Collaborative IT Tools: Leveraging Competence in HFNs
This paper was presented to the faculty and students of the Naval Postgraduate School on February 15, 2007. Enhancing the effectiveness of hastily formed networks (HFNs) at the group level is a key goal for the HFN Center. By introducing the construct of "Collaborative IT Tools Leveraging Competence," the work of Pavlou and Dimoka has explored whether, how, and why collaborative IT technologies can support HFNs.
You can navigate through the entire paper using the menu to the left or the navigation controls that appear at the bottom of each page. Please feel free to comment using the "comment" links provided. Comments are encouraged and appreciated!
| Attachment | Size |
|---|---|
| HFN_Leveraging_Competence_of_Collaborative_IT_Tools_Pavlou-Housel-Dimoka.doc | 352.5 KB |
| Pavlou_Dimoka_Housel1.jpg | 32.16 KB |
Abstract
ABSTRACT
This research focuses on the role of collaborative Information Technology (IT) tools to enhance the effectiveness of Hastily Formed Networks (HFNs) at the group level. Collaborative IT tools are an integrated set of functionalities that enable collaboration among inter-connected entities. Despite their widely touted potential to enhance various types of planned and ad hoc networks (e.g., HFNs), we still know little about whether, how, and why these IT tools can support HFNs, especially in the information-intensive environments that characterize most Naval operations.
This paper first introduces the construct of ‘Collaborative IT Tools Leveraging Capability' as the ability of work groups to effectively leverage collaborative IT tools to enhance their group activities to support HFNs. Collaborative IT Tools Leveraging Capability is conceptualized as a second-order construct formed by the group's effective use of six key IT functionalities - workspace sharing, conferencing, file sharing, scheduling, chat, and email – that are commonly present in collaborative IT tools.
This study then examines ways to enhance the effectiveness of HFNs through the user's effective leveraging of collaborative IT tools by examining the following network performance outcomes - (a) HFN efficiency, (b) situational awareness of the HFN, (c) and HFN project effectiveness. The proposed effects of ‘Collaborative IT Tools Leveraging Capability' on HFN performance is hypothesized to be more pronounced in information intensive environments.
Finally, to enhance a group's ability to effectively leverage collaborative IT tools, the study proposes a set of enabling factors: customization of the collaborative IT tools, group habits in using collaborative IT tools, the group's perceived usefulness and ease of use of collaborative IT tools, the group member's mutual trust, and the degree of environmental intensity.
Data from 365 group managers support the proposed structural model with the nature, antecedents, and consequences of Collaborative IT Tools Leveraging Capability at different levels of environmental intensity. The paper discusses the study's contributions to our better understanding the nature of Collaborative IT Tools Leveraging Capability in the context of HFNs, its impact on HFN performance, and how it can be enhanced to facilitate HFN.
Authors
AUTHORS:
Dr. Paul A. Pavlou bio
University of California, Riverside
paul.pavlou@ucr.edu
Dr. Angelika Dimoka bio
University of California, Riverside
dimoka@ucr.edu
Dr. Thomas J. Housel bio
Naval Postgraduate School
tjhousel@nps.edu
Paul A. Pavlou is an Assistant Professor of Information Systems at the University of California at Riverside. He received his Ph.D. from the University of Southern California in 2004. His research focuses on online marketplaces and e-commerce, collaborative IT tools, and information systems strategy. His research has appeared in ISR, MISQ, and JAIS, among others. His work has been cited over 200 times by the Institute of Scientific Information and over 600 times by Google Scholar. Paul won the ‘Best Doctoral Dissertation Award' of the 2004 ICIS Conference. Paul also received the 2003 MISQ ‘Reviewer of the Year' award, and the ‘Best Reviewer' award of the 2005 Academy of Management Conference. He sits on the Editorial Board of MISQ and JAIS.
back
Angelika Dimoka is a Visiting Assistant Professor of Information Systems at the University of California at Riverside with a joint appointment at the School of Engineering. She received a Ph.D. from the University of Southern California in 2006. Her research focuses on the quantitative analysis of uncertainty in online marketplaces, the use of collaborative IT tools, and experimental neuroeconomics for understanding the use of IT in organizations and markets. Her research has been published in Information Systems Research and the Journal of Neuroscience Methods.
back
Introduction
Collaborative IT technologies facilitate the ability of HFNs to reconfigure existing, no longer effective resources into new, more effective competencies through information fusion. Denning (2006) indicated that the first priority in a turbulent context (e.g., crisis event) is to allow all affected and responding parties to pool their knowledge…, understand what resources are available, assess options, plan responses, decide, commit, act, and coordinate. (p. 16) Clearly these kinds of activities in the formation of HFNs could be facilitated through the use of collaborative IT tools. However, if the groups in the HFN are not competent in using these tools, the HFN may not be very effective.
Competence in using collaborative tools will also meet Denning's requirement for effective use of HFNs in that they will help groups coordinate their actions, share conversation space (p.16-17), even if they are in different geographic locations. Indeed, Denning's directive that groups must collaborate on action plans and coordinate their execution (p. 17) speaks volumes about the need for collaborative tools to facilitate the effectiveness of HFNs as well as competence among the users of these tools. Denning (2006) is even more explicit in stating the need for competent usage of such systems in his Guide to Effective HFNs Understand and practice the effective technologies for collaborative networks. These include Web servers to distribute information, wiki and discussion thread software, chat, and instant messaging services, virtual markets, and coordination services such as Groove [a popular collaborative tool suite]. (p. 19)
The basic definition of HFNs indicates the potential for use of collaborative tools. An HFN is a distributed social and organizational network that is formed and configured rapidly in response to environmental triggers (e.g., emergency situations) that have a limited life span. While other networks typically have a longer time horizon and mature slowly (and they can be enhanced through routine observation during their lifetime), HFNs must be prepared and designed before they are needed. Despite their limited life span, it is possible to observe the formation, maintenance, and dissolution of HFNs and identify best practices in how they can be effectively prepared, staffed, and executed. One such best practice may involve the use of collaborative tools to facilitate the requirements for effective HFNs enumerated by Denning (2006) previously.
