Disentangling Trust in relation to Knowledge
Management Processes in Inter-organizational Project
Alliances
Amsterdam Business School (ABS)
Faculty of Economics and Business
Place & date: Amsterdam, Netherlands
Name, initials: Oleana, S.N.W.P.
ID number: 11707356
Thesis Supervisor: Second reader:
dr. Balazs Szatmari dr. Tsvi Vinig
Submission subject and date:
MSc. Business Administration - Thesis ‘18 22nd of June 2018
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Statement of originality
This document is written by Sander N.W.P. Oleana who declares to take full responsibility for the content of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the content.
___________________________ Sander N.W.P. Oleana
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Acknowledgements
This thesis marks an end to the MSc. Business Administration study at the University of Amsterdam in the field of Innovation and Sustainable Development. I genuinely hope the study can provide thoughts beyond just for researchers in this field, and that it is beneficial for the disruptive leaders.
This thesis would never have been accomplished without the on-going support and input from many different contributors. First and foremost, I would like to thank my supervisor Balazs Szatmari. It has been a privilege to undergo this study under his patience, guidance and creative input. Second, I would like to extend my sincere gratitude to all the survey respondents, and specially thank Hilde van Egmond and Martin Smit, who have encouraged me in this study. Last but not least, I sincerely thank my parents and friends who have always been considerate and supportive of my academic career.
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Abstract
Purpose - The purpose of this study is to empirically investigate the effect of
integrity-, benevolence- and competence trust on the mediating role of knowledge management on project performance in an alliance context, and to discover the moderating effects of alliance form.
Findings - The findings show that competence trust has a positive and linear
relationship with knowledge creation, -transfer and -adoption, whereas integrity and benevolence have no significant relationship. The results also reveal that alliance form only plays a role between knowledge adoption and project performance, positively benefitting horizontal alliances while the impact on vertical alliance is not influenced by alliance form.
Practical Implications - This study inspires organizations to carefully consider how
to select collaborators and how to reap the benefits of knowledge in an alliance. The better understanding about how multi-dimensional trust and alliance form can influence knowledge management processes, the better organizational performance organizations can attain.
Research Limitations - Due to time constraints, longitudinal studies are suggested
in order to infer and understand a causal relationship between knowledge management and project performance in collaborations. More focused case studies are suggested in order to further confirm the generalizability across sectors and nations.
Originality/value - This study pioneers the distinctive effects of integrity,
benevolence and competence on knowledge management process in alliances, expanding current literature of trust in alliances. This study also investigates the influence of alliance form on the effectiveness of trust on knowledge management.
Keywords - Alliances, Project Performance, Knowledge Management, Trust,
Competence, Benevolence, Integrity
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Table of Contents
1. Introduction 6
2. Literature Review on Knowledge & Theory 9
2.1 Knowledge Management 10
2.1.1 Knowledge Management and the Resource-Based View 12
2.1.2 Knowledge Management and Projects 14
2.2 Organizational Knowledge Management Processes 15
2.2.1 Knowledge Creation 17
2.2.2 Knowledge Transfer 19
2.2.3 Knowledge Adoption 20
2.2.4 Summary: Organizational Knowledge Management Processes 21
2.3 Trust 22
2.3.1 Trust antecedents 22
2.3.2 Trust Dimensions 23
3. Hypotheses Development 25
3.1 Overall Trustworthiness and Project Performance 25
3.2 Mediating role of Knowledge Management 27
3.3 Moderating role of Alliance Form 29
3.4 Conceptual modelling 31
4. Methodology 32
4.1 Research Design 32
4.2 Population, Sampling and Data Collection 34
4.3 Construction of Conceptual Logic and Measurement 35
5. Data Analysis and Results 38
5.1 Data analysis 38
5.1.1 Dataset and Demographics 38
5.1.2 Data Interpretation of Constructs 39
5.1.3 Factor Analysis 42
5.1.4 Reliability Analysis 43
5.1.5 Check for Normality 44
5.1.6 Outliers & Missing Data 45
5.2 Results 45
5.2.1 Descriptive Statistics 46
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5.2.3 Mediation Effects 48
5.2.4 Moderation Effects 53
6. Discussion & Implications 56
6.1 Discussion 56
6.2 Managerial Implications 63
7. Conclusion 65
7.1 Conclusion 65
7.2 Limitations and Future Research 66
References 69
Appendix 78
List of Abbreviations:
KA: Knowledge Adoption KC: Knowledge Creation KT: Knowledge Transfer KM: Knowledge Management
KMP: Knowledge Management Processes IOC: Inter-organizational Cooperation PP: Project Performance
SD: Standard Deviation
MDPT: Multidisciplinary Project Teams
List of Figures:
Figure 1: Knowledge Process
Figure 2: Conceptual Model of Hypothesized Relationships Figure 3: Mediation Analysis Results
Figure 4: Trust, and its dimensions, and their effect on KM and PP Figure 5: Knowledge Management Process in Project Management Figure 6: Knowledge in the three knowledge management phases
List of Tables:
Table 1: Research Methods of the Study
Table 2: Means, Standard Deviation and Variance of Trust, KC, KT, KA and PP Table 3: Reliability Analysis
Table 4a: Descriptive Statistics - Normal Distribution
Table 4b: Descriptive Statistics - Normal Distribution Adjusted Table 5: Means, Standard Deviations and Correlations
Table 6: Regression Results Overall Trustworthiness on PP Table 7: Mediation Effect performed with PROCESS
Table 8: Effects of IV (Trust and Dimensions) on Mediating- and Dependent Variable(s)
Table 9: Results of Moderation between KA and PP for Alliance Form Table 10: Result of Hypotheses
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1. Introduction
An increasing amount of research finds that alliances play a critical role for firms to create new knowledge and gain competitive advantage (Wang et al., 2011; Zhang et al., 2016; Borys and Demison, 1989). These capabilities are necessary to address and/or hedge against economic-, political- and social complexities and risks, which are present in our rapidly changing and turbulent business environment (Achrol, 1991). However, these alliances might suffer from opportunistic risks, for which trust is considered an antecedent in literature for knowledge creation and -transfer in alliances (Shu et al., 2012; Kuo, 2013). This emerging trend leads us to a complex system requiring collaborative knowledge and knowledge management (KM). Knowledge management, due to its rare- and difficultness to imitate and/or substitute, plays a mediating role in connecting organizational context and strategy with organizational effectiveness (Zheng, Yang and McLean, 2010; Badaracco, 1991). Despite the theoretically attainable organizational performance of these alliances, superior organizational performance is partly held back by the ineffective use of knowledge management in projects as they are viewed upon as “temporary” information projects yielding lower synergies (Madhavan and Grover, 1998).
