Determination of Expert Group Preferences in the Multi-Criteria Model for the Analysis of Local Economic Environment

• Authors: Jelena Stanković , Žarko Popović , Sanja Kostevski
• Languages of publication: EN

Abstracts

EN

Local economic environment is characterised by a range of economic, social, political and demographic parameters, based on which we can perform its analysis. Heterogeneity of relevant characteristics of the local economic environment imposes multiple criteria analysis as one of the suitable tools for the evaluation. Assessment of local economic environment often falls within the scope of group decision-making, as it is usually performed on the basis of an analysis of preferences of economic subjects or relevant experts on the issue of the economic environment at the local level. Regardless of whether it is based on economic subjects or expert group, in order to form a multi-criteria model, it is necessary to generate preferences of individuals into a single weight coefficient, which shows groups’ preference on the importance of each criterion. The subject of this paper is determination of weight coefficients in the multi-criteria model for the analysis of local economic development based on the preferences from a group of experts, by applying adequate statistical tools, and then by ranking local governments according to the quality of business environment perceived by the expert group.In addition to descriptive statistics and testing the significance of differences, in the paper is applied multi-criteria method Simple Additive Weights - SAW.

Keywords

EN

Local economic environment; multi-criteria analysis; weight coefficients; group decision-making; SAW method

• Publisher: Sciendo
• Journal: Economic Themes
• Year: 2016
• Volume: 54
• Issue: 2
• Pages: 261-280

Dates

published

2016-06-01

received

2016-03-16

accepted

2016-05-18

online

2016-07-26

Contributors

author

Jelena Stanković

• University of Nis, Faculty of Economics, Republic of Serbia

author

Žarko Popović

• University of Nis, Faculty of Economics, Republic of Serbia

author

Sanja Kostevski

• PhD student of Belgrade Banking Academy, Belgrade

References

• Burnstein, F. & Holsapple, C. W. (2008). Handbook on Decision Support Systems 1: Basic Themes. Berlin Heidelberg: Springer-Verlag.
• De Haas M. & Kleingeld A. (1999) Multilevel design of performance measurement systems: enhancing strategic dialogue throughout the organization. Manag Acc Res 10: 233-261
• Delbecq, A.L. (1967). The Management of Decision-Making within the Firm - Three Types of Decision-Making. Academy Management Journal, 322-339.
• Dias L.C. & Sarabando P. (2012) A note on a group preference axiomatization with cardinal utility. Decions Analysis 9: 231-237[Crossref]
• Eden, C. & Harris, J. (1975). Management Decision and Decision Analysis. London: The Macmillian Press LTD.
• Harisson, E. F. (1987). The Managerial Decision-Making Process (3rd Edition). Boston: Houghton Mifflin Company.
• Huang Y.S., Liao J.T. & Lin Z.L. (2009) A study on aggregation of group decisions. Syst Res Behav Sci 26: 445- 454[WoS][Crossref]
• Hülle J., Kaspar R. & Möller K. (2011) Multiple criteria decision-making in management accounting and control-state of the art and research perspectives based on a bibliometric study. Journal of Multi Criteria Decision Analysis 18:253-265
• Hwang, C. L. & Yoon, K. (1981). Multiple Attribute Decision Making, Methods and Applications. A State-of-the-Art Survey, Lecture Notes in Economics and Mathematical Systems, Berlin: Springer-Verlag.
• Keeney R.L. (2009) The foundations of collaborative group decisions. Int J Collab Eng. 9:231-237
• Kreitner R. & Cassidy C.M. (2011) Management (12th Edition). Mason: Cengage Learning.
• Lee, S. M. & Moore, L. J. (1975). Introduction to Decision Science. New York: Petrucelli.
• Mescon, M., Alberi, M. & Khedouri, F. (1985). Management. New York: Harper and Row.
• Mintzberg, H. (1973). The Natur of Managerial Work. New York: Harper and Row.
• Moody, P. E. (1983). Decision Making-Proven Methods for Better Decisions. New York, McGraw - Hill book Company.
• Pinheiro-Böhl, C. (2007). Development of Knowledge Based Decision Support System for Private Sector Participation in Water and Sanitation Utilities. http://elib.unistuttgart.de/opus/volltexte/2008/3391/pdf/Diss_Carla_Boehl_2007_08_24_FEI_final.pdf , Accessed December 15, 2015.
• Sauter, V. L. (2011). Decision Support Systems for Business Intelligence. John Wiley & Sons.
• Simon, H. A. (1960). The New Science of Management Decision. New York: Harper & Row.
• Sims R.R. (2002) Managing organizational behavior. Westport: Greenwood Publishing Group.
• Turban, E., Aronson, J. E. & Liang, T.P. (2005). Decision support systems and intelligent systems. Upper Saddle River, NJ: Pearson.
• Van den Honert, R.C. & Lootsma, F.A. (1996) Group preference aggregation in the multiplicative AHP-the model of the group decision process and Pareto optimality. European Journal of Operations Research 96: 363-370.
• Wallenius J., Dyer J.S., Fishburn P.C., Steuer R.E., Zionts S. & Deb K. (2008) Multiple criteria decision making, multiattribute utility theory: recent accomplishments. Management Science 54:1336-1349[WoS][Crossref]
• www.naled-serbia.org

Identifiers

DOI

10.1515/ethemes-2016-0013