There are numerous collaborative tool suites to choose from. Collaborative IT tools, such as UGS PLM Team Center suite, Groove, and Oracle Collaboration Suite are integrated sets of IT functionalities that enable communication and information sharing among inter-connected entities. In the current study, we selected the UGS Team Center collaborative suite because it had the richest set of capabilities to facilitate even the most sophisticated requirements (such as sharing of engineering drawings in a collapsed building) for an HFN.
By enabling collaboration to facilitate HFNs where it may not have been feasible before and improving existing collaborative work among groups, collaborative IT tools have the potential to transform the nature of collaborative group works, and they have thus sparked increased interest among academics and practitioners (e.g., Easley, Devaraj, and Crant, 2003). However, despite the widely publicized potential of collaborative IT tools to create value, we still know little about whether, how, and why these IT tools can create value by enhancing group performance, particularly in the turbulent environments that HFNs typically operate. Therefore, the first step in understanding how collaborative IT tools will facilitate the performance in groups via HFNs is to gain a basic understanding of how these tools can be leveraged through competent usage by HFNs.
To shed light on this issue, this study follows Pavlou and El Sawy (2006) proposed focus on the leveraging dimension of IT capability to introduce the notion of ‘Collaborative IT Tools Leveraging Competence.' This is defined as the ability of groups to effectively leverage the IT functionalities of collaborative IT tools to facilitate their group activities. Since collaborative IT tools can be viewed as generic information technologies whose IT functionalities cannot be differentiated across groups, the current study will enable differentiation of groups based on how well they leverage generic IT functionalities to create value for groups. Moreover, since collaborative IT tools are primarily used by groups to facilitate their group activities, the proposed construct is conceptualized at the process-level of analysis. This level of analysis was advocated by Ray, Muhanna, and Barney (2005) who argued that the process (not the firm) level of analysis was the most appropriate level for observing the value of IT.
A review of numerous commercial software packages identified the core IT functionalities that are commonly found in collaborative IT tools - workspace sharing, conferencing, file sharing, scheduling, chat, and email functionality. These functionalities are also common in UGS Teamcenter. Integrating these functionalities, Collaborative IT Tools Leveraging Competence (CITLC) is conceptualized as a formative second-order construct formed by the group's effective use of these six key functionalities.
To show the value of CITLC, we formally hypothesize its impact on HFN performance in terms of process efficiency, effectiveness, and situational awareness. The proposed value of leveraging group competence in using collaborative IT tools is hypothesized to be positively moderated by the degree of environmental uncertainty in which the HFN operates. Thus, environmental uncertainty is the surrogate for environments within which HFNs are most likely to operate.
Finally, the study identifies the key factors that enhance a group's CITLC. Extending the literature on the effective use of IT by groups, a set of antecedent variables is proposed, namely technology adoption variables (the group's perceived usefulness and ease of using collaborative IT tools), technology variables (customization of collaborative IT tools), social variables (the group member's mutual trust), post-adoption variables (the group's habit in using collaborative IT tools), and environmental variables (the degree of environmental uncertainty in which a group operates). To facilitate these HFN performance outcomes through the effective use of collaborative IT technologies, the proposed research has three goals:
1. Identify how to effectively facilitate group performance (process efficiency, project effectiveness, and situational awareness) to support HFNs.
2. Identify and prescribe the antecedent factors that enable the effective use of collaborative IT functionalities in HFNs.
3. Understand the role of collaborative IT competence in complex, data-rich, and information-intensive environments of HFNs.
Figure 1 summarizes the antecedents and consequences of Collaborative IT Tools Leveraging Competence in HFNs.
List of Figures and Tables
Figure 1: The Proposed Research Model
Figure 2: The Formative Second-Order Model of Collaborative IT Tools Leveraging Competence
Figure 3: The Proposed Formative Second-Order Model of Group Performance
Figure 4: The Formative Second-Order Model of Leveraging Competence of Collaborative IT Tools
Figure 5: The Formative Second-Order Model of Group Performance
Figure 6: PLS Results of Proposed Research Model
Table 1: Common IT Functionalities of Collaborative IT Tools
Table 2: Demographic Information
Table 3: Reliabilities, Correlation Matrix, and Average Variance Extracted
| Attachment | Size |
|---|---|
| ITTools_Fig_1.JPG | 55.26 KB |
| ITTools_Fig_2.JPG | 39.53 KB |
| ITTools_Fig_3.JPG | 28.96 KB |
| ITTools_Fig_4.JPG | 47.93 KB |
| ITTools_Fig_5.JPG | 29 KB |
| ITTools_Fig_6.JPG | 59.75 KB |
| ITTools_Tab_1.JPG | 83.86 KB |
| ITTools_Tab_2.JPG | 21.98 KB |
| ITTools_Tab_3.JPG | 65.15 KB |
| ITTools_Eq_1.JPG | 6.94 KB |
| ITTools_Eq_2.JPG | 6.81 KB |
| ITTools_Eq_3.JPG | 8.21 KB |
Notes
1. The acquisition and deployment collaborative IT tools is likely to improve group performance in an absolute sense compared to not having acquired and deployed such IT tools. However, since most groups have acquired and implemented collaborative IT tools, their acquisition and deployment are unlikely to be a differentiating factor.
2. The relationship between first and second order constructs can be of two types, either reflective or formative. Reflective ones assume that the latent second-order factor ‘causes' the first order factors. For formative ones, the second order factor is conceived to be ‘caused' by the first order factors such that each represents a unique contribution to the second order factor. Please see Diamantopoulos and Winklhofer (2001) and Edwards (2001) for a review.
3.
Theory Development
Collaborative group work is considered foundational for modern organizational success by creating value for organizations (Leonard-Barton 1992, Pavlou and El Sawy 2006, Sole and Applegate 2000). Collaborative group work has been dramatically enhanced by the infusion of newer collaborative IT tools that integrate IT functionalities enabling synchronous and asynchronous communication and information sharing among inter-connected entities from virtually any geographical location. Today's collaborative IT tools are new versions of computer-aided ‘Group Communication Support Systems', ‘Group Decision Support Systems', or ‘groupware' (Licklider and Taylor, 1968, Nunamaker, Dennis, and Valacich, 1991), that also were designed to support collaborative work. Today, Internet-based collaborative tools are becoming the primary approach for geographically dispersed groups (Wheeler, Dennis, and Press, 1999). However, there is scant systematic research on their potential value in facilitating the performance of groups operating in turbulent environments where HFNs are most likely to be formed.
