Who can I ask? How psychological safety affects knowledge sourcing among new product development team members

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Who can I ask? How psychological safety affects knowledge sourcing among new product development team members Umar Safdara,⁎, Yuosre F. Badirb, Bilal Afsarc a

Faculty of Business and Management, Information Technology University (ITU), 6th Floor, Arfa Software Technology Park, 346-B, Ferozepur Road, Lahore, Pakistan School of Management, Asian Institute of Technology (AIT), P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand c Department of Management Sciences, Hazara University, Mansehra, Khyber Pakhtoonkhwa, PK، N35 Karakoram Highway، Dhodial 2, Pakistan b

AR TI CLE I NF O

AB S T R A CT

Keywords: Psychological safety Sources of knowledge Search behavior New product development Teams

Knowledge source selection is a complex phenomenon that is often addressed from an organizational viewpoint; however, we know little about knowledge-seeking practices at the individual level. We examined knowledge sourcing in new product development (NPD) teams at the micro-level through the lens of psychological safety (PS). We investigated 1345 individuals at 85 software development teams in Pakistan to demonstrate how different levels of PS affected knowledge sourcing from three groups: within the team; within the organization; and outside the organization. Our results showed that individuals with high PS levels were more inclined to consult fellow team members and individuals with low PS levels were more likely to choose external sources. We also examined how the diversity of a team's composition affected the relationship between psychological safety and knowledge source selection. We explored the implications of these findings for managerial practice.

1. Introduction New products and services are fundamental to organizational performance and survival (Brown & Duguid, 1991; Chadwick & Raver, 2015; Collins & Smith, 2006; Ilgen, Hollenbeck, Johnson, & Jundt, 2005; Rubera, Chandrasekaran, & Ordanini, 2016), and new product development (NPD) success depends on how well NPD team members can access the best sources of knowledge and information (Carmeli & Schaubroeck, 2007; Chadwick & Raver, 2015; Frankort, 2016; Katila & Ahuja, 2002; Maggitti, Smith, & Katila, 2013; March, 1991). NPD is one of the most knowledge-intensive processes in business. Development teams must frequently adapt to shifting internal and external environments that are often uncertain, ambiguous, and confusing (Dayan, Ozer, & Almazrouei, 2016; Hoegl & Parboteeah, 2006; Sicotte & Langley, 2000). To face these challenges, and creatively solve taskrelated problems, NPD team members need up-to-date knowledge and information (Akhavan, Hosseini, & Abbasi, 2016; Knudsen, 2007; Swink, 2000). Indeed, the NPD team that is best able to identify new knowledge and information will also be the team that will best contribute to the firm's growth through strategic decision making (Cyert & March, 1963; Katila, Chen, & Piezunka, 2012; Mintzberg, 1973). Individual team members play a critical role in this search process (Ferreras-Méndez, Fernández-Mesa, & Alegre, 2016), since a team's strength depends on the quality of its members. The cumulative capability of team members to find and utilize knowledge plays a fundamental role in defining both the team's and the firm's overall capabilities (Carmeli & Schaubroeck, 2007). The knowledge sources available to NPD team members can vary along a spectrum from internal to external, with many degrees

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Corresponding author. E-mail addresses: [email protected] (U. Safdar), [email protected] (Y.F. Badir), [email protected] (B. Afsar).

http://dx.doi.org/10.1016/j.hitech.2017.04.006

1047-8310/ © 2017 Elsevier Inc. All rights reserved.

Please cite this article as: Safdar, U., Journal of High Technology Management Research (2017), http://dx.doi.org/10.1016/j.hitech.2017.04.006

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in between. Knowledge can be obtained from three types of sources (Hansen, Mors, & Lovas, 2005). First, the “within-team” allows team members to limit their knowledge search to within a team (Almirall & Casadesus-Masanell, 2010). Second, the “intraorganizational”, allows team members to access information from personal relationships in other functional areas and subsidiaries outside the team's boundaries but within organizational boundaries. Third, “external sources” allow team members to seek information from outside the firm's boundaries. NPD team members tend to have individual selection preferences when they choose a knowledge source. While the performance impact of different sources of knowledge has been well documented in the literature (Du, Leten, & Vanhaverbeke, 2014), surprisingly, the antecedents of the knowledge selection process, especially at the individual level, have not received much attention (Borgatti & Cross, 2003). Researchers have not explicitly answered questions such as what motivates an individual NPD team member to select a particular source of knowledge over other sources, or why a team member would seek knowledge outside the team, even if this knowledge is available within the team. A review of the limited literature on the antecedents of knowledge source selection reveals why this neglected area of research requires more attention. First, the strategic management literature relies on a resource-based view to examine the antecedents and suggests that a firm's existing internal capabilities is what determines how knowledge is sourced, and that this affects the level of innovativeness (Caloghirou, Kastelli, & Tsakanikas, 2004). The strategic perspective, however, focuses mainly on the firm level and ignores the team and individuals within a team. This is an important distinction because individuals in NPD teams play a pivotal role in searching, collecting (Barczak, Griffin, & Kahn, 2009), and utilizing knowledge (Du et al., 2014; Mytelka & Smith, 2002; Tang & Naumann, 2016; van de Ven, 1986). Although the firm can design, organizational systems, incentives, and procedures to encourage team members to search for new knowledge, it is the employee of an organization who actually engages in the search activity rather than the organization (Li, Maggitti, Smith, Tesluk, & Katila, 2013; Tang & Naumann, 2016). Indeed, some ethnographic studies of workplace practices have indicated that the ways in which individuals actually work may differ from the ways in which organizations describe that work in strategic plans, manuals, organizational charts, and job descriptions (Brown & Duguid, 1991). Therefore, organizations need to understand the knowledge-seeking behaviors of their individual members, especially those in NPD teams, where knowledge is needed the most. Second, social network theory (SNT) scholars have considered the same questions by examining the nature of the informal social relationships between the two sides (Gillian Ragsdell, Stadler, & Fullagar, 2016; Gupta & Govindarajan, 2000). They have typically examined the strength of the social ties within the team or network, to investigate the impact of a tie-strength on types of knowledge selection (tacit vs. explicit) and innovation (Badir & O'Connor, 2015; Wang, 2016). Social network theory focuses mainly on the social dimension of knowledge seeking and ignores any psychological processes. Although Crossan, Lane, and White (1999) argued that knowledge search behavior and learning at the individual, team, and organizational levels are linked by social as well as psychological processes, social network research has only considered the influence of observable individual attributes, such as gender, rather than investigating individual psychological characteristics (Kalish & Robins, 2006; Mehra, Kilduff, & Brass, 2001; Totterdell, Holman, & Hukin, 2008). This is unfortunate, since as Totterdell et al. (2008) discovered, the psychological attributes of individuals within a team are very likely to affect other team members, both in terms of the team's cohesion and the strength of the ties between people within the networks. In addition, SNT tends to exclude the impact on the team when an individual team member's decision making process affects the search for knowledge. There is, therefore, a need for research to explore the antecedents of knowledge source selection at the NPD team member level that take into account the impact of the NPD team members on each other, and the psychological mechanisms that may affect the relationships between the individual team member, the team as a unit, and how knowledge is sourced. In team settings, the degree of psychological safety (PS) determines individual team members' perceptions of safety within the group, the ability to learn, behavioral change, and work engagement (Edmondson, Kramer, & Cook, 2004; Newman, Donohue, & Eva, 2017). An individual's behavior is influenced by PS because the actions taken are based on the level of risk attached to them (Edmondson & Roloff, 2008; Newman et al., 2017; Yagil & Luria, 2010). In a psychologically safe environment, members share a general sense that others will not punish them for their mistakes, and consequently, they will not be reluctant to ask questions, seek knowledge and share their innovative ideas since they have no fear of being wrong or of being blamed for slowing the team's progress (Edmondson, 1999; Koopmann, Lanaj, Wang, Zhou, & Shi, 2016). If team members fear the possibility of negative social consequences (being embarrassed, criticized, or ridiculed) from risk-taking, they will probably avoid asking questions (Kark & Carmeli, 2009; Kostopoulos & Bozionelos, 2011). The effect of PS on individual and team learning has been theoretically and empirically examined (Edmondson, 1999; UngerAviram & Erez, 2016), but we know less about the relationship between PS and knowledge source selection. Therefore, to address this gap in extant research on the antecedents of knowledge source selection, our first objective is to investigate how PS affects an NPD team member's knowledge source decision making process. Most NPD projects are carried out by cross-functional teams (Ayağ, 2016; Joshi & Roh, 2009; Keller, 2001; Parker, 2003). The cross-functional team structure provides an opportunity to integrate knowledge, skills and expertise from diverse fields to achieve project goals. Scholars have suggested that a team's composition influences members' behavior towards learning (Bell, 2007; Edmondson & Lei, 2014; Mesmer-Magnus & Dechurch, 2009; Tekleab, Karaca, Quigley, & Tsang, 2016) and choosing a knowledge sources. Therefore, our second objective is to explore how team composition moderates the relationship between PS and knowledge source selection.

