Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-26T09:17:43.242Z Has data issue: false hasContentIssue false

The impact of resources on decision making

Published online by Cambridge University Press:  02 November 2012

Iain M. Boyle*
Affiliation:
Department of Design, Manufacture and Engineering Management, University of Strathclyde, Glasgow, United Kingdom
Alex H.B. Duffy
Affiliation:
Department of Design, Manufacture and Engineering Management, University of Strathclyde, Glasgow, United Kingdom
R. Ian Whitfield
Affiliation:
Department of Design, Manufacture and Engineering Management, University of Strathclyde, Glasgow, United Kingdom
Shaofeng Liu
Affiliation:
Department of Design, Manufacture and Engineering Management, University of Strathclyde, Glasgow, United Kingdom School of Management, University of Plymouth, Plymouth, United Kingdom
*
Reprint requests to: Iain M. Boyle, Department of Design, Manufacture, and Engineering Management, Architecture Building, University of Strathclyde, Glasgow G1 1XJ, United Kingdom. E-mail: iain.m.boyle@strath.ac.uk

Abstract

Decision making is a significant activity within industry and although much attention has been paid to the manner in which goals impact on how decision making is executed, there has been less focus on the impact decision making resources can have. This article describes an experiment that sought to provide greater insight into the impact that resources can have on how decision making is executed. Investigated variables included the experience levels of decision makers and the quality and availability of information resources. The experiment provided insights into the variety of impacts that resources can have upon decision making, manifested through the evolution of the approaches, methods, and processes used within it. The findings illustrated that there could be an impact on the decision-making process but not on the method or approach, the method and process but not the approach, or the approach, method, and process. In addition, resources were observed to have multiple impacts, which can emerge in different timescales. Given these findings, research is suggested into the development of resource-impact models that would describe the relationships existing between the decision-making activity and resources, together with the development of techniques for reasoning using these models. This would enhance the development of systems that could offer improved levels of decision support through managing the impact of resources on decision making.

