Antecedents of ISD team performance: Knowledge management activities

Abstract

The topic of knowledge management is an important one in team-based studies. Many previous studies have shown that the proper team structure facilitates sharing and applying the expertise and knowledge which is scattered among members, allowing for team tasks to be executed more efficiently and effectively. Knowledge management involves four basic processes: storing/retrieving, transferring, applying, and creating knowledge. This study uses transactive memory system, knowledge sharing, knowledge application and creativity as knowledge management process activities in order to explore their impact on team performance. Based on data from a study of 64 ISD teams, all our hypotheses were found to be significant.

Keywords

Knowledge sharing knowledge application team creativity transactive memory system collective knowledge efficacy

Sheng Wu is an associate professor of information management at Southern Taiwan University of Science and Technology in Taiwan. He received his Ph.D. degree from National Sun Yat-Sen University. His current research interests include knowledge management, electronic commerce, and management of information systems. His research has been accepted or published in academic journals such as Information & Management, Information Systems Journal, Decision Support Systems, Online Information Review, Journal of Organizational Computing and Electronic Commerce, Expert Systems with Applications and various other journals. He can be reached at shengwu@mail.stust.edu.tw or sheng.mis@gmail.com.

1 Introduction

Teamwork research has recognized knowledge management as an important issue. The information systems development (ISD) team is a key knowledge-based framework that enterprises must consider [64]. ISD teams are highly flexible, and team members can be recruited from different departments. This flexibility allows adjustments for dealing with tasks of various sorts. When an enterprise is confronted with a problem on a new, unstructured model, it needs access to the wide variety of knowledge held within the enterprise. The ISD team framework and knowledge management processes can be implemented together for effective knowledge integration, improving the performance of the ISD team and enhancing company competitiveness [47].

Knowledge is fundamentally different from information, since it can be formed after processing, interpretation, selection and transformation of information [116]. Knowledge is a purposeful coordination of action that it is embodied in an organism and embedded in action [115]. The knowledge management is a set of processes involving various activities that link knowledge of employees to new sources of value in order to create innovative solutions [61]. These knowledge activities consist of four basic processes (i.e., storing/retrieving, transferring, applying, and creating knowledge) which team members can employ to become efficient and productive in their work [4]. A transactive memory system (TMS) is the collection of knowledge possessed by each team member along with a collective awareness of which team members hold which knowledge (i.e., “who knows what”) [12]. In a team, a TMS is a collective system for encoding, storing, and retrieving information that is distributed across team members [106, 107].

Knowledge sharing is a process of gaining experience from another individual [2]; thus, it is also called “knowledge transfer” [34]. Of all the knowledge management activities, knowledge sharing is the most difficult one to implement [94]. In practice, knowledge sharing is at the core of knowledge management; in fact, successful knowledge management depends on knowledge sharing. However, since knowledge sharing is simply the spreading of knowledge, there is no guarantee that the shared knowledge is useful or accessible to other team members. According to Griffith et al. [47], shared knowledge must be quickly circulated among team members so that it can actually contribute to solutions. In other words, potential knowledge must be converted into usable knowledge for the ISD team. For this reason, determining how to make use of the shared knowledge becomes of paramount importance since shared knowledge that is not applied fails to improve the team’s work output.

Most studies have focused on knowledge sharing and have ignored the importance of knowledge application [32]. The ISD team is the fundamental unit for knowledge sharing and application, activities in which team members exchange, share and apply their specialized knowledge in order to stir up innovative ideas. Previous studies posited an approximate correlation between knowledge management and creativity [112, 114]. Creativity depends on— and is enhanced by— the sharing and application of knowledge among team members [62]. Consequently, an increase in knowledge sharing and application is beneficial to the enhancement of overall creativity. In this study, we integrate research on TMS, knowledge sharing, knowledge application, and team creativity to develop and test a set of hypotheses regarding knowledge management activities. These knowledge management activities are, in turn, hypothesized to influence team performance.