Collaborative IT Tools Leveraging Competence
The development of the proposed CITLC construct is rooted in the IT capability literature (Barua et al. 1995, Bharadwaj 2000) that is underpinned by the resource based view (Barney 1991). The IT capability literature argues that various complementary IT resources combine to form an IT capability, which is valuable, rare, non-imitable, and non-substitutable (Mata et al. 1995).
IT capability has been viewed as a multi-dimensional construct composed of three key dimensions: acquisition, deployment, and leveraging of IT resources. While the literature has viewed IT capability at the firm level of analysis, Ray et al. (2005) argued that the primary effects of IT should be examined at the process level, stressing the need to look beyond the firm level of analysis. Moreover, Pavlou and El Sawy (2006) noted the need to look outside of the IT unit for understanding the IT capability of clients or end users. The authors argued that the leveraging of IT resources is the primary differentiating dimension among end users, noting that the acquisition and deployment dimensions of IT capability are largely based on the IT investment decisions of IT executives and are primarily implemented by IT people within the IT unit. Moreover, collaborative IT tools are generic technologies that have little basis for differentiation in terms of acquisition and deployment. Following this logic, we focus on the leveraging dimension of IT capability that is more likely to differentiate performance among groups.[1] Therefore, CITLC is conceptualized at the group level of analysis as the effective leveraging of collaborative IT functionalities to enhance group activities and create value.
CITLC is distinct from related IT constructs, such as IT investments or spending and IT resources or functionalities. CITLC captures the effective use of collaborative IT functionalities, not merely their existence or how much IT investment or spending was required to acquire and deploy these IT functionalities.
Components of Collaborative IT Tools Leveraging Competence
To identify the components of the CITLC construct, we examined over 30 commercial collaborative packages to identify their common IT functionalities. As summarized in Table 1, the key IT functionalities are workspace sharing, conferencing, file sharing, scheduling, chat, and email functionalities.
Collaborative IT Tools Leveraging Competence as a Formative Higher-Order Model
CITLC is proposed as a multi-dimensional latent construct. To model the proposed six IT functionalities under a unitary representation, we propose a second-order formative construct formed by the effective leveraging of these six IT functionalities (Figure 2). Formative second-order models provide a coherent and parsimonious depiction of multi-dimensional phenomena,[2] and are herein employed to represent the individual effects of the key IT functionalities on a group's overall CITLC.
Since groups are likely to use these IT functionalities with different degrees of effectiveness, the effective leveraging of each IT functionality is proposed to impact CITLC in a formative fashion. In addition, since an improvement in the group's ability to leverage any single IT functionality does not necessarily imply an equal improvement in the ability to leverage any other IT functionality, a reflective model is less likely. Thus, a formative second-order model is deemed appropriate for representing the proposed construct of collaborative IT tools leveraging competence.
Impact of CITLC on HFNs
CITLC is proposed to enhance performance by enabling HFNs to complete their activities more efficiently, more effectively, and with more responsiveness. We focus on three aspects of HFN performance – process efficiency, situational awareness, and project effectiveness. Project effectiveness refers to project quality and innovativeness (Kusunoki et al. 1998). Process efficiency refers to time and cost savings (Kusunoki et al. 1998). Situational awareness reflects the group's understanding of their surroundings (Endsley 1996). These three performance components can be represented with a formative second-order model (Figure 3).
By supporting superior information processing and knowledge sharing through rich, reliable, and rapid communication and information flows (requirements for effective HFNs), the effective use of collaborative IT tools can enhance the three major components of HFN performance (i.e., project effectiveness, situational awareness, and process efficiency), as briefly explained in what follows.
HFN Project Effectiveness. The effective use of collaborative IT tools is proposed to enhance HFN effectiveness. First, the effective use of email, chat, and conferencing functionality enables HFNs to share relevant project knowledge by simultaneously viewing, discussing, and editing project documents. Second, the effective use of file sharing functionality facilitates easy access to knowledge, enabling HFNs to acquire, interpret, and synthesize knowledge. Third, the effective use of scheduling and workspace sharing functionality can enhance the HFN's problem-solving capacity, help generate new thinking, and enable HFNs to find better project solutions through rich communication (McGrath and Iansiti 1998). Taken together, the improved capabilities facilitated by the effective use of collaborative IT functionalities can help create value by enhancing the HFN's project effectiveness.
Situational Awareness of HFN. The effective leveraging of collaborative IT tools is also proposed to enhance the situational awareness of HFNs. This is critical for groups in turbulent environments where HFNs operate. First, the effective use of chat, email, and file sharing functionality helps HFNs stay current with their surroundings by obtaining and exchanging up-to-date information about their environment. Second, the effective use of scheduling and conferencing functionality enables HFNs to jointly assess real-time information about their surroundings (Sambamurthy et al. 2003). Finally, the effective use of workspace sharing functionality helps groups obtain visibility of real-time data, collectively analyze these data, thereby allowing them to have a real-time vision of their surroundings and helping them be more responsive and flexible (Wade and Hulland 2004). Thus, the effective use of collaborative IT tools creates value by enhancing the situational awareness of HFNs.
HFN Process Efficiency. The effective leveraging of collaborative IT tools is finally proposed to enhance the HFN's process efficiency. First, the effective use of chat and email functionality enables efficient communication and rapid information flows, which helps the HFN efficiency. Second, the effective use of scheduling functionality makes it easier for HFNs to identify and efficiently allocate available people and resources to the most appropriate tasks. Third, the effective use of conferencing functionality enables HFNs to avoid face-to-face meeting, thus reducing cost. Finally, the file and workspace sharing functionality enables HFNs to synchronize and simultaneously execute more activities in parallel, thereby cutting down the time required for completing their activities (Sethi et al. 2001). By reducing the cost, time, and effort required to perform group activities, the effective use of collaborative IT functionalities helps create value by increasing the process efficiency of HFNs.
Summarizing the logic by which the leveraging competence of collaborative IT tools creates value by enhancing an HFN's project effectiveness, situational awareness, and process efficiency, we propose the following hypotheses.
