In this article, the authors focus on determining whether a group’s attributes influence the effectiveness of the group’s use of group decision support systems (GDSS). Specifically, their research objective is to understand the impact of the perception of the GDSS and group cohesion on outcomes of enjoyment with the process, enjoyment with the decision, the effectiveness of the decision, and efficiency of the decision. To test their hypothesis, the authors conducted a lab experiment. The results were then calculated utilizing PLS Graph. It was found that each of the five characteristics of the innovation is a significant factor in the second-order construct, with Relative Advantage exhibiting the highest loading. The latent belief toward the GDSS was a significant driver of all the GDSS outcomes, except for Decision Efficiency. Group cohesion significantly predicted enjoyment and effectiveness, but it did not drive the group to be more efficient. Conclusions and implications for further research are also discussed.
Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582.
2.
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215.
3.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(4), 411-423.
4.
Barclay, D., Higgins, C., & Thompson R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2), 285-309.
5.
Benbasat, I., DeSanctis, G., & Nault, B. R. (1993). Empirical research in managerial support systems: A review and assessment. In C. Holsapple & A. Whinston (Eds.), Recent developments in decision support systems (NATO ASI Series F, pp. 383-437). Berlin: Springer-Verlag.
6.
Benbasat, I., & Lim, L. H. (1993). The effects of group, task, context, and technology variables on the usefulness of group support systems: A meta-analysis of experimental studies. Small Group Research, 24(4), 430-462.
7.
Bollen, K. A., & Hoyle, R. H. (1990). Perceived cohesion: A conceptual and empirical examination. Social Forces, 69(2), 479-504.
8.
Bui, T. X. (1987). Co-oP: A group decision support system for cooperative multiple criteria group decision making. Berlin: Springer-Verlag.
9.
Bui, T., & Sivasankaran, T. R. (1990). Relation between GDSS use and group task complexity. In Proceedings of the Twenty-Third Hawaii International Conference on Systems Sciences (Vol. 3, pp. 554-563). Los Alamitos, CA: IEEE Computer Society Press.
10.
Chin, W. W. (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii-xvi. Available from http://www.misq.org/archivist/vol/no22/issue1/vol22n1comntry.html
11.
Chin, W. W. (1998b). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). Mahwah, NJ: Lawrence Erlbaum.
12.
Chin, W. W., & Gopal, A. (1995). Adoption intention in GSS: Relative importance of beliefs. Data Base, 26(2:3), 42-63.
13.
Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307-341). Thousand Oaks, CA: Sage.
14.
Daft, R. L., & Lengel, R. H. (1984). Information richness: A new approach to managerial behavior and organizational design. In B. M. Staw & L. L. Cummings (Eds.), Research in organizational behavior (Vol. 6, pp. 191-233). Greenwich, CT: JAI.
15.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
16.
Deep, S. D., Bass, B., & Vaughan, J. A. (1967). Some effects of business gaming of previous quasi-group afflictions. Journal of Applied Psychology, 51(5), 426-431.
17.
Dennis, A. R., & Gallupe, R. B. (1993). A history of GSS empirical research: Lessons learned and future directions. In L. M. Jessup & J. S. Valacich (Eds.), Group support systems: New perspectives (pp. 59-77). New York: Macmillan.
18.
Dennis, A. R., & Kinney, S. T. (1998). Testing media richness theory in the new media: The effects of cues, feedback, and task equivocality. Information Systems Research, 9(3), 256-274.
19.
Dennis, A. R., & Wixom, B. H. (2001-2002). Investigating the moderators of the group support systems use with meta-analysis. Journal of Management Information Systems, 18(3), 235-257.
20.
DeSanctis, G., & Gallupe, R. B. (1987). A foundation for the study of group decision support systems. Management Science, 33, 589-609.
21.
DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5(2), 121-147.
22.
DeSanctis, G., & Poole, M. S. (1997). Transitions in teamwork in new organizational forms. Advances in Group Processes, 14, 157-176.
23.