In sum, the first purpose of this study is to explore knowledge management activities in an ISD team to understand their impact on teamwork. The second purpose is to more deeply explore the critical role of team creativity in teamwork performance. The third purpose is to explore how collective knowledge efficacy moderates the relationships between TMS, knowledge sharing, knowledge application, and team creativity. The remainder of this paper is organized as follows. First, we review the knowledge management process and draw on TMS, knowledge sharing, knowledge application, and team creativity literature to develop our hypotheses. Next, we describe our method for examining the proposed model. We conclude with the research results and their implications.

2 Literature review and hypothesis development

2.1 Transactive memory system (TMS)

A team’s ability to effectively integrate knowledge provides a competitive advantage for the organization. A team is a group of two or more individuals who must interact cooperatively and adaptively to work on shared objectives [24]. An individual team member’s knowledge is limited, and the team cannot depend entirely on some individual expert who stores specific knowledge needed by all teams. Therefore when one individual cannot solve the problem using his own knowledge, he must retrieve the required knowledge from other individuals. The term “transactive memory” has its origins in the concept of external storage acting as an extension of individual memory.

In a team, TMS is the collective system for encoding, storing, and retrieving information that is distributed across team members [106, 107]. Via this TMS, team members know who knows what, and who knows who knows what [55]. The TMS can be viewed as a knowledge set possessed by group members, coupled with an awareness of who knows what. The system includes two components: (1) an organized store of knowledge that is contained entirely in the individual memory systems of the group members; and (2) a set of knowledge-relevant transactive processes that occur among group members. The process through which team members encode, store, and retrieve information from each other is called the transactive process [107].

Past studies have shown that TMS is an important antecedent that affects team performance [32, 70]. Many scholars also point out that TMS can lead to effective knowledge retention, knowledge transfer, knowledge creation, knowledge sharing, and information gathering among team members [11 , 105]. Chen et al. [27] argue that, for a team, TMS is a useful cognitive mechanism that may explain the effectiveness of knowledge sharing within the team. Choi et al. [32] proposed that a more developed understanding of TMS will lead to more effective knowledge sharing and application in teams. It is broadly accepted that TMS is critical for effective teamwork processes and performance. For example, it is a significant predictor of problem-solving [68]. Mitchell and Nicholas [78] found that TMS is likely to have an impact on outcome creativity. Furthermore, it is important to explore how TMS affects different aspects of a team’s knowledge management processes. When a team has the knowledge, skills and abilities required to execute projects, its members can use their diverse views to search for and develop creative solutions [84]. Cheng and Yang [29] also argued that team knowledge positively influences team creative self-efficacy. Therefore, we propose the first, second and third hypotheses.

H1: An ISD team’s level of TMS is positively associated with knowledge sharing among team members.

H2: An ISD team’s level of TMS is positively associated with knowledge application among team members.

H3: An ISD team’s level of TMS is positively associated with team creativity.

2.2 Knowledge sharing

“Knowledge” plays a basic but essential role in boosting the competiveness of a company within its industry. Nowadays, knowledge sharing has become indispensable to a sound enterprise. “Knowledge sharing” is defined as allowing members within the organization or in external/internal teams to exchange or discuss knowledge within or across organizations via various channels such as face-to-face meetings, conferences, the Internet, published best practices, and databases. The primary purpose of knowledge sharing is to increase the use of such knowledge and to derive knowledge synergies. Darr and Kurtzberg [34] suggested that knowledge sharing is a process of gaining experience from another individual; thus it is also called “knowledge transfer.” The process of knowledge transfer can also consolidate organizational learning. Regarding the individual’s role in the knowledge sharing process, past studies have indicated that employee turnover in an enterprise is often considered the optimal time for promoting knowledge sharing [43, 92]. Generally, this is because of the individual’s ability to readapt and structure knowledge in different situations [6], and the ability to make use of both tacit and explicit knowledge in a new situation [19, 20]. Thus, individual knowledge in an organization must be transferred through knowledge sharing to other employees who need it in order to work efficiently, i.e., “right time, right place, right knowledge, right person.” Knowledge is authority, and it also functions as the core source of an individual’s output. This makes it difficult for employees to be unselfish with their contributions. Thus, compared with other processes of knowledge management, organizational knowledge management faces tougher challenges.

Whether knowledge management (e.g., knowledge sharing) can be successfully carried out has become a core issue. However, even if team members are willing to share their specialized knowledge, such knowledge may or may not be useful for other participants. This is because knowledge sharing is simply the spreading of knowledge.

