The out-of-shelf problem is among the most important retail problems. This work employs two different classification algorithms, C4.5 and naı̈ve Bayes, in order to build a mechanism that makes decisions about whether a product is available on a retail store shelf or not. Following the same classification methods and feature spaces, we examined the classification performance of the algorithms in ...

It is well-established that increased product visibility to shoppers leads higher sales for retailers. In this study, we propose an optimization methodology which assigns categories and subcategories store locations sublocations maximize the overall of products shoppers. The hierarchically developed meet strategic tactical layout planning needs brick-and-mortar Layouts in both levels are optimi...

The Indian economy with its liberalisation in 1991, introduced the domestic customers to new ways of shopping and raised expectations by pampering hitherto cloistered Indian. generation which grew up this customer-centric atmosphere were Millennial (currently 13 30 year olds) who not only savoured attention lavished on them, but became more demanding discerning than earlier generations. Identif...

This paper uses lottery allocation of retail store entry licenses as a natural experiment to understand the size and source returns scale in retail.

In this paper we study the drivers and consequences of understaffing in retail stores by examining the longitudinal data on traffic flow, sales and store managers’ labor planning decisions of 41 stores in a large retail chain. Assuming store managers are profit-maximizing agents, we use a structural estimation technique to estimate the contribution of labor to sales and impute the cost of labor...