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2. Theoretical background Knowledge search selection describes “where” an individual decides to look for new knowledge and it determines the kind of knowledge available to them (Fiske & Taylor, 2013; Koput, 1997). The search process for new knowledge is an integral part of the organizational learning process, through which firms attempt to solve problems in an ambiguous world (Huber, 1991). Organization's approach the search for knowledge in a wide variety of ways. Sometimes they want to optimize organizational design (Bruderer & Singh, 1996; Loebbecke, van Fenema, & Powell, 2016) for optimal manufacturing methods (Ferreras-Méndez et al., 2016; Jaikumar & Bohn, 1992), or to discover the best ways to implement new innovations (Von Hippel & Tyre, 1995). We focused here on one specific type of search, the search for solutions to problems faced by team members during the new product development phase. Social network scholars have postulated that an individual seeks knowledge from those with whom he/she has a social relationship. In this research, we draw on psychological research and suggest that how an individual chooses, develops and maintains a social relationship is determined by how that individual perceives others and how he/she imagines others perceive him/her. Our general proposition is that the source of knowledge selection depends on, and is influenced by, the level of PS of each member in the NPD team. Innovative activities and problem-solving efforts in NPD projects are associated with different types of risks, uncertainties, and even with the failure of development processes (McDermott & O'Connor, 2002; Tatikonda & Rosenthal, 2000; Veryzer, 1998). We argue that when an NPD team member feels psychologically safe, that person is more likely to search for knowledge internally, from fellow team members. Conversely, the NPD team member who does not feel psychologically safe is more likely to search for knowledge externally, or outside the team. Moreover, since project team members interact and work with each other, we argue that the team's composition, in terms of knowledge diversity, moderates the relationship between PS and the person selected as the knowledge source. 2.1. Psychological safety (PS) In today's business environment, most tasks are interrelated and are usually accomplished by individuals in a collaborative manner (Collins & Smith, 2006). Narrow fields of expertise and the complexities of modern work require people to integrate their specialized knowledge with that of others to achieve organizational goals (Knudsen, 2007). When people work together in groups they often feel that their professional reputations are at risk when they contribute ideas or suggestions. For example, if a group member admits to making an error, that person risks appearing either incompetent or less trustworthy to other members. The stakes are even higher when people admit to a mistake in front of a superior who has the power to either promote or demote them. Sometimes people will try to save face, or avoid the risk of negative social exposure, by not reporting a mistake, a unique idea or by avoiding seeking help from others (Brown & Leigh,1996; Goffman, 1955; Lee, 1997), even when they believe that their contribution would benefit the team or organization. When people are concerned about taking an interpersonal risk they tend to act in ways that inhibit them from seeking knowledge from other people. Organizational research has identified PS as an important factor in understanding how people collaborate to achieve a shared outcome (Edmondson, 1999, 2004). When all team members feel psychologically safe, this shared perception creates a key team quality (Kostopoulos & Bozionelos, 2011) that allows all members to believe that “the team is safe for interpersonal risk-taking in a particular context, such as a workplace”. The level of PS will have an impact on team member beliefs about interpersonal interactions, and these are likely to be shaped by the history of these interactions within the team. When relationships within a team are based upon mutual trust and respect, individuals feel comfortable enough to ask questions and admit to making mistakes, because they are likely to believe that they will be given the benefit of the doubt, and this will in turn contribute to a sense of psychological safety (Edmondson, 2002). Some researchers have examined PS as a feature of organizational culture (Baer & Frese, 2003), others as a team characteristic shaped by a team leader's behavior (Edmondson, 1999; Edmondson, Roberto, & Watkins, 2003), while still others have investigated PS by studying how different personal characteristics among individuals in a group can encourage or discourage taking interpersonal risks (Edmondson & Lei, 2014). In this research, we focus on how individual NPD team members perceive their own levels of psychological safety and how these perceptions influence their knowledge-sourcing behavior. The construct of PS dates back to early research on organizational change by Tierney and Farmer (2002), who found that in order for people to cope with significant change, they needed to feel psychologically safe. Schein (1985) argued that a high level of PS helped encourage innovation among team members because it allowed them to confront potentially challenging data that could disconfirm their expectations or hopes, without triggering a defensive response. Although a context that encourages PS allows people more freedom to share ideas, this does not necessarily mean it creates a cozy environment in which people are close friends, nor does it suggest an absence of pressure or problems (Carmeli, Brueller, & Dutton, 2009; Edmondson & Mogelof, 2006). The construct is distinct from group cohesiveness, which tends to reduce the willingness among group members to disagree with each other and challenge others' views (Edmondson, 1999). A psychologically safe context describes a “climate in which the focus can be a productive discussion that enables early prevention of problems and the accomplishment of shared goals, because people are less likely to focus on selfprotection” (Edmondson, 1999). It is thus important to note that PS does not reduce conflict in teams; instead, it allows the team to be managed more productive than it would be if team members felt psychologically threatened, or unsafe (Barsade, 2002; Kelly & Barsade, 2001). As discussed earlier, most NPD work is done by teams of people with a diverse range of knowledge and experience (Parker, 2003). Psychological safety can also be applied to analyse how team members choose to express their opinions, work together and learn. Researchers have studied how high PS levels can facilitate the willing contribution of ideas and actions in a shared enterprise (Collins & Smith, 2006; Siemsen, Roth, Balasubramanian, & Anand, 2009), encourage team members to offer 3

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suggestions for organizational improvements (Detert & Burris, 2007; Liang, Farh, & Farh, 2012), and give individuals the courage they need to take the initiative in an NPD team (Baer & Frese, 2003). Other researchers found that high PS levels enabled teams and organizations to learn (Bunderson & Boumgarden, 2010; Carmeli, 2007; Carmeli et al., 2009; Tucker, Nembhard, & Edmondson, 2007) and perform better (Carmeli, Tishler, & Edmondson, 2012). Gong, Kim, Lee, and Zhu (2012) studied the relationships between PS and individual creativity and information exchange. They found that proactive employees wanted to exchange information with others, which in turn fostered trusting relationships that reinforced the psychologically safe environment required for employees to share their creative activities. Siemsen et al. (2009) examined the effects of PS on knowledge sharing among co-workers in both manufacturing and service operations. They posited that when employees felt psychologically safe, they were motivated to share knowledge and they argued that the level of confidence these individuals had in the knowledge to be shared would moderate this relationship. Mu and Gnyawali (2003) studied enablers of team effectiveness measured as a function of effective communication and the development of knowledge and skills. They examined the roles that PS, task conflict, and social interactions played as antecedents of knowledge development and perceived group performance. The study involved 132 senior level undergraduate business students enrolled in a business policy and strategy course in an eastern US school, who completed two group tasks: (a) an in-depth analysis and presentation of a business case, and (b) a critique of the analysis (conducted by another group). The survey results showed that task conflict negatively affected synergistic knowledge development and that PS moderated these negative effects. That is, when PS was higher, student perceptions of group performance were better, mitigating the negative effects of conflict on performance. Mu and Gnyawali (2003) drew from these results to propose that PS helps students manage team assignments effectively. Kostopoulos and Bozionelos (2011) studied the impact of PS on exploratory and exploitative learning activities at the team level. They found that a team's PS level was positively related to exploitative learning and positively, but nonlinearly, related to exploratory learning. One possible explanation offered by the researchers was that a psychologically safe environment motivates team members to take the risk of proposing novel ideas, and that this reinforced the exploratory learning process, which in turn, enhanced team performance. Organization and psychology scholars have also suggested that PS has become both a theoretically and practically significant phenomenon because of the increasing significance of learning and innovation in today's organizations (Edmondson & Lei, 2014), and because both are critical to NPD project team success (Edmondson & Nembhard, 2009; Kostopoulos & Bozionelos, 2011). While prior research, improved our understanding of the relationship between PS and both learning and knowledge sharing in teams, only limited research has been conducted into the potential impact of PS on a team member's decision to select a particular knowledge source. This research fills this gap in the literature by investigating the relationship between the PS levels of NPD team members and why they select a particular knowledge source. 2.2. Knowledge sources Since NPD projects are characterized by particularly high levels of uncertainty and complexity (Tatikonda & Rosenthal, 2000), and search behavior is a very common response to both (McKenna, 1986). When an individual begins a search, the investigation not only improves upon that person's existing knowledge, it also increases the number of available knowledge sources from which to choose. Since technological fields are progressively dynamic and multidimensional. Individual NPD members face challenges when sourcing applicable information because that information is often distributed across organizations and people (Huber, 2013; Kogut & Zander, 1992; Rodan & Galunic, 2004). Although the knowledge management literature has analysed the transfer of knowledge from one point to another (Gupta & Govindarajan, 2000; Hansen et al., 2005; Szulanski, 1996; Zander & Kogut, 1995), it has overlooked a critical step that one might think would logically precede the knowledge transfer; the decision-making process a person follows when selecting a source of knowledge. Therefore, scholars do not know much about what motivates an individual member of an NPD team to select one source of knowledge over others. NPD project team members may rely on one or more sources of knowledge. Specialists in social network research, organizational learning, and knowledge management have all highlighted the benefits of diverse knowledge sources (Dahlander & Piezunka, 2014; Mesmer-Magnus & Dechurch, 2009; Salter, Ter Wal, Criscuolo, & Alexy, 2015). Hansen et al. (2005) identified these sources according to three categories: (i) within team boundaries; (ii) intra-organization (other functional areas or teams within the organization); and (iii) external sources outside the organization. Internal knowledge sources would include personal relationships among team members (Podolny & Baron, 1997). When a team member joins a project team with whom he/she has had a positive previous experience, this established relationship may influence that person to channel his/her time and energy towards the team. When challenged with new project-specific problems, for instance, he/she may try to solve them by interacting with team colleagues and then asking them for information (Horwitz & Horwitz, 2007). This behavior would be more likely to reduce the need to seek knowledge from outside the team, including from other functional units or teams in the organization (Hansen et al., 2005). Some benefits of seeking knowledge from within team sources include a reduced search cost and minimal knowledge transfer time (Anderson, Glassman, McAfee, & Pinelli, 2001). One consistent empirical finding in the literature has been that information seekers follow Zipf (1949) “principle of least effort”. This principle holds that people attempt to tackle their problems by taking the path of least resistance. In the context of the knowledge search, a person would be most likely to choose the most convenient source, even if that source was just good enough to meet minimal requirements. This principle advocates that convenient access to a source of knowledge is the foremost factor in source selection. Morrison (1993) argued that time pressure, which is always at play in high-tech NPD projects, might also explain why someone would seek out the most convenient source. 4

