Dynamic directional nonparametric profit efficiency analysis for a single decision-making unit: an aggregation approach

Abstract We propose a simple and intuitive nonparametric technique to assess the profit performances of a single decision-making unit over time. The particularity of our approach lies in recognizing that technological change may be present in the profit evaluation exercise. We partition the periods of time into several time intervals, in such a way that the technology is fixed within intervals but may differ between intervals. Attractively, our approach defines a new Luenberger-type indicator for dynamic profit performance evaluation when a single decision-making unit is of interest, and provides a coherent and systematic way to compare the profit performance changes between the periods of time and the time intervals. To define the interval-level concepts, we rely on a flexible weighting linear aggregation scheme. We also show how the new indicator can be decomposed into several dimensions. We illustrate the usefulness of our methodology with the case of the Chinese low-end hotel industry in 2005–2015. Our results highlight a performance regression, which is mainly due to the technical components of the indicator decomposition.

[1]  A. Arbelo,et al.  Impact of quality on estimations of hotel efficiency , 2017 .

[2]  G. Battese,et al.  Metafrontier frameworks for the study of firm-level efficiencies and technology ratios , 2008 .

[3]  Timothy Coelli,et al.  Estimating and decomposing productivity growth of the electricity generation industry in Malaysia: A stochastic frontier analysis , 2013 .

[4]  Hirofumi Fukuyama,et al.  Profit Inefficiency of Japanese Securities Firms , 2008 .

[5]  Khalid Bichou,et al.  A two-stage supply chain DEA model for measuring container-terminal efficiency , 2011 .

[6]  Barnabé Walheer,et al.  Disaggregation of the cost Malmquist productivity index with joint and output-specific inputs , 2018 .

[7]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[8]  R. Färe,et al.  Profit, Directional Distance Functions, and Nerlovian Efficiency , 1998 .

[9]  Shabnam Razavyan,et al.  A global cost Malmquist productivity index using data envelopment analysis , 2012, J. Oper. Res. Soc..

[10]  Ming-Miin Yu,et al.  Profit-oriented productivity change , 2015 .

[11]  Valentin Zelenyuk,et al.  Aggregation of Malmquist productivity indexes , 2006, Eur. J. Oper. Res..

[12]  Hans Bjurek The Malmquist Total Factor Productivity Index , 1996 .

[13]  D. Varoutas,et al.  Economies of scale, cost minimization and productivity in telecom markets under economic crisis: evidence from Greece , 2017 .

[14]  Massimo Florio,et al.  Does privatisation matter? The long-term performance of British Telecom over 40 years , 2005 .

[15]  Chao-Chung Kang,et al.  Privatization and production efficiency in Taiwan's telecommunications industry , 2009 .

[16]  R. Chambers Exact nonradial input, output, and productivity measurement , 2002 .

[17]  A. Georges Assaf,et al.  Modelling the Performance of Australian Hotels: A DEA Double Bootstrap Approach , 2011 .

[18]  Zhenshan Yang,et al.  Do regional factors matter? Determinants of hotel industry performance in China , 2016 .

[19]  Valentin Zelenyuk,et al.  On aggregate Farrell efficiencies , 2003, Eur. J. Oper. Res..

[20]  Zhenshan Yang,et al.  Performance of Chinese hotel segment markets: Efficiencies measure based on both endogenous and exogenous factors , 2017, Journal of Hospitality and Tourism Management.

[21]  G. Battese,et al.  A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies , 2004 .

[22]  Toshiyuki Sueyoshi,et al.  Estimation of Stochastic Frontier Cost Function Using Data Envelopment Analysis: an Application to the AT&T Divestiture , 1991 .

[23]  Bharat Ramaswami,et al.  Food prices and the efficiency of public intervention: the case of the public distribution system in India , 2002 .

[24]  Hani I. Mesak,et al.  Dynamic efficiency assessment of the Chinese hotel industry☆ , 2011, Journal of Business Research.

[25]  Joe Zhu,et al.  DEA models for supply chain efficiency evaluation , 2006, Ann. Oper. Res..

[26]  K. F. See,et al.  Total factor productivity analysis of Malaysia Airlines: Lessons from the past and directions for the future , 2016 .

[27]  Rob Law,et al.  Progress in Chinese hotel research: A review of SSCI-listed journals , 2014 .

[28]  Rolf Färe,et al.  Productivity and Undesirable Outputs: A Directional Distance Function Approach , 1995 .

