Benchmarking company performance from economic and environmental perspectives
| Autor: | Sicco Santema, Wouter Beelaerts van Blokland, Gabriel Lodewijks, Qinqin Zeng |
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| Rok vydání: | 2019 |
| Předmět: |
Index (economics)
Environmental perspective Operations research Computer science Strategy and Management 05 social sciences Benchmarking 010501 environmental sciences 01 natural sciences Benchmark (surveying) 0502 economics and business Production (economics) Autoregressive integrated moving average Business and International Management Akaike information criterion Time series 050203 business & management 0105 earth and related environmental sciences |
| Zdroj: | Benchmarking: An International Journal. 27:1127-1158 |
| ISSN: | 1463-5771 |
| DOI: | 10.1108/bij-05-2019-0223 |
| Popis: | Purpose The purpose of this paper is to develop an approach to measuring the performance of motor vehicle manufacturers (MVMs) from economic and environmental (E&E) perspectives. Design/methodology/approach Eight measures are identified for benchmarking the performance from E&E perspectives. A new company performance index IMVM is constructed to quantitatively generate the historical data of MVMs’ company performance. Autoregressive integrated moving average (ARIMA) models are built to generate the forecast data of the IMVM. The minimum Akaike information criteria value is used to identify the model of the best fit. Forecast accuracy of the ARIMA models is tested by the mean absolute percentage error. Findings The construction of the index IMVM is benchmarked against three frameworks by six benchmark metrics. The IMVM satisfies all of its applicable metrics while the three frameworks are incapable to satisfy their applicable metrics. Out of 15, 4 MVMs are excluded for benchmarking future performance due to their non-stationary time series data. Based on the forecast IMVM data, GM is the best performer among the 15 samples in the FY2018. Originality/value This research highlights the environmental perspective during vehicles’ production. The development of this approach is based on publicly available data and transparent about the methods it used. The data out of the approach can benefit stakeholders with insights by benchmarking the historical performance of MVMs as well as their future performance. |
| Databáze: | OpenAIRE |
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