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Another benefit of seeking knowledge from a team source is that it is not only easily accessible, but also fits the project's needs. Since the knowledge comes from those who know the project's goals, objective, and available resources, it is easier for the members to incorporate and implement this knowledge into the project (Dougherty, 1992). These members would most likely have a profound understanding of this knowledge, as it would have been used before and would be in line with the firm's knowledge. Moreover, the individual NPD team members may need organizational approval to engage with external sources of knowledge. For example, even though big R & D organizations are more inclined towards open innovation strategies, these organizations are also concerned about the creation and protection of intellectual property, which significantly affects the ways in which they engage with external sources (Salter et al., 2015). Therefore, if for example, due to the fear of knowledge leakage and the need to maintain appropriate control rights, such as the ability to obtain patents, organizations might discourage their employees from collaborating with external sources (universities or competitors) by creating internal barriers, such as insisting on prior approval from top management (Salter et al., 2015). To avoid such barriers and time constraints, NPD team members would prefer to consult internal sources, especially if they were functionally diversified, as would be the case in cross-functional teams. One caveat however, is that internally-focused teams risk ignoring opportunities and knowledge available from external sources (Ilgen et al., 2005). Intra-organizational knowledge sources refer to a kind of open culture that involves cross-functional cooperation and includes sharing knowledge and information among all staff in an organization (Bond, Walker, Hutt, & Reingen, 2004; Fey & Birkinshaw, 2005; Morrison & Phelps, 1999). These sources include colleagues, previous teammates, and friends working in other functional units (R & D, marketing, design, or manufacturing), or on other projects, and would also include consultations with other teams within the organization. Hinds and Pfeffer (2003) argued that individuals consider themselves to be part of their own functional units or work departments and that they try to set themselves apart from other work teams. According to social identity theory, an individual's wish for positive self-evaluation leads to an in-group bent, in which he/she would value the characteristics of people in their own functional unit and would devalue the characteristics of those in the “out-group” (Abrams & Hogg, 1990). This means an NPD team member would regard the knowledge of fellow team members as outstanding, up-to-date, and complete, and would minimize the value of any other knowledge that came from outside of his/her team, and this would have a negative influence on the team's project performance. External knowledge sources of knowledge refer to any source that resides outside the firm's boundaries, such as users, consultants, suppliers, university staff, and competitors (Salter et al., 2015). These external sources can sometimes offer knowledge seekers critical information that could be used to develop commercial opportunities for their organizations (Dahlander & Frederiksen, 2012; Franke, Von Hippel, & Schreier, 2006). However, external sources must be valued by the team's members before they would be accepted as worthy consultants. Organizations are changing their search strategies to acquire the most up-to-date knowledge, by opening their doors to external knowledge sources to strengthen the expertise of their internal knowledge (Cassiman & Veugelers, 2006). Scholars refer to this approach as open innovation (Chesbrough, 2003). Organizations are encouraging their R & D employees to develop external contacts as potential knowledge sources (Salter et al., 2015). These people could be users, consultants, suppliers, university staff, or competitors who might be convinced to share critical knowledge with an organization that could be applied to R & D innovations to create commercial opportunities (Dahlander & Frederiksen, 2012; Franke et al., 2006). NPD team members sometimes consult external sources of knowledge and information from their personal social networks as well. Dahl and Pedersen (2004) found that when engineers working for wireless communication firms networked with their peers (university alumni or former colleagues) outside of work, they often discovered useful information that could be applied to their own work. This access to external sources of knowledge protected them from technology development failure and output uncertainty (Ahuja, 2000; Cassiman & Veugelers, 2006; de Faria, Lima, & Santos, 2010; Veugelers & Cassiman, 1999). Even though this trend encourages individuals to become more open, research into the antecedents and consequences of this direction for individual workers has barely begun. Most research in this domain has focused mainly on the antecedents and consequences of organizational-level openness (Dahlander & Gann, 2010), and has only recently shifted to the project level (Salge, Farchi, Barrett, & Dopson, 2013). Alguezaui and Filieri (2010) investigated how certain team-level properties affected the development of team members' knowledge networks through the course of a team project. They used data from 145 software development projects and found that the teams believed that their organizational climate was suitable and safe for knowledge sharing, and that when the teams perceived networking as important for the success of the project, this fostered individual network building. However, when the team perceived its technical capability and material resources as sufficient, this discouraged individual team members from developing their own networks. While previous studies have improved our understanding regarding the benefits and limitations of different sources of knowledge in NPD teams, we do not know enough about how knowledge sources are selected. We only know that decisions are not made rationally by weighing and analysing the costs and benefits of available options. Instead, decisions seem to be based on unconscious psychological processes that weigh the pros and cons of risk-taking against how safe a team member feels. If they feel psychologically safe, they will feel safe enough to take interpersonal risks by asking others for suggestions, solutions and knowledge. 3. Hypothesis development 3.1. High PS and within-team knowledge sources According to the principle of least effort (Zipf, 1949), people strive to solve their problems in such a way as to minimize the total amount of effort that must be expended, so this suggests that internal knowledge sources would be ideal because they are easily 5

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accessible and require little effort to implement whatever is learned. Social network theory (SNT) on the other hand suggests that individuals seek knowledge from those they know and with whom they have a trust-based informal relationship that has developed over time. This theory implies that after working together for some time, NPD team members develop trust-based informal relationships with each other, and as a result, they are more likely to turn to these colleagues for help when seeking knowledge, thereby reaping the benefits of within-team sources of knowledge. If the requisite knowledge is not available from someone within the team, then the search might expand further, to sources outside the team. However, despite all the benefits that a team member could gain from seeking knowledge from fellow teammates, not all NPD team members will develop trust with each other through informal relationships (Dahl & Pedersen, 2004), and these latter individuals are more likely to seek out knowledge form other sources, even if the information they need were available from someone within the team. Why would someone behave in this way? SNT is still not able to answer this question. It has excluded the logically prior phase of the dynamic of knowledge source selection by NPD team members. We suggest that a team member's decision to choose a knowledge source will depend on his/her PS level. Specifically, he/ she would consult fellow teammates to learn something new only if he/she feels psychologically safe. We argue that a psychologically safe environment motivates team members to pursue knowledge from each other because they recognize that they have latitude and support from them (Crossan, 1998). When an NPD team member's perceived interpersonal risks are low enough, he/she would be less reluctant to seek help from colleagues within the team and to discuss errors with them. Some of these insights can be found in research that shows that high PS levels among group members can reduce the tendency to withhold unusual information (Sanna & Shotland, 1990). In sum, team members who feel psychologically safe in their teams prefer to take advantage of internal knowledge networks. H1. Team members who have a high sense of psychological safety are more likely to seek and utilize internal knowledge sources from within their teams. 3.2. Medium PS and intra-firm knowledge sources Intra-organizational sources of knowledge are part of an open culture, involving cross-functional cooperation that includes knowledge searches and sharing within an organization (Bond et al., 2004; Fey & Birkinshaw, 2005; Morrison & Phelps, 1999). This source, includes colleagues, previous teammates, and friends working in other functional units (R & D, marketing, design, or manufacturing) or projects or teams within the organization. In a medium-level psychologically safe environment, a team member may have the feeling that he/she is not safe enough to take all interpersonal risks, but, at the same time, feels that some risk would, most likely, be tolerated by his/her team members. It would mostly depend on how the particular individual personally perceived the level of risk. For instance, the team member may feel that small mistake would not be held against him/her, and that it would be all right to be perceived as being moderately different from others, in terms of skills and knowledge, so even if a risk fails, the team would not punish or blame him/her for the failure. In this environment, a team member would feel safe enough to discuss some problems with team colleagues and seek help or feedback about routine tasks that would not have a significant impact upon the team's overall outcome. However, if the outcome of critical and crucial tasks were at stake, then the team member would probably consult other sources in order to avoid taking interpersonal risks with fellow team members. When team members feel a medium PS level within their team, they would consult experts either within the organization or outside the organizational boundaries. We argue that these members would most likely seek knowledge from other members within the organization than from external sources for several reasons. First, as a member of a cross-functional team, which is the case in this research, he/she would probably have established interpersonal relationships with some members from his/her unit within the organization (Choo, Linderman, & Schroeder, 2007), or from previous NPD projects. Social network research emphasizes the positive impact of established and prior positive relationships when seeking out knowledge and sharing behavior because these relationships would feel familiar and therefore safe and secure. Second, compared to external sources, knowledge from intra-organizational sources is easily accessible and a better fit for the NPD project since the consultant would already know the project's needs and objective. The organizational familiarity would make it easier to incorporate the knowledge into the project and, consequently, it would be easier to implement. Third, there is less of an issue with information confidentiality when the knowledge comes from other sources within the organization (outside the team but within the organization) compared to accessing external sources. So, people with a medium PS level would be more likely to seek knowledge from intra-organizational sources than from within the team or from external sources. H2. Team members with a medium sense of psychological safety seeks knowledge from intra-organizational sources. 3.3. Low PS and external knowledge sources According to the principle of least effort, team members prefer to seek knowledge from the most convenient source available (Zipf, 1949), and this would usually be from their team colleagues (Morrison, 1993). However, at the same time, individuals avoid engaging in behaviors that can risk portraying them as ill-informed, ineffectual or disruptive in front of their team members (Schein & Bennis, 1965). They also will not want to risk sounding stupid, unless the team emphasizes the importance of a PS climate among team members (Carroll & Edmondson, 2002). We argue that convenient and accessible sources of knowledge are not the only criteria for selecting knowledgeable sources, because PS is an important antecedent of the source selection process. Team members who do not feel psychologically safe are more likely to perceive interpersonal exchanges as very risky, so they will avoid seeking 6

