Using a hybrid decision-making model to evaluate the sustainable development performance of high-tech listed companies

In this study, we use a triple bottom-line concept including economic, social and environmental performance as the sustainable development performance evaluation categories for companies. Moreover, an integrated model based on grey relational analysis, decision-making trial and evaluation laboratory, analytic network process and the technique for order preference by similarity to ideal solution is proposed for solving a corporate sustainability performance evaluation and ranking problem. In order to verify the proposed model, we adopt 34 high-tech listed companies in Taiwan as the research object to measure companies’ sustainable development performance and ranking in 2013. The results can be used as an important basis for management decision-making, and can also serve as reference for banks and investors when developing investment strategy

Performance drivers of green innovation under incomplete information

AbstractThe environmental management practices have been well studied; few studies are presented the firm's green innovation activities. This study is adopted to evaluate the green innovation for environment management, with a particular focus on managerial, process, product and technological aspects. The empirical analysis from Taiwanese printed circuit board manufacturing firm's reveals that such studies does exist and that the effect of focal firm's green innovation activities has been evaluated. This study identified the appropriate green innovation criteria for the case firms and developed the following selection method: (i) evaluate the weights of aspects, criteria and alternatives as described both by linguistic preferences; and (ii) rank alternative suppliers using a grey relational analysis with entropy weight. This study presents theoretical and empirical evidence of green innovation drivers in the domains of environmental management and has interesting implications for operations management research and practices. This knowledge may contribute to better decision-making towards implementing green innovation practices

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

COMPARATIVE ANALYSIS OF SOME PROMINENT MCDM METHODS: A CASE OF RANKING SERBIAN BANKS

In the literature, many multiple criteria decision making methods have been proposed. There are also a number of papers, which are devoted to comparison of their characteristics and performances. However, a definitive answer to questions: which method is most suitable and which method is most effective is still actual. Therefore, in this paper, the use of some prominent multiple criteria decision making methods is considered on the example of ranking Serbian banks. The objective of this paper is not to determine which method is most appropriate for ranking banks. The objective of this paper is to emphasize that the use of various multiple criteria decision making methods sometimes can produce different ranking orders of alternatives, highlighted some reasons which lead to different results, and indicate that different results obtained by different MCDM methods are not just a random event, but rather reality

Contracting with General Dental Services: a mixed-methods study on factors influencing responses to contracts in English general dental practice

Background: Independent contractor status of NHS general dental practitioners (GDPs) and general medical practitioners (GMPs) has meant that both groups have commercial as well as professional identities. Their relationship with the state is governed by a NHS contract, the terms of which have been the focus of much negotiation and struggle in recent years. Previous study of dental contracting has taken a classical economics perspective, viewing practitioners’ behaviour as a fully rational search for contract loopholes. We apply institutional theory to this context for the first time, where individuals’ behaviour is understood as being influenced by wider institutional forces such as growing consumer demands, commercial pressures and challenges to medical professionalism. Practitioners hold values and beliefs, and carry out routines and practices which are consistent with the field’s institutional logics. By identifying institutional logics in the dental practice organisational field, we expose where tensions exist, helping to explain why contracting appears as a continual cycle of reform and resistance. Aims: To identify the factors which facilitate and hinder the use of contractual processes to manage and strategically develop General Dental Services, using a comparison with medical practice to highlight factors which are particular to NHS dental practice. Methods: Following a systematic review of health-care contracting theory and interviews with stakeholders, we undertook case studies of 16 dental and six medical practices. Case study data collection involved interviews, observation and documentary evidence; 120 interviews were undertaken in all. We tested and refined our findings using a questionnaire to GDPs and further interviews with commissioners. Results: We found that, for all three sets of actors (GDPs, GMPs, commissioners), multiple logics exist. These were interacting and sometimes in competition. We found an emergent logic of population health managerialism in dental practice, which is less compatible than the other dental practice logics of ownership responsibility, professional clinical values and entrepreneurialism. This was in contrast to medical practice, where we found a more ready acceptance of external accountability and notions of the delivery of ‘cost-effective’ care. Our quantitative work enabled us to refine and test our conceptualisations of dental practice logics. We identified that population health managerialism comprised both a logic of managerialism and a public goods logic, and that practitioners might be resistant to one and not the other. We also linked individual practitioners’ behaviour to wider institutional forces by showing that logics were predictive of responses to NHS dental contracts at the dental chair-side (the micro level), as well as predictive of approaches to wider contractual relationships with commissioners (the macro level) . Conclusions: Responses to contracts can be shaped by environmental forces and not just determined at the level of the individual. In NHS medical practice, goals are more closely aligned with commissioning goals than in general dental practice. The optimal contractual agreement between GDPs and commissioners, therefore, will be one which aims at the ‘satisfactory’ rather than the ‘ideal’; and a ‘successful’ NHS dental contract is likely to be one where neither party promotes its self-interest above the other. Future work on opportunism in health care should widen its focus beyond the self-interest of providers and look at the contribution of contextual factors such as the relationship between the government and professional bodies, the role of the media, and providers’ social and professional networks. Funding: The National Institute for Health Research Health Services and Delivery Research programme

