Description
Structure is a fundamental, tangible or intangible notion referring to the recognition, observation, nature, and permanence of patterns and relationships of entities. This notion may itself be an object, such as a built structure, or an attribute, such as the structure of society.
ORGANIZATIONAL INFORMAL STRUCTURE INFLUENCE ON PROJECT SUCCESS: SOCIAL CAPITAL APPROACH
JinYoung Han, Korea University Business School, Seoul, South Korea, [email protected] Anat Hovav, Korea University Business School, Seoul, South Korea, [email protected]
Abstract
Knowledge sharing and organizational citizenship behavior (OCB) among project team members are crucial for project success. The IS project team is a temporary organization and has to produce outcomes in a limited time. we investigate how internal and external social capital (SoC) influence knowledge sharing and OCB within a team and how OCB and knowledge sharing affect project success. We also analyze the relationships between the three social capital dimensions. Our investigation will be analyzed using multi-level approach, which can make up for shortcomings of single-level analysis. This research adds to the current body of knowledge by examining the facilitation of knowledge sharing in the organization through informal interaction and citizenship. A statistical testing has not been complete. We will explore both HLM6 and MPLUS for multiple structural equation modeling and introduce a comparative analysis of each set of results. We expect the results of the research can provide project managers with insights on how to encourage project team members to share their knowledge and build teamwork more efficiently. Keywords: Project success, Oranizational Citizenship Behavior, OCB, Knowledge Sharing, Social Capital.
1
INTRODUCTION
As organizations increasingly rely on information systems (IS) for strategic and operational reasons, the role of IS has become essential in the business environment. Despite the importance of IS, IS project teams have experienced cost and time overrun. The dissatisfaction with the performance of IS projects is widespread (The_Standish_Group 2009). Differencing from construction or engineering projects, IS projects produce intangible outcomes and are knowledge-intensive work requiring diverse expertise such as business knowledge, processes, emerging IT techniques or skills (Pee, et al. 2010). Prior research has suggested positive relationships between knowledge –sharing (KS) and project performance (van den Hooff & Ridder 2004; Yu, et al. 2010). However, encouraging KS is still problematic as professionals are reluctant to share their knowledge and expertise. Social, culture, and technical attributes of organizational settings, which can encourage knowledge transfer, have been one of the major research topics since the introduction of knowledge management in an organization (Alavi & Leidner 2001). However, few studies have examined the social antecedents of knowledge sharing in the context of IS project success. KS is euqated with knowledge transfering (e.g. Huber 1991). Knoweldge transfering is deifned as communication of knowledge and transmission of knowledge (Ko, et al. 2005). KS depends on the attributes of the sender, receiver, and channel (Pee, et al. 2010) such as sender’s expertise (Joshi & Sarker 2007), receiver’s absortive capacity (Ko, et al. 2005), and channel’s richness (Lind & Zmud 1991). Prior research on the three elements showed mixed results (e.g. Joshi & Sarker 2007; Ko, et al. 2005). Previous research also shows the effects of intrinsic motivations (Ko, et al. 2005; Wasko & Faraj 2005) and social relationships (Ko, et al. 2005) on knowledge transmission. Individual expertise cannot transform to a group’s or an organizational knowledge without socialization (Bock, et al. 2005). Arduous relationships are negatively related to communication and interaction, while interaction is positively affected by mutual trust and shared understanding (Ko, et al. 2005). Factors such as trust, shared understanding and socializing are part of the informal structure of an organization and are often described as the dimensions of social capital (SoC). The concept of “SoC” has been examined as an increasingly essential factor of group formations (Huysman & Wulf 2004; Oh, et al. 2004; Reagans, et al. 2004). Research studies have noted that high levels of SoC are related to group cohesiveness, eventually supporting collective behavior (Adler & Kwon 2002; Yli-Renko, et al. 2001). SoC highlights the informal relationships between team members and their willingness to share knowledge based on relationships with others rather than on formal organizational structure. Using SoC lens, this study sheds light on the underlying process affecting individual and group KS, and subsequently team performance. While KS is affected by intrinsic motivation (Ko, et al. 2005; Wasko & Faraj 2005), extrinsic motivation failed to show significant impact on knowledge transfer (Ko, et al. 2005). Team members are intrinsically motivated when their satisfaction lies in the content of the activity itself (e.g., enjoying helping) (Ko, et al. 2005; Wasko & Faraj 2005). In this study, we use OCB as a manifestation of a team member’s innate behavior. Several researchers studied the antecedents of knowledge sharing in IS project context (Joshi & Sarker 2007; Ko, et al. 2005; Pee, et al. 2010). These studies mostly focused on the relationship between IT professionals and business professionals (Joshi & Sarker 2007; Pee, et al. 2010). These relationships are often contractual in nature (Joshi & Sarker 2007; Pee, et al. 2010). However, IS projects involve various stakeholders such as business analysts, system designers, hardware designers, programmers, and IT consultants. In addition, IS projects require substantial teamwork and collaboration among team members, which are often depend on social relations. Therefore, while prior research mainly dealt with contractual associations, this research extends the boundary of social relationship to include formal and informal connections. SoC has been studied at various levels from individual to country (Zaheer, et al. 2010). Aggregating SoC of individuals may affect higher level’s performance such as a team’s performance (Oh, et al. 2006). The combination of SoC at different levels may affect individual behavior or higher level’s performance (Yu, et al. 2010). However, few SoC related studies have conducted multi-level analysis. Our goal is to understand the effect of SoC on knowledge sharing and OCB among team members,
and the relationships between sharing knowledge, OCB, and project success. Moreover, we examine the relationships among the three dimensions of SoC empirically. We thus extend the social capital theory by examining the facilitation of knowledge sharing in the organization through informal interaction and citizenship behavior at two levels, individuals and groups.
2
2.1
THEORETICAL FOUNDATION
Social Capital Theory
SoC is defined as the set of social resources embedded in the network of relationships and composed of three dimensions underlying both internal and external ties (Nahapiet and Ghoshal 1998): Structural dimension refers to the information channels that connect individuals and units, relational dimension refers to the resources embedded in relationships, such as trust and reciprocity, between its members and cognitive dimension is defined as the shared meaning, and understanding that develops among members of the network as they interact. Several types of relationships exist within a project group and inter-groups. According to typology of conduits for group SoC (Oh, et al. 2006), We classify the relationships as depicted in Figure 1.
Figure 1.
Social relationship in a project
At the beginning of a project, team members may not know each other. Over time, they become familiar with other members. They might share the project’s context, and task -related knowledge using common language. Additionally, they can trust their team members or other teams through internal and external interaction. 2.2 Organizational Citizenship Behavior
The term “organizational citizenship behavior” (OCB) was proposed by Bateman and Organ (1983) and was denoted as organizationally beneficial behavior and gestures which cannot be enforced on the basis of formal role obligations (Bateman & Organ 1983). Graham(1991) separates citizen behavior into the behavior from in-role job performance and the behavior from extra-role job performance. For example, when a system designer participates in additional upkeep activities, which are not required, her behavior can be considered as a citizenship behavior. OCB is conceptualized as a broader concept which includes all positive organizational behavior of organizational members (Graham 1991; L Van Dyne, et al. 1994). 2.3 Level of Analysis
Social capital assumes social relationships or social networks among individuals. The levels of network analysis are classified as dyad, ego, and the entire network (Zaheer, et al. 2010). The dyadic level refers to a dyadic tie, which focuses on the nature of the relationship between two linked actors. Prior studies at the ego level have concentrated on the position of an ego, who is a focal actor, and the effects of the ego’s connections, for example, actor’s performance or carrier success. Recent studies at
the network level have examined the effects of complete networks on the characteristics of the entire network or individual firms (Zaheer, et al. 2010). In organizational research, two types of levels exist: level of measurement and level of analysis (Rousseau 1985). The level of measurement means the unit to which the data are directly assigned and the latter means the unit to which the data are assigned for hypothesis testing and analysis (Rousseau 1985). Accordingly , the levels of analysis of social capital studies vary from individual to society and might include multi- or mixed-level (Ali-Hassan, et al. 2010) (see Table 1). A typology of mixedlevel models includes composition, cross-level, and multi-level (Rousseau 1985). Composition models specify the relationships among nondependent variables at different levels. Cross-level models specify the causal relationships among independent and dependent variables at different levels. The third one is the multi-level model, which indentifies relationships among variables applying at two or more levels. Studies on social capital with multi-level approach are relatively new although the need for examining mixed-level organizational phenomena have been recognized (Belanger 2009). In this research, the levels of network analysis are both dyad and ego since the study deals with structural and relational dimensions of social capital. In addition, the multi-level model is used in terms of the level of analysis. The constructs, which are from three dimensions of social capital, are at the individual level. Organizational citizenship behavior is also at the individual level in the causal relationship between internal social capital and organizational citizenship behavior within a team. On the other hand, the relationship between perception of project success and real project success is cross-level as the project success is at the team level and the perceived project success is at the individual level. Thus, the proposed research model is mixed-level.