A lot of previous academic research has been done on inter-organizational cooperation and has recognized the importance of overall trustworthiness and alliance form on a particular KM process in facilitating new value creation or the effect of knowledge management (processes) on organizational performance. However, these past studies focus almost exclusively on a process of knowledge management and the influence of trust (Gold et al., 2001; Becerra et al., 2008). Additionally, researchers agree to disagree that trust is a one-dimensional concept
7 (Mayer et al., 1995; Kuo, 2013). Previous literature, on a one-dimensional trust, finds mixed and inconsistent empirical results, namely positive, negative and non-significant relationships (Krishnan, Martin and Noorderhaven, 2006; Nielsen and Nielsen, 2009; McEvily, Perrone and Zaheer, 2003). The researcher believes that this dispersion arises partly from the fact that often research is based on a one-dimensional measure of trust. Following Connelly et al. (2015) we believe that distinguishing between the dimensions of trust can provide us with a more profound understanding on how to use knowledge management in alliances, as the dimensions trust reflect different expectations.
This paper follows a knowledge-based view of the organization to examine the effects of inter-firm trust on knowledge management. Knowledge is considered one of the most important resources of an organization, and effective knowledge management can be considered a capability for an organization (Grant, 1996). Following the notion of Mayer et al. (1995), we focus on three dimensions of trust - integrity, benevolence and competence.
Through these efforts, this study endeavours to contribute to the existing knowledge-based view and social-capital literature in three ways. Firstly, through conducting a detailed analysis on overall trustworthiness of alliances on project performance with reference to the three dimensions. Secondly, this study enriches the alliance-context knowledge management research literature by empirically showing the relative effect of integrity, benevolence and competence trust on knowledge management. Thirdly, it investigates how knowledge management serves as a mediating mechanism that connects trust to project performance, expanding on previous research that emphasizes the direct effect of (one-dimensional) trust on project performance. Hence, the following research question has been formulated:
8 What is the effect of trust and alliance form on knowledge management in an inter-organizational cooperation on organizational performance?
Given these challenges, the purpose of this paper is as follows. Firstly a literature review on Knowledge Management and Organizational Development is introduced whereupon hypotheses are derived to close the above mentioned research gaps. Secondly, the methodology is elaborated upon covering the research, the samples, and how the various concepts are measured. Thirdly, the data analysis and results are presented, followed by a discussion of the results. The discussion includes a short summary of the results, including its theoretical contribution and practical implications. Lastly, a brief conclusion along with the limitations and suggestions for future research are provided.
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2. Literature Review on Knowledge & Theory
This review has been initiated with the search for research-based articles submitted to peer review for methodological rigor. These articles have been generated through various search engines, UvA Library, Google Scholar, Scopus, EBSCO and Sage Journals online, and obtained results from general management journals Journal of Management, Journal of Management Studies, Journal of Knowledge Management, Journal of Marketing and Journal of Management Information Systems. Keywords for the search included “knowledge” in combination with alliances, joint ventures, inter-organizational, consortia, co-creation, collaboration, network, inter-firm, partnership and joint project.
This review yielded a promising rise in the field of Knowledge Management and Strategy, yet did not result in a systematic, science-based approach to systematically approaching Knowledge Management Processes through effective inter-organizational knowledge management processes in project management and operationalizing it. Therefore, a unique strength of this paper is that it examines consequences related to knowledge management between horizontal- and vertical alliances, and the effect of trust and its dimensions on the KM processes.
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2.1 Knowledge Management
Drawing upon previous research, it is clear that organizations must leverage their knowledge capabilities, to use and create knowledge to favour their organizational performance. In order to leverage these knowledge capabilities, several researchers propose the effective use of knowledge management. Davenport and Prusak (1997) argue that knowledge management implementations serve for three aims:
● To make knowledge visible and show the role of knowledge in an organization;
● To develop a knowledge-intensive culture by encouraging and aggregating behaviours such as knowledge sharing and proactively seeking and offering knowledge;
● To build a knowledge infrastructure--not only a technical system, but also a web of connections among people given space, time, tools, and encouragement to collaborate.
Additionally Hackbart (1998) argue that knowledge management serves to help organizations compete and increase their innovativeness and responsiveness. However, this creation and transfer of knowledge requires social capital to be present within the organization, defined as “the sum of actual and potential resources embedded within, available through, and derived from the network of relationships possessed by a social unit (Nahapiet and Ghoshal, 1998). Grant (2002) points out that there has been a consolidation of these management perspectives that includes a host of behavioural, technological, organizational, and strategic contributions. This perspective, knowledge management, identifies processes which are imperative to acquire, develop, gather, share, apply and protect
11 knowledge in an organization, in order to improve its performance (Alavi and Leidner, 2001). These key infrastructures, structural, cultural and technological are needed in order to enable the full potential of social capital.
Organizational structure is important in leveraging knowledge management, as strategic decision often inhibit cooperation and sharing of knowledge across internal- and external stakeholders (Gold, Malhotra and Segar, 2001). For an example, without proper organizational reward and incentive schemes, there is little to no motivation to share knowledge or not addressing knowledge sharing as a KPI in project management. Sanchez and Mahoney (1996) therefore suggest a modular organizational design as they argue it allows for lower coordination and adaption costs, increasing flexibility. However, there are several organizational structures possible in order to allow for flexibility.
Cultural infrastructure is perhaps one of the most significant challenges faced by organization in implementing successful KM. This would involve having an articulated and communicated vision, which calls for a sense of involvement and contribution among employees (Davenport, Jarvenpaa and Beers, 1998). Having these cultural aspects in place, and effectively communicated, shapes an organizations ability to manage knowledge more effectively, and encourages employees to engage in knowledge sharing practices.
Technological infrastructure, although part of the structural dimension, is needed to facilitate social capital for knowledge creation. By combining information and communication systems, previously fragmented flow of knowledge can be integrated, thereby removing barriers to knowledge management. Grant (1996) found that the most effective aspects should cover business intelligence, collaboration, distributed learning, knowledge discovery, knowledge mapping,
12 opportunity generation, as well as security. These aspects allows for knowledge generation in competitive environments, facilitating inter(national) and (inter)organizational knowledge sharing, knowledge retrieval, and maintaining a knowledge logbook. In addition, knowledge transfer and –adoption systems should also ensure that knowledge is used most effective- and efficiently.
