Powerpoint with speaker notes

How organizations support distributed project teams

Key dimensions and their impact on decision making and teamwork effectiveness

Nathalie Drouin Management and technology, ESG UQAM, Montreal, Quebec, Canada, and

Mario Bourgault Department of Mathematics and Industrial Engineering,

Ecole Polytechnique de Montreal, Montreal, Canada

Abstract

Purpose – Work in distributed project teams is always a challenge for organizations. Many researchers have studies different aspects of distributed project teams, as witnessed by the impressive number of papers published in the last decade. However, it appears that the dimensions related to organizational support have still not received much attention in empirical studies. This study investigates the dimensions of organizational support in distributed project teams that contribute most to the quality of the decision-making process and teamwork effectiveness in distributed project teams. Design/methodology/approach – The initial intent of this research was to test a theoretical model on the basis of data from the field, namely real-life situations. A two-step approach (qualitative and quantitative method) was used. The research model was tested in a sample of experienced project managers on distributed project teams. Findings – The results suggest that strategic staffing and training and tools provided to team members have a positive impact on the quality of decision making and teamwork effectiveness. Team autonomy is more salient and influential in fostering decision quality in a highly culturally diverse context. Our findings also re-confirm the link between the quality of decision making and team effectiveness. Thus, teams are perceived as vehicles for identifying and integrating various individual viewpoints and combining knowledge. Practical implications – This study underscores the importance of selecting practices that enhance the recognition of team members’ contributions in the context of distributed project teams. It is now clear that managers cannot treat these distributed project teams in the same way as conventional teams. Several intervention and support methods are possible. This research contributes to identifying which of them are the most appropriate in this context. Originality/value – This study contributes to research on distributed project teams and on organizational support theory. It highlights the importance of understanding the processes or dimensions underlying the consequences of perceived organizational support. It bolsters the need to select practices that enhance the recognition of team members’ contributions and treat them favourably in the context of distributed project teams.

Keywords Decision making, Distributed project teams, Organizational support, Teamwork effectiveness

Paper type Research paper

1. Introduction In the last decade, researchers have studied many different aspects of distributed project teams (Bourgault et al., 2008; Cramton and Webber, 2005; Gibson and Cohen,

The current issue and full text archive of this journal is available at www.emeraldinsight.com/0262-1711.htm

Journal of Management Development Vol. 32 No. 8, 2013

pp. 865-885 r Emerald Group Publishing Limited

0262-1711 DOI 10.1108/JMD-07-2012-0091

The authors wish to thank Mrs Margaret McKyes for her very helpful comments during the various stages of this paper.

865

Distributed project teams

2003; Lipnack and Stamps, 1997; Mortensen and Hinds, 2001). As proposed by Martins et al. (2004), distributed or virtual project teams are defined as:

[...] teams whose members use technology to varying degrees in working across locational, temporal, and relational boundaries to accomplish an interdependent task ( p. 808).

Researchers often seek to identify antecedents that affect output variables, such as team effectiveness and viability (Martins et al., 2004; Peters and Manz, 2007). Among the input factors that have been investigated are formal processes and communication infrastructure as a means to reduce the potentially negative impact of distance (Duarte and Snyder, 2001; Fink, 2007). In addition, the recent development of communication technologies has led to explorations of how these technologies contribute to and impact distributed work practices (Pick et al., 2008; Yu et al., 2009). Other researchers have considered individual and interpersonal dimensions of teamwork as success factors. Interpersonal processes have been strongly correlated with distributed team performance and member satisfaction (De Dreu and Weingart, 2003; Raver and Gelfand, 2005). The influential role of communication in teamwork effectiveness has also been examined (Mathieu et al., 2008; Tesluk and Mathieu, 1999). For instance, Geister et al. (2006) found a positive effect of feedback on motivation, interpersonal trust, and performance in virtual (i.e. distributed) teams. Balthazard et al. (2004) investigated personality traits as a specific variable affecting virtual team performance, while Kirkman and Rosen (1999) and Kirkman et al. (2004) concluded that empowering virtual team members (i.e. giving them more responsibility and decision-making authority) is positively related to team performance. Furthermore, Bourgault and Drouin (2008) and Bourgault et al. (2008) highlighted the need to build trust throughout the project life cycle, develop a common vision, and obtain clear support from top management at all site locations.

Taken together, these results cover a wide range of explanatory factors. However, the dimensions related to organizational support have received relatively little attention in empirical studies. Bissoonauth (2002) raised this issue, but did not conduct an in-depth investigation. Earlier studies reported that distributed teams need the support of a strong organizational infrastructure (Mohrman et al., 1995; Sundstrom, 1999; Townsley, 2001). More recently, studies in real-life teams have found that organizational support, in terms of team empowerment, standardized processes, and attention paid to individual competencies, may positively impact distributed team formation and management (Bourgault et al., 2008; Zwikael, 2008; Drouin et al., 2010a).

The decision-making process has also been underinvestigated in distributed project teams. Yet project conduct is generally very sensitive to organizational decisions. Due to the temporary and specific nature of projects, decisions can be critical and irreversible. In today’s climate of technological and economic change, the decision- making process must be mastered for good project management. Nidiffer and Dolan (2005) explained the point view of practitioners and reported that:

The evolution toward distributed project management drives the need for improved processes, methods, and tools to input and share common data [y]. In our global economy, there’s a growing need to decrease the time it takes to make an informed decision, to improve the team’s decision velocity (p. 68).

The ability of a project team to take ownership for decisions that affect it is necessarily determined by the organizational environment in which it is situated (Hollenbeck et al., 1995). Far from being linear, decision making is a process that depends on a number of structural, environmental, and psychosocial factors, all of which can be difficult to grasp when projects are managed in uncertain or ambiguous environments.

866

JMD 32,8

The quality of a distributed team’s decision making could therefore provide a relevant measure of how it executes its mandates.

We explore these issues and attempt to identify the dimensions of organizational support that make the strongest contribution to the quality of the decision-making process and effective teamwork in distributed project teams. We begin by developing hypotheses about the dimensions of organizational support and their effects on the quality of decision making and effective teamwork. We then describe the research design and the data collection and hypothesis testing methods. The implications of our findings for practitioners and future research are then presented.

2. Background literature Drawing on organizational support theory (Eisenberger et al., 1986; Rhoades and Eisenberger, 2002) and the research on organizational support for distributed project teams (Drouin et al., 2010a; Mankin et al., 1996; Mathieu et al., 2008), we first consider the concept of organizational support.