Levels of network analysis Dyad Ego (Hatzakis, et al. 2005; Moran 2005; (Ali-Hassan, et al. 2010; Seibert, et al. Seibert, et al. 2001; Sherif, et al. 2006) 2001; Sherif, et al. 2006; Yang & Farn 2007) (Hatzakis, et al. 2005; Newell, et al. (Balkundi & Harrison 2006; Chang & 2004; Tsai & Ghoshal 1998) Wong 2008; Kang & Kim 2009; Newell, et al. 2004; Robert, et al. 2008; Wang, et al. 2006) (Chou, et al. 2006; Tiwana 2008) (Honig, et al. 2006; Hsieh & Tsai 2007; Ingram & Roberts 2000; Lin, et al. 2006; Nahapiet & Ghoshal 1998) (Arling and Subramani 2005; (Yu, et al. 2010) Patnayakuni et al. 2006;Ali-Hassan, et al. 2010)
Level of analysis Individual
Group or Team
Organization
Multi or Cross level
Table 1.
Two types of level of analysis
3
HYPOTHESES DEVELOPMENT
Conventional indicators of project success are cost, time and scope. Project Management Body Of Knowledge (PMBOK)’s model uses the terms “on time, in budget, to scope” (PMI 2004). Project management (PM) success can be distinguished from project success (Cooke-Davies 2002). The latter is determined by measuring against overall objectives of a project whereas the former is determined by measuring against performance of cost, schedule, and quality (Cooke-Davies 2002; Thomas & Fernandez 2008). In this research, cost, schedule, and customer satisfaction are used as measures of project success because the study deals with individual project teams, and thus cannot measure successful organizational strategy implementation. In addition, project success is investigated with two constructs: the perception of project success and “real” project success. The first mea sures team members’ perceptions of their project status and the second is the result of project status based on
formal reports and users’ surveys. Team members may feel that they have done their work efficiently and effectively while reviewing their work status. Also, team members’ perception of project success may encourage their real performance. Therefore, we suggest the following hypothesis: H1: Team member’s perception of project success has a positive effect on the project success. [Cross level] Prior research has shown that OCB has direct influence on an organization’s performance (Podsakoff, et al. 2000; Yen, et al. 2008). In IS project, team members’ OCB can contribute to the completion of a project on schedule and in budget since OCB is indicative of positive organizational behavior of organizational members. Helping behavior allows co-workers to become more productive and enhance team spirit. Exhibiting sportsmanship may enhance the ability to adapt to changes. Additionally, team members, who engage in civic virtue, actively participate in team meetings and can provide valuable suggestions for improving team’s performance. Therefore, we propose the following hypothesis: H2: OCB of a team member has a positive effect on the perception of project success. Knowledge sharing is one of the critical practices leading to IS project success (van den Hooff and Ridder 2004; Yu, et al. 2010) since IS projects are knowledge-intensive and beyond the ability of one team member. The project team operates in rapidly changing business environment. An increase in knowledge sharing between teams could help face these changes (Liao, et al. 2009). Additionally, the team’s capability is enhanced when the experts within the team share their knowledge, skills and know-how. Therefore, we hypothesized that: H3: The intention to share knowledge has a positive effect on the perception of project success. OCB can encourage an individual to attend non-required meeting (Organ 1988). Through voluntary participation, team members are likely to exchange work-related information and help each other (Bolino, et al. 2002; Organ 1988). Therefore, the following hypothesis is proposed: H4: The OCB of a team member is positively associated with the member’s intention to share knowledge within the same team. People can trust others because of the other’s integrity, goodwill, and ability (Chiu, et al. 2006). When people trust colleagues from other teams, they can access knowledge of colleagues, which can be helpful for their own team. They, however, will not share the obtained knowledge within a team without the intention to help the team or to solve team’s issues. Shared vision also has been thought to play an important role in employees’ bonding (Kouzes & Posner 1989; Pfeffer 1996). A shared vision refers to the collective goals or common understanding of the firm’s vision or project’s goals (Nahapiet & Ghoshal 1998; Tsai & Ghoshal 1998). The sub-team’s interests often conflict though the sub-teams of a project work together. Thus team member’s direct contribution to his team such as knowledge sharing can be affected by the degree of participation in his team’s activity. Thus, we hypothesize that: H5: The relationship between the extent to which a team member trusts members from other teams and the intention to share knowledge is mediated by OCB. H6: The relationship between the extent to which a team member shares a vision of the firm and the intention to share knowledge is mediated by OCB. Prior research examined the relationship between trust and OCB and showed that trusting individuals are more likely to engage in OCB (Brower, et al. 2009; Dirks & Ferrin 2001; Linn van Dyne 2000). According to Brower, et al (2009), trust in the manager or in subordinates is positively related to individual OCB. Thus, we hypothesize that:
H7: The extent to which a project team member trusts other members is positively associated with the member’s OCB. According to Roussearu et al.(1998), people, who trust others, have confidence in others and can cooperate with others (Mayer, et al. 1995). Prior research (Dirks & Ferrin 2001) provides substantial evidence that trust facilitates the exchange of knowledge. For example, people are willing to give others useful information in trusting relationships (Levin & Cross 2004; Tsai & Ghoshal 1998). Main positive effects of trust on communication are shown in various forms: the communication targets (e.g. superiors, subordinates, or co-workers), the degree of communication openness within a group, and the quality or quantity of shared information (Dirks & Ferrin 2001). Based on this prior evidence, we suggest the following hypothesis: H8: The extent to which a project team member trusts his team members is positively associated with the intention to share knowledge within the team. Prior research has investigated the relationships between norms within a collectivity and pro-social behavior (van den Hooff & Ridder 2004; Wasko & Faraj 2005) and collaboration (Kankanhalli, et al. 2005; Sherif, et al. 2006). However, the results of these studies are mixed. In the context of IS projects, these norms might have positive effect on team members’ OCB such as openness to conflicting views and intention to share knowledge within their team. Thus, we hypothesize that: H9a: The extent to which a project team member believes that other members share cooperative norms is positively associated with the member’s OCB H9b: The extent to which a project team member believes that other members share cooperative norms is positively associated with the member’s intention to share knowledge. Shared mental model has been used as a manifestation of SoC cognitive dimension. It represents members in a network with similar knowledge structures (Robert, et al. 2008). A recent meta-analysis of Team Mental Models (TMMs) shows positive relationships between TMMs and various team processes (Mohammed, et al. 2010) such as back-up behavior (Marks, et al. 2002), coordination (Marks, et al. 2002; Mathieu, et al. 2000), and communication (Mathieu, et al. 2000). Assisting teammates and coordinating represent OCB. In addition, the coordination and communication processes support exchanging information and knowledge. Therefore, we hypothesize that: H10a: The extent to which a project team member shares a mental model with his team members is positively associated with the member’s OCB. H10b: The extent to which a project team member shares a mental model with his team members is positively associated with the member’s intention to share knowledge within the team. Prior studies recognized three dimensions of SoC as defined by Nahapiet and Goshal(1998). However, only a few of them examined the relationships among the three dimensions (Tsai & Ghoshal 1998). While internal SoC relies on internal social networks that define the relationships among team members and a leader within a team, external SoC relies on extended social relationships, such as connections to other teams (Chang & Wong 2008). Prior studies have suggested that trust is developed from increased social interaction (Granovetter 1983). Furthermore, repeated and close interactions lead team members to know each other and develop share norms (e.g. cooperative norm) (Tsai & Ghoshal 1998). Therefore, we hypothesize that: H11a: The degree of interaction with other members within the same team is positively associated with the extent to which the member trusts other members within the same team. H11b: The degree of interaction with other members within the same team is positively associated with the extent to which a project team member believes that other members share cooperative norm
As the members’ interaction increase in a social network, they may influence each other by adopting and realizing others knowledge. They may create new knowledge based on common interests. Team members may also internalize their leader’s norm, values, and practices through interaction with a team leader (Tsai & Ghoshal 1998). Hence, we hypothesize that: H12: The degree of interaction with other members within the same team is positively associated with the extent to which the member shares mental model with other members within the same team. Previous studies on the external dimension of SoC have focused on the performance of an organization (e.g. product innovation and organization productivity) (Chang & Wong 2008; Ingram & Roberts 2000; Oh, et al. 2004). Team leader’s external ties may have positive influence on his or her team’s perceived trustworthiness and enforce value-sharing (Ingram & Roberts 2000). Other teams in the network of a team leader are more likely to trust his team. Social interactions with other teams increase opportunities to exchange information and share project goals. Therefore, the following hypotheses are suggested: H13: The degree of interaction with members in other teams is positively associated with the extent to which the member trusts those members. H14: The degree of interaction with members in other teams is positively associated with the extent to which a team member shares a vision of his firm. The research model is shown in Figure 2.
