Abstract:It is widely recognized that a firm's well-established corporate governance (CG) has a considerable impact on its corporate social responsibility (CSR) performance. How to determine the main trigger among CG's indicators for strengthening CSR performance is thus an urgent and complicated task due to its (i.e., CSR) multi-dimensional and numerous perspectives. In order to solve this critical problem, the study breaks down CSR into four dimensions and further examines the impact of CG's indicators on each CSR dimension by joint utilization of rough set theory (RST) and decision tree (DT). By doing so, users can realize which one CG indicator is the most essential to CSR performance. Managers can take the results as a reference to allocate valuable and scarce resources to the right place so as to enhance CSR performance in the future. To solidify our research finding, we transform the CSR forecasting model selection into a multiple criteria decision making (MCDM) task and execute a MCDM algorithm. By implementing the MCDM algorithm, users can achieve a much more reliable and consensus decision in today's highly turbulent economic environment. The proposed mechanism, examined by real cases, is a promising alternative for CSR performance forecasting.

Abstract:The influence of globalization on sports has turned out to be a popular issue widely discussed by researchers. Improvement to the sustainability of sports industry policy is an important and challenging issue, and related are inherently multiple attribute decision making (MADM) problems that can be strategically important to economic systems. The purpose of this study is to set up a new sustainability sports industry policy evaluation model that addresses the main causal factors and amends the priorities. A MADM model is combined with DEMATEL, DANP, and VIKOR for the evaluation and improvement of the sustainability of sports industry policy. The improvement priorities according to the domain expert interviews are in the following order: promotion and assistance of government policy (A), sports venues and facilities (D), enterprise sponsorship of sports quality (E), expert human resources (B), and finally sports competitions and events (C).

Abstract. The regional financial center is the propeller of regional economic development. Regional financial center modernization, however, has been the predominant propulsion of economic sustainability. Decisions related to regional financial center modernization development are inherent problems of multiple attribute decision-making (MADM), and strategically important to the government. The purpose of this paper is to set up a regional financial center improvement model for modernization development, as based on a hybrid MADM model, which addresses the main causal-effect factors and amended priorities in order to strengthen ongoing planning. This paper adopts a new hybrid MADM model combined with the DEMATEL technique to construct an influential network relationship map (INRM) and determined the influential weights of DANP. Then, a modified VIKOR method using influential weights is applied to measure and integrate the performance gaps from each criterion into dimensions, as well as the overall criterion for evaluating and improving the modernization development of the regional financial center, as based on INRM. Finally an empirical case study using data from the Guangzhou regional financial center is carried out as an example to demonstrate the suitability of the proposed hybrid MADM model for solving real-world problems. The results show the priorities for improvement, as based on the degree of the effect and impact of the dimensions, as follows: first is making "government policy", second is enforcing "financial infrastructure and safety", next is formulating "financial institutions and human resources", and finally "financial service".

The purpose of this study is to set up a new enterprise crisis improvement model for corporate governance based on the hybrid MADM model, which addresses on the main causal factors and amended priorities in order to reduce the occurrence of corporate crises. In this study, we present the use of a new hybrid MADM combined with a DEMATEL technique to construct an influential network relationship map (INRM) and find the influential weights of DANP in criteria from the influential relationship matrix, as well as the modified VIKOR method using influential weights, to evaluate and integrate the criteria performance in the gaps. This study also analyzes how to reduce the gaps to evaluate the decision for improving corporate governance effects based on INRM. This method provides decision-makers with a way to formulate improvement strategies. The results show that the overall average gap of corporate governance is 0.501 (signaling a crisis on the 0 to 1 scale). To remedy this issue, much bigger gaps are needed for improvement in each criterion. The implication is that Taiwan's current financial industry corporate governance system is too weak and needs to be strengthened, reengineered, and transformed.