Eisenberger et al. (1986) suggest that employees seek a balance in their social exchanges with organizations. That is, employees are committed to their organization insofar as they believe that the organization values and cares for them. The authors refer to these beliefs as “perceived organizational support” or POS, a term used in investigations of employee absenteeism and dedication to the organization (Shelton et al., 2010). POS has its roots in social exchange theory (Wayne et al., 1997), and stems from the norm of reciprocity: if one person does another a favour, there is a felt obligation to return the favour (Gouldner, 1960). Organizational support theory has been used to explain how employees personify the organization through social exchanges at work (Eisenberger et al., 1997). Levinson (1965) noted that actions taken by organizational agents are viewed as indications of the organization’s intent, and not the agents’ personal motives. This personification is abetted by the organization’s legal, moral, and financial responsibilities. In other words, organizational policies, norms, and culture provide continuity and prescribe role behaviours (Rhoades and Eisenberger, 2002). Rhoades and Eisenberger (2002) also conducted a meta-analysis and found that three main categories of beneficial treatment received by employees (fairness, supervisor support, and organizational rewards and favourable job conditions) were associated with POS. POS was in turn related to outcomes that were favourable to employees (e.g. job satisfaction, positive mood) and to the organization (e.g. affective commitment, performance, less withdrawal behaviour). These relationships depended on the psychological processes underlying the consequences of perceived organizational support. For instance, POS should produce a felt obligation by employees to care about the organization’s welfare and to help it achieve its objectives. POS should also strengthen employees’ beliefs that the organization recognizes and rewards performance. Shore and Shore (1995) noted that human resource practices such as recognition pay, promotions, autonomy, training, and recognition of employee contributions were positively related to POS. Rhoades and Eisenberger (2002) mentioned that:

[y] organizational support theory supposes that employees personify the organization, infer the extent to which the organization values their contribution and cares about their well-being, and reciprocate such perceived support with increased commitment, loyalty and performance (p. 711).

Organizational support theory thus underscores the need to understand and identify the processes and practices underlying the organizational support that team members perceive.

867

Distributed project teams

Drouin et al. (2010a) studied two international high-tech firms and identified certain forms of organizational support and their effects on components of distributed teams. They found that senior management can support distributed teams with human resources, resource allocation, coordination, and communication support. These types of support foster enhanced project coordination and monitoring, information exchange and access, trust building, and team cohesion. They are manifest when systems are implemented to support operational activities, with specific mechanisms for each activity. Previous studies had identified similar supports that impact team performance. For instance, coordination and communication support oversight coordination among teams and departments (Denison et al., 1996; Sundstrom et al., 1990) and facilitate access to the information that teams need to accomplish their tasks (Hall, 1998; Mohrman et al., 1995; Sundstrom et al., 1990; West, 2004). Performance support enhances team performance in terms of the corporate mission and objectives, as measured by performance and individual achievement of objectives (Denison et al., 1996; Mankin et al., 1996; Mohrman et al., 1995; West, 2004). Human resource support refers to staffing, training, and career development (Hackman and Oldham, 1980; Mankin et al., 1996; Sundstrom et al., 1990; West, 2004). Resource allocation ensures that teams have the knowledge, skills, and competencies they need to perform their roles and accomplish tasks (Sundstrom et al., 1990; West, 2004). Reward systems ensure that the team’s progress in achieving objectives is monitored (Hackman and Oldham, 1980), and technology support is used for distributing, implementing, and managing other support systems (Drouin et al., 2010a; Mankin et al., 1996; Mohrman et al., 1995).

A parallel can be drawn between organizational support as perceived by employees and team members and the organizational support that is provided to distributed project teams. In order to produce more effective teamwork and improved decision making, distributed team members must also perceive support as beneficial. However, some key aspects of organizational support have not yet been defined, especially for distributed project teams and based on concepts of organizational support theory (Bissoonauth, 2002; Eisenberger et al., 1986). In the next section, we provide an overview of these realities and develop a conceptual framework, and propose our hypotheses.

3. Conceptual model and hypothesis This study investigates the dimensions of organizational support in distributed project teams that would contribute to improved decision making and more effective teamwork. Based on organizational support theory and the research on distributed project teams, four dimensions were identified: Strategic Staffing, Training and Tools, Team Autonomy, and Top Management Monitoring. These dimensions of organizational support could impact decision-making quality and teamwork effectiveness in different terms (geographic dispersion; differences in culture, working practices, and experience) (see Figure 1). Below, we briefly discuss these concepts and develop our working hypotheses.

3.1 Dimensions of organizational support Strategic Staffing. Staffing is a key dimension of the resource allocation support system. Proper staffing ensures that teams have the knowledge, skills, and competencies to perform effectively their roles and accomplish tasks (Sundstrom et al., 1990; West, 2004). Related to staffing are individual attributes that shape the

868

JMD 32,8

distributed team and influence how it operates. Some studies (e.g. Shin, 2004) indicate that certain combinations of personal attributes (e.g. flexibility and communicative skills) equip individuals to perform more effectively in virtual teams. Katzenbach and Smith (1993) noted that technical expertise, problem solving and decision-making skills, and relational qualities are key attributes that enhance team performance. It is also recognized that teams with members who have experience in distance collaboration are deployed more rapidly. Thus, Harrison and Klein (2007) found that team success depends on the resources that are made available to the team through the qualities and attributes of the individual team members. Hertel et al. (2005) grouped the key attributes into three categories: taskwork-related attributes (conscientiousness and integrity), teamwork-related attributes (cooperation and communication skills), and telecooperation-related attributes (self-management, interpersonal trust, intercultural skills, and expertise in new media and groupware technology). Some authors add that team members should possess a minimum amount of agreeableness and conscientiousness in order to prevent conflicts (Furst et al., 2004; Zakaria et al., 2004), while Rhoades and Eisenberger (2002) argue that conscientiousness might lead to enhanced job performance, which in turn leads to enhanced treatment by the organization and heightened POS. Distributed team members are selected for their professional and technical knowledge and expertise. In a virtual team, individual attributes appear to make a key contribution to decision-making quality and team performance. Beyond professional know-how, the influence of individual attributes depends on the team’s degree of virtuality. In other words, individual characteristics become increasingly influential as the environment becomes more virtual (Drouin et al., 2010b). Leadership attributes are also considered input factors that influence team processes (coordination, creativity, knowledge sharing, empowerment, team commitment, and satisfaction) and teamwork effectiveness (Mathieu et al., 2008;

Strategic Staffing

H1

H4

H2

H3

H5

H7

H9Quality of decision making

process

Teamwork Effectiveness

H6

Contextual Variables (H10, H11, H12) Degree of dispersion, variety of cultures, variety of work practices, variety of experience

H8 Top

Management Monitoring

Training and Tools

Team Autonomy

Figure 1. Theoretical model

869

Distributed project teams

Srivastava et al., 2006). In addition, Eisenberger et al. (1997) found that perceived competence was related to task interest.

We propose that team members can be strategically selected to provide certain key competencies, and that through the team members’ perceptions of these key competencies, both decision making and team effectiveness would improve:

H1. Strategic Staffing is positively related to the quality of decision making in distributed teams.

H2. Strategic Staffing is positively related to teamwork effectiveness in distributed teams.

Training and Tools. Training is a key dimension of the human resource support system (Hackman and Oldham, 1980; Mankin et al., 1996; West, 2004). Wayne et al. (1997) suggest that job training is a discretionary practice that communicates an investment in the employee and increases POS. Hyatt and Ruddy (1997) found that organizational factors such as training and rewards systems had both direct and indirect effects on group effectiveness. Vakola and Wilson (2004) recommend that a training programme be developed for distributed team members so that they can acquire the knowledge and competencies they need to work effectively in virtual mode. Schweitzer (2005) contents that providing effective tools, budgets, and methods (e.g. hardware and software, laptops, high-speed internet access, cell phones) as well as training in working effectively in a distributed team (e.g. use of tools, time management, long-distance management) can impact team effectiveness. It is therefore assumed that Training and Tools provided to team members will have a positive effect on the quality of decision making and on teamwork effectiveness. We therefore propose the following hypotheses:

H3. Training and Tools are positively related to the quality of decision making in distributed teams.