2.3 Knowledge application

When it comes to knowledge management processes, knowledge application has been frequently mentioned by scholars such as Wiig [109], Pentland [85], Nonaka and Takeuchi [81], Andersen and APQC [9], Beckman [16], DiBella and Nevis [38], Alavi and Leidner [4], and Shin et al. [97]. These scholars have also agreed that knowledge application is an indispensable activity. Knowledge application is the use of existing knowledge to solve upcoming problems [5]. The application of knowledge is important since knowledge creation and sharing does not guarantee any improvement in overall performance unless that knowledge is applied [4, 5]. Therefore, if knowledge is simply shared or transferred within an organization without be applied to solve problems, the knowledge itself is useless. This is the so-called “knowledge-doing gap” [86]. The ISD team is the basic organizational unit for knowledge sharing and application activities. Team members come up with innovative ideas by exchanging, sharing and applying each individual’s specialized knowledge. As the level of knowledge sharing and application increases, team performance improves [62]. According to Griffith et al. [47], shared knowledge must be circulated within the team and contribute to solutions; that is, potential team knowledge must be converted into usable knowledge for the team. Thus, the means by which shared knowledge can be applied becomes significant. Based on the above studies, we conclude that knowledge application is crucial and worthy of further pursuit.

Law and Lee-Partridge [63] indicated that when knowledge is applied, the value of that knowledge is realized. Alavi and Leidner [4] argued that knowledge creation, knowledge storage/retrieval, and knowledge transfer do not necessarily promote organizational performance. By contrast, effective knowledge application will boost organizational performance. Lin [69] proposed that if an organization’s employees or teams can apply knowledge they have gained or absorbed from other places to their work processes or to solving problems, that knowledge becomes valuable. However, “motionless” knowledge that is not applied is of no value at all. Hsieh [53] suggested that an organization’s knowledge management activities should be based on individual and organizational knowledge, both of which should be effectively applied. Only the application of both types of knowledge can boost the performance of theorganization.

Knowledge application requires knowledge sharing, because knowledge must be obtained before it can be used. Individuals can certainly depend on their own knowledge gained through learning or previous experience, but, in an organizational environment, formal and informal knowledge sharing are important means by which to gain knowledge [4, 10]. Law and Lee-Partridge [63] argued that only when knowledge is applied does it become valuable. However, knowledge sharing depends on team members’ willingness to share their specialized knowledge before it can be used to solve challenges. As discussed above, as the level of knowledge sharing increases, the level of knowledge application also increases. Therefore, we propose the fourth hypothesis.

H4: An ISD team’s level of knowledge sharing is positively associated with knowledge application among team members.

2.4 Team creativity and team performance

The performance of the ISD team has been a critical issue in the field of projects [3 , 111]. The ISD team faces a constantly-changing environment, and success lies in the team’s problem solving competencies. Problems arise when the ISD team senses a gap between expectations and reality [80, 102]. Therefore, the ability to reduce the gap between the ideal and the real is the so-called “problem solving competence” [25]. With problem solving competencies, an ISD team can quickly reduce the gap between the ideal and the real, which, in turn, boosts team performance [3]. Woodman et al. [110] suggested that creativity is another manifestation of problem-solving skills. Guilford [48] suggested that creativity and problem solving occur in the same mental state. Newell et al. [79] argued that creativity is a particular problem-solving activity, characterized by novelty, peculiarity and difficulty.

Considering the scale and complexity of present day information systems, a single individual cannot possibly accomplish an entire project. Such projects require team cooperation and brainstorming, putting to use the specialized knowledge of each team member so that versatile, creative solutions can be proposed to cope with problems and challenges [60]. The successful development of an information system is dependent upon the efforts of all team members, and creativity is the most important driving force along the way [33 , 96]. Team creativity will also determine the success of an information system development project. This is because ISD requires group/team cooperation; the development process can be a manifestation of team members’ creativity. In summary, team creativity plays a critical role in the information system development process.