H1: CITLC positively influences HFN performance.
The Moderating Role of Environmental Turbulence on Business Value of Collaborative IT Tools
Environmental uncertainty or unpredictability describes whether the group's surrounding conditions are characterized by frequent changes that are difficult to forecast. In uncertain environments where HFNs are likely to be formed, rapid communication and information flows are needed to quickly adapt to environmental changes and respond to unpredictable new conditions. In such unpredictable environments, the superior information processing and knowledge sharing capabilities of collaborative IT tools are likely to be conducive to creating value by enabling groups to better respond to environmental changes. First, sharing project knowledge, generating new thinking, and finding new solutions is more important in unpredictable environments. Therefore, the leveraging competence of collaborative tools will be more pronounced in enhancing project effectiveness in uncertain environments. Second, staying current with the environment and having up-to-date information is more crucial in uncertain environments. The effective use of collaborative IT tools thus becomes more important to enhance a group's situational awareness. Finally, uncertain environments make it more difficult to allocate people and resources to tasks and synchronize group activities. Therefore, the effective use of collaborative IT functionalities is likely to have a more pronounced impact on a group's process efficiency. Summarizing these arguments, we propose that the positive impact of CITLC on HFN performance to be higher in more uncertain environments. This hypothesis speaks directly to the notion that competently using collaborative tools in turbulent environments supported by HFNs will create the greatest value. Hypothesis H2 follows from this logic.
H2: Environmental uncertainty positively moderates (reinforces) the positive impact of CITLC on HFN performance.
Enhancing the Value Potential of CITLC
Having hypothesized that CITLC has value in terms of group performance, particularly in more uncertain environments, the next hypotheses focus on how the use of collaborative IT tools can be enhanced. We identified a group of antecedent variables that are proposed to enhance the value of collaborative IT tools. These variables can be grouped into five categories: (1) adoption variables (group's perceived usefulness and ease of using collaborative IT tools); (2) technology variables (customization of collaborative IT tools); (3) social variables (group's intra-group trust); (4) post-adoption variables (group's habit of using collaborative IT tools); and (5) environmental variables (environmental uncertainty within which the group operates). The proposed effect of these variables is justified in what follows.
Group’s Adoption of Collaborative IT Tools
An important prerequisite for building group competence in leveraging collaborative IT tools is for these tools to be adopted and used by the group. Following Davis' (1989) technology acceptance model, the major determinants of IT adoption are
- perceived usefulness - the extent to which a system user believes that using a system will enhance her job performance.
- and perceived ease of use - the extent to which a system user believes that using the system will be effortless.
While these two adoption variables have been defined at the individual user level, in terms of collaborative IT tools, the group's perceived usefulness and ease of using collaborative IT tools is described at the group level. Accordingly, perceived usefulness of IT tools captures the group's aggregate perception of whether the collaborative IT functionalities enable the group to accomplish its tasks more quickly, improve its job productivity, and facilitate success. Also, perceived ease of use captures the group's aggregate perception in terms of whether the group's use of the collaborative IT tools is clear, intuitive, and effortless. Extending perceived usefulness and ease of use at the group level, the group's perceived usefulness and ease of using collaborative IT tools are proposed to enhance the group's collaborative IT tools leveraging competence. We thus hypothesize:
H3a: Group's perceived usefulness of collaborative IT tools positively influences the leveraging competence of collaborative IT tools.
H3b: Group's perceived ease of using collaborative IT tools positively influences the leveraging competence of collaborative IT tools.
Customization of Collaborative IT Tools
Collaborative IT tools can be viewed as general-purpose IT tools that can be purchased as off-the-shelf software and be deployed to help work groups accomplish their business tasks. Despite being general-purpose IT tools, collaborative IT tools have flexible functionalities that can be customized to better match a group's unique activities. For example, workspace sharing functionality can be customized to work with certain computer design software. Also, file sharing functionality can link to the group's design databases. If the collaborative IT tools are customized to the group's specific needs and are adapted to better match the group's business processes, rules, and practices, they are likely to be more effectively leveraged by the group. Hence, we offer the following hypothesis for testing:
H4: The customization of collaborative IT tools positively influences the leveraging competence of collaborative IT tools.
Intra-Group Trust
Intra-group trust reflects the extent to which group members trust each other. Trust is a prerequisite for effective HFNs (Denning, 2006, p. 19 item 6). Trust among group members also captures whether promises to each other are reliable, whether group members are honest to each other, and whether they would go out of their way to help each other. Trust is considered to be a fundamental antecedent of successful collaboration by enhancing the willingness among collaborators to share knowledge (Nonaka 1994). Moreover, by making group members feel less vulnerable, trust enhances the group's comfort with sharing sensitive information. Finally, intra-group trust enables group members to work together well without interpersonal conflicts. In summary, if groups openly share sensitive information and knowledge, they are more likely to effectively use collaborative IT tools whose primary purpose is to facilitate rich communication and rapid information flows.
H5: Intra-group trust positively influences the leveraging competence of collaborative IT tools.
Group’s Habit in using Collaborative IT Tools
Habit measures the frequency of repeated or automated performance of using a system (Limayem and Hirt 2003). The association between habit and repeated behavior suggests that the behavior is consistently performed over time (Ajzen 2002). Habit in using collaborative IT tools reflects the group's willingness to make the IT tools a part of the group's regular work routine. Since repeated use is one of the primary factors for enhancing the effectiveness of a behavior, the habitual use of collaborative IT tools is likely to enhance the leveraging competence of IT tools. All things being equal, increased frequency of use of the collaborative IT tools, on average, implies that the tools facilitate the group's outputs and thus contribute directly to the productivity, business value produced by the group. Therefore, we formally hypothesize:
H6: Group's habit in using collaborative IT tools positively influences the leveraging competence of collaborative IT tools.
Environmental Uncertainty
As noted earlier, environmental uncertainty reflects whether the group's surrounding environment is characterized by frequent changes that cannot be easily predicted. Such uncertainties characterize most of the environments within which HFNs are formed and operated. Unanticipated changes force groups to seek new information, develop new skills, and build new knowledge, which requires rapid information and knowledge flows. In such environments, groups will be forced to enhance their information processing and knowledge sharing capabilities to quickly adapt to the unpredictable environmental changes such as forming and operating HFNs. Given the need to enhance their information processing capacity, groups will attempt to use their collaborative IT tools more effectively. We thus hypothesize:
H7: Environmental uncertainty positively influences the leveraging competence of collaborative IT tools.