H4. Training and Tools are positively related to teamwork effectiveness in distributed teams.

Team Autonomy. Rhoades and Eisenberger (2002) argued that high autonomy, or the organization’s trust that employees will make wise decisions about how to do their job, should increase perceived organizational support and consequently firm performance. Stewart (2006) also found that team autonomy and intrateam coordination corresponded with higher performance. Seibert et al. (2004) found that team empowerment influenced individual performance and job satisfaction. Mathieu et al. (2008) reviewed some of the “emergent states” (pp. 424-425) that have received much attention in the past decade, including team confidence, empowerment, team climate, cohesion, trust, shared mental models, and strategic consensus. Bourgault et al. (2008) identified team autonomy as a significant attribute of successful dispersed teams, regardless of the degree of distribution. We therefore propose the following hypotheses:

H5. Team Autonomy is positively related to the quality of decision making in distributed teams.

H6. Team Autonomy is positively related to teamwork effectiveness in distributed teams.

870

JMD 32,8

Top Management Monitoring. According to Simon (1994), top management can retain control through formal feedback systems used to monitor deviations from preset performance standards, by getting involved in subordinates’ decisions, by setting limits on empowerment, and by instilling belief systems that incorporate core values and culture. Mahaney and Lederer (2010) mentioned the following:

In project management, the purpose of monitoring is to collect three main classes of information about the progress of a project against a baseline and the anticipated outcome of the project. These classes include information that 1) assures managers that the project is progressing within acceptable budget, schedule, and quality expectations; 2) supports decisions to approve the movement of the project through its stages; and 3) confirms subjective assessments that benefits will be realised (p. 15).

Mahaney and Lederer (2010) further note that information about project progress (budget, schedule, quality) constitutes feedback to team members, which can increase their accountability and motivate them to perform more diligently. Nath et al. (2008) concluded that the effect of controls such as project monitoring on the quality of offshored projects needs further study. We therefore propose the following hypotheses:

H7. Top Management Monitoring is positively related to the quality of decision making in distributed teams.

H8. Top Management Monitoring is positively related to teamwork effectiveness in distributed teams

3.2 Quality of the decision-making process as an antecedent of effective teamwork Effective group decision making is an increasing concern for organizations, including decision making within projects (Brodbeck et al., 2007). Defining and understanding decision-making models is not an easy task (Pennings, 1985). Thanks to the seminal work of researchers such as Simon (1960) and March (1988), we can conceptualize the underlying decision-making processes and mechanisms. Bourgault et al. (2008), in their study of distributed teams, found strong support for the benefits of a good-quality decision-making process for distributed teamwork. Due to the numerous discontinuities that characterize such teams, an effective decision-making process is viewed as a way to surmount obstacles and produce successful outcomes. Compared to individual decision makers, groups have access to more information due to the individual knowledge of the constituent team members (Brodbeck et al., 2007; Hollenbeck et al., 1995). It is therefore assumed that, in project teams, the Quality of the Decision-Making Process is related to effective teamwork. We therefore formulated the following hypothesis:

H9. The Quality of the Decision-Making Process is positively related to teamwork effectiveness in distributed teams.

3.3 Effective teamwork Researchers have long examined various dimensions of effective teamwork in the field (e.g. Campion et al., 1993; Gladstein, 1984; Sundstrom et al., 1990). These dimensions relate to specific criteria such as productivity, team satisfaction, degree of task completion, and the accomplishment of project goals. In distributed teams, additional dimensions must be considered in order to assess the effectiveness of teamwork, such

871

Distributed project teams

as the quality of decision making, team commitment, and cohesion between team members (Martins et al., 2004; Maznevski and Chudoba, 2000). Staples and Webster (2007) developed a self-efficacy teamwork measure based on virtual team best practices obtained from the literature and from six case studies. In the present study, Teamwork Effectiveness refers to the team members’ perceptions of team performance in terms of task completion, goal achievement, information sharing, conflict resolution, problem solving, and the ability to create and sustain a good working environment. As proposed by Mathieu et al. (2008), the criteria for effective teamwork (e.g. productivity, team satisfaction, degree of task completion, and accomplishing project goals) should be appropriately related to the team’s function and tasks. The proposed metrics are suitable for the distributed teams under study, and have been previously used by Bourgault et al. (2008).

3.4 Contextual variables that potentially affect the main relationships in the model Studies have shown the effects of contextual variables, such as the degree of distribution, cultural differences, differing work practices, and experience, on various aspects of project management and teamwork. For instance, Hoegl et al. (2007) argue that teamwork affects team performance more strongly as members become increasingly distributed. This is because high-quality teamwork can leverage the increased knowledge potential of distributed teams, and team members in more distributed teams have little possibility of compensating for low-quality teamwork through hands-on leadership. Thus, geographic proximity affects team processes and performance. Another contextual factor that affects the effectiveness of teamwork and the quality of decision making in distributed teams is the appropriate management of cultural and functional diversity among team members (Zakaria et al., 2004). Culturally diverse teams may have difficulty building trust, and extra time may be needed for such teams to work and communicate effectively (Corbitt et al., 2004). In addition, complex and interdependent tasks require synchronicity, communication, and coordination among team members, as each member plays a part in the overall team functioning. Moreover, when members of a distributed team come from different organizations, diverse work practices could impact the nature and intensity of interactions, communications, and operations (Drouin et al., 2010b). Harrison and Klein (2007) found that if the diversity attribute (e.g. different work practices or values) is vital for the completion of team tasks, then the team may bifurcate into two clusters or cliques, with few or no team members bridging the gap. This kind of behaviour may impede teamwork effectiveness and the quality of decision making. A variety of experience among team members broadens a team’s cognitive and behavioural repertoire (Harrison and Klein, 2007). Teams with a range of knowledge, functional background, or experience can make more effective decisions and deliver more creative products ( Jackson et al., 1995).

Thus, contextual variables may influence the impact of certain explanatory dimensions on outcome variables. We therefore formulated a final group of hypotheses:

H10. The context in which a distributed team operates (degree of distribution, variety of cultures, variety of work practices, variety of experience) moderates the power of organizational support to explain the Quality of the Decision- Making Process.

872

JMD 32,8

H11. The context in which a distributed team operates (degree of distribution, variety of cultures, variety of work practices, variety of experience) moderates the power of organizational support to explain Teamwork Effectiveness.

H12. The context in which a distributed team operates (degree of distribution, variety of cultures, variety of work practices, variety of experience) moderates the power of the decision-making process to explain Teamwork Effectiveness.

4. Methodology In this section we outline the empirical procedure we used to test our hypotheses. Our initial aim was to test a theoretical model based on field data, or real-life situations. Methodologically speaking, the objective was to build on empirical studies conducted by practitioners rather than to repeat the approach of earlier studies, most of which have been limited to experiments in academic settings.