Previous studies have concluded that there is an approximate correlation between knowledge management and creativity [66 , 114]. Relevant knowledge management activities can inspire the team [67]. Creativity needs the support of knowledge, so both formal knowledge and informal knowledge chains are necessary [101]. From an innovation management perspective, intensive communication and cooperation within a team can integrate team members’ specialized knowledge. Such integration enhances team and organizational creativity [22, 74]. When team members share and apply knowledge, creativity increases [62]. Hong et al. [52] found that knowledge sharing has a positive correlation with product development. Sternberg and Lubart [101] proposed an investment theory of creativity, arguing that for creativity to be exercised to its fullest extent, support is needed from other resources (such as appropriate levels of both formal and informal knowledge), and each team member must be able to apply external knowledge to problems instead of being limited by his or her internal knowledge. Liu and Phillips [71] suggested that knowledge sharing is likely to lead to higher team innovativeness. Cheng [28] found that knowledge sharing positively influences student information system development project team creativity. In a nutshell, as the level of knowledge sharing and application increases, the level of creativity also increases. Therefore, we propose the fifth and sixth hypotheses.

H5: An ISD team’s level of knowledge sharing is positively associated with team creativity.

H6: An ISD team’s level of knowledge application is positively associated with team creativity.

Previous knowledge management studies have suggested that knowledge sharing and knowledge application have a significant correlation with a team’s work performance [32]. As the team works together, knowledge cannot be simply shared but must effectively applied to challenges. Majchrzak et al. [75] indicated that the application of shared knowledge is distinct from sharing actives in knowledge management practices. Dennis [36] found that team members often failed to make use of the shared information, and this failure resulted in less desirable group decisions. Faraj and Sproull [40] noted that team performance is significantly affected by the level to which team members are able to realize the value of knowledge. Kanawattanachai and Yoo [57] also found that the ability of virtual team members to apply knowledge is an influential determinant of a virtual team’s performance. Choi et al. [32] suggested that if a team can integrate and apply extant knowledge, this integration will greatly benefit team performance. In addition, information system development is also a process in which team members exhibit their creativity, and such creativity facilitates the accomplishment of a project [33, 82]. Finally, as pointed out by Tiwana and McLean [104], team creativity strongly affects team results. To sum up, team creativity and the application of knowledge are greatly beneficial to team performance. Therefore, we propose the seventh and eighth hypotheses.

H7: An ISD team’s level of knowledge application is positively associated with team performance.

H8: An ISD team’s level of creativity is positively associated with team performance.

2.5 Collective knowledge efficacy

Bandura [13] defined self-efficacy as people’s belief in their own ability to organize and execute courses of action required to manage prospective situations. Self-efficacy can be general or specific. However, knowledge self-efficacy belongs to a specific area. Kankanhalli et al. [58] argued that knowledge self-efficacy is the confidence in one’s ability to provide knowledge that is valuable to the organization. Bandura [14] suggested that the self-efficacy concept can also be applied to groups. Bandura [13] transitioned personal efficacy to “collective efficacy” by noting in his definition the “group’s shared belief in its conjoint capabilities” (p.477). Riggs et al. [89] defined collective efficacy as each individual’s assessment of the group’s collective ability to perform job-related behaviors (p.7). Therefore, the collective knowledge self-efficacy of an ISD team refers to a shared belief in the team’s members’ ability to collaborate to provide knowledge that is valuable to the team during softwaredevelopment.

There are several studies on the moderating effect of self-efficacy, which are mostly concerning the moderating effects of self-efficacy on the relationship of certain factors to skill/knowledge related performance [17 , 103]. In the knowledge management field, studies have noted a knowledge gap between two parties: the source of knowledge and the recipient of knowledge within the team. If knowledge sharing, knowledge application, and creativity are considered to be the performance of the source party, collective knowledge efficacy is, therefore, hypothesized to have a moderating effect on these factors. Therefore, we propose the following hypotheses.

H9: The impact of TMS on knowledge sharing is moderated by the degree of collective knowledge efficacy.

H10: The impact of TMS on knowledge application is moderated by the degree of collective knowledge efficacy.

H11: The impact of TMS on team creativity is moderated by the degree of collective knowledge efficacy.

In consideration of the findings in the literature review, this paper proposes the research model shown in Fig. 1. As shown in the model, this study attempts to contribute to the team creativity research stream by applying TMS, knowledge sharing and knowledge application to the area of knowledge management.

