Request a copy

Full Text

42

CITATIONS

42 Total citations

10 Recent citations

11 Field Citation Ratio

n/a Relative Citation Ratio

publications

0

supporting

0

mentioning

0

contrasting

0

Smart Citations

0

0

0

0

Citing PublicationsSupportingMentioningContrasting

View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

• Afriat, S., Efficiency estimation of production functions. International Economic Review 13 (1972), 568–598.
• Bogetoft, P., DEA on relaxed convexity assumptions. Management Science 42 (1996), 457–465.
• Caves, D.W., Christensen, L.R., Diewert, W.E., The economic theory of index numbers and the measurement of input, output and productivity. Econometrica 50 (1982), 1393–1414.
• Camanho, A.S., Dyson, R.G., Data envelopment analysis and Malmquist indices for measuring group performance. Journal of Productivity Analysis 26 (2006), 35–49.
• Charnes, A., Cooper, W.W., Measuring the efficiency of decision making units. European Journal of Operational Research 2 (1978), 429–444.
• Chen, Y., A non-radial Malmquist productivity index with an illustrative application to chinese major industries. International Journal of Production Economics 83 (2003), 27–35.
• Chen, Y., Ali, A.I., DEA Malmquist productivity measure: new insights with an application to computer industry. European Journal of Operational Research 159 (2004), 239–249.
• Cherchye, L., Demuynck, T., De Rock, B., De Witte, K., Nonparametric analysis of multi-output production with joint inputs. Economic Journal 124 (2014), 735–755.
• Cherchye, L., De Rock, B., Dierynck, B., Roodhooft, F., Sabbe, J., Opening the black box of efficiency measurement: input allocation in multi-output settings. Operations Research 61 (2013), 1148–1165.
• Cherchye, L., De Rock, B., Vermeulen, F., Cost-efficient production behavior under economies of scope: a nonparametric methodology. Operations Research 56 (2008), 204–221.
• Cherchye, L., De Rock, B., Walheer, B., Multi-output efficiency with good and bad outputs. European Journal of Operational Research 240 (2015), 872–881.
• Cherchye, L., De Rock, B., Walheer, B., Multi-output profit efficiency and directional distance functions. Omega 61 (2016), 100–109.
• Cherchye, L., Moesen, W., Rogge, N., Van Puyenbroeck, T., An introduction to benefit of the doubt composite indicators. Social Indicators Research 82 (2007), 111–145.
• Cook, W.D., Seiford, L.M., Data envelopment analysis (DEA) - thirty years on. European Journal of Operational Research 192 (2009), 1–17.
• Cooper, W.W., Seiford, L.M., Zhu, J., Handbook on data envelopment analysis. 2004, Springer Edition.
• Cooper, W.W., Seiford, L.M., Tone, K., Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software. 2007, Springer.
• Daraio, C., Simar, L., Robust and nonparametric methods in efficiency analysis. methodology and applications. 2007, Springer.
• Debreu, G., The coefficient of resource utilization. Econometrica 19:3 (1951), 273–292.
• Despic, O., Despic, M., Paradi, J., DEA-r: ratio-based comparative efficiency model, its mathematical relation to DEA and its use in applications. Journal of Productivity Analysis 28 (2007), 33–44.
• Diewert, W.E., Parkan, C., Linear programming tests of regularity conditions for production frontiers. Shephard, R.W., Henn, R., Neumann, R., (eds.) Quantitative Studies on Production and Prices, 1983, Physics-Verlag, Heidelberg, Germany.
• Färe, R., Grosskopf, S., Network DEA. Socio-Economic Planning Sciences 34 (2000), 35–49.
• Färe, R., Grosskopf, S., Lovell, C.A.K., Production frontier. 1994, Cambridge University Press.
• Färe, R., Grosskopf, S., Norris, M., Productivity growth, technical progress and efficiency change in industrialized countries. American Economic Review 84 (1994), 66–83.
