An investigation of key performance indicators for operational excellence towards sustainability in the leather products industry

Publication Type:
Journal Article
Business Strategy and the Environment, 2020, 29, (8), pp. 3331-3351
Issue Date:
Filename Description Size
bse.2575.pdfPublished version11.75 MB
Adobe PDF
Full metadata record
© 2020 ERP Environment and John Wiley & Sons Ltd Operational excellence refers to a mixed management structure that enhances the productivity of an industry by exercising the best practices and efforts for continuous improvement. In order to achieve sustainability, operational excellence initiatives are practiced by different organizations. The intent is to investigate how to perform the practices of operational excellence towards sustainability in industries. In the existing literature, some studies investigated key performance indicators (KPIs) for other domains that are not readily applicable in the background of an emerging economy, principally for the leather products industry. To fulfill these research gaps, this study contributes to the operational excellence literature by recognizing the KPIs of operational excellence towards sustainability by examining the peer-reviewed scientific articles and through expert's suggestions. The identified KPIs are segregated into six dominant categories and 27 sub-KPIs in the field of leather products industry. Further, the prioritization of the KPIs is established by adopting the best-worst method (BWM), which involves simple pairwise comparison matrices compared with other multicriteria decision making techniques. The findings indicate that the KPIs under the “Management” category are at the highest priority. It is anticipated that the results originated from the study will support the expert's to appropriately recognize the significant KPIs and drop insignificant KPIs for successful operational excellence towards sustainability practices in the supply chain of the emerging economy.
Please use this identifier to cite or link to this item: