantitative research methods, whereas 6 used qualitative approaches. Eleven, five, three, and four papers used case study, conceptual, simulation, and mixed methods, respectively. An interesting phenomenon is that the research methods of the publications from 2018 to 2020 are relatively scattered. The results indicate that current research methods are becoming increasingly diverse, and the outcomes are gradually enriching.
4.1.3 Research levels
According to the scenario in which KT occurs, KT in the project environment includes IPKT, CPKT, and COKT. The factors involved in the different levels of KT are not entirely the same. Therefore, the three types of KT should be first described separately. Tab.1 demonstrates the information of some selected papers belonging to the ten journals that has published two or more related papers, as well as their analysis levels and research methods.
(1) IPKT
Among the 64 papers, 19 explored KT within a project. According to statistics, the number of articles using the quantitative method is the largest (15 articles). The steps of KT within the project are as follows. The first step is the formation of personal knowledge. The accumulation of personal knowledge plays a vital role in the growth of team knowledge. The second step is the formation of project team knowledge. The transfer of personal knowledge and the absorption, improvement, and coding of knowledge are completed within the team (
Buvik and Tvedt, 2017). The third step is the mutual transfer of personal knowledge and project team knowledge. In the selected literature, the main factors influencing IPKT include organizational structure (
Gopal et al., 2018), organizational culture (
Ovbagbedia and Ochieng, 2015), incentive mechanism (
Decker et al., 2009), and trust among members (
Park and Lee, 2014).
(2) CPKT
The number of articles on CPKT is the largest, with a total of 27. Among them, 12 articles used the quantitative method, and 7 articles used the case study method. CPKT refers to KT from the source project to the recipient project through horizontal transfer (direct transfer between projects) or vertical transfer (knowledge is transferred from projects to PBOs and then to other projects) (
Zhou et al., 2020). Most of the selected literature focused on horizontal transfer, studying the influencing factors and transfer effect (
Frank and Ribeiro, 2014;
Ren et al., 2018). Some studies also explored vertical KT, such as Bakker et al. (
2011) and Zhou et al. (
2020).
(3) COKT
Of all the selected literature, 18 articles had COKT as the research goal. Most of the papers (8 articles) has used quantitative method. At different stages of project construction, the tasks of each organization vary, along with the process and influencing factors of knowledge exchanges between organizations. Therefore, the KT participants proposed in the selected literature are also distinct, including owners, design units, contractors, material suppliers (
Sun et al., 2019), and academic research units (
Liu et al., 2020), as well as universities, public organizations, and customers (
Takahashi et al., 2018).
4.2 Conceptual results
Conceptual results mainly include three parts: Five-dimensional KT elements, KT outcomes, and link between the transfer elements and outcomes. The purpose of this section is to identify the elements and outcomes of KT in the project environment and relate them holistically.
4.2.1 Five-dimensional elements of KT in the project environment
At this stage, the content analysis method was used to extract elements mentioned and validated in the literature that influence KT in the project environment. Content analysis refers to a systematic technique for compressing many words into fewer content categories based on explicit coding rules (
Hsieh and Shannon, 2005). By using content analysis, a detailed and systematic examination of the content of a particular subject can be performed to extract sub-factors and variables (
Mohammadi et al., 2018). After the first round of review, 38 variables were identified as the influencing factors of KT. In the second round of review, five variables were extracted. Next, some variables with the same meaning were combined or removed. As shown in Tab.2, 35 variables of KT were identified, which belong to five dimensions.
(1) Knowledge sender and knowledge receiver
In this dimension, the most concentrated factors are transfer intention, receive intention, and absorptive capacity. Scholars proposed that KT largely depends on the willingness of the knowledge sender to express knowledge and communicate with the receiver (
Cheng et al., 2009;
Wei and Miraglia, 2017). As the other critical participant in the transfer process, the knowledge recipient’s receive intention also affects KT (
Bakker et al., 2011;
Ren et al., 2018). Besides, projects or individuals with higher absorptive capacity have lower transfer costs and faster transfer speed in KT, which significantly improve the efficiency and final effect of transfer (
Lawson and Potter, 2012;
Zhao et al., 2015). Another factor that cannot be ignored is supplier protectiveness, which is mentioned by scholars in COKT (
Lawson and Potter, 2012;
Liu et al., 2020). When knowledge providers and receivers come from different organizations, an important task of suppliers is protecting their valuable proprietary knowledge to maintain a competitive advantage.