[29]  Jean-Philippe Boussemart,et al.  A decomposition of profit loss under output price uncertainty , 2015, Eur. J. Oper. Res..

[30]  L. R. Christensen,et al.  THE ECONOMIC THEORY OF INDEX NUMBERS AND THE MEASUREMENT OF INPUT, OUTPUT, AND PRODUCTIVITY , 1982 .

[31]  Benjamin Hampf,et al.  Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases , 2015 .

[32]  Mike G. Tsionas,et al.  Directional distance functions: Optimal endogenous directions , 2016 .

[33]  Laurent Botti,et al.  Performance of French destinations: Tourism attraction perspectives , 2011 .

[34]  Barnabé Walheer,et al.  Profit Luenberger and Malmquist-Luenberger indexes for multi-activity decision-making units: The case of the star-rated hotel industry in China , 2018, Tourism Management.

[35]  T. Coelli,et al.  Total factor productivity analysis of a single vertically integrated electricity utility in Malaysia using a Törnqvist index method , 2014 .

[36]  Liang Liang,et al.  Two-stage cooperation model with input freely distributed among the stages , 2010, Eur. J. Oper. Res..

[37]  M. Farrell The Measurement of Productive Efficiency , 1957 .

[38]  D Parker,et al.  THE PERFORMANCE OF BAA BEFORE AND AFTER PRIVATISATION. A DEA STUDY , 1999 .

[39]  Antreas D. Athanassopoulos,et al.  Technical efficiency and economies of scale in state owned enterprises: The Hellenic telecommunications organisation , 1998, Eur. J. Oper. Res..

[40]  Paolo Mancuso,et al.  Regulation and efficiency in transition: The case of telecommunications in Italy , 2012 .

[41]  Kristiaan Kerstens,et al.  A Luenberger-Hicks-Moorsteen productivity indicator: its relation to the Hicks-Moorsteen productivity index and the Luenberger productivity indicator , 2004 .

[42]  Alexander Vaninsky,et al.  Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis , 2006 .

[43]  Barnabé Walheer,et al.  Multi-Output Profit Efficiency and Directional Distance Functions , 2014 .

[44]  Valentin Zelenyuk,et al.  Aggregation of Malmquist productivity indexes allowing for reallocation of resources , 2014, Eur. J. Oper. Res..

[45]  Michael J. Gross,et al.  China hotel research: A systematic review of the English language academic literature , 2013, Tourism Management Perspectives.

[46]  Jinhe Zhang,et al.  Total Factor Productivity Assessment of Tourism Industry: Evidence from China , 2015 .

[47]  Hsihui Chang,et al.  Was the bell system a natural monopoly? An application of data envelopment analysis , 2006, Ann. Oper. Res..

[48]  D. Luenberger New optimality principles for economic efficiency and equilibrium , 1992 .

[49]  Kaoru Tone,et al.  Cost, revenue and profit efficiency measurement in DEA: A directional distance function approach , 2014, Eur. J. Oper. Res..

[50]  Adel Hatami-Marbini,et al.  An overall profit Malmquist productivity index with fuzzy and interval data , 2011, Math. Comput. Model..

[51]  Shabnam Razavyan,et al.  A circular global profit Malmquist productivity index in data envelopment analysis , 2013 .

[52]  R. Pine,et al.  Strategic Implications of Government Policies on the Future Group and Brand Development of State-owned Hotels in China , 2014 .

[53]  A. Ashrafi,et al.  Cost, Revenue and Profit Efficiency Models in Generalized Fuzzy Data Envelopment Analysis , 2017 .

[54]  Jing Yang,et al.  Analysis of Beijing's environmental efficiency and related factors using a DEA model that considers undesirable outputs , 2013, Math. Comput. Model..

[55]  José L. Ruiz,et al.  Measuring scale effects in the allocative profit efficiency , 2012 .

[56]  Yan Liu,et al.  The Research of Internet Information Services on the Impact of TourismDecision-Making , 2015 .

[57]  Yongjun Li,et al.  DEA Models for Extended Two-Stage Network Structures , 2012 .

[58]  Barnabé Walheer,et al.  Aggregation of metafrontier technology gap ratios: the case of European sectors in 1995-2015 , 2018, Eur. J. Oper. Res..

[59]  Rolf Färe,et al.  On endogenizing direction vectors in parametric directional distance function-based models , 2017, Eur. J. Oper. Res..