However, in order to leverage these infrastructures, knowledge management must be present to create, transfer and store knowledge throughout the organization (Alavi and Leidner, 2001). Grant (2002) has a framework that incorporates these perspectives into the KM processes, and provides a theoretical foundation for section 2.2. The following section delves into the importance of knowledge management for an organization, looking through the lens of the resource-based view.
2.1.1 Knowledge Management and the Resource-Based View
Barney (1991) argues with its resource-based view that competitive advantages are a result of a firm’s competitiveness through a unique bundle of (in) tangible assets that are valuable, rare, imperfectly imitable and sustainable. These firm’s resources consist out of a range of organizational activities such as management skills, organizational processes, routines and the information and knowledge it controls (Barney, 1991). Extensive research has been done on the effect of these resources on organizational performance; yet lack the medium through which these results are empowered. That’s where the knowledge-based view of the firm plays a crucial role, where the ability of a firm to create and utilize knowledge is the most important source of a firm’s sustainable competitive advantage (Grant, 1996; Nonaka, 1991; Prahalad and Hamel, 1990). In the
13 knowledge-based view it is thus important to manage information flows, through Knowledge Management (KM), most effectively and efficiently to create and sustain this competitive edge, which can deliver superior organizational performance.
Knowledge management can be described as a systematic and integrative process of coordinating the acquisition, creation, storing, sharing and diffusion of information by individuals and/or groups (Rastogi, 2000; Rowley, 2011). In the former definition, information is merely considered knowledge when processed by individuals, including ideas, facts, expertise, and judgement for individuals or groups with respect to organizational performance (Bartol and Srivastava, 2002). Davenport and Prusak (1998) mention that scholars generally agree that KM practices need to fit the organizational context in order to create the competitive edge. Nonaka et. al. (2000) enforce this view and add that the process of KM is context-specific, and determines who and how an individual or group participates in the KM process. Skyrme and Arnindon (1997) argue that if KM is implemented successfully, it enhances an organization’s competitive advantage, customer focus, employee relations and development, innovation and lower costs, through i.e. faster completion of new product development.
Despite the potential benefits of proper KM, it is estimated that $31.5 billion per year are lost by Fortune 500 whom fail to capitalize on the sharing of knowledge (Babcock, 2004). Therefore, promoting organizational learning by managing knowledge helps organizations achieve and sustain competitive advantage and increase value (Kogut and Zander, 1992; Spender and Grant, 1996).
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2.1.2 Knowledge Management and Projects
The current business landscape requires organizations to react fast and flexible to interdisciplinary challenges. These interdisciplinary challenges partly arise due to rising environmental pressures, corporate responsibility, digitization and more disruptive trends that require organizational change in order to remain relevant and attain organizational success. Therefore, knowledge and experience from projects are highly relevant, as they solve these innovative and interdisciplinary challenges that are faced. This is also evident in literature, with the growing research focusing on external knowledge sources through alliances, to create new knowledge and gain competitive advantages (Wang et al., 2011).
However, despite the importance of the acquired knowledge, the knowledge often remains within the MDPT as the boundaries between the projects and the organizations are strong due to decentralization, resulting in knowledge fragmentation (Disterer, 2002). This is partly because projects are seen as temporary “organizations” with specific objectives, detailed tasks, and restricted time and budget, which its structure and operations are ceased upon completion (Disterer, 2002). Additionally, these projects often have a critical “time-to-market” KPI, which can lead to short term benefits and harm long-term efficiency gains. The project teams are often split up and put on following projects, and consequently the competencies and skills built are not systematically being documented and reflected upon, whereby the application of the knowledge and experience are difficult to retrieve for future relevant projects (Weiser and Morrison, 1998). In the best possible scenario, the project members keep the knowledge to themselves, and apply this individual tacit knowledge in the future, which inhibits attaining economies of scope and scale as it gets “lost” within the organization. Therefore, “reinventing the wheel”
15 becomes a more common practice amongst other projects, than it should be with proper knowledge management systems.
Concluding, projects are necessary to solve interdisciplinary challenges that organizations face in the turbulent business environment. However, in order to reap the full benefits of the attained knowledge organizations are suggested to manage their knowledge system well. Recognizing that the acquired knowledge can be applicable and beneficial to more projects, and therefore to the organizations success is crucial. Ayas (1996) adds that organizations are suggested to provide additional resources to the projects, in order to systematically document this knowledge to enable continuous improvement with every project. After having broadly elaborated upon knowledge management, the following section delves into the processes of managing knowledge.
2.2 Organizational Knowledge Management Processes
In this section, we develop a systematic framework that will be used to analyse and elaborate upon the potential of knowledge management process in organizational knowledge management. Due to discrepancy in literature there exist many frameworks for the knowledge management process in literature. This can be derived from the several point of views related to the key processes:
● Davenport, Jarvenpaa and Beers (1996): finding existing knowledge, creating new knowledge, packaging knowledge created, externally using existing knowledge;
● KPMG (1998): creation, organizational application, external exploitation, sharing and dissemination, encapsulation, sourcing, and learning;
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Creation
Transfer/
Learning
Adoption
● Teece (1998): creating new knowledge, accessing knowledge from outside sources, using accessible knowledge, embedding knowledge in processes, products, and/or services, representing knowledge in documents, databases and software, facilitating knowledge growth through culture and incentives, internal knowledge transfer, and measuring the value of knowledge assets and/or impact of knowledge management.
The previously mentioned views of knowledge management share a common red thread, which is the process perspective and tend to lead towards Davenport and Prusak (1998) process of knowledge management (Figure 1). These processes relate to the creation of knowledge, transferring (sharing/learning) of knowledge and applying the knowledge. Additionally, these frameworks are grounded in the sociology of knowledge, and portray an organization as social collectives (Holzner and Marx, 1979). They also recognize that the processes, and knowledge, are highly dependent on the social knowledge and interaction amongst individuals, as the codified output of the KMP derives from socialization processes amongst collective and individual knowledge (Pentland, 1995). The next sections delve into each particular organizational knowledge management process.
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2.2.1 Knowledge Creation
Knowledge Creation can be defined as the extent to which an organization successfully develops new technology, product, and market knowledge by collaborating with partners (Samaddar and Kadiyala, 2006). It is very important as knowledge creation has been found to contribute to improved organizational performance and innovation (Darr et al., 1995). However, with the increasing change of the business environment, it is a challenge for organizations to rely on internal sources only for new knowledge creation (Wang et al., 2011). Hence we observe an increased use of merger and acquisition and alliances to develop new knowledge (Lane et al., 2001).