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knowledge from their colleagues even if it is readily available to them. In extreme cases, members with very low PS levels prefer to seek knowledge and feedback externally, or from outside the firm, for the following reasons. First, a person who does not feel psychologically safe will probably be reluctant to seek information from members of other groups within the organization because of the fear that their team members would perceive them as unknowledgeable and therefore less trustworthy. Second, by asking other colleagues within the organization rather than the individual's own team members, the colleagues would be more likely to question why they were not consulted. This may lead others in the organization to suspect that there is a conflict within the team. To avoid potential conflict with colleagues, and to safeguard a personal reputation at work, the members with low PS levels would prefer to consult people from outside the organization. H3. Team members with low levels of psychological safety prefers to seek knowledge from external sources. 3.4. Team composition A team, in both a work and an organizational context, is “a task-related group, which comprises employees who work together to complete a particular task or project” (Parker, 2003). Team composition is the configuration of member attributes in a team (Levine & Moreland, 1990; Moreland, Levine, & Wingert, 2013; Somech & Drach-Zahavy, 2013); therefore, it has a powerful influence on team outcomes (Steffens et al.; Kozlowski & Bell, 2003). Scholars argue that team composition is a significant factor in promoting NPD team success (Hulsheger, Anderson, & Salgado, 2009; Somech & Drach-Zahavy, 2011) because it affects how the members' knowledge and skills are applied to a team task in terms of both task completion and interdependent work (Hackman, 1987; Huang, 2009; Koriat & Gelbard, 2014; Rulke & Galaskiewicz, 2000; Stevens & Campion, 1994). The ideal NPD project team would be comprised of members whose, knowledge and skills would match those required to successfully complete the project (He, Butler, & King, 2007). Since no single individual team member has all the knowledge and information required to complete a project alone, team members must share knowledge and information with each other to fill any (Katzenbach, 1993) knowledge gaps. Ideally the team members' diverse range of experience and knowledge will be enough to generate the ideas needed to successfully complete an NPD project (Somech & Drach-Zahavy, 2013; Somech & Khalaili, 2014). Functionally heterogeneous teams, as is the case in cross-functional teams, assemble people from different disciplines and functions who have pertinent expertise in the proposed course of action (Saravanabawan & Long, 2014). We argue however that this is not enough, and that a high level of functional diversity enhances the effect that PS will have on how knowledge sources are chosen. A well-diversified team in the presence of a psychologically safe environment increases the probability that the required knowledge will be available from people within the team (Hulsheger et al., 2009). When this information is easily accessible, team members with a PS level prefer to acquire knowledge from within their teams and the team's diversity reinforces this relationship. Similarly, in a well-diversified team, each team member has his/her personal and social networks outside the team, which enables the team to explore and utilize more knowledge sources; consequently, team diversity triggers communication with knowledge sources outside the team (Drach-Zahavy & Somech, 2001; Perry-Smith & Shalley, 2003; Somech & Drach-Zahavy, 2011). Team members that feel psychologically safe will try to utilize the social networks of their colleagues to gain access to external sources of knowledge. We can hypothesize that: H4. Team diversity will moderate the impact that PS will have on within-team knowledge sources, such that the relationship will be stronger under higher levels of team diversity. In this research, we argue that team composition has no moderating impact on either intra-organizational or external sources. When PS is either at a medium or at a low level, meaning the member does not feel safe or secure enough within the team, he/she will not seek knowledge from fellow team members, no matter how diversified the team may be or even if he/she is aware that the necessary knowledge is accessible from a team member. 4. Research method 4.1. Participants and procedures The data were collected from individuals working in NPD software development teams in four major cities in Pakistan. Targeted teams adopted the typical structure of a software development project team and had to complete each project within an allotted time. Due to the complex nature of the projects, team members had to communicate and interact intensively with each other, and with external agents, through face-to-face or electronic means, and they had to fulfil different roles. Consequently, it was crucial for teams to seek out new knowledge and to exploit the available skills and information to accomplish their project goals. To access different software houses, in Pakistan, a letter outlining the purpose of the study that included the assurance of confidentiality of the information was sent to the Pakistan Software Houses Association (P@SHA). P@SHA ranks all registered software houses, according to the previous year's sales volume, and forwarded our request to the top 250 software houses. Most of the targeted software houses were developing software for both local and international clients. Out of 250 software houses, 85 (34%) houses agreed to participate in this study. This procedure led to the selection of 85 software development project teams comprising 1345 individual members. The members were employees from various departments within these companies. Once firms agreed to participate, they were asked to identify specific contacts for future correspondence. Next, the authors and four research assistants visited each participating team and its managers, and distributed the questionnaire in English (all respondents were proficient in 7

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English). Each team and software house received a unique code to identify and measure team level diversification and to convey the results of the study. The questionnaires included measures for individual preferences for different sources of knowledge, PS, and team composition. Each team manager was asked to provide demographics and project-related information about the teams and their members (age, educational background, team size, project duration, and project type). A test for selection bias demonstrated no significant difference in project type, size, city, and project duration. Out of 85 teams, 23 were located in Lahore, 20 in Islamabad, 30 in Karachi, and 12 in Peshawar. Team size ranged from 5 to 25 members (M = 15.82, SD = 2.2), and the mean project duration was 11.5 months (SD = 7.8). All participants had either an undergraduate or a master's degree. The mean age of the participating team members was 32.5 years (SD = 3.5), and 82.5% of participants were male. 4.2. Measurement All variables except team composition were assessed based on previously developed scales. Responses were coded on 7-point Likert-type scales. The team's PS variable was measured using Edmondson (1999) 7-item scale (e.g., “If you made a mistake in this team, it was often held against you”; “It is safe to take a risk in this team”). Negatively stated the items were reversed in the scoring process so that higher scores, on the scale indicated lower PS levels. Cronbach's alpha for this measure was 0.92. The knowledge sources (within, intra-organizational, and external) were measured using a 7-item scale proposed by Laursen and Salter (2006). Items were measured on a 7-point scale ranging from 1 not used, to 7 routinely used. Cronbach's alpha for this measure was 0.87. Team composition was measured in terms of gender heterogeneity, educational heterogeneity, experience heterogeneity, and functional heterogeneity. Blau (1977) index of heterogeneity was used to develop measures of functional (programming, analysis, testing, marketing and customer services) and gender diversity within the team. The index was calculated as 1-ƩPi2 where P is the proportion of individuals in a category and I is the number of categories. Cronbach's alpha was 0.95. The project type, gender, and project duration were included as control variables. 4.3. Data analysis and common method variance Because all measures were self-reported, we conducted two tests to examine the extent of method variance in the study. First, a Harmon one-factor test was conducted (Podsakoff & Organ, 1986). We specified a model using the five variables of interest, which indicated that common method effects did not contaminate the results of the current study. These results were confirmed by performing Widaman (1985) procedures to test for common method variance. We adopted an approach proposed by Williams, Cote, and Buckley (1989) that involved testing a multifactor measurement model. This included applying a model with a single method factor and testing it, as well as a measurement model with an additional method factor, and finally, a null model was examined. The results showed that the method factor did not improve model fit and accounted only for a small portion (11%) of the total variance, which was less than the method variance (25%) observed by Williams et al. (1989). The results of these tests suggested that common method variance was not a pervasive problem in this study's results. 4.4. Confirmatory factor analysis (CFA) To ensure that there was sufficient discriminant validity among constructs, we conducted a CFA with PS levels, within-team sources, organizational sources, external sources, and team composition in terms of diversity. We then evaluated the model fit according to various fit indicators, including the χ2 goodness-of-fit test, the non-normed fit index (NNFI), the comparative fit index (CFI), and the root mean square error of approximation (RMSEA). Hu and Bentler (1999) suggested that a value close to 0.95 reflects a good fit for NNFI and CFI, and RMSEA values close to 0.06 indicate a reasonable model fit. The results of the CFA testing model were χ2 = 2792.37, df = 1125.96, χ2/df = 2.48, NFI = 0.93, CFI = 0.95, and the RMSEA = 0.052, which indicated that the model had a good fit to the data. Descriptive statistics and inter-correlations are presented in Table 1. The descriptive statistics show considerable variance for all variables, indicating that the study contained diversified working conditions. Table 1 presents the means, standard deviations, and the correlations among the study's variables. As expected, psychological Table 1 Descriptive statistics and inter-correlations (N = 1345). Mean 1 2 3 4 5 ⁎ ⁎⁎

Psychological safety Within-team Intra-organizational External Team composition

5.59 5.63 4.63 2.61 0.43

SD 1.07 0.65 1.02 1.02 0.27

1

2

3

4

5

1 0.34 − 0.31 − 0.26

1 − 0.26 − 0.44

1 − 0.19

1

⁎

1 0.30⁎⁎ 0.22⁎⁎ − 0.44⁎⁎ − 0.38⁎⁎

p < 0.05. p < 0.01.

