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Journal articles on the topic 'Luenberger Productivity Indicator (LPI)'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

AllaEldin, H. Kassam* Asma A. Mohammed Ali. "PRODUCTIVITY ANALYSIS IN IRAQI HOSPITALS." Global Journal of Engineering Science and Research Management 4, no. 5 (2017): 99–106. https://doi.org/10.5281/zenodo.801289.

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Analyzing productivity and efficiency in Iraqi hospitals using non-parametric frontier technique is important issue. Two indices approach are used: first, Malmquist productivity index (MPI), with output orientation, and the second is a Luenberger productivity indicator (LPI) that can measure by both input reduction and output expansion. A sample of three hospitals in (Baghdad) district are taken to evaluate the productivity progress and its decomposition efficiency change and technological change, over two year period (2014-2015). The results reveled all hospitals in the study had a productivi

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2

Goyal, Swati, Shivi Agarwal, and Trilok Mathur. "An evaluation of the productivity change in public transport sector using DEA-based model." Management Science Letters 12, no. 2 (2022): 125–36. http://dx.doi.org/10.5267/j.msl.2021.10.001.

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This study aims to build a framework for measuring the productivity in the public transport sector through a data envelopment analysis (DEA) technique. This paper extends the Malmquist productivity index (MP1) and Luenberger productivity indicator (I.P1) evaluation with the concept of an input-oriented new slack model (NSM). NSM model measures the efficiency with the effect of slacks and satisfies unit invariance, radial and translation invariance properties. In particular, the purpose of the proposed extension is to obtain the overall productivity change in terms of technical change (Frontier

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3

Tzeremes, Nickolaos G. "Hotel productivity: A robust Luenberger productivity indicator." Tourism Economics 25, no. 6 (2019): 987–96. http://dx.doi.org/10.1177/1354816618821271.

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The article presents a robust version of the Luenberger productivity indicator. The proposed productivity indicator is less sensitive to potential outliers and extreme values. We apply the robust productivity index on a sample of 176 hotels operating in the Canary Islands over the period from 2004 to 2013. The results indicate that hotels have increased their productivity levels over the examined time period. In relation to their productivity levels, it is also evident that hotels have demonstrated strong resilience during the global financial crisis. Finally, it is evident that hotels have be

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4

Lin, Yu-Hui, Tsu-Tan Fu, Chia-Li Chen, and Jia-Ching Juo. "Non-radial cost Luenberger productivity indicator." European Journal of Operational Research 256, no. 2 (2017): 629–39. http://dx.doi.org/10.1016/j.ejor.2016.06.031.

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5

Briec, Walter, and Kristiaan Kerstens. "A Luenberger-Hicks-Moorsteen productivity indicator: its relation to the Hicks-Moorsteen productivity index and the Luenberger productivity indicator." Economic Theory 23, no. 4 (2004): 925–39. http://dx.doi.org/10.1007/s00199-003-0403-2.

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6

Kapelko, Magdalena, Alfons Lansink, and Spiro Stefanou. "Analysis of Static and Dynamic Productivity Growth in the Spanish Meat Processing Industry." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 12, no. 3 (2012): 24–36. http://dx.doi.org/10.22630/prs.2012.12.3.35.

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This paper estimates static Malmquist and dynamic Luenberger productivity growth measures and decomposes these to identify the contributions of technical change, technical efficiency change and scale efficiency change. The Malmquist and Luenberger productivity growth measures are estimated using Data Envelopment Analysis. The empirical application uses data on Spanish meat processing firms over the period 2000-2010. The dynamic Luenberger indicator and the static Malmquist index show, in the period under investigation, a productivity decrease of, on average, 0.3% and 1% respectively. In both m

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7

Abad, Arnaud, Rabaozafy Louisa Andriamasy, and Walter Briec. "Surplus measures and luenberger Hicks–Moorsteen productivity indicator." Journal of Economics 125, no. 3 (2018): 279–308. http://dx.doi.org/10.1007/s00712-018-0611-7.

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8

Chen, Xiang, Tsu-Tan Fu, Jia-Ching Juo, and Ming-Miin Yu. "A comparative analysis of profit inefficiency and productivity convergence between Taiwanese and Chinese banks." BRQ Business Research Quarterly 23, no. 3 (2020): 193–202. http://dx.doi.org/10.1177/2340944420941439.