These alliances allow for heterogeneity of knowledge amongst collaborators, which can lead to different knowledge and perspective, which stimulate collective creative discovery of new ideas/knowledge. Therefore, it is crucial that external collaborators serve as knowledge brokers, where the organization serves as a bridge between the collaborators, to find unique combinations from the knowledge possessed by the groups (Schilling, 2013).
So the more deep and diverse collaborators are in the alliance, the more diverse information can be expected. However, having access to many diverse and deep collaborators comes along with costs, and it has been found that the collaborator’s degree of centrality has an inverted U-shaped effect on innovation performance (McFadyen and Cannella, 2004). This means that ultimately the costs of having lot of heterogeneous collaborators might exceed the benefits, due to coordination costs of maintaining the social network.
Looking at the conditions and environment that facilitate knowledge creation, Choo and de Alvarenga (2010) argue that organizations should enable conditions,
18 through i.e. organizational forms and leadership, that provide the initial building blocks of the knowledge based theory of the organization. It is also argued that knowledge creation can be stimulated by aligning its knowledge vision, creative routines, incentive systems and routines (Choo and de Alvarenga, 2010). Furthermore, Nonaka et al. (2006) add that conditions such as care, trust, courage, team atmosphere, and IT are essential. However, such a creation of new knowledge is not a codification effort or driven by a single individual, but involves the ability to interact and convince others (Venters, Cornford and Cushman, 2005). SECI is an effective mode to streamline this process efficiently and transform individual knowledge to organizational knowledge (Nonaka and Takeuchi, 1996). It involves the process of socialization in order to obtain tacit knowledge and externalize this into explicit knowledge through peer-to-peer interactions. Subsequently, this explicit knowledge is integrated with existing explicit knowledge through combination, and lastly internalized through on-the-site experiences after which the dynamic loop starts over.
Concluding, by integrating and combining external knowledge regarding technologies, products, and markets into its own knowledge stock, new knowledge is created (Zahra and George, 2002; Zhou et al., 2014). However, in order to have effect on organizational performance it needs to be transferred and learned by members of the organization in order to represent added value (Porter and Ketels, 2003). If not, it remains merely knowledge that only a few members of the organization are aware of.
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2.2.2 Knowledge Transfer
The creation of organizational knowledge requires the transfer and dissemination of personal experience, either within or between organizations, in order to make it accessible to members of the organization. Literature describes “knowledge transfer” as one of the most important components of knowledge management, as it shows to be an antecedent for organizational learning and innovation (Goh, 1998), and as the antecedent for knowledge adoption, which in turn leads to competitive advantage (Desouza, 2013). Knowledge transfer allows for harnessing and leveraging information by converting it into a widely understood form, in order to seek and develop new application to thrive in the business environment (Henderson and Cockburn, 1994). This knowledge transfer refers to the efforts of a source to share information and knowledge with a receiver and the receiver’s efforts to acquire and absorb (i.e. learn) it. This process is a key dimension of a learning organization and fundamental in order to exploit and capitalize on knowledge based resources (Davenport and Prusak, 1998). This knowledge transfer process can occur either with internal and/or external constituents, via written correspondence or face-to-face communications through networking with other experts or documenting, organizing and capturing knowledge for others (Cummings, 2004, Pulakos et al., 2003). However, according to Huber (1991) organizations often are not fully aware of what their knowledge capabilities are, and have weak systems in place to locate and retrieve these. Therefore, effective communication processes need to be in place to drive knowledge transfer within organizations.
It is important to understand that knowledge is not a static concept, but should be understood as the distinction between stocks and flows of knowledge. Although, certain firms have a stock of knowledge, reflecting its accumulated and retrieved
20 knowledge, a knowledge flow represents the effective transfer of knowledge in an alliance (Gupta and Govindarajan, 2000). The knowledge transfer process proves beneficial when knowledge in one part of an organization is transferred effectively to another, and uses its insights to solve problems or to provide new insights. For an example, Texas Instruments used its best practices insight among its 13 plants to increases its annual fabrication capacity by $1.5 billion (O’dell and Grayson, 1998). Despite the fact that knowledge transfer across organizational units provides competitive benefits, executives still often mention the lack of ability to transfer knowledge within an organization (Gupta and Govindarajan, 2000; Goh, 2002). Knowledge transfer can therefore convert collective knowledge to organizational knowledge, making it accessible to members of the organization (Yang, 2007). It is important to not stick to knowledge itself, but to also translate this into a source of competitive advantage in the application of knowledge, which is what the next section will elaborate upon.
2.2.3 Knowledge Adoption
Once knowledge is created and transferred well, effective storage and retrieval mechanisms allow for a quick and easy access (Gold, Malhotra & Segars, 2001). This is where the adoption process takes place, which refers to the decision and ability to use or implement a discrete element of knowledge, often in the form of a product, practice, or paper (Phelps, Heidl, Wadhwa, 2012). In order to evaluate the contribution of the acquired knowledge it is of particular importance to apply this to different organizational activities, such as processes or projects. If the knowledge adoption process is finished successfully and has a positive effect on performance, then this knowledge should be widespread within the organization through the KMP.
21 Hewlett-Packard, for an example, rewards those who share knowledge if this is utilized elsewhere in the organization, thus promoting organizational learning.
A major challenge of knowledge adoption in organizations is the absence of a collective mind and central memory (Alavi and Leidner, 1999). Due to these limitations, it is difficult to be aware of all knowledge stocks within an organization. Grant (1996) identifies three mechanisms for the integration of collective knowledge to create organizational knowledge, namely:
● Directives: Specific set of rules, standards, procedures, and instructions developed through the conversion of specialists’ tacit knowledge to explicit and integrated knowledge for efficient communication to non-specialists; ● Organizational Routines: Development of task performance and coordination
patterns, interaction protocols, and process specifications that allow individuals to apply and integrate their specialized knowledge without the need to articulate and communicate what they know to others. Routines may be relatively simple;
● Self-contained Teams: In situations in which task uncertainty and complexity prevent the specification of directives and organizational routines, teams of individuals with prerequisite knowledge and specialty are formed for problem solving.