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Fig. 1. The Final Structural Model.

safety was significantly positively related to internal openness (at both the team level and the organizational level) but was negatively related to external openness. Our hypotheses were tested with structural equation modelling (SEM) on the aggregated data (N = 1345) using the maximum likelihood robust method in EQS 6.1. The SEM was particularly appropriate because it permits the simultaneous estimation of multiple causal relationships and explicitly accounts for the biasing effect of random measurement error in latent constructs (Edmondson & Mogelof, 2006). The hypothesized model provided an excellent fit. All goodness-of-fit indices satisfied the recommended criteria (CFI = 0.974, NNFI = 0.968, IFI = 0.976, RMSEA = 0.043). All factor loadings for the team's internal and external openness were high (range from 0.858 to 0.949) and significant (p < 0.001). Standardized path estimates of the structural model (Fig. 1) provided support for H1 and H2, as psychological safety was significantly positively related to team level sources (β = 0.37, p < 0.1 for team level sources; β = 0.23, p < 0.01 for firm level sources; and β = −0.21, P < 0.01 for external sources). The interaction of psychological safety with team composition was significantly positively related to within-team openness (β = 0.21, p < 0.01); Hence, H4 (a) was supported. However, the team composition did not moderate the relationship between psychological safety and either within-firm sources or external sources (β = 0.01, p > 0.10 and β = 0.21, p < 0.01, respectively). 5. Discussion Over the past two decades, psychological safety has been a topic of considerable interest and activity in the fields of management, organizational behavior, social psychology, and health care management. Evidence from empirical studies conducted in diverse organizational and industrial contexts across multiple countries and regions, supports the idea that psychological safety has a significant influence on understanding organizational learning, a statement that holds true across different levels of analysis, such as the individual level (Siemsen et al., 2009), the group level (Bradley, Postlethwaite, Klotz, Hamdani, & Brown, 2012; Bresman & Zellmer-Bruhn, 2013), and the organizational level (Carmeli & Gittell, 2009). Much learning in today's organizations takes place through the interpersonal interactions of highly interdependent members (Edmondson, 2004). Learning behaviors can be limited by individual concerns about interpersonal risks and their consequences, including a fear of not achieving one's goals and learning anxiety created by feelings of incompetence that occur during the learning process (Schein, 1996). Overall, prior research has provided considerable support for the idea that people are more likely to offer ideas, admit mistakes, ask for help, or provide feedback if they believe it is safe to do so. Although the existing literature has shed light on the relationship between PS, learning behavior, and learning outcomes, not enough research has been conducted into how PS affects an individual's knowledge search behavior. This article attempts to explain how different levels of PS can affect the knowledge search behavior of individual NPD team members. The results provide strong evidence that different levels of PS affect how an individual NPD team member will select one source of knowledge over other sources. This finding is important because it extends the applicability of information management sciences. Our literature review found that most studies in the information sciences reported that the accessibility of an information source was very important due to the so-called ‘least effort principle’; however, our studies showed that psychological factors, like PS, also play an important role. In fact, when narrowed down to a very low level of PS, we found that due to the perceived very high interpersonal risk factor, the least effort principle no longer held. However, at a very high level of PS, the individual perceives a low level of interpersonal risk so in that case he/she would select a source of knowledge according to the least effort principle. Although Pettigrew, Fidel, and Bruce (2001) suggested that information search behavior is shaped by the social environment, and that the social perspective on information seeking is an important paradigm, our study indicates that the psychological approach is more appropriate to apply to information search behavior. 6. Theoretical implication This study contributes to the literatures on knowledge search, social networks, and organizational strategies in several ways. First, concerning the social network literature, we attempted to explore how the level of PS affects the knowledge source search 9

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behavior of NPD team members. Our study provides a closer look into the conceptualization of search behavior as a psychological process rather than as a social relationship process. Previous research on social relationships has explained how the strength of relationships influences knowledge acquisition and seeking (Borgatti & Cross, 2003). Our research extends this perspective by suggesting that the social relationship is embedded in the PS levels of the members. When NPD team members feel psychologically safe with each other, they are more likely to experience a cooperative group atmosphere that encourages discussion and sharing information, and thus to the increased motivation to seek knowledge from colleagues within the team. Moreover, previous research (Badir & O'Connor, 2015) found that the key determinants were the amount of time team members spent together and the quality of their social interaction. We postulated that even if team members spent a lot of time together, this would not be enough to build strong ties. Our research contributes to social network theory by positing a different explanation for why some relationships build strong ties while others form weak ties. Second, in contrast to previous studies that discussed the effect of PS on learning behavior, but ignored the search behavior, our research accentuates the importance of PS as a possible antecedent of individual's source selection process. This study takes a cognitive approach, and adds details to better explain the knowledge search process by showing how an individual's perception of his/her level of psychological safety in an NPD team will affect the ability to take interpersonal risks with team members to access the information needed to complete and an NPD project. Third, our research contributes to the organization strategy literature. While knowledge, researchers have considered the selection of knowledge sources as an aspect of organizational strategy, they have found have showed different or even mutually exclusive effects. One possible reason for these contradictory results might be that they did not consider, the search behavior as an individual level process that influences the successful implementation of a strategy. This indeed may explain why many organizations are still facing significant challenges when attempting to implement an open innovation strategy, by trying to introduce, use, and further develop a culture of openness and knowledge acquired from different sources (Minbaeva, Foss, & Snell, 2009). We argue that for the effective implementation of the search strategy (e.g., open innovation strategy), organizations need to understand the knowledge seeking behaviors of individuals, especially those in NPD teams, where knowledge is needed the most. Fourth, our research contributes also to team building literature, which has shown that to make an effective team, it is important for team members to have varied expertise and skills. We expand on this further by highlighting the importance of the effect of team diversity on knowledge seeking and sharing within the team. 7. Implication for practice We feel our work has significance for practitioners. With the popularization of the concept of social networks, the interest among practitioners in the role of PS and networks in organizational settings has increased (Aalbers, Dolfsma, & Koppius, 2013). By understanding the way in which individual team members in NPD teams seek and share knowledge, the managers are able to create and organize NPD teams sensibly to generate knowledge flows from diverse sources of knowledge. We feel that practitioners will find it fruitful to focus on ways to improve PS as a relatively inexpensive and practical way to improve the flow of useful knowledge and advice in their teams. Indeed, some organizations are already undertaking such interventions by providing training and assessing behavioral trustworthiness through evaluation procedures or by investing in processes that create a shared vision and language that foster high levels of psychological safety for team members. Zipf (1949) popularized the concept of the least effort principle, which assumes that individual team members would prefer to seek knowledge from within team sources because those sources are less costly in terms of search time, and the time it takes to implement the required knowledge (Anderson et al., 2001). This theory suggests that people are less likely to feel the need to seek knowledge from outside the team, including knowledge from other functional units or teams from within the organization (Hansen et al., 2005). High psychological safety levels support conclusions from Zipf's least effort principle, since in this case individual team members would prefer to seek knowledge from internal sources and ignore external sources. Although the literature has shown the benefits of internal knowledge sources, teams with too much internal focus are more likely to ignore the views and comments of external participants (Ashforth & Mael, 1989), which can affect the final results of NPD projects. Research has shown the importance of the diversification of knowledge (Salter et al., 2015). Therefore, managers should make sure that NPD team members are interacting and communicating well with external sources (both within the firm and outside the firm boundaries). This can be done by organizing workshops and joint-development activities with external partners (suppliers, buyers, university researchers). Scholars have named this phenomenon “open innovation” (Chesbrough, 2003), and managers should pay more attention to maintaining high PS levels among team members and encourage them to seek knowledge from external sources. High PS levels motivate employees to share with each other and discuss their ideas, as well as the knowledge they receive from external sources, without any fear of perceiving this behavior as taking interpersonal risks. This will allow the team to benefit from both internal and external knowledge sources. References Aalbers, R., Dolfsma, W., & Koppius, O. (2013). Individual connectedness in innovation networks: On the role of individual motivation. Research Policy, 42(3), 624–634. http://dx.doi.org/10.1016/j.respol.2012.10.007. Abrams, D. E., & Hogg, M. A. (1990). Social identity theory: Constructive and critical advances. Springer-Verlag Publishing. Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45(3), 425–455. Akhavan, P., Hosseini, S. M., & Abbasi, M. (2016). Selecting new product development team members with knowledge sharing approach: A fuzzy bi-objective optimization model. Program, 50(2), 195–214.

