A company performance index for motor vehicle manufacturers: company performance measurement with environmental concerns

Purpose - Current literature presents limited measurement methods of quantifying manufacturers' performance with environmental concerns. The purpose of this paper is to construct a company performance index for benchmarking motor vehicle manufacturers (MVMs) with environmental concerns. Design/methodology/approach - Methods of constructing the index include regression analysis, a modified linear method for normalizing variables and a geometric mean for aggregating variables into a single indexIMVM(index for MVMs). A case study is conducted in 12 MVMs from 2008 to 2017. A sensitivity analysis with the simple additive weighting method is performed to analyze how different aggregation methods affect the final value. The indexIMVMis assessed through a benchmark with three existing indices. Findings - Three realistic considerations are identified from MVMs, based on which proper and transparent methods are chosen to construct theIMVM. The construction of the indexIMVMhas been assessed through a benchmark against the methodologies of three other indices. The results indicate that the new measurement is feasible and effective for MVMs to measure their company performance from an environmental perspective. Practical implications - The construction of the indexIMVMcan support policymakers with accurate statistics for decision-making. As a response to current imperative climate policies, this paper raises awareness of CO2emissions in vehicles' production. For statistical organizations and stakeholders in the investment world, this paper provides available and reliable statistics for trend analysis of different MVMs. Originality/value - A new method is designed for constructing a company performance index for MVMs. Three environmental variables are identified based on literature, their environmental impact as well as their data availability from public documents. A ranking by manufacturer with environmental concerns is generated. This index can contribute with available statistics and useful insights toward decision-making.