In contrast to the previous antecedents of collaborative IT tools leveraging competence (H3-H6), H7 is a descriptive (as opposed to a prescriptive) hypothesis, which simply suggests that groups that operate in uncertain environments are more likely to effectively use collaborative IT tools.
Control Variables
Experience with Collaborative IT Tools: In addition to habit that captures the group's automated use of IT tools, we also control for the group's experience with the collaborative IT tools on their leveraging competence.
Voluntary Use of Collaborative IT Tools: Voluntariness captures whether the collaborative IT tools are voluntarily used by the group, or whether they are mandatory. Groups who are forced to use collaborative IT tools may behave differently from those who have freedom in choosing to use it or not, it is controlled for its potential impact on the leveraging competence of collaborative IT tools.
Group Size and Experience: The group's size and experience are controlled for their potential impact on both leveraging competence of collaborative IT tools and also on group performance.
Research Methodology
Proceed to Measurement Development
Measurement Development
Other than the leveraging competence of collaborative IT tools, all measurement items were adapted from existing scales. For the new measure and for measures that required significant adaptation, standard scale development procedures were used (Churchill 1979, Straub 1989). First, the content domain of each construct was specified. Second, a large pool of items was developed based on the conceptual definition, assuring that these items tap the construct's domain. From this pool, items were chosen based on whether they conveyed different, yet related shades of meaning (Churchill, 1979). The measurement items were refined based on a large-scale pretest of the survey instrument with 17 student groups. All measurement items were consistent with the study's unit of analysis at the group level (Appendix 1).
Collaborative IT Tools Leveraging Competence: A new measure was developed to capture the extent by which groups leverage collaborative IT functionalities, following Pavlou and El Sawy (2006). Special care was taken to tightly link the proposed IT functionalities (email, chat, scheduling, file sharing, shared workspace, conferencing) with specific group activities (Lind and Zmud, 1995). A total of ten items was used.
Group Performance: Project effectiveness and process efficiency were measured with two items each, following Kusunoki et al., (1998). Situational awareness was measured with three items based on Endsley (1996).
Antecedents of Collaborative IT Tools Leveraging Competence: The group's perceived usefulness and ease of using collaborative IT tools was each measured with three items (Venkatesh, 2000). The customization of collaborative IT tools was measured with two standard items. Intra-group trust was measured with four items (Jap, 1999). Habit was measured with two items (Limayem and Hirt 2003). Environmental uncertainty was measured with two items (Pavlou and El Sawy, 2006).
Survey Administration
A survey study was conducted among 400 work groups of a large multi-national corporation that specializes in product lifecycle management software and services. The benefit of surveying groups from the same company that use the same collaborative IT tool suite was to ensure that all groups had the same collaborative IT functionalities. Since the study's unit of analysis was the group, we employed key informant methodology by asking the group managers to respond on behalf of the entire group. Invitation e-mails were then sent, explaining the study's purpose and requesting their participation. The email body assured that the responses would be treated confidentially, and the results would only be reported in aggregate. The respondents were asked to click on a URL link shown in the e-mail message that linked to our online survey instrument. The respondents were offered as incentive a customized report with the study's results. To ex ante reduce the potential for common method bias, the study's instructions specifically asked the respondents to consult with other group members to collectively respond to the survey items.
In total, out of the 400 invitees for each study, a total of 365 usable responses were obtained (91% response rate). The high response rate was due to the commitment by the company's executives to promote the study and personally send the invitation e-mail to the respondents. Non-response bias was assessed by verifying that early and late respondents were not significantly different in terms of their demographic information (age, gender, education, experience with collaborative tools, and group size) (Table 1) and their actual survey responses (Armstrong and Overton 1976). Early respondents were those who responded within the first week (about 50%). All t-test comparisons between the means of the early and late respondents showed no significant differences, indicating lack of non-response bias. Demographic information is shown in Table 1.
Virtually all of the respondents indicated their position as group manager or leader. In terms of functional areas, groups had diverse activities, such as marketing and sales (20%), engineering and product development (18%), customer training and technical support (15%), accounts management (8%), product support (8%), among others.
Data Analysis and Results
We used Partial Least Square (PLS) for measurement validation and testing the structural model. PLS employs a component-based estimation method, which places minimal restrictions on sample size and residual distributions (Chin et al., 2003). PLS is best suited for testing complex relationships (Fornell and Bookstein, 1982). Notably, Wold (1985) argued: "In large, complex models with latent variables, PLS is virtually without competition" (p. 590). We chose PLS to account for the presence of a large number of variables, formative factors, and moderating effects.
Descriptive statistics and the correlations among the principal constructs are shown in Table 3.
Measurement Validation
Reliability: Reliability was assessed using the internal consistency scores (Werts, Linn, and Joreskog, 1974). [3] Internal consistencies of all variables are considered acceptable since they exceed .70, indicating tolerable reliability.
Convergent and Discriminant Validity: Convergent and discriminant validity is inferred when the PLS indicators (a) load much higher on their hypothesized factor than on other factors (own-loadings are higher than cross-loadings), and (b) when the square root of each construct's Average Variance Extracted (AVE) is larger than its correlations with other constructs (the average variance shared between the construct and its indicators is larger than the variance shared between the construct and other constructs (Chin, 1998). As shown in Table 2, the AVEs are all above 0.80, which are much larger than all correlations. Also, Appendix 2 suggests an excellent loading pattern in which all measurement items fall on their hypothesized principal constructs. These two tests suggest that all measures have adequate convergent and discriminant validity.
