Exploring, Categorizing, and Prioritizing the ESG Factors for Organizational Sustainability

Customer expectations and sustainability

Most industries have acknowledged that meeting customers’ expectations is vital for addressing sustainability issues that have become increasingly important to their success. Businesses ought to engage in strategic networks of customers to address the most difficult ESG issues and hazards (De Silva Lokuwaduge & De Silva, 2022). ESG reporting standards and indicators give objective sustainability performance data to communicate to customers. ESG measures and reporting have limited studies on customers’ sustainability perceptions, where customer support is vital for organizations’ sustainability efforts. Sustainability attempts that differ from customer demand will likely fail in decision-making towards future sustainability development (Aksoy et al., 2022).

The concept of sustainability is widely discussed among industry managers, practitioners, stakeholders, and customers. International and non-profit organizations like the Carbon Disclosure Project and Global Reporting Initiative emphasize the importance of measuring sustainability performance (Silva et al., 2019). Literature indicates that sustainability enhances a company’s competitive advantages and is rooted in ecological and environmental systems, capable of enduring or adapting to changing circumstances. Sustainable practices are crucial for current supply networks, especially in economic development (Rajesh, 2020). As environmental complexities grow, the notion of sustainable development becomes increasingly indispensable. The United Nations (UN) defined sustainable development in 1987 as meeting present needs without compromising future generations (Ardiana, 2019).

Sustainability data is commonly collected in corporate practice for sustainability reports. As a result, sustainability information is significant for customers and customer relationships with the company (Silva et al., 2019). Customer engagement may assist in the improvement of sustainability performance. Sustainability reporting practices share the idea that industry should acknowledge concerns about the environment, society, governance, and the economy when reporting to consumer groups. By incorporating sustainability concerns into strategy, governance, and operations, customer interaction aids reporting organizations in improving their business processes (Ardiana, 2019).

Overview of customer expectations in electricity industry

Assessing the sustainability of each nation’s electrical industry may be essential for economic development and success (Tavassoli et al., 2020). Electricity utility companies’ energy generation, transmission, and distribution affect the country’s environmental, social, governance, and economic activities. Customer expectations and perceptions through communication engagement in the electrical sector are crucial. Stakeholder engagement boosts corporate sustainability and competitiveness by delivering long-term value (Alrazi et al., 2020b).

A case study on project management research examining the effects of the Electricity Company of Ghana project involving stakeholder participation. Effects of poor economic growth, revenue loss, unemployment, cost escalation, and the collapse of local businesses are the consequences of a failed project on the key stakeholders (Adjabeng & Amoah, 2021). In another case study on Fukushima Nuclear Accident, electricity company TEPCO played an important post-accident recovery role and provided communication and customer engagement for expectations and perceptions as essential parts of the recovery process (Proehl et al., 2015).

Electricity companies’ operations have influenced many stakeholders, especially customers. Companies in the electricity sector are being held to higher standards on customer engagement and communicating any action or progress. Hence, it has become critical to overview the customer expectations and perceptions towards the electricity industry’s business and operation.

Development and initiation of Environment, Social, Governance and Economy

The term “ESG” was introduced in the book “Who Care Wins” in 2004, aiming to integrate ESG elements into the capital market. With increased awareness of corporate sustainability initiatives, more companies now disclose their ESG information publicly (Helfaya et al., 2023). ESG evaluates a company’s adherence to a framework encompassing environment (E), social (S), governance, and economy (G) components, originally designed to assess corporate decision-making behavior (Li et al., 2021). Currently, ESG factors are pivotal in measuring companies' sustainability and ethical impact.

ESG has gained significant prominence, engaging various stakeholders (Klarin, 2018). This approach is now widely adopted in global business practices across industries to foster sustainable development and cater to customer needs (Khovrak, 2020). ESG serves as a practical framework for sustainable marketing, offering viable strategies for enterprises. Bloomberg, for instance utilizes its ESG data service to assess companies’ ethical and social responsibility performance (Ferrell, 2021). Implementing ESG-aligned customer expectations through a robust framework leads to successful customer engagement (Dos Santos et al., 2019).

Analytic Hierarchy Process (AHP)

The AHP method is the most well-known MCDM tool that requires some steps to follow as suggested by Saaty (2008):

Decompose the problem into a hierarchical structure of criteria, sub-criteria, and alternatives. Numerical values are also assigned to each element based on their relative importance or preference.

Create pairwise comparisons between elements of all criteria, sub-criteria, and alternatives to determine their relative importance using a scale of judgments to capture the weights of the elements.

Calculate the priority weights of the elements from the pairwise comparison matrix obtained in Step 2.