(2) Relationship between the knowledge sender and receiver
The statistical results indicate that trust is the factor getting the most attention in this dimension. The higher the degree of trust between two individuals or projects is, the stronger their willingness is to transmit and receive knowledge (
Bosch-Sijtsema and Postma, 2010;
Park and Lee, 2014). Five studies indicate that the higher the similarity between two projects is, the better the effectiveness of CPKT is (
Zhao et al., 2015). Park and Lee (
2014) explored the similarity of expertise and project value between partners within the project. Besides, some scholars defined different types of distances between the knowledge sender and receiver as geographical distance (
Betz et al., 2014), relational distance (
Bakker et al., 2011), knowledge distance (
Joseph Garcia and Mollaoglu, 2020), and organizational distance (
Liu et al., 2020). These studies suggested that the greater the distance between KT participants is, the worse the transfer effect is.
(3) Knowledge characteristics
As shown in Tab.2, the most frequently mentioned variable by scholars in this dimension is knowledge tacitness, followed by knowledge complexity, embeddability, and ambiguity. Knowledge tacitness reflects the degree of tacit knowledge in the project that is difficult to encode, hindering KT to a certain extent (
Andersson et al., 2015;
van Waveren et al., 2017). Knowledge with high complexity hinders members inside or outside the project from using coding for KT (
Lievre and Tang, 2015). Additionally, project knowledge is embedded in certain cognitive and normative systems, and the management methods vary from organization to organization. This kind of knowledge embeddedness also affects KT (
Tshuma et al., 2018).
(4) Transfer media
Tab.2 demonstrates that communication and transfer channels are the most frequently mentioned factors in this dimension. According to Antwi-Afari et al. (
2016), the enhancement of communication capability can promote the effect of COKT in technology transfer projects. Transfer channel is a collective term used to describe the media of KT between sender and receiver (
van Waveren et al., 2017), including project meetings, communication through social software, and delivery of coding materials (
Souza da Conceição et al., 2019). Besides, meeting systems and document exchange are regarded as specific transfer media, which could affect the transfer effect (
Jensen et al., 2019;
McGowan Poole, 2020).
(5) Transfer context
Forty-two publications studied factors in the transfer context dimension, indicating that this dimension is the most concerning dimension. Factors involved in this dimension can be roughly divided into project characteristics, organizational characteristics, and network characteristics. According to Seres et al. (
2009) and Hermans and Castiaux (
2017), the transfer effect in different types of projects (e.g., housing construction, transportation, petrochemical, and hydropower projects) varies. Time urgency, temporary nature, project uncertainty, and standardization are also important factors related to project characteristics. Temporary nature leads to the fluidity and instability of the project team, and time urgency forces members to complete the project task at a specific time, which reduces their willingness to transfer knowledge (
Sun et al., 2019). Newell et al. (
2006) and Raziq et al. (
2020) pointed out that the project’s standardization level impacts KT. Additionally, scholars put forward the following context factors related to organizational characteristics: Organizational structure (
Gopal et al., 2018), organizational culture (
Antwi-Afari et al., 2016), incentive mechanism (
Andersson et al., 2015), and information technology (
Betz et al., 2014). In recent years, the factors of network characteristics have also attracted scholars’ attention. For example, different network structures between the knowledge senders and receivers exert different effects on KT (
Schröpfer et al., 2017).
4.2.2 Outcomes of KT in the project environment
Tab.3 illustrates all outcomes of KT based on the selected literature. In the research of Liu et al. (
2020) and Gao et al. (
2020), the amount of knowledge that the receiver obtains from the sender is used to measure the transfer effect. Both studies use the simulation method to demonstrate the transfer process and result. Using the amount of knowledge transferred simplifies the model to a certain extent and makes the transfer effect more measurable. Some scholars proposed the limitations of this measurement method because the recipient may not have implemented the transferred knowledge, which means that the transfer process is incomplete (
Bosch-Sijtsema and Postma, 2010). Additionally, some researchers used successful KT or effective KT to represent the transfer outcomes (
Decker et al., 2009;
Bakker et al., 2011). These studies pay more attention to whether KT is completed and whether the knowledge is transferred smoothly rather than the result of knowledge application.
