An empirical analysis of productivity growth in a Portuguese retail chain using Malmquist productivity index

https://doi.org/10.1016/S0969-6989(03)00053-5Get rights and content

Abstract

This paper estimates total productivity change and decomposes it into technically efficient change and technological change for a Portuguese retail store chain with data envelopment analysis. The benchmarking procedure implemented is an internal benchmarking, where the stores in the chain are compared against each other. The aim of this procedure is to seek out those best practices that will lead to improved performance throughout the whole chain. We rank the stores according to their total productivity change for the period 1999–2000, concluding that some stores experienced productivity growth while others experienced productivity decrease. Managerial implications arising from the study are considered.

Introduction

The Portuguese retail sector is confronted at the present time with several threats that clouds its future independence. These threats are the following: first, the increasing number of major international retailers (in particular, from Spain and France) entering the Portuguese retail market, intensifying the competition and the shrinkage of the margins; second, the small dimension of the Portuguese retailers, which prevents expansion into the European market, lacking the economies of scale that exist for larger operators who can benefit from doing business in several contiguous markets; third, an inadequate state policy that has prevailed in recent years, restricting the growth of hypermarkets and the shrinkage of small grocery stores (Farhangmehr et al., 2000); fourthly, the small dimension of the market and the relative shallowness of disposable income; fifth, the widespread availability of expensive, imported brands of all consumer goods, out of proportion to the market's average purchasing power. This is currently in sharper focus, owing to the effects of a severe economic downturn; lastly, the existing structural rigidities in the labour market.

The national retail industry reacts to these threats by attempting to increase the efficient use of inputs. One procedure to improve competitiveness is benchmarking. Benchmarking is the outcome of an investigation into an industry's best practices, in order that their generalised application might lead to improved performance throughout the whole industry (Walters and Laffy, 1996; Dunne et al., 1992). The efficiency of retail stores is a major theme in contemporary research, i.e. Balakrishan et al. (1994), Athanassopoulos (1995), Kamakura et al. (1996), Thomas et al. (1998) and Donthu and Yoo (1998). Among the benchmarking techniques, data envelopment analysis (DEA), a non-parametric technique, has been used previously, for example in Thomas et al. (1998) and Donthu and Yoo (1998). In the present paper, we analyse the intra-chain comparative efficiency of a major Portuguese retail company, assessing the efficiency of a sample of individual stores by applying a variety of metrics to measure inputs and outputs that combine financial, as well as operational, dimensions. Moreover, we evaluate total productivity with the Malmquist index.

The contribution of this paper to literature on the retail sector is based on the application of the Malmquist index to evaluate retail efficiency.

The paper is organised as follows. In Section 2, we describe the contextual setting, describing the Portuguese retailing sector in order to shed some light on the threats mentioned above. In Section 3, we survey the existing literature on the topic, with a view to highlighting the contribution that the present paper seeks to make. In Section 4, we explain the theoretical framework supporting the model used. In 5 Data, 6 Results, we present the data and results. In Section 7, we consider the managerial implications of the study. In Section 8, we put forward the limitations and possible extensions of the study and finally, in Section 9, we make our concluding remarks.

Section snippets

Contextual setting

On Portugal's accession to the European Union in 1986, the country's retail market embarked on a course of profound changes that are reflected in Table 1. These changes have led to the rapid and widespread expansion of hypermarkets and supermarkets throughout the country and to the concomitant decline of small self-service stores, grocery shops and pure food stores, which were formerly the nation's leading retailers of foodstuffs and other domestic products.

This trend induced a political

Literature survey

Early studies on retailing efficiency focussed on partial aspects of productivity, such as labour productivity (Ratchford and Brown, 1985); other aspects under the control of retail management that affect the efficiency of a store, such as merchandise assortment (Mahajan et al., 1988), location (Mahajan et al., 1985), pricing (Mahajan, 1991) and promotion (Weitzel et al., 1989), besides aspects beyond the management's control, such as employment patterns, business cycles and trading area

Theoretical framework

In this paper, we adopt the efficient frontier approach using the Malmquist productivity index, based on DEA.

The Malmquist productivity index allows changes in productivity to be broken down into changes in efficiency and technical change.

To set the scene for our productivity measurement, we adopt the framework set in the paper by Fare et al. (1990), Hjalmarsson and Veiderpass (1992) and Price and Weyman-Jones (1996). Fig. 1 shows two observations on the input (x) and output (y) bundles used by

Data

To estimate the production frontier, we used cross-section data for the years 1999 and 2000, obtained from one of Portugal's leading hypermarket and supermarket chains, on 47 of its retail outlets. The outlets that are considered in the analysis are those listed in Table 4. The data are used for internal marketing control purposes.

