A Study on Financial-Accounting Methods for Prospecting the Lifetime Value of Hypermarket Business: A Critical Used of Geospatial Method - Bohari, Abdul Manaf; ., Malliga Marimuthu (Information Management and Business Review, 2013)
Recently, the hypermarket profitability is an important issue for the world wide retailing industry with vast literature was found on its definitions, measurements, and models of studied. In general, majority of related work showed that various methodologies and models have been applied to evaluate the profitability of hypermarket, where more dominants on financial and accounting methods. Specifically, estimate the hypermarket profitability are always dominating by financial and accounting methods and approaches with finale attention on maximizing the customer lifetime value (CLV). In fact, most of traditional measurement have been used are interest rate, chuck rate, lease, as well as income and consumptions of consumers. However, a little attention has been given to using others variables, as well as spatial based measurement although it has big potential to contributes on prospecting the profitability of hypermarket. In addition, continuously, financial or accounting variables has been improved and reused in different ways where the method itself in overall is still remains as before. The objective of this paper is to overview the weakness of financial and accounting methods with focused on theoretical and applications issues of estimating hypermarket profitability. Secondly, this paper is aimed to suggest geospatial method as alternative ways for bridged the gap of existing works regarding the estimations of hypermarket lifetime value. By using geospatial variables as well as spatial method, this work will contributes on establish new ways of estimated the CLV of the hypermarket where spatial platform is function to visualized the real situations of financial and accounting information as well as it emerge in the real marketplaces. In future, the use of geospatial method will be brings new hope on better understanding on CLV especially how CLV can estimated by both financial-accounting and spatial variables.