PurposeThe aim of this paper is to illustrate the value of data envelopment analysis (DEA) for strategic analysis and performance management in the hotel industry.Design/methodology/approachThe paper uses a world‐wide sample of hotel companies and two cases to illustrate how DEA can be used to develop strategic guidelines to improve organizational performance.FindingsThe study shows that DEA can be used for strategic design and performance management through the analysis of two cases. Additionally, for the sample of 83 hotel companies, there are three main conclusions: a focused strategy performs better than a diversification strategy; for the bulk of the sample, the scale efficiency is higher than the pure technical efficiency, hence hotel managers should concentrate on productivity improvements (that is how to transform inputs into outputs) and not on scale issues (such as increases or decreases in the size of operations); and the majority of the hotel companies in the sample are operating under decreasing returns‐to‐scale, which implies that a decrease in the size of the companies would have a positive effect on the average efficiency level of the industry.Research limitations/implicationsThe paper has two limitations: the performance index created from the efficient frontier of the DEA model is a function of the hotel companies in the sample rather than an absolute measure; and the variables used as inputs and outputs for the DEA model were exclusively taken from the financial statements, which limits the strategic analysis.Practical implicationsThe DEA allows managers to analyze performance in terms of productivity and scale, to identify benchmarks (or peer units), to determine the targets (or optimum values) for inputs and outputs, and to detect slacks in the usage of resources or the production of outputs. Therefore, this methodology provides more insights for performance management than the traditional ratio analysis commonly used in the hotel industry.Originality/valueThe study is one of the few in the hotel industry to use DEA. The paper contributes to that corresponding literature by using: a larger sample size; a world‐wide sample of hotel companies; a longitudinal analysis (three years); and two illustrative cases to show how the information of a DEA model can be used for strategic analysis and performance management.
This paper presents the results from a field experiment that examines the effects of nonfinancial performance feedback on the behavior of professionals working for an insurance repair company. We vary the frequency (weekly and monthly) and the level of detail of the feedback that the 800 professionals receive. Contrary to what we would expect if these professionals conformed to the model of the Bayesian decision maker, more (and more frequent) information does not always help improve performance. In fact, we find that professionals achieve the best outcomes when they receive detailed but infrequent (monthly) feedback. The treatment groups with frequent feedback, regardless of how detailed it is, perform no better than the control group (with monthly and aggregate information). The results are consistent with the information in the latest feedback report being most salient and professionals in the weekly treatments overweighting their most recent performance, hampering their ability to learn.
This study investigates the performance effects of the combined use of three reinforcers, or incentive motivators, commonly used by companies: monetary incentives, feedback, and recognition. Using a field experiment in a retail services company, I test whether these incentives, which appeal to diverse motivation mechanisms—tangible payoffs, self-regulation, and social esteem—and, hence, have different utilities, are complements or substitutes. The results of the hard performance data collected, in the form of a ratio of sales relative to goals, show that monetary incentives and recognition are substitutes, while feedback is independent of the other incentives. The negative interaction between monetary incentives and recognition is evidence of crowding out between tangible payoffs and social esteem motivations. Individually, these two incentives have a positive impact on performance of about 13 percentage points, which corresponds to a 32.5 percent performance increase. Feedback interactions and main effects are not statistically significant, which suggests that, in this setting, providing feedback in the form of knowledge of results has no impact.
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