Dickson, G. W., Robinson, L., Heath, R., & Lee, J. (1989). Observations on GDSS interaction: Chauffeured, facilitated, and user-driven systems. In Proceedings of the Twenty-Second Annual Hawaii International Conference on System Sciences (Vol. 3, pp. 337-343). Waikoloa, HI: Computer Society Press.
24.
Dion, K. R. (2000). Group cohesion: From “field of forces” to multidimensional construct. Group Dynamics: Theory, Research and Practice, 4, 7-26.
25.
Drazin, R., & Van de Ven, A. H. (1985). Alternative forms of fit in contingency theory. Administrative Science Quarterly, 30(4), 514-539.
26.
Fjermestad, J., & Hiltz, S. R. (1998-1999). An assessment of group support systems experimental research: Methodology and results. Journal of Management Information Systems, 15(3), 7-149.
27.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.
28.
Gagliardi, P., & Compeau, D. (1995). The effects of group presentations on intentions to adopt smart card technology: A diffusion of innovations approach. Proceedings of the ASAC (pp. 20-32). Windsor: Administrative Sciences Association of Canada.
29.
Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of e-mail: An extension to technology acceptance model. MIS Quarterly, 21(4), 389-400.
30.
George, J. F., Northcraft, G. B., & Nunamaker, J. F. (1987). Implications of group decision support system use for management: Report of a pilot study. Tucson: College of Business and Public Administration, University of Arizona.
31.
Gerbing, D. W., & Anderson, J. C. (1985). The effects of sampling error and model characteristics on parameter estimation for maximum likelihood confirmatory factor analysis. Multivariate Behavioral Research, 20(3), 255-271.
32.
Gopal, A., & Prasad, P. (2000). Understanding GDSS in symbolic context: Shifting the focus from technology to interaction. MIS Quarterly, 24(3), 509-546.
33.
Gouran, D., Brown, C. and Henry, D. (1978). Behavioral correlates of perceptions of quality in decision making discussions. Communication Monographs, 45(1), 51-63.
34.
Gully, S. M., Devine, D. J., & Whitney, D. J. (1995). A meta analysis of cohesion and performance: Effects of level of analysis and task interdependence. Small Group Research, 26(4), 497-520.
35.
Hall, J., & Williams, M. S. (1966). A comparison of decision-making performance in established and ad-hoc groups. Journal of Personality and Social Psychology, 3, 214-222.
36.
Handy, C. (1995). Trust and the virtual organization. Harvard Business Review, 73, 40-50.
37.
Hogg, M. A. (1987). Social identity and group cohesiveness. In J. C. Turner, M. A. Hogg, P. J. Oakes, S. D. Reicher, & M. S. Wetherell (Eds.), Rediscovering the social group: A self-categorization theory (pp. 89-116). Oxford, UK: Basil-Blackwell.
38.
Hogg, M. A. (1992). The social psychology of group cohesiveness. New York: University Press.
39.
Iacono, C. S., & Weisband, S. P. (1997). Developing trust in virtual teams. In Proceedings of the Thirtieth Hawaii International Conference on System Sciences (pp. 1-9). Los Alamitos, CA: IEEE Computer Society Press.
40.
Jarvenpaa, S., & Leidner, D. (1999). Communication and trust in global virtual teams. Organization Science, 10(6), 791-815.
41.
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.
42.
Kayworth, T. R., & Leidner, D. E. (2001-2002). Leadership effectiveness in global virtual teams. Journal of Management Information Systems, 18(3), 7-41.
43.
Klein, H. J., & Mulvey, P. W. (1995). Two investigations of the relationships among group goals, goal commitment, cohesion, and performance. Organizational Behaviour and Human Decision Processes, 61, 44-53.
44.
Lam, S. S. (1997). The effects of group decision support systems and task structures on group communication and decision quality. Journal of Management Information Systems, 13(4), 193-215.
45.
Langfred, C. (1998). Is group cohesiveness a double-edged sword? An investigation of the effects of cohesiveness on performance. Small Group Research, 29(1), 124-143.
46.