Synthesize all the local set of weights to obtain a set of overall or global weights for the alternatives. The form of the pairwise comparison matrix in Step 2 is as follow:

$\mathrm{A}=\begin{array}{c}\underset{\_}{}\\ F_{\mathrm{1}}\\ F_{\mathrm{2}}\\ ⋮\\ F_n\end{array}\left|\begin{array}{cccc}\underset{\_}{F_{\mathrm{1}}}& \underset{\_}{F_{\mathrm{2}}}& \underset{\_}{\dots }& \underset{\_}{F_n}\\ a_{\mathrm{11}}& a_{\mathrm{12}}& \dots & a_{\mathrm{1}n}\\ a_{\mathrm{21}}& a_{\mathrm{22}}& \dots & a_{\mathrm{2}n}\\ ⋮& ⋮& \ddots & ⋮\\ a_{n\mathrm{1}}& a_{n\mathrm{2}}& \dots & a_{nn}\end{array}\right.$ (3.1)

Where $F_i\text{'}s$ are the factors (either criteria or alternatives whose weights are to be determined), $a_{ij}=\frac{w_i}{w_j}$, for all $i,j$ and $w={\left(w_1,w_2,\cdots ,w_n\right)}^T$ is the underlying weight vector for the $n$ factors. Each entry $a_{ij}$ represents the comparative significance of criterion with respect to criterion. To compare the relative importance of these criterions (weakly or strongly more) with respect to one another, a ratio scale ranging from 1/9 to 9 is used (Saaty, 1987, 2008). For instance, if $F_1$ is strongly more dominant over $F_2$, then $a_{12}=5$. The interpretation of all the numerical judgments within the (1/9-9) scale is shown in Table 1 below:

Note: If any factor $F_i$ has importance strength over $F_j$ as any of the above non- zero numbers, then $F_j$ has the reciprocal importance strength with $F_i$ i.e., $a_{ji}=1/a_{ij}$.

Thus, considering the given example, if $F_1$ is considered 5 times more significant than $F_2$, then $F_2$ is proportionately 1/5 times more important than $F_1$. The relationship between the elements of matrix, denoted as $a_{ij}$, has been defined as the ratio between the weights $w_i$ and $w_i$. Performing a right multiplication of matrix, by the weight vector w results in the following outcome:

$A_w=nw$

Saaty (1987) proposed the principal eigenvalue for weights and consistency measurement. Based on above equation, noted that $n$ is the eigenvalue for $n\times n$ ratio matrix (which is matrix); meanwhile; $\mathit{n}\times \mathit{1}$ is an eigenvector (which is matrix w). Due to the fact that sum of the eigenvalues of matrix are simply its trace, thus, $Tr\left(A\right)=n$. Also, $n$ is the only non-zero eigenvalue.

Noted that $a_{ij}=\left(\frac{w_i}{w_k}\right)\left(\frac{w_k}{w_j}\right)=a_{ik}{a}_{kj}$, which is known as cardinal consistency. In this case, a ratio scale of priorities can be measured only by a single row ofsince the rank of matrix is equivalent to 1. Hence, matrix is considered consistent only if ${\lambda }_{max}=n$, where ${\lambda }_{max}$ is the largest eigenvalue, which is the underlying standard scale ratio (Klutho, 2013). However, AHP framework does not impose consistency. In this case, the equation is transformed into:

$A^{\text{'}}{w}^{\text{'}}={\lambda }_{max}{w}^{\text{'}}$

Here matrix $A^{\text{'}}=\left[a_{ij}^{\text{'}}\right]$ is the perturbed value of $A=\left[a_{ij}\right]$ where the consistency relation is violated at least once. For simplicity, an in-depth explanation of the AHP calculation will not be discussed further. In practice, Expert Choice software is used to compute the weights from the pairwise comparison matrices.

The technical solution (TS) list is gathered in this stage. Multiple sources are used to collect the TS including six benchmark utility companies, selected Malaysian public-listed companies, an extensive literature review, as well as with the company’s feedbacks and inputs. Thus, an additional engagement with the management team of the electricity utility company is also being conducted.

In the fourth and conclusive phase of data collection, distinguished participants, including the management team of Malaysian electricity utility company are engaged in completing the QFD framework to discern the interconnection between CR and TS. The data analysis for this segment is conducted by employing SigmaZone software, enabling the acquisition and subsequent ranking of results for all TS.

Quality Function Deployment (QFD)

The Quality Function Deployment (QFD) method systematically translates customer requirements into engineering characteristics, aligning product development with customer needs. It captures the ‘voice of the customer’ through surveys, interviews, and focus groups, integrating prioritized requirements into design and development stages. This fosters effective communication and collaboration among cross-functional teams, resulting in high-quality products that exceed customer expectations. The House of Quality matrix is the most well-known and widely used QFD method to integrate customer’s wants and provides a visual means of prioritization and correlation (Hauser & Clausing, 1988; Shrivastava, 2016).