2.2.4 Summary: Organizational Knowledge Management Processes
To summarize, this section has elaborated on a knowledge management framework based on the view of a knowledge-based organization. There are some important implications that have been presented. Firstly, the knowledge management framework is a dynamic set of processes and practices that resides22 within individuals and physical structures. However, it is not a discrete phenomenon, as at a given point in time, members of an organization can be engaged in different aspects of the KMP. Secondly, the KMP presented is dependent on three phases, namely knowledge creation, -transfer and -adoption in order to effectively enforce KM. They can be thought of as causal links in a chain, for which they are interdependent of each other, and if one link is weak, this has consequences for the overall process. Therefore, it is important to be aware of the state of the processes and tackle the least-performing processes in order to improve the overall process. Hence, organizations should focus on the entire KMP.
2.3 Trust
Trust can be defined as the “willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the focal organization, irrespective of the ability to monitor or control that other party” (Mayer et al., 1995, p. 712). Previous research advocates trust as a key aspect of relational capital for purposes of influencing and bonding with partners (Inkpen & Tsang, 2005; Nielsen & Nielsen, 2009). Therefore it can promote collaboration, dispute resolution, and risk and cost sharing associated with the exploration of new opportunities (Molina-Morales et al., 2011).
2.3.1 Trust antecedents
Most researchers agree that trust is led by three antecedents, namely: shared values, communication and opportunistic behaviour (Zaheer et al., 1998; Aulakh et al., 1996; Inkpen and Currall, 2004).
23 Shared values refers to the importance of sharing similar values because it allows the creation of a “clan-like” environment between partners, which allows for fostering dispute resolution and trust (Das and Teng, 2001). Sako (1998) states that having shared values can create value congruence, which avoids the possibility of distrust amongst collaborators. Therefore, this social bond improves trust.
Communication refers to information exchanged between partners in a relationship and can be defined as ‘formal and informal sharing of meaningful and timely information between firms (Anderson & Narus, 1990, p. 44). Increasing inter-firm communication is considered to be a determinant of trust, as it reveals openness and willingness to rely on the collaborators (Morgan and Hunt, 1994). This increased awareness contributes to the strength of the alliance, which contributes to its success.
Opportunistic behaviour can be regarded as self-interest seeking with guile, which can lead to increased transaction costs and more formal governance structures (Williamson, 1975). Therefore, it can restrain collaborative action as this would require absence of opportunistic behaviour, and harms the building of trust amongst collaborators. Evidently, Morgan and Hunt (1994) found a negative relationship between opportunistic behaviour and trust.
2.3.2 Trust Dimensions
Researchers also argue that trust is a multidimensional concept, but the study of trust dimension has been an area, where the number and content of dimensions studies still remains to be agreed (Mayer et al., 1995; Kuo, 2013). According to social capital theory, trust is based on social judgments such as assessment of the other party's benevolence, integrity, and competence (Inkpen & Tsang, 2005; Mayer,
24 Davis, & Schoorman, 1995). These three dimensions of trust may vary independently of each other, and reflect different expectations and therefore contribute uniquely to alliance (Levin and Cross, 2004). An example thereof is, that an integrity trust might result in a reduced threat of opportunism, but competence trust does not, which highlights the importance of distinguishing these three dimensions (Connelly et al., 2015). Competence trust is the belief that a partner possesses adequate resources and capabilities to meet cooperative requirements (Lui & Ngo, 2004). Integrity trust is the overall moral character and ethical behaviour of the partner or trustee, and benevolence trust is the positive vs. egocentric orientation of the trustee in dealing specifically with the focal organization (Mayer et al., 1995). Hence, we believe that the distinctive effect of integrity, benevolence and competence trust in an alliance on knowledge management calls for further evidence to quantify the relationship and to provide more evidence on its impact.
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3. Hypotheses Development
Based on the literature review this paper derives three hypotheses and proposes a conceptual model that illustrates the suggested relationships between the theories and concepts of the organizational KM process and project performance. These are examined in the next paragraphs.
To achieve a profound understanding between the constructs used in the hypotheses, it is important that these are measured on a consistent level. Choo et al. (2010) identified four different interaction levels that enable KM, namely: Individual, Group, Organizational and Inter-organizational. Since this research follows a knowledge-based view, the level of analysis of this paper solely focuses on the organizational level, with a particular focus on projects.
3.1 Overall Trustworthiness and Project Performance
We predict that overall trustworthiness is positively associated with project performance, because it will reduce costs and increase collaborative advantage. Trust, as utilized in this paper, is defined as “the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the focal organization, irrespective of the ability to monitor or control that other party” (Mayer et al., 1995, p. 712). According to social capital theory, trust is based on multiple dimensions such as assessment of the other party's benevolence, integrity, and competence (Inkpen & Tsang, 2005; Mayer, Davis, & Schoorman, 1995). We expect to see similar effects for each of the sub-dimensions of trust, however these will be analysed empirically to validate this and to measure to what extent they affect the overall level of trustworthiness. We
26 believe trust leads to lower cooperative costs, higher relational capital and increased confidence.
Firstly, trust should decrease both ex-ante and ex-post cooperative costs, which have a negative impact on project performance (Krishnan et al., 2006). This decrease from cooperative costs can stem from several areas. For an example, in the ex-ante stage, collaborators with higher levels of trust are more likely to arrive at “meeting of the minds”, which lowers negotiation costs due to time efficiency (Zaheer et al., 1998). Additionally, for higher levels of trust amongst collaborators, the perceived risk of opportunism decreases, where organizations perceive the collaborators to be trustworthy and cooperate, and therefore can reduce costs by minimizing monitoring and evaluation systems (Chiles and McMackin, 1996). This additional time can be spent on beneficial actions for better project performance, or to cut costs on the project’s budget.
Secondly, trust can serve as a proxy for relational capital, which allows for more pleasant and frequent interactions with the collaborators, and thereby improving project performance. Additionally, higher levels of trust reduce scope, intensity and frequency of conflicts, as collaborators have greater leeway, which reduces coordination costs (Zaheer et al., 1998).
Lastly, collaborators whom trust the partners are more likely to be confident in the project, and therefore perform better on the project, than if trust was not present. Additionally if there was temporary underperformance, the collaborators are more likely to accrue this to exogenous factors, and prevent alliance to terminate too early (Doz and Hamel, 1998).
If this paper mentions the collaborator’s overall trustworthiness, we mean that the organization in the alliance has a positive attitude towards the collaborators. This
27 means that the trust worthier the focal organization perceives the collaborators, the more likely the organization is to act in a trustworthy manner. Hence, this paper proposes that organizations that engage in an inter-organizational cooperation with higher levels of trust positively influence project performance due to lower cooperative costs, higher relational capital and higher confidence.