10

Journal of High Technology Management Research xxx (xxxx) xxx–xxx

U. Safdar et al.

Alguezaui, S., & Filieri, R. (2010). Investigating the role of social capital in innovation: Sparse versus dense network. Journal of Knowledge Management, 14(6), 891–909. http://dx.doi.org/10.1108/13673271011084925. Almirall, E., & Casadesus-Masanell, R. (2010). Open versus closed innovation: A model of discovery and divergence. Academy of Management Review, 35(1), 27–47. Anderson, C. J., Glassman, M., McAfee, R. B., & Pinelli, T. (2001). An investigation of factors affecting how engineers and scientists seek information. Journal of Engineering and Technology Management, 18(2), 131–155. http://dx.doi.org/10.1016/S0923-4748(01)00032-7. Ashforth, B. E., & Mael, F. (1989). Social identity theory and the organization. Academy of Management Review, 14(1), 20–39. Ayağ, Z. (2016). An integrated approach to concept evaluation in a new product development. Journal of Intelligent Manufacturing, 27(5), 991–1005. Badir, Y. F., & O'Connor, G. C. (2015). The formation of tie strength in a strategic alliance's first new product development project: The influence of project and partners' characteristics. Journal of Product Innovation Management, 32(1), 154–169. Baer, M., & Frese, M. (2003). Innovation is not enough: Climates for initiative and psychological safety, process innovations, and firm performance. Journal of Organizational Behavior, 24(1), 45–68. Barczak, G., Griffin, A., & Kahn, K. B. (2009). Perspective: Trends and drivers of success in NPD practices: Results of the 2003 PDMA best practices study. Journal of Product Innovation Management, 26(1), 3–23. http://dx.doi.org/10.1111/j.1540-5885.2009.00331.x. Barsade, S. G. (2002). The ripple effect: Emotional contagion and its influence on group behavior. Administrative Science Quarterly, 47(4), 644–675. http://dx.doi.org/ 10.2307/3094912. Bell, S. T. (2007). Deep-level composition variables as predictors of team performance: A meta-analysis. The Journal of Applied Psychology, 92(3), 595–615. http://dx. doi.org/10.1037/0021-9010.92.3.595. Blau, P. M. (1977). Inequality and heterogeneity: A primitive theory of social structure (Vol. 7). Bond, E. U., Walker, B. A., Hutt, M. D., & Reingen, P. H. (2004). Reputational effectiveness in cross-functional working relationships. Journal of Product Innovation Management, 21(1), 44–60. Borgatti, S. P., & Cross, R. (2003). A relational view of information seeking and learning in social networks. Management Science, 49(4), 432–445. http://dx.doi.org/10. 1287/mnsc.49.4.432.14428. Bradley, B. H., Postlethwaite, B. E., Klotz, A. C., Hamdani, M. R., & Brown, K. G. (2012). Reaping the benefits of task conflict in teams: The critical role of team psychological safety climate. The Journal of Applied Psychology, 97(1), 151–158. http://dx.doi.org/10.1037/a0024200. Bresman, H., & Zellmer-Bruhn, M. (2013). The structural context of team learning: Effects of organizational and team structure on internal and external learning. Organization Science, 24(4), 1120–1139. http://dx.doi.org/10.1287/orsc.1120.0783. Brown, J. S., & Duguid, P. (1991). Organizational learning and communities-of-practice: Toward a unified view of working, learning, and innovation. Organization Science, 2(1), 40–57. Brown, & Leigh, T. W. (1996). A new look at psychological climate and its relationship to job involvement, effort, and performance. Journal of Applied Psychology, 81(4), 358. Bruderer, E., & Singh, J. V. (1996). Organizational evolution, learning, and selection: A genetic-algorithm-based model. Academy of Management Journal, 39(5), 1322–1349. Bunderson, J. S., & Boumgarden, P. (2010). Structure and learning in self-managed teams: Why “bureaucratic” teams can be better learners. Organization Science, 21(3), 609–624. http://dx.doi.org/10.1287/orsc.1090.0483. Caloghirou, Y., Kastelli, I., & Tsakanikas, A. (2004). Internal capabilities and external knowledge sources: Complements or substitutes for innovative performance? Technovation, 24(1), 29–39. http://dx.doi.org/10.1016/S0166-4972(02)00051-2. Carmeli, A. (2007). Social capital, psychological safety and learning behaviours from failure in organisations. Long Range Planning, 40(1), 30–44. http://dx.doi.org/10. 1016/j.lrp.2006.12.002. Carmeli, A., Brueller, D., & Dutton, J. E. (2009). Learning behaviours in the workplace: The role of high-quality interpersonal relationships and psychological safety. Systems Research and Behavioral Science, 26(1), 81–98. http://dx.doi.org/10.1002/sres.932. Carmeli, A., & Gittell, J. H. (2009). High-quality relationships, psychological safety, and learning from failures in work organizations. Journal of Organizational Behavior, 30(6), 709–729. Carmeli, A., & Schaubroeck, J. (2007). The influence of leaders' and other referents' normative expectations on individual involvement in creative work. Leadership Quarterly, 18(1), 35–48. http://dx.doi.org/10.1016/j.leaque.2006.11.001. Carmeli, A., Tishler, A., & Edmondson, A. C. (2012). CEO relational leadership and strategic decision quality in top management teams: The role of team trust and learning from failure. Strategic Organization, 10(1), 31–54. http://dx.doi.org/10.1177/1476127011434797. Carroll, & Edmondson, A. C. (2002a). Leading organisational learning in health care. Quality & Safety in Health Care, 11(1), 51–56. Cassiman, B., & Veugelers, R. (2006). In search of complementarity in innovation strategy: Internal R & D and external knowledge acquisition. Management Science, 52(1), 68–82. Chadwick, I. C., & Raver, J. L. (2015). Motivating organizations to learn goal orientation and its influence on organizational learning. Journal of Management, 41(3), 957–986. Chesbrough, H. (2003). Open innovation: The new imperative from creating and profiting from technology. Boston: Harvard Business School Publishing (Cerca con Google). Choo, A. S., Linderman, K. W., & Schroeder, R. G. (2007). Method and psychological effects on learning behaviors and knowledge creation in quality improvement projects. Management Science, 53(3), 437–450. http://dx.doi.org/10.1287/mnsc.1060.0635. Collins, C. J., & Smith, K. G. (2006). Knowledge exchange and combination: The role of human resource practices in the performance of high-technology firms. Academy of Management Journal, 49(3), 544–560. Crossan, M. M. (1998). Improvisation in action. Organization Science, 9(5), 593–599. Crossan, M. M., Lane, H. W., & White, R. E. (1999). An organizational learning framework: From intuition to institution. Academy of Management Review, 24(3), 522–537. Cyert, R. M., & March, J. G. (1963). A behavioral theory of the firm. Englewood Cliffs: Prentice-Hall, 2. Dahl, M. S., & Pedersen, C. O. R. (2004). Knowledge flows through informal contacts in industrial clusters: Myth or reality? Research Policy, 33(10), 1673–1686. http:// dx.doi.org/10.1016/j.respol.2004.10.004. Dahlander, L., & Frederiksen, L. (2012). The core and cosmopolitans: A relational view of innovation in user communities. Organization Science, 23(4), 988–1007. http://dx.doi.org/10.1287/orsc.1110.0673. Dahlander, L., & Gann, D. M. (2010). How open is innovation? Research Policy, 39(6), 699–709. Dahlander, L., & Piezunka, H. (2014). Open to suggestions: How organizations elicit suggestions through proactive and reactive attention. Research Policy, 43(5), 812–827. http://dx.doi.org/10.1016/j.respol.2013.06.006. Dayan, M., Ozer, M., & Almazrouei, H. (2016). The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty. Industrial Marketing Management. Detert, J. R., & Burris, E. R. (2007). Leadership behavior and employee voice: Is the door really open? Academy of Management Journal, 50(4), 869–884. Dougherty, D. (1992). Interpretive barriers to successful product innovation in large firms. Organization Science, 3(2), 179–202. Drach-Zahavy, A., & Somech, A. (2001). Understanding team innovation: The role of team processes and structures. Group Dynamics-Theory Research and Practice, 5(2), 111–123. http://dx.doi.org/10.1037//1089-2699.5.2.111. Du, J. S., Leten, B., & Vanhaverbeke, W. (2014). Managing open innovation projects with science-based and market-based partners. Research Policy, 43(5), 828–840. http://dx.doi.org/10.1016/j.respol.2013.12.008. Edmondson, A. C. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. Edmondson, A. C. (2002). The local and variegated nature of learning in organizations: A group-level perspective. Organization Science, 13(2), 128–146. Edmondson (2004). Learning in organizations: A group-level lens. Trust and distrust in organizations: Dilemmas and approaches. 239. Edmondson, A. C., Kramer, R. M., & Cook, K. S. (2004). Psychological safety, trust, and learning in organizations: A group-level lens. Trust and Distrust in Organizations: Dilemmas and Approaches, 10, 239–272.