3 Research methodology

3.1 Subjects

We conducted a study with measures to test the proposed model. Before graduation, most management information systems (MIS) departments’ students have two semesters of information system development project training courses. The main goal of these courses is to develop the students’ information system problem-solving abilities. In ISD project training, student teams must use MIS knowledge and methods to develop an IS. Our study investigated MIS student ISD teams as its major subjects. Questionnaires were filled out by ISD team members from MIS departments at universities in Taiwan. These ISD teams belonged to a senior graduation project development effort. Respondents were primarily team members from teams which had spent at least one year developing their projects under the supervision of their teachers. Subjects were rewarded with gifts in order to increase accuracy and return rates. A total of 68 teams (309 members) participated in the study. The exclusion of incomplete questionnaires resulted in a net total of 64 teams (290 members). Team sizes ranged from 3 to 6 members.

The team-level effect of collective knowledge efficacy, TMS, knowledge sharing, knowledge application, team creativity, and team performance was aggregated by averaging the scores of individual team members. We calculated between-group differences, within-group inter-rater agreement, and inter-rater reliability using one-way ANOVA [8, 93], James’ index (r_wg) [54], and the inter-class correlation coefficient (ICC) [98]. The results show statistical significance (p < 0.001) for six constructs. The r_wg values for three teams were below 0.7 [54]. We deleted the data from these teams to ensure that the retained team data were suitable for aggregation. Since the ICC Values all exceeded 0.7, the results show a reasonable level of suitability [7].

Malhotra et al. [76] pointed out that common method biases in the IS domain are not as serious as those found in other disciplines. Since we collected both independent and dependent variables simultaneously from the same respondent, common method variance might be a concern in this study. Common method bias was evaluated by using Harman’s one-factor test to ensure that there was no significant method effect on the predefined causal relationship [88]. Given the small magnitude and, thus, the insignificance of the method variance, we contend that the method is unlikely to be a serious concern for this study. Therefore, the representativeness of our sample is ensured. Finally, we examined the collinearity problem with VIF (variance inflation factor) values. The results show low VIF values (collective knowledge efficacy = 1.752, TMS = 2.091, knowledge sharing = 3.298, knowledge application = 4.195, team creativity = 4.473), all of which are far below the common cut-off threshold of 10 [37, 49], minimizing the possibility of a collinearity problem.

3.2 Measurement development

Six constructs were measured: collective knowledge efficacy, transactive memory system (TMS), knowledge sharing, knowledge application, team creativity, and team performance. Constructs were measured using a multiple-item scale drawn from pre-validated studies and reworded to relate specifically to teams. The applicability of the modified items was enhanced by a review of the literature, using two MIS professors as expert judges, and pretested using five students involved in ISD teams. During this process, scale items were trimmed and refined, and dimensions were modified to maintain content validity as our understanding of the constructs improved. All items used five-point Likert scales ranging from “strongly disagree (= 1)” to “strongly agree (= 5).” Table 1 shows the operational definitions and sources of measurement of variables.

3.3 Reliability and validity

The partial least squares (PLS) model was employed to test our measurements and proposed hypotheses. This study employed SmartPLS 2.0 M3 [91], a software program frequently adopted by studies published in top MIS journals such as MIS Quarterly. In MIS Quarterly, the most noted reason for choosing PLS is because it facilitates the use of small sample sizes [90]. PLS can model latent constructs under conditions of non-normality with small- to medium-sized samples. Item reliability, convergent validity and discriminant validity tests are often used to evaluate the measurement model in PLS. Reliability can be ensured through composite reliability (CR >0.7), Cronbach’s alpha (>0.7), item-total correlation (ITC >0.30) and factor loading (>0.7). Convergent validity should be tested when multiple indicators are used to measure one construct. This can be examined by testing the CR (>0.7) and average variance extracted (AVE >0.5) by constructs [41]. For the required discriminant validity, the correlation between construct pairs should be lower than 0.90 and the square root of AVE should be higher than the inter-construct correlation coefficients [41]. Data shown in Tables 2 and 3 indicate that all minimum requirements were met.