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To insure a proper and meaningful productivity assessment of DMUs with different production technologies, this article develops a difference-based profit metafrontier Luenberger productivity indicator. Adopting the proposed model, we empirically measure the profit inefficiency and examine the profit productivity convergence for samples banks consisting of 31 Taiwanese banks and 50 Chinese city banks over 2010–2014. Empirical results show that Chinese banks perform better in profit efficiency than Taiwanese banks. While Chinese banks have better technology in profit creation than Taiwanese bank

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9

Seufert, Juergen Heinz, Amir Arjomandi, and K. Hervé Dakpo. "Evaluating airline operational performance: A Luenberger-Hicks-Moorsteen productivity indicator." Transportation Research Part E: Logistics and Transportation Review 104 (August 2017): 52–68. http://dx.doi.org/10.1016/j.tre.2017.05.006.

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10

Briec, Walter, and Kristiaan Kerstens. "The Luenberger productivity indicator: An economic specification leading to infeasibilities." Economic Modelling 26, no. 3 (2009): 597–600. http://dx.doi.org/10.1016/j.econmod.2009.01.007.

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11

Ang, Frederic, and Pieter Jan Kerstens. "A superlative indicator for the Luenberger-Hicks-Moorsteen productivity indicator: Theory and application." European Journal of Operational Research 285, no. 3 (2020): 1161–73. http://dx.doi.org/10.1016/j.ejor.2020.02.030.

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12

Orozco Gallo, Antonio José, and Camilo Almanza Ramírez. "Evaluating Colombian public hospitals productivity during 2004-2015. A Luenberger-Indicator approach." Gerencia y Políticas de Salud 19 (October 2, 2020): 1–23. http://dx.doi.org/10.11144/javeriana.rgps19.ecph.

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Background: In Colombia, public policy has encouraged hospital efficiency and sustainability since 1993, when its health system underwent a profound change with the Law 100. Method: We estimate the efficiency and productivity of Colombian public hospitals using the Luenberger productivity indicator. This less restrictive indicator allows for a disaggregated regional analysis and does not overestimate the change in productivity when compared to other measures. It was made an empirical application to a sample of 260 hospitals during the 2004-2015 period. Results: The results show a productivity

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13

Brandouy, Olivier, Walter Briec, Kristiaan Kerstens, and Ignace Van de Woestyne. "Portfolio performance gauging in discrete time using a Luenberger productivity indicator." Journal of Banking & Finance 34, no. 8 (2010): 1899–910. http://dx.doi.org/10.1016/j.jbankfin.2009.12.015.

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14

Epure, Mircea, Kristiaan Kerstens, and Diego Prior. "Bank productivity and performance groups: A decomposition approach based upon the Luenberger productivity indicator." European Journal of Operational Research 211, no. 3 (2011): 630–41. http://dx.doi.org/10.1016/j.ejor.2011.01.041.

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15

Juo, Jia-Ching, Yu-Hui Lin, and Tsai-Chia Chen. "Productivity change of Taiwanese farmers’ credit unions: a nonparametric metafrontier Malmquist–Luenberger productivity indicator." Central European Journal of Operations Research 23, no. 1 (2013): 125–47. http://dx.doi.org/10.1007/s10100-013-0307-6.

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16

Yousif, Ibraheem A. H., Ali Abdel Hamid, Abdalsamad A. Aldabaa, et al. "Soil quality indicator-based land productivity modelling for agricultural sustainability." PLOS ONE 20, no. 1 (2025): e0316840. https://doi.org/10.1371/journal.pone.0316840.

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Rapid population expansion has made food security a global concern for humanity, necessitating a sustainable assessment of natural resources. Well evaluated and managed soil is one of the most significant resources that can assist close the gap between supply and demand for food to attain food security. A precise assessment of land productivity (LP) is essential for sustainable land use management. The primary aim of this research is to predict the land productivity index (LPI) for certain locations on Egypt’s northwest coast under current conditions using soil quality indicators (SQIs). Addit

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17

Niu, Zhiyong, Yining Zhang, Tianxiang Li, Tomas Baležentis, Dalia Štreimikienė, and Zhiyang Shen. "TOTAL FACTOR PRODUCTIVITY GROWTH IN CHINA’S CORN FARMING: AN APPLICATION OF GENERALIZED PRODUCTIVITY INDICATOR." Journal of Business Economics and Management 22, no. 5 (2021): 1189–208. http://dx.doi.org/10.3846/jbem.2021.15105.