Based on the below Figure 1, the prioritized CR are listed in the left-side of the matrix, meanwhile, all the prioritized TS are listed on the top of the house. To establish the relationship between CR and TS, the weights of their interdependence are determined based on the measurements indicated in the Table 2 provided below:

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In instances where a TS is unrelated, the corresponding cell within the grid matrix is left unpopulated. Subsequently, the weights for all the TS are determined by employing the following formula after identifying all potential relationships between each pair of CR and TS:

$t_i={\sum }_{i=1}^m{c}_i{r}_{ij},j=1,2,\dots ,n$ (3.2)

where;

$t_i$= weights of the $j^{th}$ technical requirements

$c_i$ = weight of the $i^{th}$ customer requirements (in the present study this is determined by using AHP)

$r_{ij}$ = weight of the relationship between $i^{th}$ customer requirement and $j^{th}$ technical requirement. ( $r_{ij}$ = 0 or 1or 3 or 6 or 9)

m = number of customer requirements

n = number of technical requirements

AHP results

Utilizing AHP, weightage scores are derived from survey questionnaire responses using a 9-point scale as shown in Table 1 above to rank ESG factors according to customer stakeholders’ requirements. Subsequently, a prioritization list, illustrated in subsequent figures, is developed based on the weightage scores and categorized into three ESG criteria sets: environmental, social, and governance and economy.

Environmental Domain

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Figure 2 reveals that customer stakeholders prioritize ‘Climate Change’ (0.258426) among the five GRI categories, while ‘Future Energy Mix’ scores lowest (0.099415). Figures 3 and 4 further breakdown the 22 factors, showing customer concerns center on ‘Emphasizing on RE’ (FEM2) with an AHP score of 0.633242 and ‘Implementation of energy-efficient equipment and a transparent tariff and billing system’ (ECE2) with a slightly lower AHP score of 0.571590.

The ‘Future Energy Mix’ category received the lowest score among the five GRI categories, indicating that customers prioritize other sustainability aspects over the composition of future energy sources. This could be due to a lack of awareness or understanding of the concept. Customers tend to prioritize immediate and tangible concerns such as climate change, which has gained significant attention. The utility company can address this by educating customers about the benefits and implications of a diversified energy mix to increase engagement and align priorities.

Social Domain

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The presented data as shown in Figure 5 highlights the highest priority of the ‘CSR’ category in the social domain, scoring 0.23067. Remarkably, scores across all six social categories are closely clustered, with a mere 0.11 difference between the lowest (0.122689) and highest score. Analyzing all 28 factors, customers particularly emphasize labor and employability standards, with the factor ‘Establishing labor standards’ (LMR2) receiving an impressive AHP score of approximately 0.6. Furthermore, within the ‘CSR’ category, the factor ‘Income and employment (reducing unemployment)’ (CSR5) achieves the highest score of 0.323524, as depicted in Figures 6 and 7.

These findings highlight the significance of labor-related considerations for customers. The focus on labor standards suggests that customers prioritize fair and ethical treatment of employees, as well as the creation of employment opportunities. By addressing these concerns, the utility company can enhance its CSR initiatives and strengthen its reputation as a socially responsible organization.

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Governance and Economy Domain

Within this domain, the results underscore the importance of customer-centric considerations. Customers prioritize initiatives that empower them to make sustainable energy choices and reduce their environmental impact, aligning with the global focus on consumer behavior for positive change and energy conservation. As expected, the ‘Evaluating customer experience’ category holds high priority among customer stakeholders with AHP score of 0.267031 (Figure 8). Particularly, the factor ‘Influencing consumer lifestyle on energy consumption’ (ECE2) obtained the highest priority score with 0.631122 points (Figure 10). In contrast, the ‘Business and financial performance’ category scored the lowest with 0.085203. Additionally, its factors ‘Implementing new systems and innovative technology’ (BFP1) and ‘Concentrating on the immediate marketplace and broader economy’ (BFP6) received the least priority as shown in Figures 9 and 10.

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QFD matrix results

Subsequent to obtaining the CR prioritization list, the TS prioritization list is derived through the utilization of the QFD method. The construction of the TS list in this study involves a comprehensive approach that integrates various reference sources, including six benchmark utility companies, selected Malaysian public-listed companies, an extensive literature review, as well as with some aid of the organization’s feedbacks and inputs. To further assess the TS, a QFD method is structured using the House of Quality matrix (from both CR and TS list) according to the ESG criteria. Finally, a holistic ESG framework is established by incorporating the priority scores rankings from the TS prioritization list, as depicted in Table 3 below.

The QFD score analysis from the table indicates that the highest significance lies in ‘Aligning business operations with the community, employee, and customer’s expectations.’ This involves meeting customer needs, ensuring employee satisfaction, and considering broader public interests in decision-making. Enhancing electricity services through public involvement and collaboration is also highlighted. Conversely, smart grid and smart mobility initiatives received the lowest rating, as customers prioritized other aspects over technological advancements. Prioritizing customer interests over research and development (R&D) and upholding employee integrity were deemed essential, aligning with customer preferences and labor standards in the utility company’s social domain.

This analysis stresses the importance of considering customer input and aligning business strategies accordingly. By placing emphasis on the areas that matter most to customers’ stakeholders, the Malaysian electricity utility company can ensure that their efforts and resources are directed towards meeting customer expectations and delivering value. Hence, by focusing on meeting customer expectations on climate change, CSR, and customers experience, then appropriately addressing their needs, the organization can build stronger relationships and enhance customer satisfaction, while ensuring the business sustainable growth.