4 Data analysis and results

In this paper, we assessed the hypotheses via structural equation modeling because of its ability to validate multiple causal relationships simultaneously. This study used SmartPLS 2.0 M3 with bootstrapping as a resampling technique (5000 random samples) to estimate the structural model and the significance of the paths [30, 45]. Path coefficients (t value) and R² values were used jointly to evaluate the model. Statistical tests were assessed at the 5% level of significance using a two-tailed t-test. The Goodness of Fit (GoF) index used by Wetzels et al. [108] was employed to test the model for global validity and explanatory power. The value of GoF was 0.711, exceeding the cut-off value of 0.36. This shows adequate support to globally validate the PLS model. As shown in Fig. 2, all hypotheses were supported.

First, Hypothesis 1 proposed a link between TMS and knowledge sharing. Based on our findings, TMS is significantly associated with knowledge sharing (β = 0.63, p < 0.001). TMS explains 40% of the total variance of knowledge sharing. Hence, H1 was supported. As predicted, TMS has a positive influence on knowledge sharing, which is consistent with the literature [27, 32].

Second, we found that both TMS (β = 0.30, p < 0.01) and knowledge sharing (β = 0.62, p < 0.001) have a positive impact on knowledge application. Thus, H2 and H4 were supported. As predicted, both TMS and knowledge sharing have a positive influence on knowledge application, which is consistent with the literature [11 , 105]. These two variables explain over 50% of the variance of knowledge application (R² = 71% ).

Third, for team creativity, three proposed antecedents were also found to have positive impacts. The coefficient from TMS to team creativity is 0.29 (p < 0.01), the coefficient from knowledge sharing to team creativity is 0.19 (p < 0.05), and the coefficient from knowledge application to team creativity is 0.49 (p < 0.001). This result indicates that H3, H5 and H6 were also supported. As predicted, TMS, knowledge sharing and knowledge application have a positive influence on team creativity, which is consistent with the literature [29 , 71, 78]. In addition, the combination of TMS, knowledge sharing and knowledge application explains more than 50% of the variance of team creativity (R² = 77% ).

Fourth, we found that both knowledge application (β = 0.26, p < 0.01) and team creativity (β = 0.48, p < 0.001) positively impact team performance. Thus, H7 and H8 were supported. As predicted, both knowledge application and team creativity have a positive influence on team performance, which is consistent with the literature [32, 57]. These two variables explain the variance of team performance (R² = 50% ). The explanatory power of knowledge sharing, knowledge application, team creativity, and team performance are considerably greater than the recommended level of 10% [39, 87].

Fifth, we used PLS to test the moderating effect of collective knowledge efficacy [31], with the following results: (1) Collective knowledge efficacy significantly moderates the relationship between TMS and knowledge sharing; the interaction effect with collective knowledge efficacy was 0.19 (p < 0.05). (2) Collective knowledge efficacy significantly moderates the relationship between TMS and knowledge application; the interaction effect with collective knowledge efficacy was 0.20 (p < 0.05). (3) Collective knowledge efficacy significantly moderates the relationship between TMS and team creativity; the interaction effects with collective knowledge efficacy was 0.24 (p < 0.05). Given the results of this study, collective knowledge efficacy clearly acts as a moderator in the relationship between the source of knowledge and the recipient of knowledge. Hence, hypotheses H9, H10 and H11 were all supported.

Final, the moderating effect diagrams are shown in Figs. 3, 4 and 5. The results indicate that (1) TMS has a positive effect on knowledge sharing, application and team creativity, irrespective of the level of collective knowledge efficacy (CKE); (2) although the slope for different levels of CKE is positive, it is much steeper when the level of TMS is high; (3) when TMS is low, a similar level of knowledge sharing, application and team creativity can be observed at different levels of TMS; and (4) as the level of TMS increases, much higher knowledge sharing, application and team creativity can be found for high degrees of CKE, compared with that found in the context of low degrees of CKE.

5 Discussion and conclusion

In this study, we explored how ISD teams’ TMS, knowledge sharing, knowledge application and team creativity affect team performance. We also examined the moderating effect of collective knowledge efficacy on the relationship between TMS and knowledge management activity (knowledge sharing, knowledge application and team creativity). Data from our survey of 64 ISD teams supported all of our proposed hypotheses. Our results also illustrate the robustness of collective knowledge efficacy as a moderator variable. As shown in Figs. 3, 4 and 5, the gap between high and low CKE increases as the level of TMS increases. This provides a clear picture for understanding the internal structure of TMS and CKE.