Common Method Variance: The extent of common method bias was first assessed with Harman's one-factor test by entering all the principal constructs into a principal components factor analysis (Podsakoff and Organ 1986). Evidence for common method bias exists when a general construct accounts for the majority of the covariance among all constructs. In this analysis, each principal construct explained roughly equal variance (range = 6 - 18%) (Appendix 2), indicating no substantial common method bias. Second, a partial correlation method was used (Podsakoff and Organ 1986). The highest factor from the principal component factor analysis was added to the PLS model as a control variable on all dependent variables. According to Podsakoff and Organ, this factor is assumed to contain the best approximation of the common method variance if is a general factor on which all variables load (p. 536). This factor did not produce a significant change in variance explained in any of the three dependent variables, again suggesting no substantial common method bias. Third, we used Lindell and Whitney's (2001) method, which employs a theoretically unrelated construct (marker variable) to adjust the correlations among the principal constructs. Social cohesion (Sethi et al. 2001) was used as the marker variable. Any high correlation among any of the items of the study's principal constructs and social cohesion would be an indication of common method bias, as social cohesion is weakly related to the study's principal constructs. Since the average correlation among social cohesion and the principal constructs was r=.11 (average p-value=.1.44), this test showed no evidence of common method bias. Fourth, the correlation matrix (Table 2) did not indicate any highly correlated variables, while evidence of common method bias usually results in extremely high correlations (r>.90) (Bagozzi et al. 1991). In summary, these tests suggest that common method bias does not account for the study's results.
Multicollinearity among the independent variables was not a serious issue since all recommended tests (eigenanalysis, tolerance values, VIFs) did not suggest evidence of multicollinearity. Similarly, no evidence of heteroscedasticity wad detected. Finally, outlier analysis did not denote any significant outliers.
In sum, the measurement properties of the study's principal constructs are deemed adequate.
Validation of Formative Second-Order Models
To estimate the formative second-order models of CITLC and group performance, we modeled the coefficients (ï§i) of each first-order factor to the latent second-order factor following Diamantopoulos and Winklhofer (2001, p. 270)
Formative Second-Order Model of Leveraging Competence of Collaborative IT Tools
As shown in Figure 4, the impact of all first-order constructs that capture the effective use of the proposed six collaborative IT functionalities on collaborative IT tools leveraging competence is significant (p<.01).
We also examined the correlations among the first-order constructs since significant correlations suggest that the first-order constructs may belong to the same set, even if formative constructs need not be correlated (Chin 1998). The correlations among the first-order factors ranged from .33 to .63 (p<.01). Since a reflective model would render extremely high correlations (often above 0.80), a formative model seems more likely. We also tested whether the second-order construct of the leveraging competence of the collaborative IT tools fully mediates the impact of the first-order constructs (effective use of specific IT functionalities) on group performance, using a mediation test (omitted for brevity). This step ensures that the second-order construct is a more parsimonious representation of the first-order constructs and fully captures their predictive power on the dependent variable. (Chin 1998). The CITLC measure is the only significant predictor when all first-order constructs are controlled for, confirming its primary mediating role. In sum, these tests support the proposed second-order formative model of collaborative IT tools leveraging competence and verify its construct validity.
Formative Second-Order Model of Group Performance
The proposed formative second-order model of group performance was assessed using a similar procedure to CITLC. As shown in Figure 5, all first order constructs (project effectiveness, situational awareness, and process efficiency) had a significant impact (p<.01) on overall group performance. Moreover, the correlations among the first-order factors ranged from .73 to .76 (p<.01). These results suggest the construct validity of group performance.
The Structural Model
The proposed research model was tested with PLS Graph 3.0. The PLS path coefficients (which can be interpreted as standardized regression coefficients) are shown in Figure 6, and the significance levels were assessed with 200 bootstrap runs. The moderating effect of environmental uncertainty with leveraging competence of collaborative IT tools were tested as part of the overall structural model with interaction terms formed by cross-multiplying all standardized items of each constructs (Chin et al. 2003). Moreover, we examined all possible interaction effects among the proposed antecedents of CITLC, and also their direct effects on performance. For clearer exposition, the PLS item loadings of each construct are omitted since they are all above 0.80, and also only significant relationships and control effects are shown.
The impact of collaborative IT tools leveraging competence on group performance was significant (beta=.42, p<.01), validating H1. The moderating effect of environmental uncertainty on the relationship between leveraging competence on collaborative IT tools and group performance was also significant (beta=.12, p<.01). To examine the significance of this interaction effect, we performed the following tests (Carte and Russell 2003, Chin et al., 2003): First, we calculated the additional variance explained due to the interaction effect, which was substantial (ΔR2=5.6%). Second, we examined if the variance explained due to the moderated effects is significant beyond the main effects, using the equation (Carte and Russel 2003, p. 481):
The F-statistic was 1.05, which was statistically significant (p<.05).
Third, the variance explained between the main and interaction effects was tested with Cohen's f2 (Chin et al. 2003). Cohen's f2 was .12, which denotes a medium effect.
Taken together, these findings and additional tests render support for H2.
In terms of the antecedents of CITLC, the technology adoption variables (group perceived usefulness (beta=.16, p<.01) and perceived ease of using (beta=.22, p<.01) collaborative IT tools) were both significant, rendering support for H3a and H3b, respectively. The customization of collaborative IT tools also had a significant effect (beta=.17, p<.01), supporting H4. Group's habit (beta=.15, p<.01) significantly influences the leveraging competence of collaborative IT tools, rendering support for H5. The impact of intra-group trust on collaborative IT tools leveraging competence was also significant (beta=.14, p<.01), supporting H6. Finally, environmental uncertainty had a significant impact (beta=.15, p<.01), rendering support for H7.
We also examined whether the proposed antecedents of CITLC had a significant direct effect on HFN performance. Only intra-group trust had a significant direct impact on CITLC (beta=.33, p<.01), while all other variables became insignificant when the mediating role of CITLC was included. This relationship can be explained by the fact that trust has more comprehensive positive effects on groups beyond merely enhancing their effectiveness in using IT tools.
Moreover, we examined potential interaction effects among the proposed antecedents of collaborative IT tools leveraging competence. Only the interaction between intra-group trust and perceived usefulness was significant (beta=.12, p<.05, ΔR2=4.2%). This relationship can be explained by the complementary effects between trust and perceived usefulness; if there is trust among the group members, the collaborative IT tools are more likely to be used more effectively, implying an interaction effect.