Figure 2.
Research Model
4
4.1
PROPOSED METHODOLOGY
Measurement
Each construct will be measured using and adapting existing instruments as depicted in table 2. A pilot test for the instrument will be performed on a representative sample of the target population using conditions similar to those anticipated during actual data collection. Due to the research context, members of IS project teams will be targeted as the main respondents.
Construct External social network (Degree of interaction) Internal social network (Degree of interaction) External Trust Shared vision Trust Cooperative Norm Shared mental
Measurement Adopted ego-centric approach (Hansen, et al. 2005; Yu, et al. 2010) Adopted ego-centric approach(Hansen, et al. 2005; Yu, et al. 2010) The degree centrality of the inter-team trusting networks (Tsai & Ghoshal 1998) The level of shared vision in the different teams (Tsai & Ghoshal 1998) The level of trusting other members in the same team (Jarvenpaa, et al. 2004) Individuals’ willingness to value diversity, the openness to critical thought, and teamwork spirits (Kankanhalli, et al. 2005) Rated each attribute of the mental model in team process and expertise and measured mental model centrality and convergence (Mathieu, et al. 2000) A second order construct with three dimensions which are helping behavior, sportsmanship, and civic virtue (Yen, et al. 2008) Individuals’ willingness to share knowledge (Bock, et al. 2005) Individuals’ perception of the project’s status against team’s targeted schedule, man-hour and customer satisfaction Measured in terms of “on time”, “within man-hours”, and customer satisfaction based on formal documents(e.g. closure reports or survey of user’s satisfaction)
Level Individual Individual Individual Individual Individual Individual Individual
OCB
Individual
Intention to share knowledge Perception of project success Project success
Individual Individual Team
Table 2. 4.2 Analysis
Operationalization of Constructs
I will adopt a multilevel modelling technique. The multilevel analysis has several advantages comparing to single-level analysis: (1) the research model can be specified at its correct hierarchical levels, (2) the variability in an outcome can be estimated better, and (3) the analysis can provide flexibility of the model’s range (Heck & Thomas 2009). We will use the Hierarchical Linear Modeling (HLM6) or MPLUS to conduct multiple structural equation model approach. Due to the novelty of multi-dimension analysis in MIS research, we will explore both tools and introduce a comparative analysis of each set of results. 4.3 Plan for completion
Schedule 3rd week of May 2011 4th week of May 2011 1st - 2nd week of June 2011 3rd – 4th week of June 2011 After doctoral consortium August – September 2011 October 2011 November – December 2011 December 2011 – January 2012
Task Preparing survey questionnaire in English Preparing survey questionnaire in Korean by using forward and backward translations Performing a pilot test on a representative sample Analysis of pilot data Refining model, measurements and questionnaire Full data collection from members of IS project teams Conducting a multi-level statistical analysis Finalize writing Proof reading, editing, formatting
Table 3.
Schedule of completion
References
Adler, P., and Kwon, S. (2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1), 17-40. Alavi, M., and Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. Mis Quarterly, 25(1), 107-136. Ali-Hassan, H., Nevo, D., and Nevo, S. (2010). Mobile collaboration: exploring the role of social capital. ACM SIGMIS Database, 41(2), 9-24. Balkundi, P., and Harrison, D. (2006). Ties, leaders, and time in teams: Strong inference about network structure's effects on team viability and performance. Academy of Management Journal, 49(1), 49. Bateman, T., and Organ, D. (1983). Job satisfaction and the good soldier: The relationship between affect and employee" citizenship". Academy of Management Journal, 26(4), 587-595. Belanger, F. (2009). Conducting Multi-Level Research in Information Systems. Bock, G., Zmud, R., Kim, Y., and Lee, J. (2005). Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. Mis Quarterly, 29(1), 87-111. Bolino, M., Turnley, W., and Bloodgood, J. (2002). Citizenship behavior and the creation of social capital in organizations. Academy of Management Review, 27(4), 505-522. Brower, H., Lester, S., Korsgaard, M., and Dineen, B. (2009). A closer look at trust between managers and subordinates: Understanding the effects of both trusting and being trusted on subordinate outcomes. Journal of Management, 35(2), 327. Chang, k.-c., and Wong, J.-H. (2008). System Development Team Flexibility:Its Antecedents and Project Performance. PACIS 2008 Proceedings. Chiu, C., Hsu, M., and Wang, E. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872-1888. Chou, T., Chen, J., and Pan, S. (2006). The impacts of social capital on information technology outsourcing decisions: A case study of a Taiwanese high-tech firm. International Journal of Information Management, 26(3), 249-256. Cooke-Davies, T. (2002). The" real" success factors on projects. International Journal of Project Management, 20(3), 185-190. Dirks, K., and Ferrin, D. (2001). The role of trust in organizational settings. Organization Science, 12(4), 450-467. Graham, J. (1991). An essay on organizational citizenship behavior. Employee Responsibilities and Rights Journal, 4(4), 249-270. Granovetter, M. (1983). The strength of weak ties: A network theory revisited. Sociological theory, 1, 201-233. Hansen, M., Mors, M., and Lovas, B. (2005). Knowledge sharing in organizations: Multiple networks, multiple phases. Academy of Management Journal, 48(5), 776-793. Hatzakis, T., Lycett, M., Macredie, R., and Martin, V. (2005). Towards the development of a social capital approach to evaluating change management interventions. European Journal of Information Systems, 14(1), 60-74. Heck, R. H., and Thomas, S. L. (2009). An introduction to multilevel modeling techniques (2nd Edition ed.). New York : Routledge: Lawrence Erlbaum. Honig, B., Lerner, M., and Raban, Y. (2006). Social Capital and the Linkages of High-Tech Companies to the Military Defense System: Is there a Signaling Mechanism? Small Business Economics, 27(4), 419-437. Hsieh, M.-H., and Tsai, K.-H. (2007). Technological capability, social capital and the launch strategy for innovative products. [doi: DOI: 10.1016/j.indmarman.2006.01.002]. Industrial Marketing Management, 36(4), 493-502. Huysman, M., and Wulf, V. (2004). Social capital and information technology. Cambridge, Mass: The MIT Press. Ingram, P., and Roberts, P. (2000). Friendships among competitors in the Sydney hotel industry. American journal of sociology, 106(2), 387-423.