To choose the inputs of the DMUs, we must take into account the distinction between controllable and uncontrollable factors. There are two alternatives for making

Results

The Malmquist index can be calculated in several ways (Caves et al., 1982). In the present study, we estimate an output-oriented Malmquist productivity index, based on DEA. Output-oriented efficiency measurements are adequate, if we assume that retail stores behave in a competitive way. In output-oriented models, such as the one adopted in this paper, the DEA seeks to identify technical inefficiency as a proportional increase in output usage. However, it is possible to measure an input-oriented

Managerial implications of the study

This paper has proposed a simple framework for the evaluation of retail chains and the rationalisation of their management activities. The analysis is based on a DEA model that allows for the incorporation of multiple inputs and outputs in determining the relative efficiencies. Benchmarks are provided for improving the operations of poorly performing stores. We emphasise two managerial implications of our findings. First, the group management should change its managerial procedure in order to

Limitations and extensions of this study

The DEA model does not impose any functional form on the data, nor make distributional assumptions for the inefficiency term. This efficiency measurement assumes that the production function of the fully efficient outlet is known. In practice, this is not the case and the efficient isoquant must be estimated from the sample data. In these conditions, the frontier is relative to the sample considered in the analysis. Moreover, without statistical distribution hypotheses, the DEA does not allow

Conclusion

This article has proposed a simple framework for the evaluation of retail outlets and the rationalisation of their operational activities. The analysis is based on a DEA model that allows for the incorporation of multiple inputs and outputs in determining the relative efficiencies. Benchmarks are provided for improving the operations of poorly performing retail outlets. Several interesting and useful managerial insights and implications from the study are raised. The general conclusion is that

References (34)

  • D.W Caves et al.

    The economic theory of index numbers and the measurement of input, output and productivity

    Econometrica

    (1982)
  • Coelli, T.J., 1996. A guide to DEAP version 2.1: a data envelopment analysis (Computer) program. Working Paper No....
  • T.J Coelli et al.

    An Introduction to Efficiency and Productivity Analysis

    (1998)
  • J Doutt

    Comparative productivity performance in fast food retail distributions

    Journal of Retailing

    (1984)
  • P Dunne et al.

    Retailing

    (1992)
  • R.S Fare et al.

    Production Frontiers

    (1994)
  • M.J Farrel

    The measurement of productive efficiency

    Journal of the Royal Statistical Society, Series A

    (1957)
  • Cited by (88)

    • Spillover effects of investment in big data analytics in B2B relationships: What is the role of human capital?

      2020, Industrial Marketing Management
      Citation Excerpt :

      Some studies focus on technical efficiency change and its contribution to productivity growth. For instance, Barros and Alves (2004) and Sellers-Rubio and Mas-Ruiz (2007) have computed a Malmquist index and its components to measure technical efficiency change of Portuguese and Spanish supermarket chains, respectively. Barros and Alves (2004) have used the Malmquist index to decompose productivity growth of 47 stores of a Portuguese supermarket chain into pure technical efficiency change; scale efficiency change; and technology change.

    • Sustainability-oriented efficiency of retail supply chains: A combination of Life Cycle Assessment and dynamic network Data Envelopment Analysis

      2020, Science of the Total Environment
      Citation Excerpt :

      The evaluation of RSC efficiency can serve as an instrument for sustainability assessment, pursuing the delivery of competitively priced goods and services that satisfy human needs while reducing the use of resources and the environmental impacts from a life-cycle perspective. Among the analytical tools available for efficiency assessment, Data Envelopment Analysis (DEA) has been extensively applied to the service sector (Avkiran, 2011), including the assessment of retail stores (Barros and Alves, 2003, 2004). It is a linear programming methodology that quantifies in an empirical manner the relative efficiency of multiple similar entities, called decision making units (DMUs) (Cooper et al., 2007).

    • Sustainability-oriented management of retail stores through the combination of life cycle assessment and dynamic data envelopment analysis

      2019, Science of the Total Environment
      Citation Excerpt :

      Previous studies in this area have presented a number of methods to evaluate operational retail efficiency, e.g. data envelopment analysis (DEA), regression, and stochastic frontier analysis. In particular, compared to other options such as parametric regression, DEA emerges as a suitable tool for measuring retail efficiency when assessing a large number of resembling entities without relying on an exogenous definition of a specific production function (Barros and Alves, 2003, 2004; Lozano et al., 2009; Avkiran, 2011). It is a linear programming methodology that quantifies in an empirical manner the comparative productive efficiency of multiple similar entities or decision making units (DMUs) such as – in this case – retail stores within a firm (Cooper et al., 2007).

    • Efficiency, productivity gains, and the size of Brazilian supermarkets

      2018, International Journal of Production Economics
    • Investment efficiency of urban infrastructure systems: Empirical measurement and implications for China

      2017, Habitat International
      Citation Excerpt :

      However, there were ups and downs of TEC throughout the analysis period. Since TEC is the product of PEC and SEC, the fluctuation of technical efficiency is a combined effect of PEC and SEC. The improvement in PEC indicates a progress in management skills, such as a better balance between inputs and outputs, the improvement of quality (Barros & Alves, 2004). From 2005 to 2008, the technical efficiency was decreased; the main reason is that the pure efficiency decreased, that is, management and operations activities are the major cause for the decline in TEC.

    View all citing articles on Scopus
    View full text