Finally, since non-linear (quadratic) effects for the antecedent variables may confound the proposed moderators (Carte and Russell 2003), we included quadratic (X2) factors as additional antecedents in the proposed model. The results showed that none of the quadratic factors was statistically significant and that none explained a substantial amount of variance. Therefore, fears of quadratic confounds were alleviated. This was expected since none of the correlations among the antecedent variables was extremely high, nor there was evidence of multicollinearity.
Discussion
In sum, the results strongly confirm the hypothesized relationship between CITLC and HFN performance. The results also indicated that CITLC was affected by environmental uncertainty of the type found in contexts where HFNs are formed and operated.
Overall, the results clearly indicate that leveraging collaborative tools results in better HFN performance. As various HFNs that must work together in uncertain environments improve their ability to leverage collaborative technology, all participating groups should improve their performance and especially when they are operating in uncertain environments.
One of the contributions of this study to the collaborative research arena is the introduction of the leveraging concept in the context of group performance. This research extends the prior research by focusing on the group level. This focus reflects the reality that most collaboration occurs among groups as well as within groups. It also extends the IT leveraging concept to collaborative IT as well as how such leverage can improve group performance even in the kinds of uncertain environments where HFNs are formed and operate.
Organizations, such as the Department of Defense, are making large investments in collaborative IT with the expectation that such investments will provide value in general and especially when crises occur. One way for this to happen is if work groups can leverage their competence in using collaborative tools on a routine basis before they encounter turbulent environments where HFNs may be required. Failure to leverage such tools in these environments may result in worse performance even if HFNs are present and operating.
If groups cannot leverage their competence in using the collaborative tools, the tools will become an additional overhead and a burden, negatively affecting their performance. The critical issue may not be so much the presence of such tools, but the group's ability to leverage these tools to support their needs during crises (Denning, 2006, p. 19, items 5 and 7). It follows that if groups want to mitigate the downside risks of introducing collaborative IT, their leadership will have to find ways to help work groups leverage their competence in using these tools.
This study identified a viable set of collaborative functionalities that future researchers who focus on the group level of analysis within the context of HFN environments may find useful. The concept of leveraging appears to be extensible to any IT tools that would enhance group performance and may be critical when conceptualizing the effects of IT on organizational performance.
The study raises interesting new avenues for HFN and collaborative IT research. For example, it may be useful to try to review group performance in the context of HFNs before and after the introduction of collaborative tools with the functionalities identified in this research. It may also prove useful to compare organizations with work groups that are able to effectively leverage collaborative IT competence with those that use collaborative tools but are not as adept at leveraging them.
Future research should include multiple organizations in the context of HFNs in highly turbulent environments that use collaborative IT. This study obtained its subjects from one very large organization. One reason for this was the great difficulty in securing the cooperation of multiple organizations to participate in such research efforts.
References
Ajzen, I. The Theory of Planned Behavior, Organizational Behavior and Human Decision Processes, 50, (1991), 179-211.
Ajzen, I. Constructing a TpB Questionnaire: Conceptual and Methodological Considerations, Working Paper, University of Massachusetts, Amherst, (2002). Online: http://www-unix.oit.umass.edu/~aizen/ 2004.
Armstrong, J. S. and Overton, T. Estimating Nonresponse Bias in Mail Surveys, Journal of Marketing Research, 19, (1976), pp. 396-402.
Bandura, A., Self-efficacy: The exercise of control, New York: W.H. Freeman, (1997).
Becerra-Fernandez, I., and R. Sabherwal, Organizational Knowledge Management: A Contingency Perspective, Journal of Management Information Systems, 18, 1, (2001), 23-55.
Bensaou, M., and N. Venkatraman, Configurations of Interorganizational Relationships: A Comparison between U.S. and Japanese Automakers, Management Science, 41, 9, (1995), 1471-1492.
Bharadwaj, A., A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation, MIS Quarterly, 24,1, (2000), 169-196.
Chin, W.W., "Issues and Opinions on Structural Equation Modeling," MIS Quarterly, 22, 1, (1998), 7-16.
Churchill, G. A Paradigm for Developing Better Measures of Marketing Constructs, Journal of Marketing Research, 16, 1, (1979), pp. 64-73.
Communication News, Web Meetings Benefit Bottom Line, Communication News, 40, 6, (2003).
Compeau, D. and Higgins, C. Application of Social Cognitive Theory to Training for Computer Skills, Information Systems Research, 6, 2, (1995), 118-143.
Davis, F. D., Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, 13, 3, (1989), 319-340.
Denning, P. Hastily Formed Networks, Communications of the ACM, 49, 4, (2006), 15-20.
Easley, R. F., S. Devaraj, and M. J. Crant, Relating Collaborative Technology Use to Teamwork Quality and Performance: An Empirical Investigation, Journal of Management Information Systems, 19, 4, (2003), 247-268.
Endsley, M. R. Situation Awareness Measurement in Test and Evaluation, In T. G. O'Brien and S. G. Charlton (Eds.), Handbook of Human Factors Testing & Evaluation (1996) Mahwah, New Jersey: Lawrence Erlbaum, 159-180.
Feeney, D.F., and L. P. Wilcocks, Core IS Capabilities for Exploiting Information Technology, Sloan Management Review, 39, Spring, (1998)
Fornell, C. and F. Bookstein, "Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory," Journal of Marketing Research, 19, (1982), 440-452.
Grantham, C.E. and L. Nichols, The Digital Workplace: Designing Groupware Platforms, Van Nostrand, New York, 1993.
Goodhue, D. L. Understanding User Evaluations of Information Systems, Management Science, 41, 12, (1995), 1827-1844.
Hamilton, S., "A better way to manage product development," Machine Design, 73, 16, (2001), 80-86.
Harmon, A., Staffs Make a Virtue of Necessity, The New York Times, (October 29, 2001), C.1.
Housel, T and G. Cook, Email Overload Study at Fleet Numeric Monterey, Working Paper, (Winter 2004).
Jap, S. D., Pie-Expansion Efforts: Collaboration Processes in Buyer-Supplier Relationships, Journal of Marketing Research, 36, (1999), 461-475.
Jap, S. D., Perspectives on Joint Competitive Advantage in Buyer-Supplier Relationships, International Journal of Research in Marketing, 18, 1 (2001), 19-35.
King, W.R. IT Capabilities, Business Processes, and Impact on the Bottom Line, Journal of Information Systems, 19, 2, (2002), 85-92.