Jarvenpaa, S., Shaw, T., and Staples, D. (2004). Toward contextualized theories of trust: The role of trust in global virtual teams. Information Systems Research, 15(3), 250-267. Joshi, K., and Sarker, S. (2007). Knowledge transfer within information systems development teams: Examining the role of knowledge source attributes. Decision Support Systems, 43(2), 322-335. Kang, S., and Kim, T. (2009). Opinion Leaders, Social Capital, and Innovations in Teams. Seoul Journal of Business, 15(2), 137-155. Kankanhalli, A., Tan, B. C. Y., and Kwok-Kee, W. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. [Article]. Mis Quarterly, 29(1), 113-143. Ko, D. G., Kirsch, L. J., and King, W. R. (2005). Antecedents of knowledge transfer from consultants to clients in enterprise system implementations. Mis Quarterly, 29(1), 59-85. Kouzes, J., and Posner, B. (1989). The leadership challenge: How to get extraordinary things done in organizations (1st Edition ed.). San Francisco:Jossey-Ba. Levin, D. Z., and Cross, R. (2004). The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer. Management Science, 50(11), 1477-1490. Liao, C., Yu-Ping Liu, Lin, H.-N., and Huang, Y.-H. (2009). The Effect of Knowledge Sharing on IS Outsourcing Success. AMCIS 2009 Proceedings. Lin, B., Li, P., and Chen, J. (2006). Social capital, capabilities, and entrepreneurial strategies: a study of Taiwanese high-tech new ventures. Technological Forecasting and Social Change, 73(2), 168181. Lind, M. R., and Zmud, R. W. (1991). The influence of a convergence in understanding between technology providers and users on information technology innovativeness. Organization Science, 2(2), 195-217. Marks, M., Sabella, M., Burke, C., and Zaccaro, S. (2002). The impact of cross-training on team effectiveness. Journal of Applied Psychology, 87(1), 3-13. Mathieu, J., Heffner, T., Goodwin, G., Salas, E., and Cannon-Bowers, J. (2000). The influence of shared mental models on team process and performance. Journal of Applied Psychology, 85(2), 273-283. Mayer, R., Davis, J., and Schoorman, F. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734. Mohammed, S., Ferzandi, L., and Hamilton, K. (2010). Metaphor No More: A 15-Year Review of the Team Mental Model Construct. Journal of Management, 36(4), 876. Moran, P. (2005). Structural vs. relational embeddedness: social capital and managerial performance. Strategic Management Journal, 26(12), 1129-1151. Nahapiet, J., and Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. The Academy of Management Review, 23(2), 242-266. Newell, S., Tansley, C., and Huang, J. (2004). Social capital and knowledge integration in an ERP project team: The importance of bridging and bonding. British Journal of Management, 15(s 1), 43-57. Oh, H., Chung, M., and Labianca, G. (2004). Group social capital and group effectiveness: The role of informal socializing ties. Academy of Management Journal, 47(6), 860-875. Oh, H., Labianca, G., and Chung, M. (2006). A multilevel model of group social capital. Academy of Management Review, 31(3), 569. Organ, D. (1988). Organizational citizenship behavior: The good soldier syndrome (Vol. 133). Lexington, MA: Lexington books Pee, L. G., Kankanhalli, A., and Kim, H. W. (2010). Knowledge Sharing in Information Systems Development: A Social Interdependence Perspective. Journal of the Association for Information Systems, 11(10), 550-575. Pfeffer, J. (1996). Competitive advantage through people: Unleashing the power of the work force: Harvard Business Press. PMI. (2004). A Guide to the Project Management Body of Knowledge (PMBOK Guide) (3rd ed.). Newtown Square, PA: Project Management Institute. Podsakoff, P., MacKenzie, S., Paine, J., and Bachrach, D. (2000). Organizational citizenship behaviors: A critical review of the theoretical and empirical literature and suggestions for future research. Journal of Management, 26(3), 513.
Reagans, R., Zuckerman, E., and McEvily, B. (2004). How to make the team: Social networks vs. demography as criteria for designing effective teams. Administrative Science Quarterly, 101-133. Robert, L. P., Jr., Dennis, A. R., and Ahuja, M. K. (2008). Social Capital and Knowledge Integration in Digitally Enabled Teams. Information Systems Research, 19(3), 314-334. Rousseau, D. (1985). Issues of levels in organizational research: Multi-level and cross-level. Research in organizational behavior, 7, 1-37. Seibert, S., Kraimer, M., and Liden, R. (2001). A social capital theory of career success. Academy of Management Journal, 44(2), 219-237. Sherif, K., Hoffman, J., and Thomas, B. (2006). Can technology build organizational social capital? The case of a global IT consulting firm. Information & management, 43(7), 795-804. The_Standish_Group. (2009). CHAOS summary 2009 report: The Standish Group. Thomas, G., and Fernandez, W. (2008). Success in IT projects: A matter of definition? International Journal of Project Management, 26(7), 733-742. Tiwana, A. (2008). Do bridging ties complement strong ties? An empirical examination of alliance ambidexterity. Strategic Management Journal, 29(3), 251. Tsai, W., and Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. The Academy of Management Journal, 41(4), 464-476. van den Hooff, B., and Ridder, J. (2004). Knowledge sharing in context: the influence of organizational commitment, communication climate and CMC use on knowledge sharing. Journal of Knowledge Management, 8(6), 117-130. van Dyne, L. (2000). Collectivism, propensity to trust and self-esteem as predictors of organizational citizenship in. Journal of Organizational Behavior, 21(1), 3. Van Dyne, L., Graham, J., and Dienesch, R. (1994). Organizational citizenship behavior: Construct redefinition, measurement, and validation. Academy of Management Journal, 37(4), 765-802. Wang, E. T. G., Ying, T.-C., Jiang, J. J., and Klein, G. (2006). Group cohesion in organizational innovation: An empirical examination of ERP implementation. [doi: DOI: 10.1016/j.infsof.2005.04.006]. Information and Software Technology, 48(4), 235-244. Wasko, M., and Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. Mis Quarterly, 29(1), 35-57. Yang, S.-C., and Farn, C.-K. (2007). Exploring Tacit Knowledge Sharing Intention and Behavior within Workgroup from the Perspectives of Social Capital and Behavioral Control. PACIS 2007 Proceedings. Yen, H., Li, E., and Niehoff, B. (2008). Do organizational citizenship behaviors lead to information system success? Testing the mediation effects of integration climate and project management. Information & management, 45(6), 394-402. Yli-Renko, H., Autio, E., and Sapienza, H. (2001). Social capital, knowledge acquisition, and knowledge exploitation in young technology-based firms. Strategic Management Journal, 22(6-7), 587-613. Yu, A., Hao, J., Dong, X., and Khalifa, M. (2010). Revisiting the effect of social capital on knowledge sharing in work teams:A multilevel approach. Zaheer, A., Gö zü bü yü k, R., and Milanov, H. (2010). It's the Connections: The Network Perspective in Interorganizational Research. Academy of Management Perspectives, 24(1), 62-77.
doc_907670405.pdf
Structure is a fundamental, tangible or intangible notion referring to the recognition, observation, nature, and permanence of patterns and relationships of entities. This notion may itself be an object, such as a built structure, or an attribute, such as the structure of society.