4.1 Measuring instrument and data collection The empirical work was conducted in several steps. At the outset of the project, we carried out several field studies (i.e. case studies) with the aim of gaining an in-depth understanding of the dimensions of organizational support for distributed teams. Our initial sample was highly diversified. For example, it included a multinational firm whose employees routinely work with colleagues around the world. It also included small- and medium-size companies that partake in international projects on an ad hoc basis. In this first step, we met with 13 project managers from ten different companies to discuss their positions and responsibilities and inquire about the issues and challenges they face when working with faraway colleagues and partners. The objectives were to gain as much information as possible and to identify the dimensions involved in managing distributed project teams, such as organizational support (see Bourgault et al., 2009 for more details). We then added case studies that addressed a single activity sector in order to limit interorganizational differences. Two Canadian-based international high-tech companies were selected. Care was taken to select firms with experience in managing distributed project teams. Data were collected in Canada over a six-month period, using a combination of in-depth interviews and archival research to enhance accuracy. In-depth interviews were conducted with nine managers who had experience in distributed project team management, using a pretested interview guide. Each interview lasted from two to four hours and was conducted in French (for more details see Drouin et al., 2010a).

Based on the literature review and case studies, we developed a questionnaire as a measurement instrument. We opted for a customized web questionnaire, with the assistance of an expert programmer. The questionnaire was repeatedly reviewed by the research team and pretested by ten representative respondents from our sample (practising professionals). We then corrected certain interpretation errors, primarily related to the translation of the questionnaire (which was available in two languages: French and English).

Data were collected over a six-month period from project management practitioners who had experience with distributed teams. To identify potential respondents, we worked together with the local chapter of the Project Management Institute, an organization for project management professionals. With their support, invitations were emailed to 1,000 managers. Of this number, we obtained a total of 149 completed and usable questionnaires. The usable sample comprised a diversity of project

873

Distributed project teams

manager and project profiles. The average project duration, project budget, and number of team members was, respectively, 16.5 months, C$42.2 million, and 24.5 members. All respondents had experience working with distributed project teams. Although the amount of experience varied, the sample appeared highly suitable to test our hypotheses.

We primarily targeted the team manager, who was assumed to have the best overview of the project. In many cases, however, other influential project actors responded to the questionnaire. Respondents were asked to classify themselves into one of three main roles: project management oversight, administrative support for the project team, or technical expertise. Of the 149 completed usable questionnaires, these roles accounted for 60, 25, and 15 per cent of respondents, respectively.

We are aware of the limitations of using a single responder per team. To control for a potential bias effect of the respondent’s role, we began by running a means test (Kruskall-Wallis, 5 per cent confidence coefficient) on all items to detect between-group differences for the three main roles. Of the 41 items (variables) considered in the analysis, a significant difference was found for only five items. We therefore concluded that the role bias was insufficient to affect the analysis results.

4.2 Data analysis The model in Figure 1 (12 hypotheses) was validated using structural equation models that are frequently used in similar studies (e.g. Isik et al., 2009; Mom et al., 2007; Chen et al., 2006). Models were run using SPSS 11.0 for Windows and EQS 6.1 for Windows. All analyses are presented in detail in appendices A, B, C, and D. We performed an initial principal components analysis (PCA) to aggregate the measures into factors that were correctly interpretable and coherent with the studied concepts (cut-off level of 0.5 for each loading). A confirmatory factor analysis (CFA) was also performed to verify the convergent and discriminant validity of the dimensions obtained (Hair et al., 1998). Three groups of factors were used in this model, with the same procedure repeated three times.

For the first group of factors (explanatory variables in the model), the PCA generated four clearly defined factors based on a number of questionnaire items. The factor Strategic Staffing is composed of four items (Cronbach’s a¼0.69 and variance¼20.1 per cent). It represents the team’s competency as well as the team leader’s authority and leadership. These characteristics are presumed to depend largely on the management’s role in staffing the team. The factor Training and Tools is composed of two items (Cronbach’s a¼0.60 and variance¼15.94 per cent). It represents the organization’s support in terms of preparing teams well and providing them with the tools they need to function in distributed mode. The factors Team Autonomy and Top Management Monitoring include two items each (Cronbach’s a¼0.71 and 0.73 and variance¼15.73 and 16.63 per cent, respectively). Here, autonomy refers to the team’s ability to make decisions about the way it functions and how the project budget is used. The final factor represents management’s presence in the project, both in the upstream phases (requirements specification) and during project conduct (monitoring). The unidimensionality and convergent validity of the factors were verified by CFA. According to the statistics provided by the model, the dimensions demonstrate strong convergent validity (w2¼ 24.589; p¼0.372; df¼23; w2/df¼1.069; GFI¼0.959; IFI¼0.994; CFI¼0.993; RMSEA¼0.025).

The same procedure was applied to the model’s two other principal dimensions Quality of the Decision-Making Process and Team Effectiveness. Quality of the

874

JMD 32,8

Decision-Making Process refers to elements such as the assessment of different alternatives or options, time constraints (i.e. decisions were made within a reasonable timeframe), team cooperation and consensual support for decisions, and variations and changes in final decisions (i.e. once made, decisions did not usually change) (Bourgault et al., 2008). We used a two-item construct established by PCA (Cronbach’s a¼0.87 and variance¼28.8 per cent) to measure whether the team was making decisions based on good practices (i.e. after collecting sufficient information and considering all possible options). Team Effectiveness refers to the team members’ perceptions of activities such as setting common objectives, planning and organizing tasks, holding meetings, sharing information, resolving problems, and creating and sustaining a good working environment (Bourgault et al., 2008). The effectiveness of the team’s work was therefore assessed with a six-item measure (Cronbach’s a¼0.92, variance¼46.87 per cent) to determine the quality of traditional team tasks such as planning and organization of activities, appropriate distribution of information, problem solving and conflict resolution, and tracking and assessing task performance. The unidimensionality and convergent validity of these measures were verified in the same way as for the first group of factors (w2¼17.593; p¼0.348; df¼16; w2/df¼1.100; GFI¼0.966; IFI¼0.998; CFI¼0.998; RMSEA¼0.029).

We also identified four contextual variables in the same way as described above. The variety of work methods measures within-team differences with respect to key functional factors such as task-related education and technical competencies the ways in which decisions are made and conflicts resolved (Cronbach’s a¼0.84, variance¼33.05 per cent). Our measure of cultural diversity captures the different nationalities and working languages within the team (Cronbach’s a¼0.75 and variance¼17.20 per cent). The measure of geographic distribution is a special case, because, as several authors have suggested, it can be measured in numerous ways (O’Leary and Cummings, 2007). We sought to establish an index that would capture the maximum variance in three respects: number of sites where the team is distributed, number of time zones between team members, and average distance between team members and the project leader.

The global distributedness index (GDI), proposed in Bourgault et al. (2008), is calculated as shown in Figure 2. Overall, this index provided the necessary variance for subsequent analysis (minimum¼2.00; maximum¼31.24). Once the variables of the model were established, we attempted to verify our hypotheses, as described in the next section.

5. Results In this section, we present the results of the statistical analyses performed on the overall sample, as recommended by Joreskog and Sorbom (1993). We first analysed the behaviour of our variables based on the overall model (Model 1, Table I) without distinguishing the contextual variables (control variables). As presented in Table I, the overall model shows good explanatory power for both Quality of the Decision-Making

Where NS is the number of sites; NZ the number of time zones between the most distant team members; AD the average distance between all team members and the project manager’s site (log)

GDI = NS + NZ + Log(AD)

Figure 2. Global distributedness

index

875

Distributed project teams

Process (R2¼26.38 per cent) and Team Effectiveness (R2¼65.66 per cent). This means that the dimensions related to organizational support explain the variables in question well. Two explanatory variables stand out: Strategic Staffing (0.341 and 0.396) and Training and Tools (0.254 and 0.160).

