A risk-based hybrid multi-criteria approach to support managers in the industrial location selection in developing countries: A case study of textile sector in Africa

Despite the growing attention around industrial opportunities in African countries, the region is still struggling to enter the global competition. To seize opportunities and limit persisting risks, investors need to evaluate the most suitable country to locate or re-locate the supply chain relying on companies and sector requirements and considering all the variables. Researchers and practitioners have widely investigated methods and tools to support the decision-making process for location selection, primarily through the multi-criteria decision-making models. However, the criteria and approach required in developing countries are entirely different from developed ones primarily due to the variability and complexity of the context. As a matter of fact, there is no proof of integration of gap assessment elements and risk evaluation within the aim of multi-criteria decision-making models in emerging markets. This paper proposes a full-blown method that supports business leaders in the optimal foreign locations, integrating multi-criteria decision-making models (Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution) and cluster analysis (K-Means) with gap assessment evaluations. The proposed approach differs from the classical one in considering the distance between the selected options and target values, providing essential information to provide a risk assessment and positively affect the investment performance. The approach has been tested on African countries, considering a group of decision-makers from a Textile & Clothing Italian company. The results highlight that Mauritius is the most suitable location for the company, matching the current situation in the country. Moreover, the gap assessment phase provides crucial information about the main discrepancy in Mauritius, highlighting that there are still significant gaps in the “Environmental and territory conditions”, “Local infrastructure,” and “Technology and logistic supplier”.