ORGANIZATIONAL INFORMAL STRUCTURE INFLUENCE ON PROJECT SUCCESS: SOCIAL CAPITAL APPROACH
JinYoung Han, Korea University Business School, Seoul, South Korea, [email protected] Anat Hovav, Korea University Business School, Seoul, South Korea, [email protected]
Abstract
Knowledge sharing and organizational citizenship behavior (OCB) among project team members are crucial for project success. The IS project team is a temporary organization and has to produce outcomes in a limited time. we investigate how internal and external social capital (SoC) influence knowledge sharing and OCB within a team and how OCB and knowledge sharing affect project success. We also analyze the relationships between the three social capital dimensions. Our investigation will be analyzed using multi-level approach, which can make up for shortcomings of single-level analysis. This research adds to the current body of knowledge by examining the facilitation of knowledge sharing in the organization through informal interaction and citizenship. A statistical testing has not been complete. We will explore both HLM6 and MPLUS for multiple structural equation modeling and introduce a comparative analysis of each set of results. We expect the results of the research can provide project managers with insights on how to encourage project team members to share their knowledge and build teamwork more efficiently. Keywords: Project success, Oranizational Citizenship Behavior, OCB, Knowledge Sharing, Social Capital.
1
INTRODUCTION
As organizations increasingly rely on information systems (IS) for strategic and operational reasons, the role of IS has become essential in the business environment. Despite the importance of IS, IS project teams have experienced cost and time overrun. The dissatisfaction with the performance of IS projects is widespread (The_Standish_Group 2009). Differencing from construction or engineering projects, IS projects produce intangible outcomes and are knowledge-intensive work requiring diverse expertise such as business knowledge, processes, emerging IT techniques or skills (Pee, et al. 2010). Prior research has suggested positive relationships between knowledge –sharing (KS) and project performance (van den Hooff & Ridder 2004; Yu, et al. 2010). However, encouraging KS is still problematic as professionals are reluctant to share their knowledge and expertise. Social, culture, and technical attributes of organizational settings, which can encourage knowledge transfer, have been one of the major research topics since the introduction of knowledge management in an organization (Alavi & Leidner 2001). However, few studies have examined the social antecedents of knowledge sharing in the context of IS project success. KS is euqated with knowledge transfering (e.g. Huber 1991). Knoweldge transfering is deifned as communication of knowledge and transmission of knowledge (Ko, et al. 2005). KS depends on the attributes of the sender, receiver, and channel (Pee, et al. 2010) such as sender’s expertise (Joshi & Sarker 2007), receiver’s absortive capacity (Ko, et al. 2005), and channel’s richness (Lind & Zmud 1991). Prior research on the three elements showed mixed results (e.g. Joshi & Sarker 2007; Ko, et al. 2005). Previous research also shows the effects of intrinsic motivations (Ko, et al. 2005; Wasko & Faraj 2005) and social relationships (Ko, et al. 2005) on knowledge transmission. Individual expertise cannot transform to a group’s or an organizational knowledge without socialization (Bock, et al. 2005). Arduous relationships are negatively related to communication and interaction, while interaction is positively affected by mutual trust and shared understanding (Ko, et al. 2005). Factors such as trust, shared understanding and socializing are part of the informal structure of an organization and are often described as the dimensions of social capital (SoC). The concept of “SoC” has been examined as an increasingly essential factor of group formations (Huysman & Wulf 2004; Oh, et al. 2004; Reagans, et al. 2004). Research studies have noted that high levels of SoC are related to group cohesiveness, eventually supporting collective behavior (Adler & Kwon 2002; Yli-Renko, et al. 2001). SoC highlights the informal relationships between team members and their willingness to share knowledge based on relationships with others rather than on formal organizational structure. Using SoC lens, this study sheds light on the underlying process affecting individual and group KS, and subsequently team performance. While KS is affected by intrinsic motivation (Ko, et al. 2005; Wasko & Faraj 2005), extrinsic motivation failed to show significant impact on knowledge transfer (Ko, et al. 2005). Team members are intrinsically motivated when their satisfaction lies in the content of the activity itself (e.g., enjoying helping) (Ko, et al. 2005; Wasko & Faraj 2005). In this study, we use OCB as a manifestation of a team member’s innate behavior. Several researchers studied the antecedents of knowledge sharing in IS project context (Joshi & Sarker 2007; Ko, et al. 2005; Pee, et al. 2010). These studies mostly focused on the relationship between IT professionals and business professionals (Joshi & Sarker 2007; Pee, et al. 2010). These relationships are often contractual in nature (Joshi & Sarker 2007; Pee, et al. 2010). However, IS projects involve various stakeholders such as business analysts, system designers, hardware designers, programmers, and IT consultants. In addition, IS projects require substantial teamwork and collaboration among team members, which are often depend on social relations. Therefore, while prior research mainly dealt with contractual associations, this research extends the boundary of social relationship to include formal and informal connections. SoC has been studied at various levels from individual to country (Zaheer, et al. 2010). Aggregating SoC of individuals may affect higher level’s performance such as a team’s performance (Oh, et al. 2006). The combination of SoC at different levels may affect individual behavior or higher level’s performance (Yu, et al. 2010). However, few SoC related studies have conducted multi-level analysis. Our goal is to understand the effect of SoC on knowledge sharing and OCB among team members,
and the relationships between sharing knowledge, OCB, and project success. Moreover, we examine the relationships among the three dimensions of SoC empirically. We thus extend the social capital theory by examining the facilitation of knowledge sharing in the organization through informal interaction and citizenship behavior at two levels, individuals and groups.
2
2.1
THEORETICAL FOUNDATION
Social Capital Theory
SoC is defined as the set of social resources embedded in the network of relationships and composed of three dimensions underlying both internal and external ties (Nahapiet and Ghoshal 1998): Structural dimension refers to the information channels that connect individuals and units, relational dimension refers to the resources embedded in relationships, such as trust and reciprocity, between its members and cognitive dimension is defined as the shared meaning, and understanding that develops among members of the network as they interact. Several types of relationships exist within a project group and inter-groups. According to typology of conduits for group SoC (Oh, et al. 2006), We classify the relationships as depicted in Figure 1.
Figure 1.
Social relationship in a project
At the beginning of a project, team members may not know each other. Over time, they become familiar with other members. They might share the project’s context, and task -related knowledge using common language. Additionally, they can trust their team members or other teams through internal and external interaction. 2.2 Organizational Citizenship Behavior
The term “organizational citizenship behavior” (OCB) was proposed by Bateman and Organ (1983) and was denoted as organizationally beneficial behavior and gestures which cannot be enforced on the basis of formal role obligations (Bateman & Organ 1983). Graham(1991) separates citizen behavior into the behavior from in-role job performance and the behavior from extra-role job performance. For example, when a system designer participates in additional upkeep activities, which are not required, her behavior can be considered as a citizenship behavior. OCB is conceptualized as a broader concept which includes all positive organizational behavior of organizational members (Graham 1991; L Van Dyne, et al. 1994). 2.3 Level of Analysis
Social capital assumes social relationships or social networks among individuals. The levels of network analysis are classified as dyad, ego, and the entire network (Zaheer, et al. 2010). The dyadic level refers to a dyadic tie, which focuses on the nature of the relationship between two linked actors. Prior studies at the ego level have concentrated on the position of an ego, who is a focal actor, and the effects of the ego’s connections, for example, actor’s performance or carrier success. Recent studies at
the network level have examined the effects of complete networks on the characteristics of the entire network or individual firms (Zaheer, et al. 2010). In organizational research, two types of levels exist: level of measurement and level of analysis (Rousseau 1985). The level of measurement means the unit to which the data are directly assigned and the latter means the unit to which the data are assigned for hypothesis testing and analysis (Rousseau 1985). Accordingly , the levels of analysis of social capital studies vary from individual to society and might include multi- or mixed-level (Ali-Hassan, et al. 2010) (see Table 1). A typology of mixedlevel models includes composition, cross-level, and multi-level (Rousseau 1985). Composition models specify the relationships among nondependent variables at different levels. Cross-level models specify the causal relationships among independent and dependent variables at different levels. The third one is the multi-level model, which indentifies relationships among variables applying at two or more levels. Studies on social capital with multi-level approach are relatively new although the need for examining mixed-level organizational phenomena have been recognized (Belanger 2009). In this research, the levels of network analysis are both dyad and ego since the study deals with structural and relational dimensions of social capital. In addition, the multi-level model is used in terms of the level of analysis. The constructs, which are from three dimensions of social capital, are at the individual level. Organizational citizenship behavior is also at the individual level in the causal relationship between internal social capital and organizational citizenship behavior within a team. On the other hand, the relationship between perception of project success and real project success is cross-level as the project success is at the team level and the perceived project success is at the individual level. Thus, the proposed research model is mixed-level.
