Exploring the retail industry environment using nonlinear analysis

Abstract

PurposeThe purpose of this paper is to explore the dynamics of the relationships between sales and internal and external environmental drivers in a retail company using a systems perspective in order to support retail management decisions with nonlinear methods.Design/methodology/approachThe research and results are presented in two parts: the collection and explorative analysis of the data; and discussion of the managerial implications following a systems perspective. The exploratory analysis is conducted using a statistical comparison of linear and nonlinear models of sales data from a retail company. The data, which comprise two data sets, come from 45 retail stores located in different regions of the USA.FindingsSpecifically, nonlinear models provided a better explanation of variation in retail activity (R2=46 per cent) than linear models (R2=16 per cent). In such a situation, the nonlinear analysis captures the influence of internal and external environmental drivers on retail sales.Research limitations/implicationsWith a limited variety of external and internal drivers, the exploratory analysis aims to describe a general situation in which retailers are managing activities in complex environments as opposed to reflect on a particular retail chain.Practical implicationsThe systems perspective is used to interpret the managerial implications of the nonlinear analysis fits, particularly in cases where retail decision-makers are adapting, transforming and restructuring sources of competitive advantage in complex environments.Originality/valueThe paper provides an alternative perspective (the systemic one) of how retailers could interpret the relationships between internal and external variables in the dynamic environment of the retail chains with nonlinear models.