With the rapid growth of modern technology in all facets of trade and industry, traditional auditing systems can no longer meet today’s ever-increasing technological requirements; contemporary auditing is in urgent need of straightforward and quick cloud computing services to meet the needs of auditors. In keeping with current trends, auditors must be provided with the means of using data and auditing information stored in cloud systems for more efficient and elastic auditing. However, the risks involved in cloud computing auditing are widespread and complex. Dimensions should be established, a mutually influential relationship used to delineate the influence weights of the dimensions and criteria should be determined. To this end, a Multiple Attribute Decision Making (MADM) model can precisely solve multi-criteria problems simultaneously. Therefore, the main focus of this study is to determine how to assess and establish the best improvement strategies to achieve the aspiration level for cloud auditing risk factors, by using the opinions and practical experience of China’s accounting experts, applied with a Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, DEMATEL-based ANP (DANP) and modified VIKOR method. The results provide cloud auditing risks with a knowledge-based understanding of the problem sources in order to establish the best improvement strategies for reducing risk-auditing performance gaps and attaining the aspiration levels. Based on the degree of impact of the dimensions/criteria on an Influence Network Relation Map (INRM), improvements should be prioritized as follows: system operations, technology risks, identity and access management and data protection.

In today’s big-data era, enterprises are able to generate complex and non-structured information that could cause considerable challenges for CPA firms in data analysis and to issue improper audited reports within the required period. Artificial intelligence (AI)-enabled auditing technology not only facilitates accurate and comprehensive auditing for CPA firms, but is also a major breakthrough in auditing’s new environment. Applications of an AI-enabled auditing technique in external auditing can add to auditing efficiency, increase financial reporting accountability, ensure audit quality, and assist decision-makers in making reliable decisions. Strategies related to the adoption of an AI-enabled auditing technique by CPA firms cover the classical multiple criteria decision-making (MCDM) task (i.e., several perspectives/criteria must be considered). To address this critical task, the present study proposes a fusion multiple rule-based decision making (MRDM) model that integrates rule-based technique (i.e., the fuzzy rough set theory (FRST) with ant colony optimization (ACO)) into MCDM techniques that can assist decision makers in selecting the best methods necessary to achieve the aspired goals of audit success. We also consider potential implications for articulating suitable strategies that can improve the adoption of AI-enabled auditing techniques and that target continuous improvement and sustainable development.

In a highly intertwined and connected business environment, globalized layout planning can be an effective way for enterprises to expand their market. Nevertheless, conflicts and contradictions always exist between parent and subsidiary enterprises; if they are in different countries, these conflicts can become especially problematic. Internal control systems for subsidiary supervision and management seem to be particularly important when aiming to align subsidiaries’ decisions with parent enterprises’ strategic intentions, and such systems undoubtedly involve numerous criteria/dimensions. An effective tool is urgently needed to clarify the relevant issues and discern the cause-and-effect relationships among them in these conflicts. Traditional statistical approaches cannot fully explain these situations due to the complexity and invisibility of the criteria/dimensions; thus, the fuzzy rough set theory (FRST), with its superior data exploration ability and impreciseness tolerance, can be considered to adequately address the complexities. Motivated by efficient integrated systems, aggregating multiple dissimilar systems’ outputs and converting them into a consensus result can be useful for realizing outstanding performances. Based on this concept, we insert selected criteria/dimensions via FRST into DEMATEL to identify and analyze the dependency and feedback relations among variables of parent/subsidiary gaps and conflicts. The results present the improvement priorities based on their magnitude of impact, in the following order: organizational control structure, business and financial information system management, major financial management, business strategy management, construction of a management system, and integrated audit management. Managers can consider the potential implications herein when formulating future targeted policies to improve subsidiary supervision and strengthen overall corporate governance.

While CPA (Certified Public Accountant) firms utilize cloud auditing technologies to generate auditing reports and convey information to their clients in the Internet of Things (IoT) Era, they often cannot determine whether cloud auditing is a secure and effective form of communication with clients. Strategies related to cloud auditing provider evaluation and improvement planning are inherently multiple attribute decision making (MADM) issues and are very important to the auditor industry. To overcome these problems, this paper proposes an evaluation and improvement planning model to be a reference for CPA firms selecting the best cloud auditing provider, and illustrates an application of such a model through an empirical case study. The DEMATEL (decisionmaking trial and evaluation laboratory) approach is first used to analyze the interactive influence relationship map (IIRM) between the criteria and dimensions of cloud auditing technology. DANP (DEMATEL-based ANP) is then employed to calculate the influential weights of the dimensions and criteria. Finally, the modified VIKOR method is utilized to provide improvement priorities for performance cloud auditing provider satisfaction. Based on expert interviews, the recommendations for improvement priorities are privacy, security, processing integrity, availability, and confidentiality. This approach is expected to support the auditor industry to systematically improve their cloud auditing provider selection.