Levels of network analysis Dyad Ego (Hatzakis, et al. 2005; Moran 2005; (Ali-Hassan, et al. 2010; Seibert, et al. Seibert, et al. 2001; Sherif, et al. 2006) 2001; Sherif, et al. 2006; Yang & Farn 2007) (Hatzakis, et al. 2005; Newell, et al. (Balkundi & Harrison 2006; Chang & 2004; Tsai & Ghoshal 1998) Wong 2008; Kang & Kim 2009; Newell, et al. 2004; Robert, et al. 2008; Wang, et al. 2006) (Chou, et al. 2006; Tiwana 2008) (Honig, et al. 2006; Hsieh & Tsai 2007; Ingram & Roberts 2000; Lin, et al. 2006; Nahapiet & Ghoshal 1998) (Arling and Subramani 2005; (Yu, et al. 2010) Patnayakuni et al. 2006;Ali-Hassan, et al. 2010)
Level of analysis Individual
Group or Team
Organization
Multi or Cross level
Table 1.
Two types of level of analysis
3
HYPOTHESES DEVELOPMENT
Conventional indicators of project success are cost, time and scope. Project Management Body Of Knowledge (PMBOK)’s model uses the terms “on time, in budget, to scope” (PMI 2004). Project management (PM) success can be distinguished from project success (Cooke-Davies 2002). The latter is determined by measuring against overall objectives of a project whereas the former is determined by measuring against performance of cost, schedule, and quality (Cooke-Davies 2002; Thomas & Fernandez 2008). In this research, cost, schedule, and customer satisfaction are used as measures of project success because the study deals with individual project teams, and thus cannot measure successful organizational strategy implementation. In addition, project success is investigated with two constructs: the perception of project success and “real” project success. The first mea sures team members’ perceptions of their project status and the second is the result of project status based on
formal reports and users’ surveys. Team members may feel that they have done their work efficiently and effectively while reviewing their work status. Also, team members’ perception of project success may encourage their real performance. Therefore, we suggest the following hypothesis: H1: Team member’s perception of project success has a positive effect on the project success. [Cross level] Prior research has shown that OCB has direct influence on an organization’s performance (Podsakoff, et al. 2000; Yen, et al. 2008). In IS project, team members’ OCB can contribute to the completion of a project on schedule and in budget since OCB is indicative of positive organizational behavior of organizational members. Helping behavior allows co-workers to become more productive and enhance team spirit. Exhibiting sportsmanship may enhance the ability to adapt to changes. Additionally, team members, who engage in civic virtue, actively participate in team meetings and can provide valuable suggestions for improving team’s performance. Therefore, we propose the following hypothesis: H2: OCB of a team member has a positive effect on the perception of project success. Knowledge sharing is one of the critical practices leading to IS project success (van den Hooff and Ridder 2004; Yu, et al. 2010) since IS projects are knowledge-intensive and beyond the ability of one team member. The project team operates in rapidly changing business environment. An increase in knowledge sharing between teams could help face these changes (Liao, et al. 2009). Additionally, the team’s capability is enhanced when the experts within the team share their knowledge, skills and know-how. Therefore, we hypothesized that: H3: The intention to share knowledge has a positive effect on the perception of project success. OCB can encourage an individual to attend non-required meeting (Organ 1988). Through voluntary participation, team members are likely to exchange work-related information and help each other (Bolino, et al. 2002; Organ 1988). Therefore, the following hypothesis is proposed: H4: The OCB of a team member is positively associated with the member’s intention to share knowledge within the same team. People can trust others because of the other’s integrity, goodwill, and ability (Chiu, et al. 2006). When people trust colleagues from other teams, they can access knowledge of colleagues, which can be helpful for their own team. They, however, will not share the obtained knowledge within a team without the intention to help the team or to solve team’s issues. Shared vision also has been thought to play an important role in employees’ bonding (Kouzes & Posner 1989; Pfeffer 1996). A shared vision refers to the collective goals or common understanding of the firm’s vision or project’s goals (Nahapiet & Ghoshal 1998; Tsai & Ghoshal 1998). The sub-team’s interests often conflict though the sub-teams of a project work together. Thus team member’s direct contribution to his team such as knowledge sharing can be affected by the degree of participation in his team’s activity. Thus, we hypothesize that: H5: The relationship between the extent to which a team member trusts members from other teams and the intention to share knowledge is mediated by OCB. H6: The relationship between the extent to which a team member shares a vision of the firm and the intention to share knowledge is mediated by OCB. Prior research examined the relationship between trust and OCB and showed that trusting individuals are more likely to engage in OCB (Brower, et al. 2009; Dirks & Ferrin 2001; Linn van Dyne 2000). According to Brower, et al (2009), trust in the manager or in subordinates is positively related to individual OCB. Thus, we hypothesize that:
H7: The extent to which a project team member trusts other members is positively associated with the member’s OCB. According to Roussearu et al.(1998), people, who trust others, have confidence in others and can cooperate with others (Mayer, et al. 1995). Prior research (Dirks & Ferrin 2001) provides substantial evidence that trust facilitates the exchange of knowledge. For example, people are willing to give others useful information in trusting relationships (Levin & Cross 2004; Tsai & Ghoshal 1998). Main positive effects of trust on communication are shown in various forms: the communication targets (e.g. superiors, subordinates, or co-workers), the degree of communication openness within a group, and the quality or quantity of shared information (Dirks & Ferrin 2001). Based on this prior evidence, we suggest the following hypothesis: H8: The extent to which a project team member trusts his team members is positively associated with the intention to share knowledge within the team. Prior research has investigated the relationships between norms within a collectivity and pro-social behavior (van den Hooff & Ridder 2004; Wasko & Faraj 2005) and collaboration (Kankanhalli, et al. 2005; Sherif, et al. 2006). However, the results of these studies are mixed. In the context of IS projects, these norms might have positive effect on team members’ OCB such as openness to conflicting views and intention to share knowledge within their team. Thus, we hypothesize that: H9a: The extent to which a project team member believes that other members share cooperative norms is positively associated with the member’s OCB H9b: The extent to which a project team member believes that other members share cooperative norms is positively associated with the member’s intention to share knowledge. Shared mental model has been used as a manifestation of SoC cognitive dimension. It represents members in a network with similar knowledge structures (Robert, et al. 2008). A recent meta-analysis of Team Mental Models (TMMs) shows positive relationships between TMMs and various team processes (Mohammed, et al. 2010) such as back-up behavior (Marks, et al. 2002), coordination (Marks, et al. 2002; Mathieu, et al. 2000), and communication (Mathieu, et al. 2000). Assisting teammates and coordinating represent OCB. In addition, the coordination and communication processes support exchanging information and knowledge. Therefore, we hypothesize that: H10a: The extent to which a project team member shares a mental model with his team members is positively associated with the member’s OCB. H10b: The extent to which a project team member shares a mental model with his team members is positively associated with the member’s intention to share knowledge within the team. Prior studies recognized three dimensions of SoC as defined by Nahapiet and Goshal(1998). However, only a few of them examined the relationships among the three dimensions (Tsai & Ghoshal 1998). While internal SoC relies on internal social networks that define the relationships among team members and a leader within a team, external SoC relies on extended social relationships, such as connections to other teams (Chang & Wong 2008). Prior studies have suggested that trust is developed from increased social interaction (Granovetter 1983). Furthermore, repeated and close interactions lead team members to know each other and develop share norms (e.g. cooperative norm) (Tsai & Ghoshal 1998). Therefore, we hypothesize that: H11a: The degree of interaction with other members within the same team is positively associated with the extent to which the member trusts other members within the same team. H11b: The degree of interaction with other members within the same team is positively associated with the extent to which a project team member believes that other members share cooperative norm
As the members’ interaction increase in a social network, they may influence each other by adopting and realizing others knowledge. They may create new knowledge based on common interests. Team members may also internalize their leader’s norm, values, and practices through interaction with a team leader (Tsai & Ghoshal 1998). Hence, we hypothesize that: H12: The degree of interaction with other members within the same team is positively associated with the extent to which the member shares mental model with other members within the same team. Previous studies on the external dimension of SoC have focused on the performance of an organization (e.g. product innovation and organization productivity) (Chang & Wong 2008; Ingram & Roberts 2000; Oh, et al. 2004). Team leader’s external ties may have positive influence on his or her team’s perceived trustworthiness and enforce value-sharing (Ingram & Roberts 2000). Other teams in the network of a team leader are more likely to trust his team. Social interactions with other teams increase opportunities to exchange information and share project goals. Therefore, the following hypotheses are suggested: H13: The degree of interaction with members in other teams is positively associated with the extent to which the member trusts those members. H14: The degree of interaction with members in other teams is positively associated with the extent to which a team member shares a vision of his firm. The research model is shown in Figure 2.
