Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong.
School of Business, Western Sydney University, Australia.
J Environ Manage. 2023 Jul 15;338:117758. doi: 10.1016/j.jenvman.2023.117758. Epub 2023 Mar 28.
Nowadays, the popularity of environmental, social, and governance (ESG) performance measurement has dramatically increased, particularly to listed companies, for supporting various investment decisions. Companies with high ESG scores imply that their ongoing business development is recognised to be economically, socially, and environmentally sustainable. From the current ESG measurement practice, the measurement frameworks are built on rating schemes, such as KLD and ASSET4, so as to derive the ESG scores for listed companies. However, such existing measurement frameworks are difficult to be implemented in small and medium enterprises (SMEs) with unstructured and non-standardised business data, especially in logistics and supply chain management (LSCM) practice. In addition, it is inevitable for listed companies to work with SMEs, for example logistics service providers, but they need a systematic framework to source the responsible SMEs to maintain the ESG performance. To address the above industrial pain-points, this study proposes an ESG development prioritisation and performance measurement framework (ESG-DPPMF) by means of the Bayesian best-worst method enabling the group decision-making capability to prioritise the ESG development areas and formulate the performance measurement scheme. Through consolidating the opinions from logistics practitioners, it is found that fair labour practice, reverse logistics and human right in supply chains are the most essential areas to further enhance ESG capabilities in the logistics industry. In addition, the viability of the ESG performance measurement has been validated, and thus the sustainable and human-centric logistics practice can be developed to achieve business sustainability.
如今，环境、社会和治理（ESG）绩效衡量的普及程度显著提高，特别是对上市公司来说，因为这有助于支持各种投资决策。ESG 得分高的公司意味着其正在进行的业务发展被认为在经济、社会和环境方面是可持续的。从当前的 ESG 衡量实践来看，衡量框架是基于评级方案构建的，例如 KLD 和 ASSET4，以便为上市公司得出 ESG 分数。然而，这种现有的衡量框架在中小企业（SMEs）中难以实施，因为中小企业的业务数据是非结构化和非标准化的，特别是在物流和供应链管理（LSCM）实践中。此外，上市公司与中小企业（例如物流服务提供商）合作是不可避免的，但他们需要一个系统的框架来寻找负责任的中小企业，以维持 ESG 绩效。为了解决上述行业痛点，本研究通过贝叶斯最佳最差法提出了 ESG 发展优先级和绩效衡量框架（ESG-DPPMF），使群体决策能力能够优先考虑 ESG 发展领域并制定绩效衡量方案。通过整合物流从业者的意见，发现公平劳工实践、逆向物流和供应链中的人权是进一步提高物流业 ESG 能力的最关键领域。此外，还验证了 ESG 绩效衡量的可行性，从而可以开发可持续和以人为本的物流实践，以实现业务的可持续性。