Regarding the transfer outcomes in the second stage, the receiver’s knowledge application and the effectiveness of KT are the most mentioned in the literature. In different situations, the standards for measuring the receiver’s knowledge application vary. For example, knowledge application within the project is reflected in the promotion of the project performance brought by members using the transferred knowledge (
Joseph Garcia and Mollaoglu, 2020). At the cross-project level, the project’s activity mode can be used by other similar projects through KT, and knowledge application is reflected in the extent to which the transferred knowledge is used in recipient’s project (
Frank and Ribeiro, 2014;
Tshuma et al., 2018). According to Antwi-Afari et al. (
2016), cross-organizational knowledge application refers to how the organization uses the knowledge absorbed from other organizations in operation. Moreover, scholars also gave different definitions of the effectiveness of KT (EKT). Zhao et al. (
2015) measured EKT by the completion time of the project task, the realization degree of the project goal, and the improvement level of business value after KT. Zhou et al. (
2020) used the improvement of project knowledge reserves, the completion of project goals, and the improvement of technology and management level to measure EKT. Overall, EKT reflects the extent to which KT is completed on time, on budget, and on the satisfaction of the recipient (
Gopal et al., 2018).
Project performance is an extension of knowledge application because the improvement of project performance brought about by KT can be regarded as the result of knowledge application (
Gopal et al., 2018). Project performance is defined as the extent to which a project team realizes the project goals (
Landaeta, 2008), whereas project outcome is measured as the quality of project completion and the degree of satisfaction with user needs (
Ko, 2014). Gopal et al. (
2018) divided project outcome into two aspects: Product outcome (e.g., schedule and cost optimization) and service quality (e.g., individual satisfaction and mutual association). Innovation performance is a deeper concept than project performance, and only one article explored it deeply. Following Zhang and Min (2021), the innovation performance of the new product development (NPD) project means not only the achievement of project targets but also the market recognition of the new product. Another situation needs a special explanation. Scholars regarded KT as the dependent variable and discussed the impact of various factors on KT (
Ovbagbedia and Ochieng, 2015). For example, Lawson and Potter (
2012) directly used the learned technical knowledge, mastered technical skills, and reduced technical dependence to measure KT.
4.2.3 Link between elements and outcomes of KT in the project environment
In this section, a comprehensive framework of causal relationships between transfer elements and outcomes is first obtained from the selected literature. Fig.3 shows the five dimensions of factors affecting KT and transfer outcomes in the project environment. The representative factors of each dimension are the factors that frequently appear in the reviewed literature. Additionally, the analysis of the selected literature demonstrates that the relationship between the elements of different dimensions is not isolated. They affect each other and ultimately influence the transfer outcomes. Milagres and Burcharth (
2019) proposed that the same factor can promote or hinder KT in various ways. Therefore, the authors summarized the influence paths and influence directions (positive or negative) of the transfer elements on the outcomes. All dimensions are connected in Fig.4, which provides an overall summary of the relationship between the transfer elements and outcomes in the project environment.
In the selected literature, the factors of the knowledge characteristics dimension have two main influence paths on the transfer outcomes: One is to affect RKA directly (
Tshuma et al., 2018), and the other is to impact the transfer outcomes by affecting RI (
Liu et al., 2020). As for the factors of the relationship dimension, they have a certain degree of mutual influence, such as similarity promoting trust (
Park and Lee, 2014). The influence paths of factors in this dimension on the transfer outcomes also include direct effects (
Ko, 2014) and indirect effects by increasing or reducing TI (
Zhou et al., 2020). Additionally, most factors (i.e., CM, TC, and DE) in the transfer media dimension directly impact EKT or SKT. Only Ren et al. (2019) proposed that the meeting system positively affects the transfer effectiveness by influencing communication. Moreover, the transfer context is the dimension that contains the most factors, and the causal relationship between these factors and the transfer outcomes is the most complicated. Factors in this dimension can directly affect the transfer results through the intermediary effects of factors (e.g., TR, CM, TI, and RI) belonging to the dimensions of relationship, transfer media, and transfer subject. Lastly, according to the selected literature, the influence of the transfer subject on the transfer outcomes is direct. For example, the positive effects of AC on AKT, SKT, EKT, and KT are explored in the literature.