• Färe, R., Grosskopf, S., Norris, M., Productivity growth, technical progress and efficiency change in industrialized countries: reply. American Economic Review 87 (1997), 1040–1043.
• Färe, R., Grosskopf, S., Roos, P., On two definitions of productivity. Economics Letters 53 (1996), 269–274.
• Färe, R., Grosskopf, S., Noh, D.W., Weber, W., Characteristics of a polluting technology: theory and practice. Journal of Econometrics 126 (2005), 469–492.
• Färe, R., Grosskopf, S., Whittaker, G., Network DEA. Zhu, J., Cook, W., (eds.) Modeling data irregularities and structural complexities in data envelopment analysis, 2007, Springer.
• Färe, R., Grosskopf, S., Zelenyuk, V., Aggregation of cost efficiency: indicators and indexes across firms. Academia Economic Papers 32:3 (2004), 395–411.
• Färe, R., Zelenyuk, V., Aggregation of cost efficiency: indicators and indexes across firms. European Journal of Operational Research 146 (2003), 615–620.
• Färe, R., Zelenyuk, V., On Farrell's decomposition and aggregation. International Journal of Business and Economics 4:2 (2005), 167–171.
• Färe, R., Zelenyuk, V., Extending färe and Zelenyuk (2003). European Journal of Operational Research 179 (2007), 594–595.
• Farrell, M., The measurement of productive efficiency. Journal of the Royal Statistical Society, 1957, 253–281 Series 1, General, 120, Part 3.
• Fried, H., Lovell, C.A.K., Schmidt, S., The measurement of productive efficiency and productivity change. 2008, Oxford University Press.
• Goto, M., Tsutsui, M., Comparison of productive and cost efficiencies among japanese and US electric utilities. Omega 2 (1998), 177–194.
• Hanoch, G., Rothschild, M., Testing assumptions of production theory: a nonparametric approach. Journal of Political Economy 80 (1972), 256–275.
• Hattori, T., Relative performance of US and japanese electricity distribution: an application of stochastic frontier analysis. Journal of Productivity Analysis 18 (2002), 269–284.
• Huang, M.-Y., Juo, J.-C., Metafrontier cost Malmquist productivity index: an application to taiwanese and chinese commercial banks. Journal of Productivity Analysis 44 (2015), 321–335.
• Henderson, D.J., Russell, R.R., Human capital and convergence: a production-frontier approach. International Economic Review 46:4 (2005), 1167–1205.
• Kao, C., Malmquist productivity index based on common-weights DEA: the case of taiwan forests after reorganization. Omega 38 (2010), 484–491.
• Kao, C., Hwang, S.-N., Multi-period efficiency and Malmquist productivity index in two-stage production systems. European Journal of Operational Research 232 (2014), 512–521.
• Korhonen, P., Luptacik, M., Eco-efficiency of power plants: an extension of data envelopment analysis. European Journal of Operational Research 154:2 (2004), 437–446.
• Kumar, S., Russell, R., Technological change, technological catch-up, and capital deepening: relative contributions to growth and convergence. American Economic Review 92:3 (2002), 527–548.
• Malmquist, S., Index numbers and indifference surfaces. Trabajos de Estatistica 4 (1953), 209–242.
• Maniadakis, N., Thanassoulis, E., A cost Malmquist productivity index. European Journal of Operational Research 154 (2004), 396–409.
• Mayer, A., Zelenyuk, V., Aggregation of Malmquist productivity indexes allowing for reallocation of resources. European Journal of Operational Research 238 (2014), 774–785.
• Mayer, A., Zelenyuk, V., An Aggregation Paradigm for Hicks-Moorsteen Productivity Indexes, No WP012014. CEPA Working Papers Series, 2014, University of Queensland, School of Economics.
• O'Donnell, C.J., An aggregate quantity framework for measuring and decomposing productivity change. Journal of Productivity Analysis 38 (2012), 255–272.
• Oh, D.H., Lee, J.-D., A metafrontier approach for measuring Malmquist productivity index. Empirical Economics 38 (2010), 47–64.
• Panzar, J.C., Willig, R.D., Economies of scope. American Economic Review 71:2 (1981), 268–272.