11

Journal of High Technology Management Research xxx (xxxx) xxx–xxx

U. Safdar et al.

Edmondson, A. C., & Lei (2014). Psychological safety: The history, renaissance, and future of an interpersonal construct. Annual Review of Organizational Psychology and Organizational Behavior, 1(1), 23–43. http://dx.doi.org/10.1146/annurev-orgpsych-031413-091305. Edmondson, & Mogelof, J. (2006). Explaining psychological safety in innovation teams: Organizational culture, team dynamics, or personality. Creativity and Innovation in Organizational Teams, 109–136. Edmondson, A. C., & Nembhard, I. M. (2009). Product development and learning in project teams: The challenges are the benefits*. Journal of Product Innovation Management, 26(2), 123–138. Edmondson, A. C., Roberto, M. A., & Watkins, M. D. (2003). A dynamic model of top management team effectiveness: Managing unstructured task streams. Leadership Quarterly, 14(3), 297–325. http://dx.doi.org/10.1016/S1048-9843(03)00021-3. Edmondson, A., & Roloff, K. (2008). Overcoming barriers to collaboration: Psychological safety and learning in diverse teams. Team effectiveness in complex organizations: Cross-disciplinary perspectives and approaches (pp. 183–208). . de Faria, P., Lima, F., & Santos, R. (2010). Cooperation in innovation activities: The importance of partners. Research Policy, 39(8), 1082–1092. Ferreras-Méndez, J. L., Fernández-Mesa, A., & Alegre, J. (2016). The relationship between knowledge search strategies and absorptive capacity: A deeper look. Technovation, 54, 48–61. Fey, C. F., & Birkinshaw, J. (2005). External sources of knowledge, governance mode, and R & D performance. Journal of Management, 31(4), 597–621. Fiske, S. T., & Taylor, S. E. (2013). Social cognition: From brains to culture. London, England: Sage. Franke, N., Von Hippel, E., & Schreier, M. (2006). Finding commercially attractive user innovations: A test of lead-user theory*. Journal of Product Innovation Management, 23(4), 301–315. Frankort, H. T. (2016). When does knowledge acquisition in R & D alliances increase new product development? The moderating roles of technological relatedness and product-market competition. Research Policy, 45(1), 291–302. Gillian Ragsdell, D., Stadler, R., & Fullagar, S. (2016). Appreciating formal and informal knowledge transfer practices within creative festival organizations. Journal of Knowledge Management, 20(1), 146–161. Goffman, E. (1955). On face-work; an analysis of ritual elements in social interaction. Psychiatry, 18(3), 213–231. Gong, Y., Kim, T. Y., Lee, D. R., & Zhu, J. (2012). A multilevel model of team goal orientation, information exchange, and creativity. Academy of Management Journal, 56(3), 827–851. http://dx.doi.org/10.5465/amj.2011.0177. Gupta, A., & Govindarajan, V. (2000). Knowledge flows within multinational corporations. Strategic Management Journal, 21(4), 473–496. Hackman, J. R. (1987). The design of work teams. Ariel, 129, 32–197. Hansen, M. T., Mors, M. L., & Lovas, B. (2005). Knowledge sharing in organizations: Multiple networks, multiple phases. Academy of Management Journal, 48(5), 776–793. He, J., Butler, B. S., & King, W. R. (2007). Team cognition: Development and evolution in software project teams. Journal of Management Information Systems, 24(2), 261–292. http://dx.doi.org/10.2753/Mis0742-1222240210. Hinds, P., & Pfeffer, J. (2003). Why organizations don't “know what they know”: Cognitive and motivational factors affecting the transfer of expertise. Sharing expertise: Beyond knowledge management (pp. 3–26). . Hoegl, M., & Parboteeah, K. P. (2006). Team reflexivity in innovative projects. R & D Management, 36(2), 113–125. http://dx.doi.org/10.1111/j.1467-9310.2006. 00420.x. Horwitz, S. K., & Horwitz, I. B. (2007). The effects of team diversity on team outcomes: A meta-analytic review of team demography. Journal of Management, 33(6), 987–1015. Huang, C.-C. (2009). Knowledge sharing and group cohesiveness on performance: An empirical study of technology R & D teams in Taiwan. Technovation, 29(11), 786–797. Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures Special Issue: Organizational Learning: Papers in Honor of (and by) James G. March. Organization Science, 2(1), 88–115. Huber, F. (2013). Knowledge-sourcing of R & D workers in different job positions: Contextualising external personal knowledge networks. Research Policy, 42(1), 167–179. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. Hulsheger, U. R., Anderson, N., & Salgado, J. F. (2009). Team-level predictors of innovation at work: A comprehensive meta-analysis spanning three decades of research. The Journal of Applied Psychology, 94(5), 1128–1145. http://dx.doi.org/10.1037/a0015978. Ilgen, D. R., Hollenbeck, J. R., Johnson, M., & Jundt, D. (2005). Teams in organizations: From input-process-output models to IMOI models. Annual Review of Psychology, 56, 517–543. Jaikumar, R., & Bohn, R. E. (1992). A dynamic approach to operations management: An alternative to static optimization. International Journal of Production Economics, 27(3), 265–282. Joshi, A., & Roh, H. (2009). The role of context in work team diversity research: A meta-analytic review. Academy of Management Journal, 52(3), 599–627. Kalish, Y., & Robins, G. (2006). Psychological predispositions and network structure: The relationship between individual predispositions, structural holes and network closure. Social Networks, 28(1), 56–84. http://dx.doi.org/10.1016/j.socnet.2005.04.004. Kark, R., & Carmeli, A. (2009). Alive and creating: The mediating role of vitality and aliveness in the relationship between psychological safety and creative work involvement. Journal of Organizational Behavior, 30(6), 785–804. http://dx.doi.org/10.1002/job.571. Katila, R., & Ahuja, G. (2002). Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal, 45(6), 1183–1194. http://dx.doi.org/10.2307/3069433. Katila, R., Chen, E. L., & Piezunka, H. (2012). All the right moves: How entrepreneurial firms compete effectively. Strategic Entrepreneurship Journal, 6(2), 116–132. http://dx.doi.org/10.1002/sej.1130. Katzenbach, J. R. (1993). The wisdom of teams: Creating the high-performance organization. Harvard Business Press. Keller, R. T. (2001). Cross-functional project groups in research and new product development: Diversity, communications, job stress, and outcomes. Academy of Management Journal, 44(3), 547–555. http://dx.doi.org/10.2307/3069369. Kelly, J. R., & Barsade, S. G. (2001). Mood and emotions in small groups and work teams. Organizational Behavior and Human Decision Processes, 86(1), 99–130. http:// dx.doi.org/10.1006/obhd.2001.2974. Knudsen, M. P. (2007). The relative importance of interfirm relationships and knowledge transfer for new product development success. Journal of Product Innovation Management, 24(2), 117–138. http://dx.doi.org/10.1111/j.1540-5885.2007.00238.x. Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397. Koopmann, J., Lanaj, K., Wang, M., Zhou, L., & Shi, J. (2016). Nonlinear effects of team tenure on team psychological safety climate and climate strength: Implications for average team member performance. Koput, K. W. (1997). A chaotic model of innovative search: Some answers, many questions. Organization Science, 8(5), 528–542. Koriat, N., & Gelbard, R. (2014). Knowledge sharing motivation among IT personnel: Integrated model and implications of employment contracts. International Journal of Information Management, 34(5), 577–591. http://dx.doi.org/10.1016/j.ijinfomgt.2014.04.009. Kostopoulos, K. C., & Bozionelos, N. (2011). Team exploratory and exploitative learning: Psychological safety, task conflict, and team performance. Group & Organization Management, 36(3), 385–415. http://dx.doi.org/10.1177/1059601111405985. Kozlowski, S. W., & Bell, B. S. (2003). Work groups and teams in organizations. Handbook of Psychology. Laursen, K., & Salter, A. (2006). Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Management Journal, 27(2), 131–150. http://dx.doi.org/10.1002/smj.507. Lee, F. (1997). When the going gets tough, do the tough ask for help? Help seeking and power motivation in organizations. Organizational Behavior and Human Decision Processes, 72(3), 336–363. Levine, J. M., & Moreland, R. L. (1990). Progress in small group research. Annual Review of Psychology, 41(1), 585–634.

