Evaluation of city sustainability using multi-criteria decision-making considering interaction among criteria in Liaoning province China

http://tkuir.lib.tku.edu.tw:8080/dspace/retrieve/152470/Using+a+hybrid+method+for+evaluating+and+improving+the+service+quality+of+public+bike-sharing+systems.pdf

Using a hybrid method for evaluating and improving the service quality of public bike-sharing systems

https://onlinelibrary.wiley.com/doi/pdf/10.1002/csr.2206

Performance measurement tools for sustainable business: A systematic literature review on the sustainability balanced scorecard use

Developing a strategy map for forensic accounting with fraud risk management: An integrated balanced scorecard-based decision model.

The intuitionistic fuzzy numbers (IFNs) have been extensively studied in recent years. However, the traditional operational rules (ORs) of the IFNs still have some drawbacks in solving the practical decision-making problems. Einstein t-conorm and t-norm (TAT) are an important and typical class of the TAT, but the ORs for the IFNs based on the Einstein TAT (ETAT) cannot consider the interaction between the membership degree (MD) and the non-membership degree (N-MD), they may get the unreasonable evaluation results in some realistic decision-making situations. So this paper proposes some new Einstein interactive ORs for the IFNs, then, it further presents the intuitionistic fuzzy Einstein interactive weighted averaging (IFEIWA) operator to overcome above existing drawbacks, and some properties of this operator are proved. Simultaneously, in order to eliminate the effects of the existing biases of some decision experts in the process of evaluating attributes, this paper proposes the intuitionistic fuzzy Einstein interactive power averaging (IFEIPA) operator and the intuitionistic fuzzy Einstein interactive weighted power averaging (IFEIWPA) operator based on the revised power weighted averaging operator, and then gives their some desirable properties. Further, by using the IFEIPA operator and the IFEIWPA operator, this paper presents a novel method for the multi-attribute group decision making (MAGDM) problems to solve practical decision-making problems. Lastly, this paper uses some actual application examples to verify the applicability and validity of the proposed MAGDM method, and then demonstrates the superiority of novel method by detailed comparison analysis with other typical methods.

Multiple Attribute Group Decision Making Method Based on Intuitionistic Fuzzy Einstein Interactive Operations

A hybrid multiple criteria decision making model of sustainability performance evaluation for Taiwanese Certified Public Accountant firms

To strengthen the development of enterprises and optimize knowledge management strategies, the current situation of enterprise knowledge management (EKM) is investigated and the evaluation indicators of EKM strategies are analyzed. The specific structure and principles of neural network algorithms are studied using big data. Finally, neural networks (NNs) technology is used to evaluate EKM strategies and calculate the specific weight and strategy application of EKM using big data. The results show that with the support of big data, the use of NNs technology can analyze not only the knowledge management strategies, but also the different strategies of knowledge management used by different enterprises. When analyzing EKM strategies, enterprises indicators collected by big data vary greatly. The highest and lowest values are approximately 0.94 and 0.28, respectively. It indicates that NNs technology can be used to study different knowledge management strategies. Using this technology, the knowledge management strategies of different enterprises are calculated and optimized. The error between the final calculation and the actual result is relatively small, with a maximum and minimum of approximately 0.197 and 0.012, respectively. With the support of big data, the innovation and development of EKM strategy using NNs technology provides technical support for EKM and a reference. 

Development and innovation of enterprise knowledge management strategies using big data neural networks technology

Variance investigation (VI) has been identified as an effective mechanism to reduce budgetary slack at the ex ante budgeting stage. This paper focuses on two further research questions: (1) the extent to which two different accountability-oriented control aspects (i.e., external investigation and self-reporting) of VI affect budgetary slack and (2) the extent of the moderating effect of moral development on the relationship between these two accountability-oriented control aspects and budgetary slack. Our experimental results show that both external investigation and self-reporting can reduce the propensity of creating slack at the ex ante budgeting stage. More specifically, the effect of external investigation on reducing the propensity of creating budgetary slack is greater than that of self-reporting. This study further reveals that moral development moderates the effect of external investigation on budgetary slack. When comparing subordinates with low moral development with those with high moral development, our results show that the effect of external investigation on budgetary slack is stronger among the former group than the latter group. This study does not find any moderating effect of moral development on the relationship between self-reporting and budgetary slack. Our study sheds some new light on varying effects of two accountability-oriented control aspects of VI on budgetary slack, which are also moderated by different levels of subordinates' moral development. These results may be considered in the design and implementation of management control systems.

/pdf/the-impact-of-accountability-oriented-control-aspects-of-44g094h221.pdf

The Impact of Accountability-oriented Control Aspects of Variance Investigation on Budgetary Slack and Moderating Effect of Moral Development

Sustainability is a comprehensive concept that integrates at least three dimensions of environment, economy and society. The power system is the primary source of greenhouse gas emissions, adversely impacting environmental sustainability. It also generates necessary energy supplies, which promote economic and social sustainable development. Based on the sustainability nature of power system, this study puts forward an improved methodology, namely “Planning-Searching-Screening-Reporting-Reflecting” (PSSRR Cycle) to review the literature systematically on power system performance evaluation from a sustainability perspective over the past 20 years, with the aim of describing the current state of the whole performance evaluation system including the evaluation framework, evaluation indicators and evaluation methods, and providing research suggestions for future research. This study finds in the current literature that the Triple Bottom Line theory is the most commonly used theoretical evaluation framework; environmental and economic sustainability indicators are more emphasized; the DEA and MCDM methods are the more common evaluation methods. This study presents some future research notes, including improving the Sustainable Balanced Scorecard as a sustainable performance evaluation framework, emphasizing more social sustainability indicators, and using a combination of existing evaluation methods to make performance evaluation more efficient and accurate.

Subin Wen

Papers

A hybrid multiple criteria decision making model of sustainability performance evaluation for Taiwanese Certified Public Accountant firms

Development and innovation of enterprise knowledge management strategies using big data neural networks technology

The Impact of Accountability-oriented Control Aspects of Variance Investigation on Budgetary Slack and Moderating Effect of Moral Development

A Systematic Literature Review on Performance Evaluation of Power System From the Perspective of Sustainability