Using the Sustainability-Balanced Scorecard for Assessing Sustainability Issues of the Green Energy Companies

Abstract

Assessing the sustainability issues of the green energy companies is a multiple criterion decision that includes both quantitative and qualitative elements. The sustainability-balanced scorecard (SBSC) for sustainability evaluation is more difficult than an internal evaluation and it requires more serious investigation in the green energy companies. This paper objectives to mix this sustainability evaluation and use fuzzy information with the SBSC. The study presents a fuzzy DEMATEL (decision-making trial and evaluation laboratory) method to develop an assessment model that integrates triangular fuzzy numbers, and DEMATEL to develop a fuzzy assessment, which prioritizes the relative influence of SBSC for green energy companies’ elements. First, this paper conducts a literature review on SBSC regarding sustainability issues to generate 15 elements with five aspects, which are used to measure the sustainability assessment. Next, fuzzy DEMATEL is employed to manage the uncertain linguistic terms, then to set up an influential network relationship map (INRM). This suggested model provides a structure for the related green energy companies to select the evaluation method and could arrange the sustainability approach according to future competitive pressure. The result shows that environmental aspect is the most direct effect and social aspect is the most important effect aspect to the other aspects.

Bayesian Network-Based Marketing Risk Warning Method for Integrated Energy Companies

“…And at this stage, energy enterprises energy marketing risk control and prevention measures, mainly market instruments. In the face of market risks in energy marketing, for example, in response to risks from natural disasters, which are objective and unavoidable, energy companies can only use the purchase of equipment insurance, innovative technologies, and other actions to reduce losses as much as possible [16]. For the contradiction between supply and demand in the energy market, on the one hand, energy companies should encourage customers to save energy as much as possible, and on the other hand, they should eliminate obsolete equipment in order to ensure that the energy load can be adjusted in a timely manner [17].…”

Assessing the Diffusion of Fintech Innovation in Financial Industry: Using the Rough McDm Model

“…This DEMATEL method includes assembling a fundamental model that solves multiplex issues by a matrix and mathematics to investigate the influences of separate factors (Lu et al 2020(Lu et al , 2022. DEMATEL technique is combined with the fundamental ANP concepts to acquire a series of influence weights for individual perspectives and factors.…”

“…Some traditional MCDM prototypes cannot be classified as intricate network among the dissimilar hierarchical structures of environmental elements in the financial industry. This model MCDM usually uses the average judgment of specialist/expert regarding the decision-making procedure (Lu et al, 2022(Lu et al, , 2020. Nevertheless, the method may be incorrect because there are considerable differences in the opinions/observations of experts.…”

“…Therefore, we can apply rough numbers for determining the vague and subjective consensus decisions of specialists/experts. Rough numbers have a flexible boundary that can replicate the fuzzy and subjective decisions of decision makers (Lu et al, 2020(Lu et al, , 2022(Lu et al, , 2023Liou et al, 2019). This approach develops a rough MCDM prototype that uses a rough number to evaluate the fuzziness and ambiguity of opinions based on the domain experts with practical experience.…”

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“…Gabus & Fontela, 1972). This methodology has grown in terms of its importance and application to diverse decision problems in multiple fields such as computer science and artificial intelligence, OR, management, civil engineering and environmental sciences (Dong et al, 2021;Dwijendra et al, 2021;Lu et al, 2022;Tzeng et al, 2007;Yazdi et al, 2020). DEMATEL applications follow six steps, which are described below (cf.…”