12

Journal of High Technology Management Research xxx (xxxx) xxx–xxx

U. Safdar et al.

Li, Q., Maggitti, P. G., Smith, K. G., Tesluk, P. E., & Katila, R. (2013). Top management attention to innovation: The role of search selection and intensity in new product introductions. Academy of Management Journal, 56(3), 893–916. http://dx.doi.org/10.5465/amj.2010.0844. Liang, J., Farh, C. I. C., & Farh, J. L. (2012). Psychological antecedents of promotive and prohibitive voice: A two-wave examination. Academy of Management Journal, 55(1), 71–92. http://dx.doi.org/10.5465/amj.2010.0176. Loebbecke, C., van Fenema, P. C., & Powell, P. (2016). Managing inter-organizational knowledge sharing. The Journal of Strategic Information Systems, 25(1), 4–14. Maggitti, P. G., Smith, K. G., & Katila, R. (2013). The complex search process of invention. Research Policy, 42(1), 90–100. http://dx.doi.org/10.1016/j.respol.2012.04. 020. March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. McDermott, C. M., & O'Connor, G. C. (2002). Managing radical innovation: An overview of emergent strategy issues. Journal of Product Innovation Management, 19(6), 424–438. http://dx.doi.org/10.1111/1540–5885.1960424 (doi: Pii S0737-6782(02)00174-1). McKenna, C. J. (1986). Theories of individual search behaviour. Bulletin of Economic Research, 38(3), 189–207. Mehra, A., Kilduff, M., & Brass, D. J. (2001). The social networks of high and low self-monitors: Implications for workplace performance. Administrative Science Quarterly, 46(1), 121–146. Mesmer-Magnus, J. R., & Dechurch, L. A. (2009). Information sharing and team performance: A meta-analysis. The Journal of Applied Psychology, 94(2), 535–546. http://dx.doi.org/10.1037/a0013773. Minbaeva, D., Foss, N., & Snell, S. (2009). Bringing the knowledge perspective into HRM introduction. Human Resource Management, 48(4), 477–483. http://dx.doi. org/10.1002/hrm.20303. Mintzberg, H. (1973). The nature of managerial work. Moreland, R. L., Levine, J., & Wingert, M. (2013). Creating the ideal group: Composition effects at work. Understanding Group Behavior, 2, 11–35. Morrison, E. W. (1993). Newcomer information seeking: Exploring types, modes, sources, and outcomes. Academy of Management Journal, 36(3), 557–589. Morrison, E. W., & Phelps, C. C. (1999). Taking charge at work: Extrarole efforts to initiate workplace change. Academy of Management Journal, 42(4), 403–419. Mu, S. H., & Gnyawali, D. R. (2003). Developing synergistic knowledge in student groups. Journal of Higher Education, 74(3), 689 −+. http://dx.doi.org/10.1353/jhe. 2003.0040. Mytelka, L. K., & Smith, K. (2002). Policy learning and innovation theory: An interactive and co-evolving process. Research Policy, 31(8-9), 1467–1479. http://dx.doi. org/10.1016/S0048–7333(02)00076–8 (doi: Pii S0048-7333(02)00076-8). Newman, A., Donohue, R., & Eva, N. (2017). Psychological safety: A systematic review of the literature. Human Resource Management Review. Parker, G. M. (2003). Cross-functional teams: Working with allies, enemies, and other strangers. John Wiley & Sons. Perry-Smith, J. E., & Shalley, C. E. (2003). The social side of creativity: A static and dynamic social network perspective. Academy of Management Review, 28(1), 89–106. Pettigrew, K. E., Fidel, R., & Bruce, H. (2001). Conceptual frameworks in information behavior. Annual Review of Information Science and Technology, 35(43–78), 43–78. Podolny, J. M., & Baron, J. N. (1997). Resources and relationships: Social networks and mobility in the workplace. American Sociological Review, 673–693. Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544. Rodan, S., & Galunic, C. (2004). More than network structure: How knowledge heterogeneity influences managerial performance and innovativeness. Strategic Management Journal, 25(6), 541–562. http://dx.doi.org/10.1002/Smj.398. Rubera, G., Chandrasekaran, D., & Ordanini, A. (2016). Open innovation, product portfolio innovativeness and firm performance: The dual role of new product development capabilities. Journal of the Academy of Marketing Science, 44(2), 166–184. Rulke, D. L., & Galaskiewicz, J. (2000). Distribution of knowledge, group network structure, and group performance. Management Science, 46(5), 612–625. Salge, T. O., Farchi, T., Barrett, M. I., & Dopson, S. (2013). When does search openness really matter? A contingency study of health-care innovation projects. Journal of Product Innovation Management, 30(4), 659–676. Salter, A., Ter Wal, A. L. J., Criscuolo, P., & Alexy, O. (2015). Open for ideation: Individual-level openness and idea generation in R & D. Journal of Product Innovation Management, 32(4), 488–504. http://dx.doi.org/10.1111/jpim.12214. Sanna, L. J., & Shotland, R. L. (1990). Valence of anticipated evaluation and social facilitation. Journal of Experimental Social Psychology, 26(1), 82–92. Saravanabawan, A., & Long, L. (2014). How task interdependence moderate the effect of team member collectivism on team creativity: An empirical study in Sri Lankan context. International Journal, 2(5), 144–156. Schein, E. H. (1985). Defining organizational culture. Classics of Organization Theory, 3, 490–502. Schein, E. H. (1996). Kurt Lewin's change theory in the field and in the classroom: Notes toward a model of managed learning. Systems Practice, 9(1), 27–47. Schein, E. H., & Bennis, W. G. (1965). Personal and organizational change through group methods: The laboratory approach. New York: Wiley. Sicotte, H., & Langley, A. (2000). Integration mechanisms and R & D project performance. Journal of Engineering and Technology Management, 17(1), 1–37. Siemsen, E., Roth, A. V., Balasubramanian, S., & Anand, G. (2009). The influence of psychological safety and confidence in knowledge on employee knowledge sharing. M & Som-Manufacturing & Service Operations Management, 11(3), 429–447. http://dx.doi.org/10.1287/msom.1080.0233. Somech, A., & Drach-Zahavy, A. (2011). Translating team creativity to innovation implementation: The role of team composition and climate for innovation. Journal of Management, 39(3), 684–708. http://dx.doi.org/10.1177/0149206310394187. Somech, A., & Drach-Zahavy, A. (2013). Translating team creativity to innovation implementation: The role of team composition and climate for innovation. Journal of Management, 39(3), 684–708. http://dx.doi.org/10.1177/0149206310394187. Somech, A., & Khalaili, A. (2014). Team boundary activity: Its mediating role in the relationship between structural conditions and team innovation. Group & Organization Management, 39(3), 274–299. http://dx.doi.org/10.1177/1059601114525437. Steffens, N. K., Shemla, M., Wegge, J., & Diestel, S. Exploring the cross-level effects of organizational tenure on employee performance. Broadening team composition research by conceptualizing team diversity as a cross-level moderating variable, 43. Stevens, M. J., & Campion, M. A. (1994). The knowledge, skill, and ability requirements for teamwork: Implications for human resource management. Journal of Management, 20(2), 503–530. Swink, M. (2000). NPD complexity and technology novelty as antecedents of design-manufacturing integration: Effects on product design quality. Paper presented at the Academy of Management Proceedings. Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practice within the firm. Strategic Management Journal, 17(S2), 27–43. Tang, C., & Naumann, S. E. (2016). Team diversity, mood, and team creativity: The role of team knowledge sharing in Chinese R & D teams–Corrigendum. Journal of Management & Organization, 1. Tatikonda, M. V., & Rosenthal, S. R. (2000). Technology novelty, project complexity, and product development project execution success: A deeper look at task uncertainty in product innovation. IEEE Transactions on Engineering Management, 47(1), 74–87. Tekleab, A. G., Karaca, A., Quigley, N. R., & Tsang, E. W. (2016). Re-examining the functional diversity–performance relationship: The roles of behavioral integration, team cohesion, and team learning. Journal of Business Research, 69(9), 3500–3507. Tierney, P., & Farmer, S. M. (2002). Creative self-efficacy: Its potential antecedents and relationship to creative performance. Academy of Management Journal, 45(6), 1137–1148. http://dx.doi.org/10.2307/3069429. Totterdell, P., Holman, D., & Hukin, A. (2008). Social networkers: Measuring and examining individual differences in propensity to connect with others. Social Networks, 30(4), 283–296. http://dx.doi.org/10.1016/j.socnet.2008.04.003. Tucker, A. L., Nembhard, I. M., & Edmondson, A. C. (2007). Implementing new practices: An empirical study of organizational learning in hospital intensive care units. Management Science, 53(6), 894–907. http://dx.doi.org/10.1287/mnsc.1060.0692. Unger-Aviram, E., & Erez, M. (2016). The effects of situational goal orientation and cultural learning values on team performance and adaptation to change. European Journal of Work and Organizational Psychology, 25(2), 239–253. van de Ven, A. H. (1986). Central problems in the management of innovation. Management Science, 32(5), 590–607. Veryzer, R. W. (1998). Discontinuous innovation and the new product development process. Journal of Product Innovation Management, 15(4), 304–321. Veugelers, R., & Cassiman, B. (1999). Make and buy in innovation strategies: Evidence from Belgian manufacturing firms. Research Policy, 28(1), 63–80.

13

Journal of High Technology Management Research xxx (xxxx) xxx–xxx

U. Safdar et al.

Von Hippel, E., & Tyre, M. J. (1995). How learning by doing is done: Problem identification in novel process equipment. Research Policy, 24(1), 1–12. Wang, J. (2016). Knowledge creation in collaboration networks: Effects of tie configuration. Research Policy, 45(1), 68–80. Widaman, K. F. (1985). Hierarchically nested covariance structure models for multitrait-multimethod data. Applied Psychological Measurement, 9(1), 1–26. Williams, L. J., Cote, J. A., & Buckley, M. R. (1989). Lack of method variance in self-reported affect and perceptions at work: Reality or artifact? Journal of Applied Psychology, 74(3), 462. Yagil, D., & Luria, G. (2010). Friends in need: The protective effect of social relationships under low-safety climate. Group & Organization Management, 35(6), 727–750. http://dx.doi.org/10.1177/1059601110390936. Zander, U., & Kogut, B. (1995). Knowledge and the speed of the transfer and imitation of organizational capabilities: An empirical test. Organization Science, 6(1), 76–92. Zipf, G. K. (1949). Human behavior and the principle of least effort.

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