Optimal Selection of Cities of Energy Outlets in Developing Countries: An Application of Fuzzy Set Theory to Sri Lankan Solar Industry

Abstract

The concept of benefit gains is inherently fuzzy in nature. Hence, this study seeks to propose a logic-based innovative formalism that helps in effective decision-making in dynamic, imprecise, inconclusive, and volatile business environments underpinned by technology. Such an attempt, deriving from Fuzzy Set Theory, is needed as we apply this model to the financial gain based optimal selection of cities to establish business outlets with reference to the solar power generation industry. Modelling the perceptions of domain experts is an integral part of the fuzzy approach. However, these linguistic inputs of experts become intelligible only when quantified through similarity methods and fuzzy tolerance relations comparing the yielded values against proximity ratios. The acquisition of expert knowledge was made by interviewing five economic and finance-proficient individuals in Sri Lanka with tacit know-how. The fuzzy inference was used to transform qualitative words and quantitative data into objective crisp values. The study was operationalized through computing with words, cosine amplitude transformation, and Bellman Zadeh approach. Both the Fuzzy Inference System and Bellman Zadeh’s approach were amalgamated for data analysis. In deriving the membership values, two business goals of monetary nature were formulated. The findings reveal that the country’s politics, business owners’ financial solvency, operational maintenance, and business foresight are the constraints that impact financial gains and accomplishing defined goals at variance. Among these, politics and business foresight are external factors, while solvency and operational maintenance are internalised.