Type
Special Issue Articles
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Arroba, T. (1977). Styles of decision-making and their use: an empirical study. British Journal of Guidance and Counselling 5(2), 149158.CrossRefGoogle Scholar
Austin, J.R. (1993). A cognitive framework for understanding demographic influences in groups. International Journal of Organizational Analysis 5(4), 342359.CrossRefGoogle Scholar
Baltes, B., Dickson, M.W., Sherman, M.P., Bauer, C.C., & LaGanke, J.S. (2002). Computer-mediated communication and group decision-making: A meta-analysis. Organizational Behavior and Human Decision Processes 87(1), 156179.CrossRefGoogle Scholar
Beach, L.R., & Mitchell, T.R. (1987). Image theory: principles, goals, and plans in decision-making. Acta Psychologica 66, 201220.CrossRefGoogle Scholar
Beers, P.J., Boshuizen, H.P.A., Kirschner, P.A., & Gijselaers, W.H. (2006). Common ground, complex problems and decision-making. Group Decision and Negotiation 15, 529556.CrossRefGoogle Scholar
Belton, V., & Stewart, T.J. (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Boston: Kluwer Academic.CrossRefGoogle Scholar
Boyle, I.M, Duffy, A.H.B., Whitfield, R.I., & Liu, S. (2009). Towards an understanding of the impact of resources on the design process.Proc. 17th Int. Conf. Engineering Design (ICED '09). Stanford, CA: Design Society.Google Scholar
Brim, O.G., Glass, D.C., Lavin, D.V., & Goodman, N. (1962). Personality and Decision Processes: Studies in the Social Psychology of Thinking. Stanford, CA: Stanford University Press.Google Scholar
Busenitz, L.W., & Barney, J.B. (1997). Differences between entrepreneurs and managers in large organizations: biases and heuristics in strategic decision-making. Journal of Business Venturing 12, 930.CrossRefGoogle Scholar
Camarinha-Matos, L.M. (2009). Collaborative networked organizations: status and trends in manufacturing. Annual Reviews in Control 33, 199208.CrossRefGoogle Scholar
Cebeci, U. (2009). Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Systems With Applications 36(5), 89008909.CrossRefGoogle Scholar
Chalupnik, M.J., Wynn, D.C., & Clarkson, P.J. (2009). Approaches to mitigate the impact of uncertainty in development processes. Proc Int. Conf. Engineering Design (ICED'09). Stanford, CA: Design Society.Google Scholar
Coates, G., Duffy, A.H.B., Whitfield, R.I., & Hills, W. (2003). An integrated agent-oriented approach to real-time operational design coordination. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 17, 287313.CrossRefGoogle Scholar
Cohen, D.K., March, J.G., & Olsen, J.P. (1972). A garbage can model of organizational choice. Administrative Science Quarterly 17, 125.CrossRefGoogle Scholar
Dean, J.W., & Sharfman, M.P. (1996). Does decision process matter? A study of strategic decision-making effectiveness. Academy of Management Journal 39(2), 368396.CrossRefGoogle Scholar
Dennis, A.R. (1996). Information exchange and use in group decision-making: you can lead a group to information, but you can't make it think. MIS Quarterly 20(4), 433457.CrossRefGoogle Scholar
Duffy, A.H.B. (2002). Designing design. Proc. 3rd Int. Seminar and Workshop Engineering Design in Integrated Product Development, pp. 3746.Google ScholarPubMed
Etzioni, A. (1967). Mixed scanning: A third approach to decision-making. Public Administration Review 27, 385392.CrossRefGoogle Scholar
Fenton, N., & Neil, M. (2011). The use of Bayes and causal modelling in decision-making, uncertainty, and risk. CEPIS Upgrade 12(5) 1021.Google Scholar
Galbraith, J.R. (1974). An information processing view. Interfaces 4(3), 2836.CrossRefGoogle Scholar
Gao, Z.Zhang, D., & Ge, Y. (2010). Design optimization of a spatial six degree-of-freedom parallel manipulator based on artificial intelligence approaches. Robotics and Computer-Integrated Manufacturing 26, 180189.CrossRefGoogle Scholar
Griffin, D.W., Gonzalez R., Koehler, D.J., & Gilovich, T. (2012). Judgemental heuristics: A historical overview. InThe Oxford Handbook of Thinking and Reasoning (Holyoak, K.J., & Morrison, R.G., Eds.), pp. 322345. New York: Oxford University Press.CrossRefGoogle Scholar
Jackson, S.E., May, K.E., & Whitney, K. (1995). Understanding the dynamics of diversity in decision-making teams. In Team Effectiveness and Decision-Making in Organizations (Guzzo, R.A., & Salas, E., Eds.), pp. 204261. San Francisco, CA: Jossey–Bass.Google Scholar
Kahneman, D., Lovallo, D., & Sibony, O. (2011). Before you make that big decision. Harvard Business Review 89(6), 5160.Google ScholarPubMed
Keen, G.W.K., & Morton, M.S.S. (1978). Decision Support Systems: An Organizational Perspective. Reading, MA: Addison–Wesley.Google Scholar
Klein, G. (2008). Naturalistic decision-making. Human Factors 50(3), 456460.CrossRefGoogle ScholarPubMed
Klein, G.A., Wolf, S., Militello, L., & Zsambok, C.E. (1995). Characteristics of skilled option generation in chess. Organization Behavior and Human Decision Processes 62, 6369.CrossRefGoogle Scholar
Lindblom, C.E. (1959). The science of muddling through. Public Administrative Review 19, 7999.CrossRefGoogle Scholar
Lipshitz, R., & Strauss, O. (1997). Coping with uncertainty: a naturalistic decision-making analysis. Organizational Behaviour and Human Decision Process 69(2), 149163.CrossRefGoogle Scholar
