Efficiency analysis of the Portuguese wine industry using accounting and operational metrics

Results in Engineering - Tập 14 - Trang 100389 - 2022
Rui Fragoso1, António A.C. Vieira1,2
1CEFAGE Research Centre, University of Évora, Évora, Portugal
2Algoritmi Research Centre, University of Minho, Guimarães, Portugal

Tài liệu tham khảo

Bisson, 2002, The present and future of the international wine industry, Nature, 418, 696, 10.1038/nature01018 Jradi, 2018, Tracking carbon footprint in French vineyards: a DEA performance assessment, J. Clean. Prod., 192, 43, 10.1016/j.jclepro.2018.04.216 2020 Annunziata, 2018, The role of organizational capabilities in attaining corporate sustainability practices and economic performance: evidence from Italian wine industry, J. Clean. Prod., 171, 1300, 10.1016/j.jclepro.2017.10.035 Frigon, 2020, Drivers of eco-innovation and conventional innovation in the Canadian wine industry, J. Clean. Prod., 275, 124115, 10.1016/j.jclepro.2020.124115 BdP, 2020 2019, 2019 Al-Falahat, 2022, Energy performance and economics assessments of a photovoltaic-heat pump system, Results in Engineering, 13, 100324, 10.1016/j.rineng.2021.100324 Giral-Ramírez, 2021, Spectral decision analysis and evaluation in an experimental environment for cognitive wireless networks, Results in Engineering, 12, 100309, 10.1016/j.rineng.2021.100309 Wheatley, 2021, Design improvement of a laboratory prototype for efficiency evaluation of solar thermal water heating system using phase change material (PCMs), Results in Engineering, 12, 100301, 10.1016/j.rineng.2021.100301 Grassauer, 2021, Eco-efficiency of farms considering multiple functions of agriculture: concept and results from Austrian farms, J. Clean. Prod., 297, 126662, 10.1016/j.jclepro.2021.126662 Lima-Junior, 2017, Quantitative models for supply chain performance evaluation: a literature review, Comput. Ind. Eng., 113, 333, 10.1016/j.cie.2017.09.022 Lima-Junior, 2019, Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks, Int. J. Prod. Econ., 212, 19, 10.1016/j.ijpe.2019.02.001 Lee, 2021, Hierarchical balanced scorecard-based organizational goals and the efficiency of controls processes, J. Bus. Res., 132, 270, 10.1016/j.jbusres.2021.04.038 Osman, 2021, Hospitality issues and trends: a balanced scorecard solution for B hotels and resorts, Adv. Math.: Scientific Journal, 10, 1547 Trivedi, 2013, A framework for performance measurement in supply chain using balanced score card method: a case study, International Journal of Recent Trends in Mechanical Engineering, 4, 20 Awad, 2022, Extracting the planning elements for sustainable urban regeneration in dubai with AHP (analytic hierarchy process), Sustain. Cities Soc., 76, 103496, 10.1016/j.scs.2021.103496 Sotiros, 2022, Analysing the export potentials of the Portuguese footwear industry by data envelopment analysis, Omega, 108, 102560, 10.1016/j.omega.2021.102560 Tomikawa, 2022, Efficiency assessment of Japanese National Railways before and after privatization and divestiture using data envelopment analysis, Transport Pol., 118, 44, 10.1016/j.tranpol.2022.01.012 Koengkan, 2022, Measuring the economic efficiency performance in Latin American and Caribbean countries: an empirical evidence from stochastic production frontier and data envelopment analysis, International Economics, 169, 43, 10.1016/j.inteco.2021.11.004 Aparicio, 2013, Accounting for slacks to measure and decompose revenue efficiency in the Spanish Designation of Origin wines with DEA, Eur. J. Oper. Res., 231, 443, 10.1016/j.ejor.2013.05.047 Varas, 2021, Measuring efficiency in the Chilean wine industry: a robust DEA approach, Appl. Econ., 53, 1092, 10.1080/00036846.2020.1826400 Goncharuk, 2018, Wine business performance benchmarking: a comparison of German and Ukrainian wineries, Benchmark Int. J., 