Abstract
In this paper, we examine the issue of strategic industrial location selection in uncertain decision making environments for implanting new industrial corporation. In fact, the industrial location issue is typically considered as a crucial factor in business research field which is related to many calculations about natural resources, distributors, suppliers, customers, and most other things. Based on the integration of environmental, economic and social decisive elements of sustainable development, this paper presents a hybrid decision making model combining fuzzy multi-criteria analysis with analytical capabilities that OLAP systems can provide for successful and optimal industrial location selection. The proposed model mainly consists in three stages. In the first stage, a decision-making committee has been established to identify the evaluation criteria impacting the location selection process. In the second stage, we develop fuzzy AHP software based on the extent analysis method to assign the importance weights to the selected criteria, which allows us to model the linguistic vagueness, ambiguity, and incomplete knowledge. In the last stage, OLAP analysis integrated with multi-criteria analysis employs these weighted criteria as inputs to evaluate, rank and select the strategic industrial location for implanting new business corporation in the region of Casablanca, Morocco. Finally, a sensitivity analysis is performed to evaluate the impact of criteria weights and the preferences given by decision makers on the final rankings of strategic industrial locations.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-015-1404-x) contains supplementary material, which is available to authorized users.
Highlights
Strategic industrial location decisions have garnered considerable attention from the academic and business communities
Computational study we show the numerical experiments for the strategic industrial location selection using our hybrid multi-criteria/multidimensional approach
In the following stage, the weights of criteria and sub-criteria are calculated using fuzzyAHP, and these calculated weight values are used as input in the OLAP-MCDA process
Summary
Strategic industrial location decisions have garnered considerable attention from the academic and business communities. The success or failure of most industrial businesses often depends on the formal business plan of these businesses, and on the owner’s ability to choose his location within or among several industrial areas In this context, a priori selection of a suitable industrial location is a complex process which involves a number of different potential criteria, such as cost of investment, availability of acquisition material, human resources, etc., that must be considered in selecting a strategic industrial location (Yong 2005). A priori selection of a suitable industrial location is a complex process which involves a number of different potential criteria, such as cost of investment, availability of acquisition material, human resources, etc., that must be considered in selecting a strategic industrial location (Yong 2005) Following these considerations, several contributions have been dedicated to the location selection problem using different multi-criteria decision making methods such as fuzzy Delphi, fuzzy AHP, ANP (Analytic Network Process), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluations). Rao et al (2015) presents a fuzzy multi-attribute group decision making technique based on a linguistic 2-tuple for the location selection of a City Logistics Centers from a sustainability perspective
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