This Special Issue of Business Research Quarterly is devoted to a very timely subject, the illustration and application of performance measurement methodologies designed to guide managerial decision-making and enhance business performance. Establishing a link between managerial decision-making and business performance is of critical importance, and has been the subject of renewed interest recently, notably at the World Management Survey (http://worldmanagementsurvey.org/), where a global data base supports research into the drivers of, and business performance consequences of, the widely documented variation in the quality of management practices. Quantifying and explaining the equally widely documented gap between “the best and the rest” performing businesses features prominently in the OECD Global Forum on Productivity (http://www.oecd.org/global-forum-productivity/).
The concept of business performance is broad, potentially encompassing the efficiency with which labor, materials, and other resources under management control are allocated to the production of goods and services; the efficiency with which produced goods and services are allocated across markets; the growth in the productivity of employed resources in generating desired goods and services, and, ultimately; business competitiveness and financial performance.
The concept of measurement is central to establishing a linkage between management and performance because, as Peter Drucker is alleged to have claimed, “you can’t manage what you can’t (or don’t) measure”. The performance measurement methodologies we consider are reasonably well-established, having originated in the economics, management science and operations research literatures in the 1970s. These methodologies use econometric and mathematical programming techniques to estimate best practice “frontiers” that envelop, rather than intersect, performance data obtained from a sample of comparable businesses. The techniques are used to measure the performance of businesses relative to best practice, and to identify high-performing peers that may serve as useful role models. Best practice frontiers can be defined in many useful ways. They can consist of the most energy-efficient businesses, the most productive businesses, the most environmentally or socially responsible businesses, the most cost-efficient businesses, the businesses having the highest return on assets or other popular financial ratio, and so on, depending on the perceived objectives of the sampled businesses and the constraints under which they operate.
It is useful to think of these business performance measurement methodologies as sophisticated versions of, or preferably as complements to, the wide-ranging collection of business practices known as benchmarking, presumably against best practice somehow defined, typically through the specification of key performance indicators. A significant difference between these business performance measurement methodologies and conventional benchmarking is that the former have been developed in academe, and tend to be more mathematically and statistically sophisticated than the latter, which have been developed largely outside academe, beginning perhaps with Robert C. Camp, Manager of Benchmarking Competency Quality and Customer Satisfaction at Xerox, ironically also in the 1970s. Equally ironically, the literature suggests that 40 years on, Xerox was not a well-managed firm. A second difference concerns the concept of best practice itself, which is rigorously defined in the former and loosely defined in the latter, leading us to conjecture that intellectual interaction may be mutually beneficial.
A consequence of the differences between the two methodologies concerns their relative popularity. A recent Google search on “stochastic frontier analysis”, the econometric performance measurement methodology, returned over two million results, and a Google search on “data envelopment analysis”, the mathematical programming performance measurement methodology, returned over one million results. In sharp contrast, a Google search on “benchmarking” returned over 50 million results, and a narrower search on “benchmarking against best practice” returned over 22 million results. The performance measurement methodologies applied in this Special Issue are making inroads in the management and business literature, but they remain in catch-up mode.
Just as benchmarking has many variants, so too do the performance measurement methodologies employed in the papers selected for inclusion in this Special Issue. Four papers adopt the econometric approach to analyze business performance, one adopts the mathematical programming approach, and all are compatible with both approaches. Some papers examine variants of productive efficiency, some examine competitiveness and some examine financial performance. Markets within which business performance is evaluated range from running shoes in Spain, to production lines at a Brazilian manufacturer, to small- and medium-sized Spanish firms, to regulated Dutch municipal public services, to US banks, and to an international sample of knowledge-intensive business service firms. The final paper, our contribution with Turon, is relevant to all firms and agencies, and explores how the creation of private and social value can contribute to the progress of society.
We anticipate that the papers in this Special Issue will spark the interest of readers of, and contributors to, Business Research Quarterly, in learning about these business performance measurement methodologies and their considerable potential for guiding management practices and enhancing business performance, however it may be measured. A brief summary of each paper follows.
In “Estimating Product Efficiency through a Hedonic Pricing Best Practice Frontiers” Arrondo and colleagues use the econometric approach to examine a common marketing problem, product pricing as a determinant of business financial performance. They estimate the efficiency of product pricing of running shoes in Spain. Among their interesting insights, they suggest that, controlling for a range of product characteristics, running shoes are overpriced, some brands more than others, relative to a competitive pricing frontier. The use of best practice frontier techniques to examine pricing efficiency rather than production efficiency is novel, and is to be encouraged.
In “Do the Improvement Programs Really Matter? An Analysis Using Data Envelopment Analysis” Guarani de Souza and colleagues use the mathematical programming approach to examine the impacts of continuous improvement programs and training of production teams on production volume and productive efficiency across production lines at an ageing Brazilian armaments manufacturer. The authors attribute disappointing impacts of these popular management strategies on both production volume and productive efficiency to the obsolescence of the machinery and technology at the business.
In “Profit Efficiency and its Determinants in Small- and Medium-Sized Enterprises in Spain” Pérez-Gómez and colleagues use the econometric approach to explore the ability of small and medium-sized Spanish food manufacturing enterprises to reach their profit potential as determined by best practice in a large domestic panel. After controlling for firm age, size, export status and other influences, the authors still find surprisingly low average profit efficiency, suggesting an enormous amount of foregone, or wasted, profit that threatens the survival of lagging enterprises. The authors discuss alternative management strategies and public policies that might close the profit gap between leaders and laggards.
In “Measuring the Performance of Local Administrative Public Services” Blank uses the econometric approach to evaluate the efficiency with which a large panel of Dutch municipalities delivers a range of local public services. Requested services must be provided, making cost efficiency an appropriate criterion for evaluating performance. Among the policy-relevant findings are the presence of scale economies, suggesting that merging small municipality offices and splitting up large municipality offices might both confer cost savings, a relatively narrow variation in cost efficiency, suggesting a limited role for efficiency gains through learning and other channels, and the absence of productivity growth despite growth in ICT adoption.
In “Frontier Efficiency, Capital Structure, and Portfolio Risk: An Empirical Analysis of U.S. Banks” Ding and Sickles use the econometric approach to estimate cost efficiency in a large panel of US banks. They find that relatively cost-efficient banks tend to increase capital buffers, variously defined, beyond Basel I and Basel II requirements and reduce riskiness, also variously defined, of their asset portfolios. They also find that portfolio risk varies directly with bank size, which supports a “too big to fail” hypothesis, and inversely with cost efficiency, which supports a moral hazard hypothesis. Although banks are idiosyncratic institutions in many ways, most of the hypotheses tested in this paper are applicable to other businesses.
Finally, in “The Business Foundations of Social Economic Progress” Grifell-Tatjé, Lovell and Turon extend business performance measurement beyond the boundaries of an individual business to the society in which it operates, and develop an approach that shares some features with the corporate social responsibility (CSR) literature. They view business value creation as a necessary, but not sufficient, condition for the business to contribute to social economic progress, defined broadly and loosely to include (i) reduced economic inequality, (ii) re-employment of resources, primarily labor, displaced by the productivity growth that created value, and (iii) minimization of negative externalities such as environmental degradation. They provide an analytical framework within which to examine social economic value creation, and which can be implemented using either econometric or mathematical programming methodologies.