• Pastor, J.T., Lovell, C.A.K., A global Malmquist productivity index. Economics Letters 88 (2005), 266–271.
• Pastor, J.T., Asmild, M., Lovell, C.A.K., The biennial Malmquist productivity change index. Socio-Economic Planning Sciences 45 (2011), 10–15.
• Petersen, N.C., Data envelopment analysis on a relaxed set of assumptions. Management Science 36 (1990), 305–314.
• Portela, M.C.A.S., Thanassoulis, E., Malmquist indices for measuring productivity in the presence of negative data: an application to bank branches. Journal of Banking and Finance 34 (2010), 1472–1483.
• Ray, S., Desli, E., Productivity growth, technical progress and efficiency change in industrialized countries: comment. American Economic Review 87 (1997), 1033–1039.
• Salerian, J., Chan, C., Restricting multiple-output multiple-input DEA models by disaggregating the output-input vector. Journal of Productivity Analysis 24 (2005), 5–29.
• Sarkis J., Cordeiro J.J. Ecological modernization in the electrical utility industry: an application of a bads-goods DEA model of ecological and technical efficiency. European Journal of Operational Research, 2012; 219, 386–395.
• Shephard, R.W., Cost and production functions. 1953, Princeton University Press.
• Shephard, R.W., Theory of cost and production functions. 1970, Princeton University Press.
• Simar, L., Outliers in frontier models: a simple approach. Journal of Productivity Analysis 20 (2003), 391–424.
• Thanassoulis, E., Shiraz, R.K., Maniadakis, N., A cost Malmquist productivity index capturing group performance. European Journal of Operational Research 241 (2015), 796–805.
• Tohidi, G., Razavyan, S., Tohidnia, S., A global cost Malmquist productivity index using data envelopment analysis. Journal of the Operational Research Society 63 (2012), 72–78.
• Tone, K., Tsutsui, M., Decomposition of cost efficiency and its application to japanese-US electric utility comparisons. Socio-Economic Planning Sciences 41 (2007), 91–106.
• Tone, K., Tsutsui, M., Network DEA: a slacks-based measure approach. European Journal of Operational Research 197 (2009), 243–252.
• Tulkens, H., On FDH analysis: some methodological issues and applications to retail banking, courts and urban transit. Journal of Productivity Analysis 4 (1993), 183–210.
• Varian, H.R., The non-parametric approach to production analysis. Econometrica 52 (1984), 579–598.
• Walheer, B., A multi-sector nonparametric production-frontier analysis of the economic growth and the convergence of the European countries. Pacific Economic Review 21:4 (2016), 498–524.
• Walheer, B., Growth and convergence of the OECD countries: a multi-sector production-frontier approach. European Journal of Operational Research 252 (2016), 665–675.
• Wang, Y.-M., Lan, Y.-X., Measuring Malmquist productivity index: a new approach based on double frontiers data envelopment analysis. Mathematical and Computer Modelling 54 (2011), 2760–2771.
• Yaisawang, S., Klein, J.D., The effects of sulfur-dioxide controls on productivity change in the united states electric-power industry. Review of Economics and Statistics 76 (1994), 447–460.
• Yang, B., Youliang, Z., Zhang, H., Zhang, R., Xu, B., Factor-specific Malmquist productivity indexbased on common weights DEA. Operation Research 16 (2016), 51–70.
• Yang, Y.L., Huang, C.J., Estimating the Malmquist productivity index in the taiwanese banking industry: a production and cost approach. Taiwan Economic Review 37 (2009), 353–378.
• Yu, M.M., The capacity productivity change and the variable input productivity change: a new decomposition of the Malmquist productivity index. Applied Mathematics and Computation 185 (2007), 375–381.
• Zelenyuk, V., Aggregation of Malmquist productivity indexes. European Journal of Operational Research 174 (2006), 1076–1086.