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Total factor productivity (TFP) growth measures usually focus on a certain direction of optimization and ignore the general setting encompassing the input and output orientations simultaneously. This paper uses the generalized Luenberger-Hicks-Moorsteen (LHM) TFP indicator which is additively complete and can be decomposed by three mutually exclusive elements. The input- and output-oriented analysis is undertaken in order to derive the generalized TFP measured. The paper uses the corn production data from 19 Chinese provinces over the period of 2004–2017. This research is important as China is

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18

Shen, Zhiyang, Tomas Baležentis, and Gary D. Ferrier. "Agricultural productivity evolution in China: A generalized decomposition of the Luenberger-Hicks-Moorsteen productivity indicator." China Economic Review 57 (October 2019): 101315. http://dx.doi.org/10.1016/j.chieco.2019.101315.

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19

Barros, Carlos Pestana, António Gomes de Menezes, Nicolas Peypoch, Bernardin Solonandrasana, and José Cabral Vieira. "An analysis of hospital efficiency and productivity growth using the Luenberger indicator." Health Care Management Science 11, no. 4 (2008): 373–81. http://dx.doi.org/10.1007/s10729-007-9043-6.

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20

Wang, Daoping, Kerui Du, and Ning Zhang. "Measuring technical efficiency and total factor productivity change with undesirable outputs in Stata." Stata Journal: Promoting communications on statistics and Stata 22, no. 1 (2022): 103–24. http://dx.doi.org/10.1177/1536867x221083886.

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In this article, we introduce two community-contributed data envelopment analysis commands for measuring technical efficiency and productivity change in Stata. Over the last decades, an important theoretical progression of data envelopment analysis, a nonparametric method widely used to assess the performance of decision-making units, is the incorporation of undesirable outputs. Models able to deal with undesirable outputs have been developed and applied in empirical studies for assessing the sustainability of decision-making units. These models are getting more and more attention from researc

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21

Setiawan, Maman, Nury Effendi, Rina Indiastuti, Mohamad Fahmi, and Budiono. "Innovation and Dynamic Productivity Growth in the Indonesian Food and Beverage Industry." Resources 11, no. 11 (2022): 98. http://dx.doi.org/10.3390/resources11110098.

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This paper examines the relationship between innovation and dynamic productivity growth in the Indonesian food and beverage industry. Dynamic productivity growth is calculated using a Luenberger indicator, and innovation is represented by a process innovation. This research uses firm-level data for the period 1980–2015 sourced from the Indonesian Central Bureau of Statistics. This research uses a panel data regression model to estimate the relationship between innovation and dynamic productivity growth. This research finds that innovation is relatively low in the Indonesian food and beverage i

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22

Abad, A. "An environmental generalised Luenberger-Hicks-Moorsteen productivity indicator and an environmental generalised Hicks-Moorsteen productivity index." Journal of Environmental Management 161 (September 2015): 325–34. http://dx.doi.org/10.1016/j.jenvman.2015.06.055.

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23

Barros, Carlos Pestana, Nicolas Peypoch, and Jonathan Williams. "A note on productivity change in European cooperative banks: the Luenberger indicator approach." International Review of Applied Economics 24, no. 2 (2010): 137–47. http://dx.doi.org/10.1080/02692171003590047.

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24

Barros, Carlos Pestana, and Nicolas Peypoch. "Comparing Productivity Change in Italian and Portuguese Seaports using the Luenberger Indicator Approach." Maritime Economics & Logistics 9, no. 2 (2007): 138–47. http://dx.doi.org/10.1057/palgrave.mel.9100176.

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25

Mahlberg, Bernhard, and Biresh K. Sahoo. "Radial and non-radial decompositions of Luenberger productivity indicator with an illustrative application." International Journal of Production Economics 131, no. 2 (2011): 721–26. http://dx.doi.org/10.1016/j.ijpe.2011.02.021.

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26

Barnhart, Bradley L., Moriah Bostian, Rolf Färe, Shawna Grosskopf, and Sophia M. Lochner. "A productivity indicator for adaptation to climate change." PLOS Climate 2, no. 11 (2023): e0000199. http://dx.doi.org/10.1371/journal.pclm.0000199.