In sum, these results confirm earlier studies that emphasized the importance of competent, carefully created teams to perform distributed teamwork. This type of team selection appears to impact Team Effectiveness more than all other aspects of organizational support considered in our study. The organization plays a major and visible role in the selection process: assigning people with appropriate profiles to distributed teams. In addition to the right people, organizations must provide teams with the necessary technical support, which wield a direct and highly significant effect on Team Effectiveness and decision making (high and significant b’s). We also note the strong explanatory power of Quality of the Decision-Making Process (QDMP) on Team Effectiveness (TE), as predicted, according to Bourgault et al. (2008).

The dimensions Top Management Monitoring (TMM) and Team Autonomy (TA) show much lower (negligible) explanatory power in our model. Nevertheless, TMM and TA are not devoid of interest, as shown by the discriminant (intergroup) analyses presented below.

We next verified the effect of the contextual variables on the relationships in the initial model (Tables II and III). All the hypotheses addressing the moderating effects (H10, H11, H12) were tested. Thus, we reran the analyses on subsamples defined by the median for the control variable (Byrne, 1994): submodels 2A and 2B (effect of distribution), 3A and 3B (effect of cultural differences), 4A and 4B (effect of different working methods), and 5A and 5B (effect of different experience).

The results presented in Table II suggest that distribution has a strong influence when the explanatory power of Strategic Staffing (SS) on Quality of Decision-Making Process (QDMP) is considered (see Models 2A and 2B). Given that other variables play a role in the model, it appears that this dimension becomes more influential with increasing team distribution. Although this dimension has a different effect on Team Effectiveness (TE), the influence does not differ with the level of distribution (high and significant b’s, but no difference across subgroups). The same holds true for the impact of Training and Tools (TT), which was significant in the first model: it is unaffected by distribution.

Table II shows the results of the effect of cultural differences on distributed teams (see Models 3A and 3B). TT is influential in teams with major cultural differences (b¼0.377). Training and Tools support would most probably mitigate interpretation and communication problems in such cases. Similarly, TA shows a significantly higher

b R2

H1 Strategic Staffing (SS)-Quality of DMP (QDMP) 0.341**** 26.38 H3 Training and Tools (TT) - Quality of DMP (QDMP) 0.254*** H5 Team Autonomy (TA) - Quality of DMP (QDMP) 0.053ns

H7 Top Management Monitoring (TMM) - Quality of DMP (QDMP) 0.092ns

H2 Strategic Staffing (SS) - Teamwork Effectiveness (TE) 0.396 **** 65.66 H4 Training and Tools (TT) - Teamwork Effectiveness (TE) 0.160*** H6 Team Autonomy (TA) - Teamwork Effectiveness (TE) 0.075* H8 Top Management Monitoring (TMM) - Teamwork Effectiveness (TE) – 0.085* H9 Quality of DMP (QDMP) - Teamwork Effectiveness (TE) 0.470****

Table I. Statistics for initial structural model (Model 1)

876

JMD 32,8

M o d

el 2 A

: N

o t

v er

y d

is tr

ib u

te d

M o d

el 2 B

: V

er y

d is

tr ib

u te

d p

/2 M

o d

el 3 A

: F

ew cu

lt u

ra l

d if

fe re

n ce

s M

o d

el 3 B

: L

a rg

e cu

lt u

ra l

d if

fe re

n ce

s p

/2

H 1

S S -

Q D

M P

0 .1

4 9

0 .4

4 5

* * * *

0 .0

7 7 0

0 .3

2 3 * *

0 .3

8 5 * * * *

0 .2

7 3 5

H 3

T T -

Q D

M P

0 .3

2 1 * *

0 .2

4 5 * *

0 .4

0 7 0

0 .1

7 3

0 .3

7 7

* * * *

0 .0

8 6 5

H 5

T A

- Q

D M

P 0 .0

7 7

0 .0

5 1

0 .4

4 1 0

– 0 .0

7 5

n s

0 .1

8 1

* *

0 .0

6 2 5

H 7

T M

M -

Q D

M P

0 .0

7 6

0 .0

4 6

0 .4

4 2 5

0 .0

9 9

0 .0

3 4

0 .3

6 2 0

H 2

S S -

T E

0 .3

6 4 * * * *

0 .4

0 0 * * * *

0 .3

6 6 0

0 .3

1 6 * * * *

0 .3

7 6 * * * *

0 .3

7 6 5

H 4

T T -

T E

0 .1

5 4 *

0 .1

5 2 * *

0 .4

8 6 0

0 .1

9 9 * *

0 .1

4 3 *

0 .3

1 3 0

H 6

T A

- T

E 0 .0

3 9

0 .0

9 5

0 .3

5 7 5

0 .0

2 4

0 .1

5 9 * *

0 .1

2 7 0

H 8

T M

M -

T E

– 0 .1

7 8

* *

0 .0

3 3

0 .0

4 4 0

– 0 .0

0 4

– 0 .1

3 3 *

0 .1

5 9 0

H 9

Q D

M P -

T E

0 .5

4 4

* * * *

0 .4

0 9

* * * *

0 .0

7 3 0

0 .5

8 3

* * * *

0 .4

3 3

* * * *

0 .0

3 8 5

Table II. Statistics for structural models with contextual

variables (I)

877

Distributed project teams

effect on highly culturally diverse teams than on more homogeneous teams (0.181 vs –0.075).

Finally, the explanatory power of QDMP on TE is informative. The results differ significantly across subgroups for both control variables (dispersion and cultural differences), indicating a lower explanatory power of QDMP for TE. The difference is small but significant, and may be explained by the greater explanatory power of the other variables in the model, among others.

We now turn to the impact of the two other contextual variables (Table III) intrateam differences in work methods (Models 4A and 4B) and common experience with teamwork (Models 5A and 5B). Contrary to expectation, differences in work methods, which are frequently mentioned in the literature on distributed teams, have only a moderate impact on the relationships in our model. Only the (QDMP-TE) relationship is influenced by this factor. QDMP therefore becomes a preponderant factor in explaining team success with large intrateam differences (b¼0.570) relative to the other dimensions of the model. The differences between subgroups are more significant when the impact of intrateam differences in experience is considered. Significant differences are found for five of the nine relationships studied.

As with all the subgroups with marked differences in degree of distribution, SS plays a greater role in explaining QDMP with increasing intrateam differences in teamwork experience. This is attributable to the fact that TA does not have a significant impact on the same variable in the subgroup with the greatest difference in experience (b¼–0.072). Thus, SS is more influential when a team contains large differences in experience. SS appears to act as a compensatory mechanism, showing greater intensity in teams with greater than less marked differences in experience. TT shows a similar effect on TE. The greater the difference in team members’ experience, the greater the explanatory power of TT for Team Effectiveness. Note that the explanatory power of TT for QDMP remains considerable and significant in all subgroups, even though the difference between subgroups is not significant (b¼0.221, 0.252, 0.257 and 0.248).