H1: Overall Trustworthiness is positively related to Project Performance
3.2 Mediating role of Knowledge Management
The relationship between Overall Trustworthiness and PP is likely to be mediated by Knowledge Management. Through IOCs, information and knowledge are created from different stakeholders, with cooperation being the overall aim of the process (Roloff, 2007). Knowledge creation requires the sharing and dissemination (i.e. collaboration) of personal experiences (Inkpen and Dinur, 1998). By bringing together individual differences, i.e. tools, background, an experience etc., the creation of new knowledge is facilitated through the presence of the IOC’s. Given this new knowledge, exploitative or explorative innovation can be sought for.
We expect overall trustworthiness to promote knowledge creation in two ways. On the one hand, when an organization feels confident about the capabilities of a collaborator, it will reduce the cost and time verifying the validity and usefulness of the knowledge (Kuo, 2013). This reduction of costs and time stems from a lower need and frequency of explanation, and spend time more productive for the project instead (Das and Teng, 2001). Additionally, the speed is improved, which allows the collaboration to seize the benefits of the collaborator’s knowledge, and apply this for new knowledge creation. On the other hand, trust generates incentives and
28 reciprocity for collaborative knowledge in IOC (Doney et al., 1998). This can lead to higher levels of intimacy, which allows for more collaborators to become more open and receptive of new knowledge and explore new opportunities together (Molina-Morales et al., 2011).
Secondly, once knowledge is created, it requires to be transferred, or disseminated, from one person, project or organization to another (Lee, 2001). Knowledge transfer enables organizations to replace out-dated knowledge with new knowledge acquired from the IOC, therefore maximizing the efficiency and effectiveness of its operations (Gold, Malhotra and Segars, 2001). Knowledge transfer enables or enhances the access to knowledge, which is needed to activate the transformation of collective individual knowledge to organizational knowledge.
Lastly, new knowledge can engage its recipients, through the knowledge transfer process, in learning but needs sufficient stimuli to activate the recipient (Thompson et al., 2009). According to Gold, Malhotra and Segars (2001) this results in accelerated product development times, increased functionality, and widespread adoption of knowledge if done well. Davenport and Klahr (1998) have experienced improved efficiency and reduced costs due to the effective application of knowledge in a customer support case. Thus, knowledge application can be used to adjust strategic direction of organizations, and their projects, and solve new challenges through organizational learning. Hence, this paper proposes that the KM process positively influences the effectiveness of the relationship between Overall Trustworthiness and project performance.
H2: The relationship between Overall Trustworthiness and PP is mediated by knowledge creation, -transfer and -adoption in serial, such that Overall
29 Trustworthiness will interact with knowledge creation, -transfer and -adoption in serial, which has positive impact on project performance.
3.3 Moderating role of Alliance Form
It is generally well empirically proven in literature that trusts supports exchange, of i.e. knowledge, and fosters cooperation (Doney and Cannon, 1997). However, the synergy of trust can be dependent upon the nature and form of the relationship (Park and Russo, 1996). Previous literature provides insights regarding the differential impact of horizontal versus vertical co-operations. For an example, Smith and Barclay (1997, p. 6) found that the “relative importance [of trust] may depend upon the nature and form of the relationship in which trust unfolds”. Therefore, this paper would like to add to literature by exploring the potential moderating effect of Alliance Form on the relationship between Overall Trustworthiness, Knowledge Management and Project Performance. Alliance form can be explored into two forms, namely: a horizontal alliance and a vertical alliance. A horizontal alliance is formed between partners operating in the same business area, whereas a vertical alliance is a partnership between a firm and its up- or downstream value chain players (Sarkissian, 2018).
Firstly, we expect horizontal alliances to experience a higher level of opportunistic self-interests compared to vertical alliances. This effect might be due to the competitive tension that exists between horizontal collaborators, as collaborators might use the cooperation purely to gain market position at the expense of a partner (Bucklin and Sengupta, 1993). Therefore, we expect that the level of trust is lower due to the relative higher level of opportunistic behaviour of horizontal alliances, and can inhibit the willingness to engage in knowledge management with the
30 “collaborator”-competitors. Therefore, trust serves as a less effective form of governance, as the collaborators are unable to know the motives of the others involved.
Secondly, trust facilitates exchange of knowledge but this effect is strengthened for vertical alliances due to their resource dependence (Doney and Cannon, 1997). This is in line with the findings of Gulati (1995) whom found that vertical alliances have greater interdependence due to their complementary assets of skills, than those of horizontal alliances. This interdependence might let organizations overlook their collaborators trust, as they are much dependent on the collaborators valuable resources for their inputs (Pfeffer and Salancik, 1978). Following the logic of Doney and Cannon (1997) they propose that different levels of dependence are likely to moderate the development and influence of trust. Therefore, we expect that vertical alliance forms engage in higher levels of KM than horizontal alliances due to their interdependence.
Hence, we expect that the relationship between Overall Trustworthiness, KM and Project performance be moderated by Alliance Form, such that vertical alliances perform stronger in KM than horizontal alliances due to lower opportunism and higher interdependence.
H3: The relationship between Overall Trustworthiness and PP through knowledge creation and -transfer in serial is moderated by Alliance form. Specifically, such that the relationship between Overall Trustworthiness and PP is stronger for vertical alliances than for horizontal alliances.
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3.4 Conceptual modelling
The conceptual model is one of the main aims of theory building in order to understand and/or explain a phenomenon. Based on the above-mentioned hypotheses a conceptual model, figure 2, has been designed to place these in relation to each other.
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4. Methodology
This section provides an overview of the applied research methodology for the current study of the three hypotheses mentioned in section three. A detailed description of the research design, data collection, sampling and the measures are provided in order to provide insights to how the construct is operationalized. Firstly, the research design is explained. Secondly, the population, sampling and data collection to obtain the data are explained. Finally, the construction of conceptual logic and measurements are presented.
4.1 Research Design
The researcher believes that management research can be understood as an applied field. This assumption is based upon the fact that organizations are not only concerned with understanding the true nature of organizations, but also with solving problems that are related to managerial practice (Bryman & Bell, 2011, p.5).
Research Approach Deductive use with inductive analysis
Research Strategy Quantitative Analysis
Time-horizon Cross-sectional study with Survey
Level of Analysis The organization
Research Design Self-completion Questionnaire
Analysis Technique Multiple Regression Analysis
33 Research Strategy
This study utilized a quantitative approach, which has been obtained through a self-completion survey (Appendix 1). This survey began with a concise introduction to the topic and its purpose, and ethics of conduct. The survey included a range of questions, related to, trust and its dimensions, alliance form, the three stages of the KM process, project performance, and some control- and moderating variables. In order to validate our research model empirically, we employ quantitative methods of data collection by means of a self-collection survey, as these are often employed to generalize a population from samples (Fowler, 2013).