Kraut, R. and L. Streeter, "Coordination in Software Development," Communications of the ACM, 38, (1995), 69-81.
Kusunoki, K., I. Nonaka and A. Nagata, Organizational Capabilities in Product Development of Japanese Firms: A Conceptual Framework and Empirical Findings, Organization Science, 9, 6 (1998), 699-718.
Licklider, J.C.R. and R. Taylor, "The Computer as a Communication Device," Science and Technology, (April 1968).
Limayem, M., and S. G. Hirt, Force of Habit and Information Systems Usage: Theory and Initial Validation, Journal of the Association of Information Systems, 4, 3, (2003), 65-97.
Lind, M. and R.W. Zmud, "Improving Interorganizational Effectiveness through Voice Mail Facilitation of Peer-to-Peer Relationships," Organization Science, 6, 4, (1995), 445-461.
Lohmoller, J., Latent Variable Path Modeling with Partial Least Squares, Heidelberg, Physica-Verlag, (1989).
McGrath, M. J., and M. Iansiti, Envisioning IT-Enabled Innovation, Insight Magazine, 2, 10, (1998).
Molloy, S. and C.R. Schwenk, "The Effects of Information Technology on Strategic Decision Making," Journal of Management Studies, 32, 3, (1995), 283-311.
Nunamaker, J.F., A.R. Dennis and J.S. Valacich, "Electronic Meeting Systems to Support Group Work," Communications of the ACM, 34, 7, (1991), 40-61.
Orlikowski, W.J. and C.S. Iacono, "Desperately seeking the "IT" in IT research: A call to theorizing the IT artifact," Information Systems Research, 12, 2, (2001), 121-134.
Pavlou, P. A. and O. A. El Sawy, From IT Leveraging Competence to Competitive Advantage in Turbulent Environments: The Case of New Product Development, Information Systems Research, (2006), (forthcoming).
Podsakoff, P. M. and D. W. Organ, Self-reports in Organizational Research: Problems and Prospects, Journal of Management, 12, 4, (1986), 531-544.
Ray, G., W.A. Muhanna, and J.B. Barney Information Technology and the Performance of the Customer Service Process: A Resource-Based Analysis, MIS Quarterly, 29, 4, (2005), 625-642.
Rockart, J.F. and J.E. Short, "IT in the 1990s: Managing Organizational Interdependence," Sloan Management Review, 31, (1989), 7-17.
Ross, J. R., M. R. Vitale, and C. M. Beath, Develop Long-Term Competitiveness Through IT-Assets, Sloan Management Review, 38, 1, (1996)
Sambamurthy, V. and R.W. Zmud, "Research Commentary: The Organizing Logic of an Enterprise's IT Activities in the Digital Era - A Prognosis of Practice and a Call for Research," Information Systems Research, 11, 2, (2000), 105-114.
Sethi, R., D. C. Smith and W. Park, Cross-Functional Product Development Teams, Creativity, and the Innovativeness of New Consumer Products, Journal of Marketing Research, 38, (2001), 73-85.
Straub, D.W. Validating Instruments in MIS Research, MIS Quarterly, 13, 2, (1989), pp. 147-169.
Taman, S., Collaborative IT at the DON; An Overview of the Current Status July 04, DoN CIO Power Point Briefing, July 23, 2004.
Tully, S., Rebuilding Wall Street, Fortune, (October 1, 2001), p92.
Venkatesh, V., Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model, Information Systems Research, 11, 4, (2000), 342-365.
Werts, C.E., R. L. Linn, and K. G. Joreskog, Interclass Reliability Estimates: Testing Structural Assumptions, Education and Psychological Measurement, 34, (1974), pp. 25-33.
Wheeler, B.C., A.R. Dennis and L.I. Press, "Groupware Comes to the Internet: Charting a New World," The DATABASE for Advances in Information Systems, 30, 3,4, (1999), 8-21.
Wiseman, C., Strategic Information Systems, Homewood Il: Irwin (1988)
Wold, H., Partial Least Squares, In N.L. Johnson (Ed.), Encyclopedia of Statistical Sciences, New York, Wiley, (1990).
Appendix 1. Measurement Items
Appendix 1. Measurement items
(1: strongly disagree/7: strongly agree)
- Email to exchange messages among team members.
- Chat/Instant Messaging to share information in real-time.
- Calendar for connecting time and location information for all team members.
- Scheduling for providing up-to-date calendar information.
- File sharing to store, archive, and reuse information and best practices.
- Consolidation and synchronization of files into a single repository for easy access.
- Conferencing for spawning new ideas and solutions.
- Collaboration among team members to interact in real time.
- Shared workspace for simultaneously working together in real-time.
- Whiteboard functionality for bringing together team members.
(1: strongly disagree/7: strongly agree)
- We were able to meet our project timeline deliverables.
- We efficiently managed our daily workflow.
- Our project deliverables were of high quality.
- Improvements in quality of group's activities.
- Do you have a coherent mental picture and good understanding of your project status?
- Do you have the feeling that you are able to anticipate problems?
(1: strongly disagree/7: strongly agree)
- Using the system would enable me to accomplish tasks quicker.
- Using the system would improve my job performance.
- Using the system in my job would increase my productivity.
- My interaction with the system is clear and understandable.
- Learning to use the system was intuitive and did not require a lot of my mental effort.
- I find the system to be easy to use.
- We trust each other.
- Our promises to each other are reliable.
- We are honest in dealing with each other.
- We would go out of our way to help each other out.
- Our environment has a high operational tempo.
- Our environment is continuously changing.
- Environmental changes in our area are difficult to forecast.
- My use of the system is voluntary.
- Using the system is not compulsory to my job.
- Given the choice I would choose to use the Collaborative System I now use.
- The collaborative system we use adapts to our business processes, rules, and practices.
- The collaborative system we use is customized to our specific needs.
- Using a collaborative system has become a habit for me.
- Using my existing system has become natural for me.
- How many months has your group been using a Collaborative System?
- # Individuals in Group.
- Your Position in the Group:
- How many years of work experience do you have?
- What is your age?
- Please provide your email address if you would like a copy of the results of this study.
- Gender:
- What is your educational level?