Application of Grey Theory in the Construction of Impact Criteria and Prediction Model of Players’ Salary Structure

[[abstract]]Salaries of professional players are usually determined prior to the execution of the responsibilities assigned by the organizations and are often based on the expected future performance of these players as derived from their past achievement. The study first identifies criteria that would affect players’ salaries through literature reviews and then utilizes grey relational analysis (GRA) and grey prediction model to calculate weights of salary impact criteria, players’ annual performance index, and salary prediction for the coming year. The performance data of players from the Chinese Professional Baseball League (CPBL) are used in this study. The results are as follows: (i) CPBL teams do refer to players’ past performance records and future performance prediction when deciding on their salaries and (ii) future performance prediction must be made using at least a 3-year data set. The proposed prediction model is able to effectively provide relevant and useful information to the CPBL teams’ management during players’ salary adjustment.[[notice]]補正完

A fuzzy-grey- weighted aggregate sum product assessment methodical approach for multi-criteria analysis of maintenance performance systems

Diverse maintenance performance models have been previously proposed in literature. However, many of these frameworks perform inefficiently or are not applicable in real-world problems due to their over-simplified assumptions. Such models do not take into account peculiarities of the maintenance situation in which multiple factors need to be prioritised under uncertain conditions. Keeping the above issues in mind, this communication proposes a framework for ranking maintenance performance systems using integrated fuzzy entropy weighting method, grey relational analysis (GRA) and weighted aggregate sum product assessment (WASPAS). The values of criteria weights were determined using fuzz entropy weighting method. Ranking was carried out using GRA and WASPAS methods. GRA ranking considered a criterion, while WASPAS method considered multi-criteria. It is the belief of the authors that merging these three mentioned tools generates synergy. The synergic advantage of the fusion is that these tools interact to create the combined results of ability to handle logic decisions, or partial information and choice among complex alternatives, demonstrated in this paper. The built-up frame-work was illustrated with practical data from five manufacturing companies operating in Nigeria with information gathered through the questionnaire approach to show that the approach can be effectively implemented in practice. Based on the proposed framework’s results, the highest ranked maintenance system belongs to companies 4 and 5, while the lowest ranked maintenance system belongs to company 5. TOPSIS method was used to determine the best performing maintenance function of the companies. It was observed that maintenance system of company 4 was the highest ranked system. The results from model testing confirmed that the presented scheme is feasibility in industrial settings, efficient and capable of revealing the best company in performance according to certain six input criteria. The novelty of this approach is its uniqueness of the combined frameworks’ structures in achieving the highest accuracy of estimation, introduced for the first time in maintenance performance assessment in a multi-criteria framewor