Finally, it is noteworthy that the TMM dimension is not significant in any of the models. In fact, when b is significant, it is usually negative (models 1, 2A, 3B, 4B, and 5B). This result is counterintuitive. We initially assumed that management’s involvement in monitoring projects would be useful for projects that were highly distributed, whether geographically, culturally, or in other senses. But the reverse

Model 4A: Few differences

in work methods

Model 4B: Large

differences in work methods p/2

Model 5A: Few

differences in experience

Model 5B: Large

differences in experience p/2

SS - QDMP 0.429**** 0.255** 0.1185 0.236 ** 0.462**** 0.0545 TT - QDMP 0.221** 0.252** 0.3545 0.257** 0.248** 0.4650 TA - QDMP 0.166* –0.048 0.1210 0.163* �0.072ns 0.0790 TMM - QDMP 0.188** 0.056 0.2690 0.122 0.090 0.4970 SS - TE 0.521**** 0.361**** 0.1015 0.550**** 0.244*** 0.0345 TT - TE 0.220*** 0.133* 0.3470 0.054 0.219*** 0.0655 TA - TE 0.189** 0.055 0.1950 0.049 0.129** 0.2660 TMM - TE 0.003 �0.109* 0.1455 �0.002 �0.157 ** 0.0565 QDMP - TE 0.184** 0.570**** 0.0015 0.413**** 0.543**** 0.1235

Table III. Statistics for structural models with contextual variables (II)

878

JMD 32,8

appears to be true. This issue should be examined in more depth. In sum, we found empirical support for hypotheses H1, H2, H3, H4, H9, H10, H11, and H12. H5, H6, H7, and H8 were not supported.

6. Conclusion The aim of this study was to investigate four dimensions of organizational support that are related to superior decision-making quality and teamwork effectiveness in distributed project teams. Four main findings emerged.

First, strategic staffing is significantly associated with the quality of decision making and teamwork effectiveness. Strategic staffing is therefore a key dimension of organizational support that positively impacts distributed project team success. To conduct a successful distributed project, individuals with key attributes must be assigned to the team in order to enhance the quality of the team’s decision-making process and its performance. As working environments become increasingly distributed, strategic staffing should become increasingly vital, particularly for the quality of decision making. These results are in line with previous findings by Drouin et al. (2010b), who found that the influence of individual team member characteristics depends on the team’s degree of virtuality. However, our results underscore that, for highly distributed teams, strategic staffing makes a greater contribution to the quality of decision making than to teamwork effectiveness. This supports the contentions of Clark and Stephenson (1989) and Hollenbeck et al. (1995), who view the team as a vehicle for combining and integrating a variety of knowledge, ideas, attributes, and perspectives in order to produce high-quality decisions. Compared to individual decision makers, groups have access to more information due to the wider range of knowledge contributed by the members.

Second, training and tools also constitute a key dimension of organizational support that positively impacts both teamwork effectiveness and the quality of decision making. These findings are consistent with studies that underscored the need to develop a training programme so that individuals can acquire the necessary competencies to work effectively in a virtual context (Duarte and Snyder, 2001; Mankin et al., 1996; Vakola and Wilson, 2004). Furthermore, by providing training, the organization demonstrates its recognition of employees’ contributions. This perceived organizational support (POS) has a constructive influence on teamwork effectiveness and the quality of decision making (Shore and Shore, 1995). Consistent with Schweitzer’s (2005) findings, we confirmed our hypothesis that providing effective tools and methods to distributed teams has a positive impact on teamwork effectiveness. Our results also underscore the importance of providing training and adequate tools to team members to enhance the quality of decisions in teams with wide cultural differences. Zakaria et al. (2004) also argued the need to manage cultural and functional diversities within virtual teams. Thus, training and tools constitute a dimension of organizational support that helps mitigate the impact of cultural diversity on team effectiveness and the quality of decision making.

Third, Bourgault et al. (2008) found that team autonomy is a critical dimension, regardless of the degree of distribution. In the present study, we found more specifically that team autonomy may be more salient and influential on the quality of decision making in a highly culturally diverse team. Our findings also support the association between the quality of decision making and team effectiveness, particularly in a highly distributed and culturally diversified context. Teams are perceived as vehicles for identifying and integrating individual viewpoints,

879

Distributed project teams

knowledge, and backgrounds. It is therefore proposed that if the organization adequately equips and supports distributed project teams, they will be in a position to make decisions and conduct their work effectively.

This study contributes to the research on distributed project teams and on organizational support theory. The need to understand the dimensions that underlie the consequences of perceived organizational support (Rhoades and Eisenberger, 2002) is underscored. This conclusion is in line with competency-based management research (Draganidis and Mentzas, 2006), as it addresses the key knowledge that managers at the organizational level should possess in order to support both the quality of decision making and teamwork effectiveness in distributed project teams. According to recent research in competency-based management, this type of organizational support is directly related to personnel development plans (Draganidis and Mentzas, 2006; Beck, 2003), insofar as it involves dimensions such as strategic staffing, training and tools, team autonomy, and top management monitoring. Our findings confirm the need to implement practices designed to increase the recognition of team members’ contributions (e.g. provide team autonomy) and treat them favourably (e.g. provide training and tools) in order to conduct successful distributed projects. Team members perceive such practices as beneficial treatment by top management. Consequently, decision-making quality improves and teamwork becomes more effective.

7. Limitations This study has certain limitations: it examined firms and respondents based in North America, and therefore the results may not be transferable to other cultures, including European and Asian. Further research in other countries with multiple respondents per team is recommended to deepen our understanding of the influence of country on the investigated relationships. Similarly, firms from different industries may show different relationships between variables. Future studies could also consider additional dimensions of organizational support, such as recognition pay and promotions, job security, and organization size, as proposed by authors such as Rhoades and Eisenberger (2002) and Shore and Shore (1995).

Much remains to be explored in terms of how corporate management can optimally support the work of distributed teams. However, it appears clear that managers cannot treat these teams in the same way as conventional teams. Several intervention and support methods show promise, and we believe that further studies in this area can contribute to identify the most appropriate applications for distributed teamwork.

References

Balthazard, P., Potter, R.E. and Warren, J. (2004), “Expertise, extraversion and group interaction style as performance indicators in virtual teams”, Advances in Information Systems, Vol. 35 No. 1, pp. 42-64.

Beck, S. (2003), “Skill and competence management as a base of an integrated personnel development (IPD)- a pilot project in the Putzmeister, Inc/Germany”, Journal of Universal Computer Science, Vol. 9 No. 12, pp. 1381-1387.

Bissoonauth, B. (2002), “Virtual project work: investigating critical success factors of virtual project performance”, master’s thesis, The John Molson School of Business, Concordia University, Montreal.

880

JMD 32,8

Bourgault, M. and Drouin, N. (2008), How’s Your Distributed Team Doing? Ten Suggestions from the Field, Project Management Institute, Upper Darby, PA.

Bourgault, M., Drouin, N. and Hamel, E. (2008), “Decision-making within distributed project teams: an exploration of formalization and autonomy as determinants of success”, Project Management Journal, Vol. 39 Nos S97-S110, pp. 97-110.

Bourgault, M., Drouin, N., Daoudi, J. and Hamel, E. (2009), Understanding Decision-Making within Distributed Project Teams, PMI Publications, Upper Darby, PA, p. 109.

Brodbeck, F.C., Kerschreiter, R., Mojzisch, A. and Schulz-Hard, S. (2007), “Group decision making under conditions of distributed knowledge: the information asymmetries model”, The Academy of Management Review, Vol. 32 No. 2, pp. 459-479.