Time-horizon and Research Design
This study obtained data in a specific time horizon (April - June 2018), which is also referred to as a cross-sectional design, in order to explain the relationship between knowledge management and project performance in co-operations. However, this study recognizes that learning is an on-going process, and that with our cross-sectional design we cannot infer causality between our constructs as it is measured at one point in time (Volberda et al., 2010). Therefore, a longitudinal approach would have been preferred as it involves multiple measurements of the same variables over a period of time allowing for causality inferences, and could demonstrate how perceived cooperation and trust develop the KM process of projects over time.
By means of the survey strategy the data is collected by a self-completion survey (appendix 1) on all samples and at a certain point in time (Bryman & Bell, 2011, p.54). The benefit of the survey strategy over that of the qualitative, is that they are cheaper and quicker to administer due to the absence of interviewer
34 effect/variability and their convenience for respondents (Bryman & Bell, 2011, p. 232-233).
4.2 Population, Sampling and Data Collection
Population and Sampling
In order to be able to assess the relationship between knowledge management and project performance in co-operations, the respondents should be located in high positions of the respective project. This study initially focused on founders, project managers and senior managers from various industries, geographies and firm sizes. However, as this study uses a single-respondent to represent an organization, there is a possibility of self-serving bias (Bryman & Bell, 2011, p. 190). This limitation presents itself due to the associated sampling strategy.
Data Collection and Input
This study operationalized its data collection through an Internet based survey system, namely Qualtrics, in order to collect, standardize and overlook the process. This English survey was accessible via Internet browsers, and all mobile devices with an Internet connection. An alliance has been established with a financial organization and an internal project management association in order to collect data. The research has been introduced to the population of interest by a newsletter including additional information about the research and a call-to-action to participate and forward to potential others people of interest. Additionally, the researcher has approached his personal network to recruit participants that fit the population of interest.
35 Concluding, this study combines a voluntary and snowball-sampling technique, as respondents were free to cooperate on this research and forward the questionnaire to the population of interest.
4.3 Construction of Conceptual Logic and Measurement
The questionnaire consisted out of established measures from existing literature capturing the various constructs of the conceptual model (Figure 2) in order to increase the likelihood of meaningful results (Churchill, 1979). Most of the measures utilized use multiple-indicator measures, and were rated on a 7-point Likert scale ranging from “Strongly Disagree” to “Strongly Agree” unless stated differently. By averaging the item means, the overall scale scores were computed per variable. The next sections shortly describe how each of the constructs were measured.
Dependent variable: Project Performance
In this study, project performance is identified as the single dependent variable. This construct is measured with seven items of Aladwani (2002). In their study, the composite reliability of project performance (0.89) exceeded the threshold of 0.70 with a .89 composite reliability. Therefore, measuring project performance along these measurements provide strong support for the reliability and validity of project performance.
Independent variables
Knowledge Creation, Knowledge Transfer and Knowledge Adoption are measured with items of Gold, Malhotra & Segars’ (2001) scale. Sample items include
36 “My organization has processes for acquiring knowledge about its customer” and “My organization has processes for replacing out-dated knowledge”. Overall Trustworthiness is measured with 12 items of Mayer and Davis (1999) measuring Integrity (⍺ = 0.83), Benevolence (⍺ = 0.83) and Competence (⍺ = 0.89) and Becerra et al. (2008) reported a ⍺ of 0.91 overall. Sample items include: “We never have to worry about whether this firm will keep to its word”. Alliance Form is measured by building a one-item construct to measure the nature of the collaboration. The construct of alliance form is operationalized by asking the respondent the following question: “Is the collaboration considered a horizontal or a vertical alliance?”.
Controls
In addition to the above-mentioned variables, this paper included five variables as covariates, namely, organizational difference, number of collaborators, number of FTEs on project, project duration and strategic level. The former two are organizational characteristics, whereas the latter three variables relate to the project. These variables are not directly related to this study, but might influence the other variables.
Firstly, the organizational size is of particular importance, as most research found a positive effect (Gupta and Govindarajan, 2000). Smaller organizations can gain management support easier given the flatter organizational structure. Therefore, it can be argued that the communication between stakeholders is more effective than those for large organizations, and in turn enhances the project performance. Previous research argued that aging organizations become inert and possess a limited ability to learn and adapt to changing circumstances (Boulding, Cyert and March, 1964). Younger organizations, in turn, are adaptive given their cognitive and
37 relational patterns and seem to have learning advantages over “older” organizations (Frost et al., 2002).
Secondly, the number of organizational collaborators is directly determined by the requesting the respondents to list how many collaborators were involved. This number has been adjusted accordingly, in consultation with the collaborators, if there were differing responses amongst respondents.
Thirdly, number of full-time employees (FTEs) on project is determined by requesting the respondents to indicate how many FTEs were involved in the project. This research suggest that there might be an inverted U-shape relationship, such that the more people involved would lead to an increase of heterogeneous knowledge creation and -sharing. However, this effect is expected to diminish as the cost of maintaining relationships will outweigh the benefits at a certain point.
Fourthly, project duration is a critical aspect of project size, which has been proposed to have affect project performance (McFarlan, 1981). Therefore, this research deemed controlling for its effect as imperative.
Lastly, strategic level is measured by three levels of importance, namely, strategic, managerial or operational. Wainwright et al. (2003) demonstrated that strategic projects call for higher complexity, which can result in lower project performance compared to non-strategic projects.
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5. Data Analysis and Results
This section provides a detailed description on the steps taken to analyse the acquired data from 85 samples to test the hypotheses and their potential linkage. All of the respondents completed the survey between April and June of 2018 with an average of 9 minutes. A step-by-step description is provided in the next sections, with more extensive analysis in the appendix. The analytical strategy and procedure of the analysis are described first, followed by a rich description of the data results of the analysis.
5.1 Data analysis
This section provides information about the gathered data set, including the respondents’ demographics (5.1.1). Subsequently, a general descriptive overview is provided to obtain a first impression of the research. Lastly, the validity analysis results are provided in order to ensure the validity requirements are met prior to the data analysis (5.2). To analyse the data, IBMs Statistical Package for Social Sciences (SPSS) version 24 was used.