5 Discussion
5.1 Comprehensive framework of KT in the project environment
As mentioned earlier, KT in the project environment includes three levels: IPKT, CPKT, and COKT. Fig.5 demonstrates the transfer elements and outcomes and their relationships at the three levels. At the IPKT level, except for the dimension of transfer media, factors in the other dimensions can directly affect the transfer outcomes. Transfer media impacts the transfer outcomes through the intermediary effect of the relationship between the knowledge sender and receiver. Therefore, handling the relationships between individuals within the project is critical for members to improve the effectiveness of IPKT. Scholars proposed that project managers can build a project environment of mutual trust to reinforce relationship management (
Nesheim and Smith, 2015;
Buvik and Tvedt, 2017). At the CPKT level, the relationship between various factors in different dimensions is more complicated. Each dimension has one or several factors that directly impact the transfer outcomes. According to the selected literature, relationship impacts transfer context, and transfer context affects transfer media and transfer subject. Therefore, transfer context is in a significant position of the model. Based on previous studies, the cultural atmosphere of knowledge sharing should be cultivated, and project construction should be optimized to improve the effectiveness of CPKT (
Zhao et al., 2015;
Zhou et al., 2020). At the COKT level, each dimension has one or several factors that directly influence the transfer outcomes. Knowledge characteristics, relationship, transfer context, and transfer media influence the transfer outcomes through the intermediary effect of the transfer subject. Therefore, the willingness and ability of project participating organizations to carry out cross-organizational transfer activities must be improved (
Lawson and Potter, 2012;
Sun et al., 2019).
5.2 Knowledge gaps and recommendations for future research
According to the above analysis, the authors highlight the knowledge gaps, and provide recommendations to help better manage the process of KT within and outside the project and optimize the transfer outcomes in future research work.
(1) The elements of KT should be deeply explored, and the relationships between transfer elements and outcomes need further research. For example, in research on the transfer context, scholars pay more attention to organizational characteristics than project and network characteristics. Project characteristics are the most unique attributes in the research on project KT. However, the existing research does not reveal the causalities between some factors (e.g., project uncertainty, project type, and standardization) and transfer outcomes. This article suggests scholars pay attention to project characteristics and the manner in which they affect the transfer outcomes, which can open a promising way for follow-up research. Besides, some papers explored the influence of network characteristics on KT in project management and proposed a new concept of project network (
Schröpfer et al., 2017;
Gao et al., 2020). In this context, studying the influencing factors and outcomes of project KT from the network perspective is valuable. However, the ambiguity of knowledge and complexity of the network make it difficult for scholars to clearly understand the mechanism of KT in the project network. With the emergence of new technologies, data mining and machine learning can be used to construct a network model, explore the structural characteristics of the network, and thus deeply analyze the laws of knowledge flow.
(2) There is a hysteresis effect in knowledge learning and absorption (
van Wijk et al., 2008). For example, KT takes a certain time to complete, so knowledge may no longer be needed when transferred to the recipient. In this case, the recipient receives the knowledge but often no longer applies the knowledge, resulting in the failure of knowledge reuse. However, few studies focus on the timeliness of the transfer process and knowledge application. Therefore, the authors call for future research to expand the scope of the investigation and adopt more direct observation and case study methods to reveal better the dynamics of the transfer process and the complexity of the results. As many scholars prefer to measure KT effectiveness and project performance subjectively, the reliability of this data collection method is also questioned (
Martinkenaite, 2011). In attempting to deal with these problems, subjective evaluation and objective measurement can be combined as an available approach. Using different standards to measure “successful knowledge transfer” and “organizational/project performance” at different stages of project or PBO development may help improve the quality of research.
(3) The literature review suggests that most papers used quantitative research methods such as questionnaire surveys, limiting the inference of causality between variables from different dimensions. According to the description in the literature, a positive or negative linear relationship exists between factors, but it may be curvilinear. For example, with strengthening the relationship between transfer participants, when a certain threshold is exceeded, under the premise of fixed time and energy, the increase in the cost of maintaining the relationship may affect the transfer effect. Therefore, future research can focus on whether a curvilinear relationship exists between the transfer elements and outcomes. Furthermore, qualitative data is a vital resource that cannot be ignored, and there are many ways to help researchers make greater use of them. For example, multiple case studies may be combined with specific project scenarios to reveal the relationship between the transfer elements and outcomes.
(4) The framework of this study indicates that the smooth implementation of KT requires high-level coordination across the entire project and even organizational structures, mechanisms, and cultures. To solve the problem appearing in project knowledge management, the authors remind researchers to adopt a holistic perspective at the organizational level. The purpose of project management is not only to complete the one-time tasks of the project but also to promote the sustainable development of the organization. Additionally, research at the IPKT level pays more attention to individuals, but few scholars focus on individuals in the transfer process at the CPKT and COKT levels. No matter at what level, the investigation of individuals is a fundamental research approach because management measures at the organization and project levels are ultimately implemented at the individual level. The authors encourage individual-focused research to expand the KT mechanisms identified at the overall level.