Byrne, B. (1994), Structural Equation Modelling with EQS and EQS Windows, Sage, Thousand Oaks, CA.

Campion, M.A., Medsker, G.J. and Higgs, A.C. (1993), “Relations between work group characteristics and effectiveness: implications for designing effective work groups”, Personnel Psychology, Vol. 46 No. 4, pp. 823-850.

Chen, G., Tjosvold, D. and Liu, C. (2006), “Cooperative goals, leader people and productivity values: their contribution to top management teams in China”, Journal of Management Studies, Vol. 43 No. 5, pp. 1177-1200.

Clark, N.K. and Stephenson, G.M. (1989), “Group remembering”, in Paulus, P. B. (Ed.), Psychology of Group Influence, Lawrence Erlbaum Associates, Hillsdale, NJ, pp. 357-391.

Corbitt, G., Gardiner, L.R. and Wright, L.K. (2004), “A comparison of team developmental stages, trust and performance for virtual versus face-to-face teams”, Proceedings of the 37th Hawaii International Conference on System Sciences, IEEE Computer Society, Hawaii, HI.

Cramton, C.D. and Webber, S.S. (2005), “Relationships among geographic dispersion, team processes, and effectiveness in software development work teams”, Journal of Business Research, Vol. 58 No. 6, pp. 758-765.

De Dreu, C.K.W. and Weingart, L.R. (2003), “Task versus relationship conflict: team performance, and team member satisfaction: A meta-analysis”, Journal of Applied Psychology, Vol. 88 No. 4, pp. 741-749.

Denison, D.R., Stuart, L.H. and Kahn, J.A. (1996), “From chimneys to cross-functional teams: developing and validating a diagnostic model”, Academy of Management Journal, Vol. 39 No. 4, pp. 1005-1023.

Draganidis, F. and Mentzas, G. (2006), “Competency based management: a review of systems and approaches”, Information Management & Computer Security, Vol. 14 No. 1, pp. 51-64.

Drouin, N., Bourgault, M. and Gervais, C. (2010a), “Effects of organizational support on components of virtual project teams”, International Journal of Managing Projects in Business, Vol. 3 No. 4, pp. 625-641.

Drouin, N., Bourgault, M. and Gervais, C. (2010b), “Managing virtual project teams: recent findings”, in Sherif, M.H. (Ed.), Handbook on Enterprise Integration, 3rd ed., Auerbach Publications, Boca Raton, FL.

Duarte, D.L. and Snyder, N.T. (2001), Mastering Virtual Teams: Strategies, Tools and Techniques That Succeed, 2nd ed., Jossey-Bass, San Francisco, CA.

Eisenberger, R., Cummings, J., Armeli, S. and Lynch, P. (1997), “Perceived organizational support, discretionary treatment, and job satisfaction”, Journal of Applied Psychology, Vol. 82 No. 5, pp. 812-830.

Eisenberger, R., Huntington, R., Hutchison, S. and Sowa, D. (1986), “Perceived organizational support”, Journal of Applied Psychology, Vol. 71, pp. 500-507.

881

Distributed project teams

Fink, L. (2007), “Coordination, learning, and innovation: the organizational roles of e-collaboration and their impacts”, International Journal of e-Collaboration, Vol. 3 No. 3, pp. 53-70.

Furst, S.A., Reeves, M., Rosen, B. and Blackburn, R.S. (2004), “Managing the life cycle of virtual teams”, Academy of Management Executive, Vol. 18 No. 2, pp. 6-20.

Geister, S., Konradt, U. and Hertel, G. (2006), “Effects of process feedback on motivation, satisfaction, and performance in virtual teams”, Small Group Research, Vol. 37 No. 5, pp. 459-489.

Gibson, C.B. and Cohen, S.G. (2003), Virtual Teams That Work: Creating Conditions for Virtual Team Effectiveness, John Wiley & Sons, San Francisco, CA.

Gladstein, D. (1984), “Groups in context: a model of task group effectiveness”, Administrative Science Quarterly, Vol. 29 No. 4, pp. 499-517.

Gouldner, A.W. (1960), “The norm of reciprocity: a preliminary statement”, American Sociological Review, Vol. 25 No. 2, pp. 161-178.

Hackman, J.R. and Oldham, G.R. (1980), Work Redesign, Addison-Wesley, Reading, MA.

Hair, J.F Jr, Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, 5th ed., Prentice Hall, Upper Saddle River, NJ.

Hall, C.A. (1998), “Organizational support systems for team-based organizations: employee collaboration through organizational structures”, doctoral thesis, University of North Texas, Denton, TX.

Harrison, D. and Klein, K. (2007), “What’s the difference? Diversity constructs as separation, variety, or disparity in organizations”, Academy of Management Review, Vol. 32 No. 4, pp. 1199-1228.

Hertel, G., Geister, S. and Konradt, U. (2005), “Managing virtual teams: a review of current empirical research”, Human Resource Management Review, Vol. 15 No. 1, pp. 69-95.

Hoegl, M., Ernst, H. and Porserpio, L. (2007), “How teamwork matters more as team member dispersion increases”, Journal of Product Innovation Management, Vol. 24 No. 2, pp. 156-165.

Hollenbeck, J.R., Ilgen, D.R., Tuttle, D.B. and Sego, D.J. (1995), “Team performance on monitoring tasks: an examination of decision errors in contexts requiring sustained attention”, Journal of Applied Psychology, Vol. 80 No. 6, pp. 685-696.

Hyatt, D.E. and Ruddy, T.M. (1997), “An examination of the relationship between work group characteristics and performance: once more into the breach”, Personnel Psychology, Vol. 50 No. 3, pp. 553-585.

Isik, Z., Arditi, D., Dikmen, I. and Birgonul, M.T. (2009), “Impact of corporate strengths/ weaknesses on project management competencies”, International Journal of Project Management, Vol. 27 No. 6, pp. 629-637.

Jackson, S.E., May, K.E. and Whitney, K. (1995), “Understanding the dynamics of diversity in decision-making teams”, in Guzzo, R.A. and Salas, E. (Eds), Team Effectiveness and Decision Making in Organizations, Jossey-Bass, San Francisco, CA, pp. 204-261.

Joreskog, K.G. and Sorbom, D. (1993), Lisrel 8 User’s Reference Guide (Chapter 4: Causal Models for Directly Observed Variables), Scientific Software International, Lincolnwood, IL.

Katzenbach, J.R. and Smith, D.K. (1993), The Wisdom of Teams: Creating the High Performance Organization, Harvard Business School Press, Boston, MA.

Kirkman, B.L. and Rosen, B. (1999), “Beyond self-management: antecedents and consequences of team empowerment”, Academy of Management Journal, Vol. 42 No. 1, pp. 58-74.

Kirkman, B.L., Rosen, B., Tesluk, P.E. and Gibson, C.B. (2004), “The impact of team empowerment on virtual team performance. The moderating role of face-to-face interaction”, Academy of Management Journal, Vol. 47 No. 2, pp. 175-192.

882

JMD 32,8

Levinson, H. (1965), “The relationship between man and organization”, Administrative Science Quarterly, Vol. 9 No. 4, pp. 370-390.

Lipnack, J. and Stamps, J. (1997), Virtual Teams: Reaching across Space, Time and Organizations with Technology, John Wiley & Sons, New York, NY.