5.1.1 Dataset and Demographics
The online questionnaire was distributed in a number of ways. Firstly, the online questionnaire was directly sent to 150 email addresses of the researchers’ contacts. Secondly, it was distributed through an internal mailing list of a financial institution. Lastly, it was distributed by an international project management association mailing list. Out of these distribution channels, 145 started the survey and 86 completely finished it, a completion rate of 59.3%. However, one particular
39 case was excluded from the dataset because this respondent answered all questions with “Agree” (score 2 on the 7-point Likert scale) and therefore appears to be highly unreliable, leading to a total dataset of 85 complete cases.
The demographics of the dataset are divided into project, organizational and personal characteristics. Looking at the project characteristics (Appendix 2), the majority of the projects have been performed on a strategic level (45.9%) followed by operational projects (43.5%). When looking at the project’s duration, the majority of the projects have taken over 25 months (30.6%), followed by shorter projects ranging from 1 to 6 months (29.4%). Taking a closer look the geographical situation, most projects have been performed in the European Union (64.7%), followed by projects performed in the Caribbean region (11.8%). Lastly, amount of FTEs involved in the projects ranged from 1 to 50 FTEs with an M of 9.5 FTEs involved with a SD of 12.88.
Looking at the organizational characteristics, the majority of respondents agree that the collaborators differ in terms of their resources (52.9%). When it comes to the amount of collaborating organizations involved, the range was from 2 to 80 organizations with an M of 8.96 organizations and a SD of 10.9.
Looking at the personal characteristics, the larger part of the respondents have senior roles, ranging from BU Manager (37.7%), Consultant (16.5%), Founder (14.1%) to Board Member (11%).
5.1.2 Data Interpretation of Constructs
This section provides a brief understanding of how the respondents have answered the questionnaire, and will cover the constructs of KC, KT, KA, PP and
40 Trust. Table 2 provides an overview of the means, standard deviations and variances of the aforementioned variables.
Min. Max Mean Std. Deviation Variance
Trust 1.00 4.25 2.58 0.79 0.63
KC 1.00 5.44 2.79 0.92 0.84
KT 1.33 5.00 2.89 0.83 0.69
KA 1.00 5.92 2.73 0.84 0.71
PP 1.00 4.43 2.51 0.68 0.47
Valid N (list wise), N = 69
Table 2: Means, Standard Deviation and Variance of Trust, KC, KT, KA and PP
There are several interesting aspects when looking at the answers given by the respondents to the Trust statements. Firstly, the respondents have a tendency to agree with the statements (M = 2.58, SD = 0.79). This means that the respondents of the sample believe, on average, that they trust the collaborators. Secondly, when diving a bit deeper into the dimension of trust, namely Integrity, Benevolence and Competence, there is a big discrepancy between the three. Competence scores highest on agree (M = 2.12, SD = 0.65), followed by Integrity (M = 2.63, SD = 1.08) and lastly Benevolence scores lowest on agree (M = 2.99, SD = 1.07). This means that the collaborations conceive the collaboration slightly more based on competence than Integrity or benevolence. Thirdly, looking at the variance, competence scores lower than Integrity or benevolence, meaning that the dispersion in the answers of the total sample (n = 85) is smaller for competence than for integrity and benevolence. This suggests that the respondents are more uniform with their ratings when it comes to the collaborators competence than for integrity or benevolence. Fourthly, when looking at the statements individually, organizations score highest on knowing what type of work the collaborators are good at (TrustCom4, M = 1.99, SD = 0.932). However, respondents also generally shed
41 doubt on the collaborators as they disagree on the fact that collaborators will go out of their way to help the organization (TrustBen4, M = 3.21, SD = 1.481) and that they do not have to worry about whether the collaborators will keep to their word (TrustInt2, M = 3.06, SD = 1.475). Apparently, the answers of the respondents indicate that collaborations are most often engaged in for the collaborator’s competence, but that integrity and benevolence play a less prominent role in their collaborative formation.
Taking a look at KC processes, the respondents have a tendency to agree with the statements (M = 2.79, SD = 0.92). This means that the respondents, on average, believe that their organization does enforce knowledge creation processes to an extent on their projects. When looking at the statements individually, it seems that organization score best on using feedback from projects to improve subsequent projects (KC4, M = 2.42, SD = 1.209). However, organizations have most difficulty with processes for benchmarking performance (KC10, M = 3.06, SD = 1.469) and on average do not have devoted teams in place that identify best practices (KC11, M = 3.04, SD = 1.609).
Taking a look at KT processes, the respondents have a tendency to agree with the statements (M = 2.89, SD = 0.83). This means that the respondents, on average, believe that their organization does enforce knowledge transfer processes to an extent on their projects. When looking at the statements individually, it seems that organizations score best on using processes for converting knowledge into the design of new products / services (KT1, M = 2.47, SD = 1.019). Interesting to note is that most respondents agree that their organization does not have processes for replacing out-dated knowledge (KT9, M = 3.49, SD = 1.629), and a large dispersion indicating this strongly differs amongst organizations. Additionally, generally the
42 respondents agree that their organization does not have processes for integrating different sources of types of knowledge (KT7, M = 3.30, SD = 1.302).
Taking a look at KA processes, the respondents have a tendency to agree with the statements (M = 2.73, SD = 0.84). This indicates that the respondents, on average, believe that their organization does enforce knowledge adoption processes to an extent on their projects. When looking at the statements individually, it seems that organization score best on using processes for applying knowledge learned from experiences (KA2, M = 2.45, SD = 1.097). Interestingly, organizations score lowest on quickly applying knowledge to critical competitive needs (KA11, M = 3.08, SD = 1.450) and identifying the sources of knowledge to solve new problems (KA5, M = 3.00, SD = 1.299) combined with locating and applying knowledge to changing competitive needs (KA8, M = 3.05, SD = 1.154).
Taking a look at PP, the respondents have a tendency to agree with the statements (M = 2.51, SD = 0.68). This indicates that the respondents of this sample believe, on average, that they have a positive project performance. However, when looking at the statements individually, all items are near the total mean PP3, which lays right of the total mean. This means that the respondents tend to agree that the projects just meet their initial budgets (PP3, M = 3.09, SD = 1.379).
5.1.3 Factor Analysis
In order to ensure that there is no overlap between the items measured, a factor analysis test has been performed (Thompson, 2004). The Kaiser-Meyer-Olkin (KMO) measure verified the sampling adequacy for the analysis of PP, KMO= 0.767. Bartlett’s test of sphericity 𝒳2 (21) = 130.199, p < .001, indicating that the correlation between the items were sufficiently large for Principal Axis Factoring (PAF) analysis.
