Abstract
Environmental, social, and governance (ESG) has become a concern for companies, investors, and regulators. Its significance cannot be underestimated, as stakeholders increasingly demand accountability and transparency regarding corporate practices in these areas. Government agencies enforce laws mandating companies adhere to established ESG standards in response. However, despite these regulatory pressures, several obstacles have hindered organizations from effectively implementing sustainability initiatives, often resulting in lackluster outcomes. In this study, we developed a framework to implement ESG principles across various companies, utilizing the critical success factor (CSF) theory. By incorporating the perspectives of stakeholders, we identified the essential elements to achieve ESG. The developed framework in ESG studies employed the hybrid Delphi technique and the analytical hierarchy process (AHP), a structured method for organizing and analyzing complex decisions. Based on the results obtained from targeted questions, variables that influence ESG performance were identified. The effectiveness of different sustainability initiatives was also assessed to understand stakeholder engagement strategies and evaluate the impact of organizational culture on ESG adoption.
1. Introduction
In the supply chain, raw materials are transferred for industrial manufacturing [1] and converted into waste after manufacturing in a linear economy. However, the linear economy model cannot balance supply and demand for natural resources [2]. Furthermore, a business strategy to preserve natural resources and the environment, innovative manufacturing techniques, models, and services are related to climate change and ecosystem degradation globally [3,4,5]. Okorie et al. stated that supply chains are the origin of the circular economy (CE), which offers environmentally friendly corporate solutions and strategies [6]. According to Kouhizadeh et al. [7], CE aims to extend the life cycle of products and materials, add value to them, and renew them till the end of their useful lives. Due to the growing cost, complexity, unpredictability, and susceptibility of the supply chain due to the CE attribution, managers look for better, faster, and less expensive vertical and horizontal supply chain collaboration.
To overcome the aforementioned challenges [8,9], provide sustainable output [10], and minimize human–machine interaction for the adoption of sustainability practices and CE principles [11], supply chains must also be innovative. The digital supply chain is a powerful means for sustainability. It aims to reduce environmental impact, improve efficiency, and promote social responsibility. Digital technologies provide tools and frameworks to enable and enhance circularity within supply chains.
Environmental, social, and governance (ESG) factors increasingly play a significant role in corporate decision-making and performance evaluation. ESG policies boost companies’ stock liquidity [12] and cumulative abnormal returns [13]. However, stakeholders are worried about ESG and how companies handle them. For example, investors look for ESG data to identify sustainable companies. Therefore, ESG factors are included in risk management, performance evaluation, and strategic decision-making. The leading cause is the pressure from numerous stakeholders, such as workers, investors, clients, and regulators, who demand that companies demonstrate accountability and openness about ESG matters.
ESG principles are adopted to enhance supply chain resilience by positively impacting a company’s willingness to adopt innovative technologies with technology adoption and improved supply chain resilience [14]. ESG management in the supply chain positively impacts supply chain resilience through information network capability and emerging information technologies. Supply chain collaboration, supply chain management capabilities, supply chain risks, and green-product innovation positively impact a company’s willingness to adopt innovative technologies, subsequently leading to positive effects on supply chain resilience and performance [15].
Therefore, it is necessary to understand the obstacles to putting ESG into practice in the manufacturing supply chain based on variables and research questions in the previous studies, is the basis of this study.
2. Methodology
We employed methods that combine qualitative and quantitative research techniques. By integrating various methodologies, factors influencing ESG implementation across various organizations were determined. Stakeholder interviews and focus group discussions were conducted along with data collection through surveys. The data collected were analyzed using the Delphi technique and the analytical hierarchy process (AHP). The variables identified were used to construct the questionnaire (Figure 1). We conducted a literature review by gathering and examining publications from reliable academic sources, including Google Scholar, Web of Science, and ScienceDirect. We chose publications to assess and compare the results of this study with those of previous studies. The Delphi and AHP techniques were used to identify important variables. The Delphi technique was used to collect expert opinions agreed on variables. At the same time, AHP was used to assign weights to these variables according to their relative importance.
