| dc.description.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. | en_US |