Lipnack, J., & Stamps, J. (1997). Virtual teams: Reaching across space, time, and organizations with technology. New York: John Wiley.
47.
Lott, A. J., & Lott, B. E. (1965). Group cohesiveness as intrapersonal attraction: A review of relationships with antecedent and consequent variables. Psychological Bulletin, 64, 259-309.
48.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149.
49.
McKenney, J. L., & Dill, W. R. (1966). Influences on learning in simulation games. American Behavioral Scientist, 10(2), 28-32.
50.
Mennecke, B. E., & Valacich, J. S. (1998). Information is what you make of it: The influence of group history and computer support on information sharing, decision quality, and member perceptions. Journal of Management Information Systems, 15(2), 173-197.
51.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
52.
Moore, G. C., & Benbasat, I. (1996). Integrating diffusion of innovations and theory of reasoned action models to predict utilization of information technology by end-users. In K. Kautz & J. Pries-Heje (Eds.), Diffusion and adoption of information technology (pp. 132-146). London: Chapman & Hall.
53.
Mullen, B., & Copper, C. (1994). The relation between group cohesiveness and performance: An integration. Psychological Bulletin, 115(2), 210-227.
54.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.
55.
Orlikowski, W. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398-427.
56.
Orlikowski, W., & Iaconno, S. (2001). Desperately seeking the “IT” in IT research. Information Systems Research, 12(2), 121-135.
57.
Orlikowski, W. J., & Robey, D. (1991). Information technology and the structuring of organizations. Information Systems Research, 2(2), 398-427.
58.
Plouffe, C. R., Hulland, J., & Vandenbosch, M. (2001). Research report: Richness versus parsimony in modeling technology adoption decisions—Understanding merchant adoption of a smart card-based payment system. Information Systems Research, 12(2), 208-222.
59.
Powell, A., Piccoli, G., & Ives, B. (2004). Virtual teams: A review of the current literature and directions for future research. DATABASE for Advances in Information Systems, 35(1), 6-36.
60.
Rogers, E. M. (1983). Diffusion of innovations (3rd ed.). New York: Free Press.
61.
Sambamurthy, V. (1989). Supporting group performance during stakeholder analysis: The effects of alternative decision-based designs. Unpublished doctoral dissertation, University of Minnesota.
62.
Sharda, R., Barr, S. H., & McDonnell, J. C. (1988). Decision support system effectiveness: A review and an empirical test. Management Science, 34, 139-159.
63.
Shaw, G. J. (1998). User satisfaction in group support systems research: A meta-analysis of experimental results. In Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences (pp. 360-369). Los Alamitos, CA: IEEE Computer Society Press.
64.
Spranger, E. (1928). Types of men (5th German ed., Trans. P. W. J. Pigors). Halle, Germany: Max Niemeye Vrerlag.
65.
Steeb, R., & Johnson, S. C. (1981). A computer-based interactive system for group decision-making. IEEE Transactions on Systems, Man, and Cybernetics, SMC-11, 544-552.
66.
Townsend, A. M., deMarie, S. M., & Hendrickson, A. R. (1998). Virtual teams and the work-place of the future. Academy of Management Executive, 12(3), 17-29.
67.
Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
68.
Watson, R. T. (1987). A study of group decision support system use in three and four-person groups for a preference allocation decision. Unpublished Ph.D. dissertation, University of Minnesota, Minneapolis.
69.
Werts, C. E., Linn, R. L., & Joreskog, K. G. (1974). Interclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34, 25-33.
70.
White, J. C., Varadarajan, P. R., & Dacin, P. A. (2003). Market situation interpretation and response: The role of cognitive style, organisational culture, and information use. Journal of Marketing, 67, 63-79.
71.
Yoo, Y., & Alavi, M. (2001). Media and group cohesion: Relative influences on social presence, task participation, and group consensus. MIS Quarterly, 25(3), 371-390.
72.
Zhang, T. (1995). The value of IT-enabled retailer learning: Can personalized product recommendations (PPRS) improve customer store loyalty in electronic markets? Unpublished doctoral dissertation, University of Maryland.