Figure 1.
Method used in this study.
3. Result and Discussion
3.1. Variable
Critical success factors (CSFs) are essential for organizations to enhance sustainability and long-term value creation through ESG integration. These factors guide the effective implementation and management of ESG strategies: corporate governance [16], long-term value creation [17,18], stakeholder engagement [17,19], transparency and reporting [17,18], senior management involvement [17,18], risk management [17], use of technology and data [18]. Martiny et al. [20] selected 14 variables for the implementation of ESG: company strategy, company characteristics, CEO features, CEO compensation, corporate governance, audit committees, investor relationship, regulatory framework, country governance, industry, period, economic development, financial performance, and market performance. Khamisu et al. [21] chose 20 variables: financial performance, market performance, environmental performance, earnings quality, ESG reporting guidelines, board size, board diversity, board independence, signaling future performance, third-party ratings, mandatory disclosure policies, managerial attributes, company characteristics, demand by stakeholders, presence of CSR committee, ESG materials, reputation insurance, disclosure costs, audit and assurance, reduced information system.
The following variables were chosen based on discussion with experts in the Delphi method: company strategy, company characteristics, chief executive officer (CEO) features, CEO compensation, corporate governance, audit committees, investor relationship, regulatory framework, country governance, industry, period, economic development, financial performance, market performance, environmental performance, earnings quality, ESG reporting guidelines, board size, board diversity, board independence, signaling future performance, third-party ratings, mandatory disclosure policies, managerial attributes, company characteristics, demand by stakeholders, presence of CSR committee, ESG materials, reputation insurance, disclosure costs, audit and assurance, reduced information system. The variables were validated using AHP.
3.2. AHP
The variables were chosen using AHP [22] and ranked based on their weight. After using AHP, variables prioritized in the model development process were identified. These variables were validated by using the consistency ratio. The consistency index (CI) was calculated using Equation (1).
where The term “maximum value of Eigenvalue” refers to the highest eigenvalue of a matrix, and n represents the order or size of the matrix. Finally, it is necessary to compute the consistency ratio (CR) by dividing the consistency index by the random consistency index using Equation (2).
The CR was 0.07, which indicated that the weights were consistent. The weight of the variables was calculated based on the Pareto rule.
Institutional investors, board independence, media monitoring, perception of CSR, formal institutions, industrial visibility, board diversity, board size, and earnings quality had low weights (Figure 2). Therefore, they were not used in the next stage. Table 1 shows the variables grouped by organizational characteristics, performance, strategy, corporate governance, investor relations, ESG adoption, and technology. These variable were used for constructing questions (Table 2).
Figure 2.
Global weight and cumulative global weight.
Table 1.
Variables and categories.
Table 2.
Variables and questions.
4. Conclusions
A framework for implementing ESG principles across various companies was developed based on the CSF theory. By incorporating the perspectives of stakeholders, we identified the variables for the achievement of ESG goals. Twenty variables were selected for this research and classified into seven groups. The variables were used for data collection related to ESG. These variables ensured that ESG was embedded into the supply chain process and aligned with business goals. By prioritizing these variables, companies need to enhance their competitiveness, reduce risks, and develop long-term value, in addition to meeting ESG goals. Integrating ESG factors into digital supply chains is crucial for sustainable, ethical, and responsible business practices while enhancing efficiency.
Author Contributions
Conceptualization, R.M.S.; methodology, H.-L.C.; software, R.M.S.; validation, Y.-T.J., R.S. and A.S.; formal analysis, R.S.; investigation, R.M.S.; resources, H.-L.C.; data curation, R.S.; writing—original draft preparation, R.M.S.; writing—review and editing, R.M.S.; visualization, R.S.; supervision, Y.-T.J.; project administration, S.P.D.K. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No new data were created.
Conflicts of Interest
The authors declare no conflict of interest.
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