Furthermore, the result shown in Fig. 2 notes that team creativity has a greater impact on team performance than do either knowledge sharing or knowledge application. Many previous studies have shown that team creativity plays a very import mediating role [33 , 96]. Therefore, we conducted three Sobel tests to examine the significance level of the mediation effect [100]. The results show that the effects of TMS (z-value = 2.854, p < 0.01), knowledge sharing (z-value = 3.388, p < 0.001), and knowledge application (z-value = 3.012, p < 0.01) on team performance are significantly mediated by team creativity. In addition, we tested the mediating relationship in accordance with Baron and Kenny [15]. The results show that the effects of TMS (the significance level was increased from p < 0.001 to p < 0.01), knowledge sharing (the significance level was increased from p < 0.001 to p < 0.05), and knowledge application (the significance level was increased from p < 0.001 to p < 0.01) on team performance are partially mediated by team creativity. Therefore, we can conclude that team creativity is an important mediating variable between knowledge activities and team performance in a teamwork context. However, while creativity has been crucial for business success, creativity in ISD is becoming more and more important. Therefore, MIS students must be taught how to solve problems in a team context when developing information systems.

6 Implications and limitations

6.1 Implications

Findings from this study provide critical implications for researchers and practitioners interested in team knowledge management. For researchers, this study contributes to the knowledge management stream by examining team creativity and the performance of ISD teams. Previous studies focused primarily on knowledge sharing, and ignored the importance of knowledge application and creativity. This study shows that TMS is a very important factor that affects knowledge sharing, knowledge application, and team creativity. Our survey of previous studies indicates that TMS affects team performance [55, 57]. In this study, the path coefficients were calculated to show the direct and indirect effects of each dimension of team performance. The total effects of each dimension on team performance rank in descending order as follows: TMS (0.535), knowledge application (0.491), team creativity (0.480) and knowledge sharing (0.395). Previous studies have also shown that TMS is critical for effective teamwork processes and performance [1 , 70]. However, our result shows that TMS influences team performance through knowledge sharing, knowledge application and team creativity. Therefore, we believe that team creativity is an important mediating variable between TMS and team performance. In addition, our study also shows that collective knowledge efficacy clearly acts as a moderator in the relationship between the source of knowledge and the recipient of knowledge. This echoes the concern about the knowing– doing gap [32, 86].

For practitioners, our results show a significant direct effect of team creativity on team performance (Fig. 2). While creativity is often portrayed as something that cannot be defined, implemented, or created, the findings of Tiwana and McLean [104] suggest that IS managers can indeed help design ISD teams to be more creative, albeit within organizational constraints. Therefore, our study suggests that setting up an excellent ISD team is dependent upon an environment rich in knowledge application and creativity because creative teamwork maximizes members’ contributions, leading to higher levels of efficiency and productivity, i.e., greater performance. The findings of this study suggest that enterprises should put knowledge application and knowledge sharing on equal grounds to increase team performance.

6.2 Limitations

This study is not without limitations. First, although the results of the Harman’s single factor test showed CMV not to be a potential problem in our study, the independent and dependent variables of this study were, in fact, drawn from the same respondents. In the future, to avoid the risk of common method variance, data should be collected from different sources or during different time slots. Second, this study sample is made up of student teams. However, past research has shown that organizational culture and norms have a significant impact on teamwork processes. Therefore, the results of this study should not be overgeneralized to include corporate teams. Third, this study does not measure how ISD teams’ collective knowledge efficacy, transactive memory systems, knowledge sharing, knowledge application, team creativity, and team performance change over time. All measures of these constructs were taken at a single point in time. Finally, although information technology (IT) was not included directly in the research model, we believe that IT can be used to support the forming of TMS or to enhance the knowledge management process within the ISD team.

Footnotes

Acknowledgments

The author is thankful to the Ministry of Science and Technology under the Grants NSC 100-2410-H-218-005 and NSC 101-2410-H-218-003.

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