Mahaney, R.C. and Lederer, A.L. (2010), “The role of monitoring and shirking in information systems project management”, International Project Management Journal, Vol. 28 No. 1, pp. 14-25.

Mankin, D., Cohen, S.G. and Bikson, T.K. (1996), Teams and Technology: Fulfilling the Promise of the New Organization, Harvard Business School Press, Cambridge, MA.

March, J.G. (1988), Decisions and Organization, Blackwell, London.

Martins, L.L., Gilson, G.L. and Maynard, M.T. (2004), “Virtual teams: what do we know and where do we go from here?”, Journal of Management, Vol. 30 No. 6, pp. 805-835.

Mathieu, J., Maynard, T.M., Rapp, T. and Gilson, L. (2008), “Team effectiveness 1997–2007: a review of recent advancements and a glimpse into the future”, Journal of Management, Vol. 34 No. 3, pp. 410-476.

Maznevski, M.L. and Chudoba, K.M. (2000), “Bridging space over time: global virtual team dynamics and effectiveness”, Organization Science, Vol. 11 No. 5, pp. 473-492.

Mohrman, S.A., Cohen, S.G. and Mohrman, A.M Jr (1995), Designing Team-Based Organizations: New Forms for Knowledge Work, Jossey-Bass, San Francisco, CA.

Mom, T.J.M., Van Den Bosch, F.A.J. and Volberda, H.W. (2007), “Investigating managers’ exploration and exploitation activities: the influence of top-down, bottom-up, and horizontal knowledge inflows”, Journal of Management Studies, Vol. 44 No. 6, pp. 910-931.

Mortensen, M. and Hinds, P.J. (2001), “Conflict and shared identity in geographically distributed teams”, International Journal of Conflict Management, Vol. 12 No. 3, pp. 212-238.

Nath, D., Sridhar, V. and Malik, A. (2008), “Project quality of off-shore virtual teams engaged in software requirements analysis: an exploratory comparative study”, Journal of Global Information Management, Vol. 16 No. 4, pp. 24-45.

Nidiffer, K.E. and Dolan, D. (2005), “Evolving distributed project management”, IEEE Software, Vol. 22 No. 5, pp. 63-72.

O’Leary, M. and Cummings, J.N. (2007), “The spatial, temporal, and configurational characteristics of geographic dispersion in work teams”, MIS Quarterly, Vol. 31 No. 3, pp. 433-452.

Pennings, J. (1985), Strategic Decision Making in Complex Organizations, Jossey-Bass Publishers, San Francisco, CA.

Peters, L.M. and Manz, C.C. (2007), “Identifying antecedents of virtual team collaboration”, Team Performance Management, Vol. 13 Nos 3/4, pp. 117-129.

Pick, J.M., Romano, N.C. and Roztocki, N. (2008), “Synthesizing the research advances in electronic collaboration: theoretical frameworks”, International Journal of e-Collaboration, Vol. 5 No. 1, pp. 1-12.

Raver, J.L. and Gelfand, M.J. (2005), “Beyond the individual victim: linking sexual harassment, team processes, and team performance”, Academy of Management Journal, Vol. 48 No. 3, pp. 387-400.

Rhoades, L. and Eisenberger, R. (2002), “Perceived organizational support: a review of the literature”, Journal of Applied Psychology, Vol. 87 No. 4, pp. 698-714.

883

Distributed project teams

Schweitzer, L. (2005), “Understanding virtual team effectiveness: an exploration”, doctoral thesis, Carleton University, Ottawa, ON.

Seibert, S.E., Silver, S.R. and Randolph, W.A. (2004), “Taking empowerment to the next level: a multiple-level model of empowerment, performance, and satisfaction”, Academy of Management Journal, Vol. 47 No. 3, pp. 332-349.

Shelton, P.M., Waite, A.M. and Makela, C.J. (2010), “Highly effective teams: a relational analysis of group potency and perceived organizational support”, Advances in Developing Human Resources, Vol. 12 No. 1, pp. 93-114.

Shin, Y. (2004), “A person-environment fit model for virtual organizations”, Journal of Management, Vol. 30 No. 5, pp. 725-743.

Shore, L.M. and Shore, T.H. (1995), “Perceived organizational support and organizational justice”, in Cropanzano, R. and Kacmar, K.M. (Eds), Organizational Politics, Justice and Support: Managing Social Climate at Work, Quorum Press, Westport, CT, pp. 149-164.

Simon, H.A. (1960), The New Science of Management Decision, Harper & Row, New York, NY.

Simon, R. (1994), “How new top managers use control systems as levers of strategic renewal”, Strategic Management Journal, Vol. 15 No. 3, pp. 169-189.

Srivastava, A., Bartol, K.M. and Locke, E.A. (2006), “Empowering leadership in management teams: effects on knowledge sharing, efficacy, and performance”, Academy of Management Journal, Vol. 49 No. 6, pp. 1239-1251.

Staples, D.S. and Webster, J. (2007), “Exploring traditional and virtual team members’ best practices. A social cognitive theory perspective”, Small Group Research, Vol. 38 No. 1, pp. 60-97.

Stewart, G.L. (2006), “A meta-analytic review of relationships between team design features and team performance”, Journal of Management, Vol. 32 No. 1, pp. 29-54.

Sundstrom, E. (1999), “The challenges of supporting work team effectiveness”, in Sundstrom, E. and Associates (Eds), Supporting Work Team Effectiveness, Jossey-Bass, San Francisco, CA.

Sundstrom, E., De Meuse, K.P. and Futrell, D. (1990), “Work teams: applications and effectiveness”, American Psychologist, Vol. 45 No. 2, pp. 120-133.

Tesluk, P.E. and Mathieu, J.E. (1999), “Overcoming roadblocks to effectiveness: incorporating management of performance barriers into models of work group effectiveness”, Journal of Applied Psychology, Vol. 84 No. 2, pp. 200-217.

Townsley, C. (2001), “Virtual teams: the relationship between organizational support systems and effectiveness”, master’s thesis, University of North Texas, Denton, TX.

Vakola, M. and Wilson, I. (2004), “The challenge of virtual organization: critical success factors in dealing with constant change”, Team Performance Management, Vol. 10 Nos 5/6, pp. 112-120.

Wayne, S., Shore, L. and Liden, R. (1997), “Perceived organizational support and leader-member exchange: a social exchange perspective”, Academy of Management Journal, Vol. 40 No. 1, pp. 82-111.

West, M.A. (2004), Effective Teamwork: Practical Lessons from Organizational Research, Blackwell Publishing, Oxford.

Yu, M.Y., Lang, K.R. and Kumar, N. (2009), “Internationalization of online professional communities: an empirical investigation of AIS-ISWorld”, International Journal of e-Collaboration, Vol. 5 No. 1, pp. 13-31.

884

JMD 32,8

Zakaria, N., Amelinckx, A. and Wilemon, D. (2004), “Working together apart? Building a knowledge-sharing culture for global virtual teams”, Creativity and Innovation Management, Vol. 13 No. 1, pp. 15-29.

Zwikael, O. (2008), “Top management involvement in project management: a cross country study of the software industry”, International Journal of Managing Projects in Business, Vol. 1 No. 4, pp. 498-511.

Corresponding author Nathalie Drouin ca be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

885

Distributed project teams

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Week 5 Assignment Resources/The relationship between leadership behaviors team learning.pdf