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INTERNAL BENCHMARKING IN RETAILING WITH DEA AND GIS: THE CASE OF A LOYALTY-ORIENTED SUPERMARKET CHAIN
Author(s) -
Amparo BavieraPuig,
Tomás Baviera,
Juan Manuel Buitrago Vera,
Carmen Escribá Pérez
Publication year - 2020
Publication title -
journal of business economics and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.485
H-Index - 37
eISSN - 1611-1699
pISSN - 2029-4433
DOI - 10.3846/jbem.2020.12393
Subject(s) - benchmarking , data envelopment analysis , loyalty , business , principal component analysis , variable (mathematics) , set (abstract data type) , computer science , marketing , industrial organization , operations research , mathematics , statistics , mathematical analysis , artificial intelligence , programming language
Data Envelopment Analysis (DEA) is a relative measure of efficiency applied to a set of decision units and is being used more and more frequently in the supermarket sector. Nonetheless, given how strongly the sector’s financials depend on demand, companies need to combine this measurement with trade area information to best manage corporate efficiency. In this paper, the proposal consists of integrating DEA with a clearly articulated, structural typology so that supermarkets, based on their particular characteristics, can determine which variables are most critical for improving their efficiency. This methodology has been validated in the case of one of Spain’s five largest supermarket chains. A principal component analysis and a classification analysis were carried out on a series of internal management variables from 61 locations for which DEA had been used to calculate efficiency and to which multiple trade area variables were added using GIS. Some of them are related to the loyalty scheme membership programme. These latter variables described the implantation of the loyalty scheme member programme and were revealed as key elements for the efficiency of the supermarket. This methodology provides marketing profiles that are more adapted to local circumstances, thus allowing companies to set better internal benchmarking objectives.

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