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This study draws on economic index theory to construct a new indicator for adaptation to changing environmental conditions, most notably climate change, which may shift the production technology over time. Such environmental shifts are largely exogenous to firm decision making, for instance investments in research and development, which may also lead to technology change. Few existing measures of total factor productivity (TFP) make this distinction, between exogenous environmental shifts and shifts due to firm decision making or innovation. We introduce a nonparametric Luenberger productivity

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27

Isupova, Yulia, Maria Kuznetsova, Ekaterina Gimazitdinova, and Ekaterina Martynova. "Efficiency of breeding value genomic assessment of Holstein stud bulls in comparison with the assessment of the offspring quality." BIO Web of Conferences 36 (2021): 06045. http://dx.doi.org/10.1051/bioconf/20213606045.

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A comparative analysis of the genomic assessment results of Holstein breed stud bulls and their assessment on the offspring quality in the conditions of the Udmurt Republic was carried out. To analyze the efficiency of using stud bulls assessed by different methods, data from farms included in the ranking of the top 20 enterprises in terms of milk yield per cow for 2019-2020 were used. A high indicator of the complex LPI index (over 2500) was obtained in three bulls at the beginning of the assessment, by the end of the assessment there were two bulls left - J. Koln-M 11087837 and Super 6413103

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28

Williams, Jonathan, Nicolas Peypoch, and Carlos Pestana Barros. "The Luenberger indicator and productivity growth: a note on the European savings banks sector." Applied Economics 43, no. 6 (2011): 747–55. http://dx.doi.org/10.1080/00036840802599859.

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29

Ang, Frederic, and Pieter Jan Kerstens. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture." European Journal of Operational Research 260, no. 1 (2017): 359–75. http://dx.doi.org/10.1016/j.ejor.2016.12.015.

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30

Hamid, Salman, and Ke Wang. "Environmental total factor productivity of agriculture in South Asia: A generalized decomposition of Luenberger-Hicks-Moorsteen productivity indicator." Journal of Cleaner Production 351 (June 2022): 131483. http://dx.doi.org/10.1016/j.jclepro.2022.131483.

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31

Miao, Zhuang, Xiaodong Chen, Tomas Baležentis, and Chuanwang Sun. "Atmospheric environmental productivity across the provinces of China: Joint decomposition of range adjusted measure and Luenberger productivity indicator." Energy Policy 132 (September 2019): 665–77. http://dx.doi.org/10.1016/j.enpol.2019.06.019.

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32

ZHU, Ning, Ning ZHANG, Bing WANG, and Tomas BALEŽENTIS. "What contributes to total factor productivity growth in the Chinese banking sector?" Technological and Economic Development of Economy 24, no. 2 (2018): 792–811. http://dx.doi.org/10.3846/tede.2018.249.

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We propose a new metafrontier, non-radial, biennial Luenberger productivity indicator to evaluate the total factor productivity growth of the Chinese banking sector, during the period of 2004–2012. The bootstrapping approach is also taken into account to introduce the statistical inference of the total factor productivity, and its components. It is found that the overall Chinese banking sector operated well with an average growth rate of 5.4%, where technological progress was the driving force promoting the development of the Chinese banking sector during the earlier studied period, and effici

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33

Briec, W., and K. Kerstens. "Infeasibility and Directional Distance Functions with Application to the Determinateness of the Luenberger Productivity Indicator." Journal of Optimization Theory and Applications 141, no. 1 (2009): 55–73. http://dx.doi.org/10.1007/s10957-008-9503-2.

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34

Molinos-Senante, María, Alexandros Maziotis, and Ramón Sala-Garrido. "The Luenberger productivity indicator in the water industry: An empirical analysis for England and Wales." Utilities Policy 30 (September 2014): 18–28. http://dx.doi.org/10.1016/j.jup.2014.07.001.

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35

Wang, Ke, and Yi-Ming Wei. "Sources of energy productivity change in China during 1997–2012: A decomposition analysis based on the Luenberger productivity indicator." Energy Economics 54 (February 2016): 50–59. http://dx.doi.org/10.1016/j.eneco.2015.11.013.

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36

Deng, Haiyan, Haodong Li, Anzhe Pan, and Zhiyang Shen. "Decomposition of Green Agricultural Productivity Gain Under a Multiple-Frontier Framework." Journal of Global Information Management 30, no. 6 (2022): 1–23. http://dx.doi.org/10.4018/jgim.297115.