25, 1864, 10.1108/BIJ-06-2017-0131 Gardijan Kedžo, 2021, The financial efficiency of small food and drink producers across selected European Union countries using data envelopment analysis, Eur. J. Oper. Res., 291, 586, 10.1016/j.ejor.2020.01.066 Nudurupati, 2011, State of the art literature review on performance measurement, Comput. Ind. Eng., 60, 279, 10.1016/j.cie.2010.11.010 Reddy, 2019, A review on supply chain performance measurement systems, Procedia Manuf., 30, 40, 10.1016/j.promfg.2019.02.007 Mishra, 2014, Benchmarking SCM performance and empirical analysis: a case from paint industry, Logistics Research, 7, 113, 10.1007/s12159-014-0113-0 Rasolofo-Distler, 2018, Using the balanced scorecard to manage service supply chain uncertainty: case studies in French real estate services, Knowl. Process Manag., 25, 129, 10.1002/kpm.1572 Thanki, 2018, A quantitative framework for lean and green assessment of supply chain performance, Int. J. Prod. Perform. Manag., 67, 366, 10.1108/IJPPM-09-2016-0215 Zuniga, 2018, Modeling of critical products supply chain required to affected people on earthquakes and tsunamis through use of SCOR model, 53 Charkha, 2014, Supply chain performance measurement system: an overview, Int. J. Bus. Perform. Supply Chain Model., 6, 40, 10.1504/IJBPSCM.2014.058892 Govindan, 2017, Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies, Prod. Plann. Control, 28, 552, 10.1080/09537287.2017.1309716 Dobos, 2018, Inventory-related costs in green supplier selection problems with Data Envelopment Analysis (DEA), Int. J. Prod. Econ., 209, 374, 10.1016/j.ijpe.2018.03.022 Gallear, 2014, An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams, Prod. Plann. Control, 25, 1182, 10.1080/09537287.2013.808838 Vázquez-Rowe, 2012, Joint life cycle assessment and data envelopment analysis of grape production for vinification in the Rías Baixas appellation (NW Spain), J. Clean. Prod., 27, 92, 10.1016/j.jclepro.2011.12.039 Sellers-Rubio, 2015, Economic efficiency of members of protected designations of origin: sharing reputation indicators in the experience goods of wine and cheese, Review of Managerial Science, 9, 175, 10.1007/s11846-014-0124-x Urso, 2018, Efficiency analysis of Italian wine producers, Wine Economics and Policy, 7, 3, 10.1016/j.wep.2017.11.003 Goncharuk, 2017, Exploring the factors of efficiency in German and Ukrainian wineries, J. Wine Res., 28, 294, 10.1080/09571264.2017.1383888 Santos, 2020, Efficiency analysis of viticulture systems in the Portuguese Douro region, Int. J. Wine Bus. Res., 32, 573, 10.1108/IJWBR-10-2019-0052 Jalalvand, 2011, A method to compare supply chains of an industry, Supply Chain Manag.: Int. J., 16, 82, 10.1108/13598541111115347 Balfaqih, 2016, Review of supply chain performance measurement systems: 1998–2015, Comput. Ind., 82, 135, 10.1016/j.compind.2016.07.002 Chopra, 2016, Supply chain management: strategy, planning & operation, 265 Dash, 2018, Performance analysis of clustering techniques over microarray data: a case study, Phys. Stat. Mech. Appl., 493, 162, 10.1016/j.physa.2017.10.032 Johnson, 2014 Troccoli, 2022, K-means clustering using principal component analysis to automate label organization in multi-attribute seismic facies analysis, J. Appl. Geophys., 198, 104555, 10.1016/j.jappgeo.2022.104555 Banker, 1984, Some models for estimating technical and scale inefficiencies in data envelopment analysis, Manag. Sci., 30, 1078, 10.1287/mnsc.30.9.1078 Voces, 2012, Characterization and explanation of the sustainability of the European wood manufacturing industries: a quantitative approach, Expert Syst. Appl., 39, 6618, 10.1016/j.eswa.2011.12.040 Wasiaturrahma, 2020, Financial performance of rural banks in Indonesia: a two-stage DEA approach, Heliyon, 6, 10.1016/j.heliyon.2020.e04390 Marôco, 2018 Wooldridge, 2012