(5) The existing research fails to capture the factors affecting KT and its related outcomes in different stages (e.g., decision making, design, construction, completion, and acceptance) of the project life cycle. Considering that the purpose of KT at different project stages is diverse and the participants involved in each phase are not the same, future studies can categorize transfer elements and outcomes into stages of the project life cycle. Moreover, KT is a complicated dynamic interactive evolution process in which related parameters are constantly changing (
Martinkenaite, 2011;
Shahbaznezhad et al., 2019). The use of computer simulation and artificial intelligence (AI) can contribute to exploring the transfer elements and outcomes and their relationships. Specifically, system dynamics and agent-based modeling can be used to simulate the actual situation of KT across the project life cycle. Some AI methods (e.g., neural networks, genetic algorithms, and decision trees) can predict the hidden effects of related factors, which can provide a reference for project practitioners to implement effective KT strategies.
5.3 Research contributions
This study contributes to the research field of project management from the following three aspects. First, this article divided KT in the project environment into three levels according to the transfer scenario, namely, IPKT, CPKT, and COKT. The current research on these three levels is relatively scattered, and a comprehensive framework with a high degree of recognition has not been formed. The smooth implementation of KT at any level requires high-level coordination of the entire project and organizational structure, mechanism, and culture. Project knowledge management aims to complete the one-time task of projects and promote the sustainable development of PBOs and enterprises. Therefore, this study can enlighten other researchers to comprehensively consider the different levels of KT in the project environment.
This study identifies and analyzes 35 factors of five-dimensional transfer elements and 7 factors of two-dimensional transfer outcomes. The results show that the elements of KT still need to be discussed in some dimensions. For example, in the research on the transfer context dimension, more scholars pay attention to organizational characteristics rather than project and network characteristics. Project characteristics are the most unique attribute in project KT research. How factors such as project uncertainty, project type, and degree of standardization affect KT need to be further explored. Therefore, this research provides a complete and clear framework for the transfer elements and outcomes in the project environment, and points out the direction for factors that require further research.
Lastly, this study fills the gap in the research of project knowledge management by developing a comprehensive model to link the elements and outcomes of KT in the project environment. According to the existing literature, there are positive and negative linear relationships between factors, but these relationships may be curvilinear. The authors suggest that future research can combine multiple case studies with specific project scenarios to reveal the complex relationship between the transfer elements and outcomes. This article helps project managers and members choose and control different elements in KT process to improve the transfer outcome. In other words, the integration of the relationship between the factors provides more ideas for scholars and practitioners to optimize the transfer results from factors of different dimensions.
6 Conclusions
This study conducts a literature review of KT in the project environment and summarizes and links the transfer elements and outcomes from three levels: IPKT, CPKT, and COKT. First, based on the sample with 64 selected papers from relevant journals, statistics indicate that the number of papers published in the past two decades (2000–2021) showed an upward trend. The quantitative method was used most frequently among all the selected articles, followed by the case study and qualitative methods. The elements of KT were identified and grouped into five aspects: The knowledge sender and receiver, the relationship between the sender and receiver, knowledge characteristics, transfer media, and transfer context. Transfer outcomes were divided into two dimensions: The amount of knowledge transferred and the degree of knowledge application of the knowledge receiver. Then, 35 factors of transfer elements and 7 factors of transfer outcomes were determined by reviewing the 64 articles. The top-cited factors of transfer elements included trust, organizational culture, information technology, incentive mechanism, transfer intention, time urgency, and so on. The most common outcome factors were the effectiveness of KT, the receiver’s knowledge application, and project performance. Moreover, relationships between the transfer elements and outcomes were identified and gathered for creating an integrated roadmap. Finally, the authors systematically emphasized the literature contributions and gaps related to KT in the project environment, which provide the direction for project management and knowledge management fields that need to be studied deeply.
Despite the contributions to the research of project management and knowledge management, several limitations of this study need to be acknowledged. This research restricts the search of articles to English journal articles in Web of Science, Scopus, and SpringerLink. There may be some articles in other databases or other languages that can provide a widespread understanding of this research. Expanding the survey scope of the literature is suggested. More databases can be used to collect articles related to this topic, and non-English papers can be collected to make the study more robust. A more comprehensive survey can help future researchers explore more research possibilities.
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