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This paper investigates structural variation of agricultural productivity growth in China using a multiple-frontier approach. Agricultural productivity gain in Sichuan province is decomposed into technological progress, technical, mix and scale efficiency changes in terms of economic and environmental performance. The results show that agricultural Luenberger productivity indicator in Sichuan presents a significant increase trend with annual growth rate of 2.5% over the period of 1997-2017. The agricultural green growth in Sichuan is most driven by technological progress. Of the decline in the

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37

Li, Yanzi, Cai Chen, Fuqiang Liu, and Jian Wang. "Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning." Journal of Food Quality 2022 (March 16, 2022): 1–11. http://dx.doi.org/10.1155/2022/9297205.

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When analyzing agriculture’s total factor productivity, traditional measurement approaches do not take into account the inefficiency value. The production functions are assumed to be analyzed on basis of the random boundaries, which makes the analysis results inaccurate and unreliable. As a result, this paper proposes an analytical approach for agricultural total factor productivity based on the stochastic block model (SBM), which combines the benefits of statistics and machine learning. It uses the SBM direction distance function and the Luenberger productivity index to measure the agricultur

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38

Zhu, Liyun, and Alfons Oude Lansink. "Dynamic sustainable productivity growth of Dutch dairy farming." PLOS ONE 17, no. 2 (2022): e0264410. http://dx.doi.org/10.1371/journal.pone.0264410.

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The economic, environmental and social sustainability of Dutch dairy farms have attracted increasing societal concern in the past decades. In this paper, we propose a recently developed dynamic Luenberger indicator based on the by-production model to measure dynamic productivity growth in the economic, environmental and social dimensions of sustainability of Dutch dairy farms. Subsequently, we investigate the statistical associations between productivity growth and socio-economic factors using the OLS bootstrap regression model. We find that dairy farms have suffered a decline in dynamic susta

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39

Boussemart, Jean-Philippe, Gary D. Ferrier, Hervé Leleu, and Zhiyang Shen. "An expanded decomposition of the Luenberger productivity indicator with an application to the Chinese healthcare sector." Omega 91 (March 2020): 102010. http://dx.doi.org/10.1016/j.omega.2018.11.019.

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40

Wang, Ke, Yujiao Xian, Yi-Ming Wei, and Zhimin Huang. "Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function." Ecological Indicators 66 (July 2016): 545–55. http://dx.doi.org/10.1016/j.ecolind.2016.02.034.

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41

Yang, Wan-Ping, Zhen-Ya Zhang, Ping-Ping Luo, and Ya-Juan Wang. "Temporal and spatial evolution and influencing factors of urban ecological total factor productivity in the Yellow River basin under strong sustainable development." Science Progress 106, no. 1 (2023): 003685042311527. http://dx.doi.org/10.1177/00368504231152742.

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A growing consensus worldwide has indicated the need to protect the ecological environment and achieve sustainable development. Ensuring ecological protection and high-quality development of the Yellow River basin have become China's major national strategy. We reviewed extant literature, summarised government reports and guidance documents on the Yellow River basin, and proposed introducing a strong sustainable development theory into the study of total factor productivity (TFP). The spatial–temporal evolution and influencing factors of urban ecological TFP in the Yellow River basin are of gr

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42

Aparicio, Juan, Lidia Ortiz, and Daniel Santín. "Comparing group performance over time through the Luenberger productivity indicator: An application to school ownership in European countries." European Journal of Operational Research 294, no. 2 (2021): 651–72. http://dx.doi.org/10.1016/j.ejor.2021.02.005.

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43

Zhang, Ning, and Bing Wang. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case." Energy Economics 51 (September 2015): 88–98. http://dx.doi.org/10.1016/j.eneco.2015.06.003.

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44

Aparicio, Juan, Juan F. Monge, Lidia Ortiz, and Jesus T. Pastor. "Changes in productivity in the virgin olive oil sector: An application to Protected Designations of Origin in Spain." Spanish Journal of Agricultural Research 14, no. 3 (2016): e0104. http://dx.doi.org/10.5424/sjar/2016143-9433.