Figure 2.
Research Model
4
4.1
PROPOSED METHODOLOGY
Measurement
Each construct will be measured using and adapting existing instruments as depicted in table 2. A pilot test for the instrument will be performed on a representative sample of the target population using conditions similar to those anticipated during actual data collection. Due to the research context, members of IS project teams will be targeted as the main respondents.
Construct External social network (Degree of interaction) Internal social network (Degree of interaction) External Trust Shared vision Trust Cooperative Norm Shared mental
Measurement Adopted ego-centric approach (Hansen, et al. 2005; Yu, et al. 2010) Adopted ego-centric approach(Hansen, et al. 2005; Yu, et al. 2010) The degree centrality of the inter-team trusting networks (Tsai & Ghoshal 1998) The level of shared vision in the different teams (Tsai & Ghoshal 1998) The level of trusting other members in the same team (Jarvenpaa, et al. 2004) Individuals’ willingness to value diversity, the openness to critical thought, and teamwork spirits (Kankanhalli, et al. 2005) Rated each attribute of the mental model in team process and expertise and measured mental model centrality and convergence (Mathieu, et al. 2000) A second order construct with three dimensions which are helping behavior, sportsmanship, and civic virtue (Yen, et al. 2008) Individuals’ willingness to share knowledge (Bock, et al. 2005) Individuals’ perception of the project’s status against team’s targeted schedule, man-hour and customer satisfaction Measured in terms of “on time”, “within man-hours”, and customer satisfaction based on formal documents(e.g. closure reports or survey of user’s satisfaction)
Level Individual Individual Individual Individual Individual Individual Individual
OCB
Individual
Intention to share knowledge Perception of project success Project success
Individual Individual Team
Table 2. 4.2 Analysis
Operationalization of Constructs
I will adopt a multilevel modelling technique. The multilevel analysis has several advantages comparing to single-level analysis: (1) the research model can be specified at its correct hierarchical levels, (2) the variability in an outcome can be estimated better, and (3) the analysis can provide flexibility of the model’s range (Heck & Thomas 2009). We will use the Hierarchical Linear Modeling (HLM6) or MPLUS to conduct multiple structural equation model approach. Due to the novelty of multi-dimension analysis in MIS research, we will explore both tools and introduce a comparative analysis of each set of results. 4.3 Plan for completion
Schedule 3rd week of May 2011 4th week of May 2011 1st - 2nd week of June 2011 3rd – 4th week of June 2011 After doctoral consortium August – September 2011 October 2011 November – December 2011 December 2011 – January 2012
Task Preparing survey questionnaire in English Preparing survey questionnaire in Korean by using forward and backward translations Performing a pilot test on a representative sample Analysis of pilot data Refining model, measurements and questionnaire Full data collection from members of IS project teams Conducting a multi-level statistical analysis Finalize writing Proof reading, editing, formatting
Table 3.
Schedule of completion
References
Adler, P., and Kwon, S. (2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1), 17-40. Alavi, M., and Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. Mis Quarterly, 25(1), 107-136. Ali-Hassan, H., Nevo, D., and Nevo, S. (2010). Mobile collaboration: exploring the role of social capital. ACM SIGMIS Database, 41(2), 9-24. Balkundi, P., and Harrison, D. (2006). Ties, leaders, and time in teams: Strong inference about network structure's effects on team viability and performance. Academy of Management Journal, 49(1), 49. Bateman, T., and Organ, D. (1983). Job satisfaction and the good soldier: The relationship between affect and employee" citizenship". Academy of Management Journal, 26(4), 587-595. Belanger, F. (2009). Conducting Multi-Level Research in Information Systems. Bock, G., Zmud, R., Kim, Y., and Lee, J. (2005). Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. Mis Quarterly, 29(1), 87-111. Bolino, M., Turnley, W., and Bloodgood, J. (2002). Citizenship behavior and the creation of social capital in organizations. Academy of Management Review, 27(4), 505-522. Brower, H., Lester, S., Korsgaard, M., and Dineen, B. (2009). A closer look at trust between managers and subordinates: Understanding the effects of both trusting and being trusted on subordinate outcomes. Journal of Management, 35(2), 327. Chang, k.-c., and Wong, J.-H. (2008). System Development Team Flexibility:Its Antecedents and Project Performance. PACIS 2008 Proceedings. Chiu, C., Hsu, M., and Wang, E. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872-1888. Chou, T., Chen, J., and Pan, S. (2006). The impacts of social capital on information technology outsourcing decisions: A case study of a Taiwanese high-tech firm. International Journal of Information Management, 26(3), 249-256. Cooke-Davies, T. (2002). The" real" success factors on projects. International Journal of Project Management, 20(3), 185-190. Dirks, K., and Ferrin, D. (2001). The role of trust in organizational settings. Organization Science, 12(4), 450-467. Graham, J. (1991). An essay on organizational citizenship behavior. Employee Responsibilities and Rights Journal, 4(4), 249-270. Granovetter, M. (1983). The strength of weak ties: A network theory revisited. Sociological theory, 1, 201-233. Hansen, M., Mors, M., and Lovas, B. (2005). Knowledge sharing in organizations: Multiple networks, multiple phases. Academy of Management Journal, 48(5), 776-793. Hatzakis, T., Lycett, M., Macredie, R., and Martin, V. (2005). Towards the development of a social capital approach to evaluating change management interventions. European Journal of Information Systems, 14(1), 60-74. Heck, R. H., and Thomas, S. L. (2009). An introduction to multilevel modeling techniques (2nd Edition ed.). New York : Routledge: Lawrence Erlbaum. Honig, B., Lerner, M., and Raban, Y. (2006). Social Capital and the Linkages of High-Tech Companies to the Military Defense System: Is there a Signaling Mechanism? Small Business Economics, 27(4), 419-437. Hsieh, M.-H., and Tsai, K.-H. (2007). Technological capability, social capital and the launch strategy for innovative products. [doi: DOI: 10.1016/j.indmarman.2006.01.002]. Industrial Marketing Management, 36(4), 493-502. Huysman, M., and Wulf, V. (2004). Social capital and information technology. Cambridge, Mass: The MIT Press. Ingram, P., and Roberts, P. (2000). Friendships among competitors in the Sydney hotel industry. American journal of sociology, 106(2), 387-423.