Lipshitz, R., Klein, G., Orasanu, J., & Salas, E. (2001). Taking stock of naturalistic decision-making. Journal of Behavioral Decision-Making 14, 331352.CrossRefGoogle Scholar
Liu, S., Duffy, A.H.B., Whitfield, R.I., Boyle, I.M., & McKenna, I. (2009). Towards the realization of an integrated decision support environment for organizational decision-making. International Journal of the Decision Support System Technology 1(4), 3558.CrossRefGoogle Scholar
Mackinnon, A.J., & Wearing, A.J. (1980). Complexity and decision-making. Systems Research and Behavioral Science 25(4), 285296.Google Scholar
Martin-Alcazar, F., Romero-Fernandez, P.M., & Sanchez-Gardey, G. (2011). Effects of diversity on group decision-making processes: The moderating role of human resource management. Group Decision and Negotiation. Advance online publication. doi:10.1007/s10726-011-9243-9Google Scholar
Martinovski, B., & Mao, W. (2009). Emotion as an argumentation engine: modelling the role of emotion in negotiation. Group Decision and Negotiation 18, 235259.CrossRefGoogle Scholar
Mintzberg, H., Raisinghani, D., & Theoret, A. (1976). The structure of “unstructured” decision processes. Administrative Science Quarterly 21, 246275.CrossRefGoogle Scholar
Mizoguchi, R., Vanwelkenhuysen, J., & Ikeda, M. (1995). Task ontology for reuse of problem solving knowledge. In Towards Very Large Knowledge Bases (Mars, N.J.I., Ed.), pp. 4659. Amsterdam: IOS Press.Google Scholar
Nutt, P. (1984). Types of organizational processes. Administrative Science Quarterly 29(3), 414450.CrossRefGoogle Scholar
Nutt, P. (1993). The formulation processes and tactics used in organizational decision-making. Organization Science 4(2), 226251.CrossRefGoogle Scholar
Nutt, P. (2011). Making decision-making research matter: Some issues and remedies. Management Research Review 34(1), 516.CrossRefGoogle Scholar
Nutt, P.C. (1976). Models for decision-making in organizations and some contextual variables which stipulate optimal use. Academy of Management Review 1(2), 8498.CrossRefGoogle Scholar
O'Donnell, F.J., & Duffy, A.H.B. (2002). Modelling design development performance. International Journal of Operations and Production Management 22(11), 11981221.CrossRefGoogle Scholar
Olson, B.J., Parayitam, S., & Bao, Y. (2007). Strategic decision-making: the effects of cognitive diversity, conflict, and trust on decision outcomes. Journal of Management 33(2), 196222.CrossRefGoogle Scholar
Rao, R.V., Savsani, V.J., & Vakharia, D.P. (2011). Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems. Computer-Aided Design 43(3), 303315.CrossRefGoogle Scholar
Rittel, H.W.J., & Webber, M.M. (1973). Dilemmas in a general theory of planning. Policy Sciences 4(2), 155169.CrossRefGoogle Scholar
Salas, E., Rosen, M.A., & DiazGranados, D. (2010). Expertise-based intuition and decision-making in organizations. Journal of Management 36(4), 941973.CrossRefGoogle Scholar
Salo, A., & Hämäläinen, R.P. (2010). Multicriteria decision analysis in group decision processes. In Handbook of Group Decision and Negotiation (Kilgour, D.M., & Eden, C., Eds.), pp. 269283. Dordrecht: Springer.CrossRefGoogle Scholar
Scherpereel, C.M. (2006). Decision orders: a decision taxonomy. Management Decision 44(1), 123136.CrossRefGoogle Scholar
Shrivastava, P., & Grant, J.H. (1985). Empirically derived models of strategic decision-making processes. Strategic Management Journal 6, 97113.CrossRefGoogle Scholar
Simon, H.A. (1960). The New Science of Decision-Making. New York: Harper & Row.Google Scholar
Simon, H.A. (1993). Decision-making: rational, non-rational, and irrational. Educational Administration Quarterly 29, 399411.CrossRefGoogle Scholar
Tarter, C.J., & Hoy, W.K. (1998). Toward a contingency theory of decision-making. Journal of Educational Administration 36(3), 212228.CrossRefGoogle Scholar
Tsoukiàs, A. (2008). From decision theory to decision aiding methodology. European Journal of Operational Research 187, 138161.CrossRefGoogle Scholar
Wang, J.X., Tang, M.X., Song, L.N., & Jiang, S.Q. (2009). Design and implementation of an agent-based collaborative product design system. Computers in Industry 60, 520535.CrossRefGoogle Scholar
Whitfield, R.I., Duffy, A.H.B., & Coates, G. (2007). Real time resource scheduling within a distributed collaborative design environment. Proc. Int. Conf. Engineering Design (ICED'07). Paris: Design Society.Google Scholar
Whitfield, R.I., Duffy, A.H.B., York, P., Vassalos, D., & Kaklis, P. (2011). Managing the exchange of engineering product data to support through life ship design. Computer-Aided Design 43(5), 516532.CrossRefGoogle Scholar
Wiseman, C. (1979 a). Selection of major planning issues. Policy Sciences 12, 103113.Google Scholar
Wiseman, C. (1979 b). Strategic planning in the Scottish Health Service: a mixed scanning approach. Long Range Planning 12, 7186.CrossRefGoogle ScholarPubMed
Yang, J.B. (2001). Rule and utility based evidential reasoning approach for multi attribute decision analysis under uncertainties. European Journal of Operational Research 131, 3161.CrossRefGoogle Scholar
Yen, J., Fan, X., Sun, S., Hanratty, T., & Dumer, J. (2006). Agents with shared mental models for enhancing team decision-making. Journal of Decision Support Systems 41(3), 634653.CrossRefGoogle Scholar