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Virgin olive oil is a key ingredient of the renowned Mediterranean diet. In this context, the main objective of this study was to estimate and decompose productivity change for Protected Designations of Origin (PDOs) in the Spanish virgin olive oil sector for the period 2008-2013. To this end, we introduced a Luenberger-type indicator based on a specific weighted additive model in Data Envelopment Analysis (DEA), which, in contrast to previous studies, captured all sources of inefficiency and avoided infeasibilities. Regarding the results, we found a reduction in productivity, in average terms

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45

ИСУПОВА, Ю. В., Е. А. ГИМАЗИТДИНОВА, Г. В. АЗИМОВА, and Е. Н. МАРТЫНОВА. "EFFICIENCY OF BREEDING VALUE GENOMIC ASSESSMENT OF HOLSTEIN BULLS IN COMPARISON WITH THE ASSESSMENT OF THE OFFSPRING QUALITY." Molochnoe i miasnoe skotovodstvo, no. 1 (March 8, 2022): 7–10. http://dx.doi.org/10.33943/mms.2022.87.53.002.

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Проведен сравнительный анализ результатов геномной оценки быков-производителей голштинской породы и их оценки по качеству потомства в условиях Удмуртской Республики. Для исследования были использованы данные хозяйств, входящих в рейтинг 20-ти лучших предприятий по надоям молока на 1 корову за 2019—2020 годы. На начало оценки получен наивысший показатель комплексного индекса LPI (более 2500) у 2 быков, к ее окончанию — только у одного (Ж. Кольн-М 11087837). Аутсайдерами рейтинга LPI были быки Парламент 52800347 и Патрик 51660096. У всех анализируемых производителей показатель комплексного индек

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46

YILDIRIM, Metin. "Cluster Analysis on Supply Chain Management-Related Indicators." İnsan ve Toplum Bilimleri Araştırmaları Dergisi 12, no. 5 (2023): 2499–520. http://dx.doi.org/10.15869/itobiad.1251841.

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The supply chain performance of countries has a significant impact on the overall performance of countries. These indices primarily emphasized countries' standings, rankings, and improvement areas. Clustering countries based on a single index does not always yield the desired results. Using cluster analysis may help get critical information when many indicators are evaluated. The supply chain-connected indicators were chosen to be included in the research initially. In this study, three global indices were selected. We chose the Logistics Performance Index(LPI) to evaluate the logistics indust

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47

Stenger, Melle Agathe, and Agathe Stenger. "A remark on the definition of the Färe–Lovell measure for infeasible production vectors: implication for the Luenberger productivity indicator." International Journal of Production Economics 184 (February 2017): 1–6. http://dx.doi.org/10.1016/j.ijpe.2016.10.023.

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48

Li, Ying, and Siyu Li. "The Influence Study on Environmental Regulation and Green Total Factor Productivity of China’s Manufacturing Industry." Discrete Dynamics in Nature and Society 2021 (April 20, 2021): 1–15. http://dx.doi.org/10.1155/2021/5580414.

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Green development is the theme of the current era. Environmental regulation is an essential means to achieve environmental benefits and improve the total green factor productivity of manufacturing facing a series of problems brought by the development model of “high investment, high pollution, and high consumption.” Appropriate environmental regulations need to be implemented to achieve economic and environmental harvest. Based on the panel data of 25 manufacturing industries from 2003 to 2016 in China, this thesis constructs a comprehensive indicator of environmental regulation and calculates

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49

Wang, Shuo, Yueping Zheng, and Hailan Yang. "Digital economy and green total factor productivity in China." PLOS ONE 19, no. 3 (2024): e0299716. http://dx.doi.org/10.1371/journal.pone.0299716.

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The development of information technology has created conducive conditions for the digital economy. The digital economy is regarded as a critical pathway for transforming traditional economic models. Green total factor productivity serves as an indicator for assessing the quality of economic development. During pivotal periods of economic transition, the digital economy and green total factor productivity have emerged as two prominent themes for achieving sustainable economic development. But the impact of digital economy on green total factor productivity is less discussed. Innovation environ

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50

Wang, Jian, Xuying Yang, and Sonia Kumari. "Investigating the Spatial Spillover Effect of Transportation Infrastructure on Green Total Factor Productivity." Energies 16, no. 6 (2023): 2733. http://dx.doi.org/10.3390/en16062733.

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Abstract:

Green development and the high-quality economic growth model have replaced the extensive growth model in an effort to reduce the large amounts of energy consumption and pollution emissions. Green total factor productivity has become an important indicator to more accurately measure the quality of economic growth. Transportation infrastructure is a fundamental component that may effectively integrate regional resources, increase regional cooperation, and encourage the sensible use of resources, and is a key factor in increasing productivity. At present, transportation infrastructure should focu

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