Jarvenpaa, S., Shaw, T., and Staples, D. (2004). Toward contextualized theories of trust: The role of trust in global virtual teams. Information Systems Research, 15(3), 250-267. Joshi, K., and Sarker, S. (2007). Knowledge transfer within information systems development teams: Examining the role of knowledge source attributes. Decision Support Systems, 43(2), 322-335. Kang, S., and Kim, T. (2009). Opinion Leaders, Social Capital, and Innovations in Teams. Seoul Journal of Business, 15(2), 137-155. Kankanhalli, A., Tan, B. C. Y., and Kwok-Kee, W. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. [Article]. Mis Quarterly, 29(1), 113-143. Ko, D. G., Kirsch, L. J., and King, W. R. (2005). Antecedents of knowledge transfer from consultants to clients in enterprise system implementations. Mis Quarterly, 29(1), 59-85. Kouzes, J., and Posner, B. (1989). The leadership challenge: How to get extraordinary things done in organizations (1st Edition ed.). San Francisco:Jossey-Ba. Levin, D. Z., and Cross, R. (2004). The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer. Management Science, 50(11), 1477-1490. Liao, C., Yu-Ping Liu, Lin, H.-N., and Huang, Y.-H. (2009). The Effect of Knowledge Sharing on IS Outsourcing Success. AMCIS 2009 Proceedings. Lin, B., Li, P., and Chen, J. (2006). Social capital, capabilities, and entrepreneurial strategies: a study of Taiwanese high-tech new ventures. Technological Forecasting and Social Change, 73(2), 168181. Lind, M. R., and Zmud, R. W. (1991). The influence of a convergence in understanding between technology providers and users on information technology innovativeness. Organization Science, 2(2), 195-217. Marks, M., Sabella, M., Burke, C., and Zaccaro, S. (2002). The impact of cross-training on team effectiveness. Journal of Applied Psychology, 87(1), 3-13. Mathieu, J., Heffner, T., Goodwin, G., Salas, E., and Cannon-Bowers, J. (2000). The influence of shared mental models on team process and performance. Journal of Applied Psychology, 85(2), 273-283. Mayer, R., Davis, J., and Schoorman, F. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734. Mohammed, S., Ferzandi, L., and Hamilton, K. (2010). Metaphor No More: A 15-Year Review of the Team Mental Model Construct. Journal of Management, 36(4), 876. Moran, P. (2005). Structural vs. relational embeddedness: social capital and managerial performance. Strategic Management Journal, 26(12), 1129-1151. Nahapiet, J., and Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. The Academy of Management Review, 23(2), 242-266. Newell, S., Tansley, C., and Huang, J. (2004). Social capital and knowledge integration in an ERP project team: The importance of bridging and bonding. British Journal of Management, 15(s 1), 43-57. Oh, H., Chung, M., and Labianca, G. (2004). Group social capital and group effectiveness: The role of informal socializing ties. Academy of Management Journal, 47(6), 860-875. Oh, H., Labianca, G., and Chung, M. (2006). A multilevel model of group social capital. Academy of Management Review, 31(3), 569. Organ, D. (1988). Organizational citizenship behavior: The good soldier syndrome (Vol. 133). Lexington, MA: Lexington books Pee, L. G., Kankanhalli, A., and Kim, H. W. (2010). Knowledge Sharing in Information Systems Development: A Social Interdependence Perspective. Journal of the Association for Information Systems, 11(10), 550-575. Pfeffer, J. (1996). Competitive advantage through people: Unleashing the power of the work force: Harvard Business Press. PMI. (2004). A Guide to the Project Management Body of Knowledge (PMBOK Guide) (3rd ed.). Newtown Square, PA: Project Management Institute. Podsakoff, P., MacKenzie, S., Paine, J., and Bachrach, D. (2000). Organizational citizenship behaviors: A critical review of the theoretical and empirical literature and suggestions for future research. Journal of Management, 26(3), 513.
Reagans, R., Zuckerman, E., and McEvily, B. (2004). How to make the team: Social networks vs. demography as criteria for designing effective teams. Administrative Science Quarterly, 101-133. Robert, L. P., Jr., Dennis, A. R., and Ahuja, M. K. (2008). Social Capital and Knowledge Integration in Digitally Enabled Teams. Information Systems Research, 19(3), 314-334. Rousseau, D. (1985). Issues of levels in organizational research: Multi-level and cross-level. Research in organizational behavior, 7, 1-37. Seibert, S., Kraimer, M., and Liden, R. (2001). A social capital theory of career success. Academy of Management Journal, 44(2), 219-237. Sherif, K., Hoffman, J., and Thomas, B. (2006). Can technology build organizational social capital? The case of a global IT consulting firm. Information & management, 43(7), 795-804. The_Standish_Group. (2009). CHAOS summary 2009 report: The Standish Group. Thomas, G., and Fernandez, W. (2008). Success in IT projects: A matter of definition? International Journal of Project Management, 26(7), 733-742. Tiwana, A. (2008). Do bridging ties complement strong ties? An empirical examination of alliance ambidexterity. Strategic Management Journal, 29(3), 251. Tsai, W., and Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. The Academy of Management Journal, 41(4), 464-476. van den Hooff, B., and Ridder, J. (2004). Knowledge sharing in context: the influence of organizational commitment, communication climate and CMC use on knowledge sharing. Journal of Knowledge Management, 8(6), 117-130. van Dyne, L. (2000). Collectivism, propensity to trust and self-esteem as predictors of organizational citizenship in. Journal of Organizational Behavior, 21(1), 3. Van Dyne, L., Graham, J., and Dienesch, R. (1994). Organizational citizenship behavior: Construct redefinition, measurement, and validation. Academy of Management Journal, 37(4), 765-802. Wang, E. T. G., Ying, T.-C., Jiang, J. J., and Klein, G. (2006). Group cohesion in organizational innovation: An empirical examination of ERP implementation. [doi: DOI: 10.1016/j.infsof.2005.04.006]. Information and Software Technology, 48(4), 235-244. Wasko, M., and Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. Mis Quarterly, 29(1), 35-57. Yang, S.-C., and Farn, C.-K. (2007). Exploring Tacit Knowledge Sharing Intention and Behavior within Workgroup from the Perspectives of Social Capital and Behavioral Control. PACIS 2007 Proceedings. Yen, H., Li, E., and Niehoff, B. (2008). Do organizational citizenship behaviors lead to information system success? Testing the mediation effects of integration climate and project management. Information & management, 45(6), 394-402. Yli-Renko, H., Autio, E., and Sapienza, H. (2001). Social capital, knowledge acquisition, and knowledge exploitation in young technology-based firms. Strategic Management Journal, 22(6-7), 587-613. Yu, A., Hao, J., Dong, X., and Khalifa, M. (2010). Revisiting the effect of social capital on knowledge sharing in work teams:A multilevel approach. Zaheer, A., Gö zü bü yü k, R., and Milanov, H. (2010). It's the Connections: The Network Perspective in Interorganizational Research. Academy of Management Perspectives, 24(1), 62-77.
doc_907670405.pdf