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

Using Grey Relational Analysis to Determine the Financial Performance of Turkish Football Clubs

Football has become an important industry in Turkey. A huge amount of sponsoring, advertising, betting funds into football and television rights are sold for billions of Turkish Liras. In order to better compete in Turkish leagues, football clubs have made considerable investments and have aspired to be listed on the stock exchange. The pioneer was Beşiktaş that went public in 2002. After that three football clubs were listed on Borsa Istanbul (BIST). The aim of this study is to evaluate the financial performance of four big football clubs (Beşiktaş, Fenerbahçe, Galatasaray and Trabzonspor) listed on BIST from 2009-2010 to 2012-2013. In order to evaluate these clubs, Grey Relational Analysis (GRA) is used. GRA is widely used in various disciplines such as economics, engineering, sociology and finance. It can be used as a rating, classification and decision making technique to determine the important factors among those required for a system with a limited number of data set

Applying grey relational analysis to Italian football clubs: A measurement of the financial performance of serie a teams

Extant literature on the financial analysis of football clubs has applied a vast array of techniques in determining the fiscal stability of such entities. Although many studies have provided useful comparisons and analyses of the states of various clubs, direct research comparing the financial performance among various clubs is still scant. Hence, we present an application of financial ratio analysis to the greater Italian football market within the Serie A. The main purpose of this study is to assess the financial performance of the top three Italian football clubs currently listed on the Borsa Italiana (Italian Stock Exchange), those being: Juventus F.C., A.S. Roma, and S.S. Lazio. In accomplishing this, we offer a comparative analysis of these clubs through the usage of grey relational analysis (GRA), an optimal performance technique derived from engineering. Overall, our results suggest that S.S. Lazio appears to be the most financially stable club among the sampled, publicly traded Serie A teams. In light of these findings, this study furthers the application of economic evaluation into larger segments of international football

Profitability Evaluation and Ranking of Indian Non-Life Insurance Firms using GRA and TOPSIS

This paper evaluates the profitability of the Indian non-life insurance firms in the period 2008-2013 using multi criteria decision analysis methods :GRA and TOPSIS based on the profitability ratios. Also, ranking of the non-life insurance firms is arrived. Few studies on efficiency of Indian non-life insurance firms using different DEA models were studied, but the number of inputs and outputs considered are very few as the DEA convention doesn't allow number of DMUs more than three times the sum of inputs and outputs. But, the profitability evaluation involves more number of decision variables considered in efficiency studies using DEA models. This paper addresses this gap by evaluating the profitability of the alternative non-life firms with more number of decision variables or criteria using Multi-Criteria Decision Analysis: GRA and TOPSIS Keywords: Non-life Insurance, Profitability, GRA,TOPSI

Exploration and Mitigation of Green Lean Six Sigma Barriers: A Higher Education Institutions perspective

Purpose-The study aims to identify Green Lean Six Sigma (GLSS) barriers in the context of Higher Education Institutions (HEIs) and prioritize them for executing the GLSS approach. Design/methodology/approach-A systematic literature review (SLR) was used to identify a total of fourteen barriers, which were then verified for greater relevance by the professional judgments of industrial personnel. Moreover, many removal measures strategies are also recommended in this study. Furthermore, this work also utilizes Gray Relational Analysis (GRA) to prioritize the identified GLSS barriers. Findings-The study reveals that Training and education, continuous assessment of SDG, organizational culture, resources and skills to facilitate implementation, and assessment of satisfaction and welfare of the employee are the most significant barriers to implementing this approach. Research limitations/implications-The present study provides an impetus for practitioners and managers to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. In this case, the outcomes of this research, and in particular the GRA technique presented by this work, can be used by managers and professionals to rank the GLSS barriers and take appropriate action to eliminate them. Practical implications-The ranking of GLSS barriers gives top officials of higher education institutes a very clear view to effectively and efficiently implementing GLSS initiatives. The outcomes also show training and education, sustainable development goals, and organizational culture as critical barriers. The findings of this study provide an impetus for managers, policymakers, and consultants to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. Societal implications-The GLSS barriers in HEIs may significantly affect the society. HEIs can lessen their environmental effect by using GLSS practices, which can support sustainability initiatives and foster social responsibility. Taking steps to reduce environmental effect can benefit society as a whole. GLSS techniques in HEIs can also result in increased operational effectiveness and cost savings, which can free up resources to be employed in other areas, like boosting student services and improving educational programs. However, failing to implement GLSS procedures in HEIs could have societal repercussions as well. As a result, it's critical for HEIs to identify and remove GLSS barriers in order to advance sustainability, social responsibility, and operational effectiveness. Originality/value-GLSS is a comprehensive methodology that facilitates the optimum utilization of resources, reduces waste, and provides the pathway for sustainable development so, the novelty of this study stands in the inclusion of its barriers and HEIs to prioritize them for effective implementation

Effects of sustainable governance to sustainable development

Sustainable development advocates effective and efficient planning of both present and future use of resources. Governance, on the other hand, is based on the joint and coordinated management of multidimensional variables, which is the basis of the sustainability approach. This study aims to determine how much sustainable governance influences the fulfillment of multidimensional sustainable development. Multiple regression analysis was used to determine the variables that reveal the impact of governance on development in terms of sustainability while the gray relational analysis method was used to rank the countries. The results reveal that increases in the number of people using the internet in society, as well as in the levels of developments in e-government and human development, environmental performance, and political reform, all assist countries achieve their SDGs. Furthermore, it was found that governance has a positive and significant impact on SDGs. In addition, an MCDM model consisting of BWM and gray relational analysis was used to evaluate countries based on their performance in sustainable development, the economic, governance and environment. The gray relational analysis results, on the other hand, revealed that developed and wealthy countries ranked first, while underdeveloped countries experiencing instability, such as war and conflict, ranked last. The Nordic countries outperform other countries in terms of governance and sustainability, depending on the strength of their democracy and executive capacity. © 2022 by the authors

Multi-Criteria Decision Analysis for Optimizing CO2 and NH3 Removal by Scenedesmus dimorphus Photobioreactors

Numerous technologies have been investigated for mitigating air pollutant emissions from swine barns. Among them, algal photobioreactors (PBRs) can remove and utilize air pollutants such as CO2 and NH3 from barn exhaust. However, a challenge to PBR operation is that it involves multiple system input parameters and output goals. A key question is then how to determine the appropriate CO2 and NH3 concentrations in this case. Conventional statistical methods are inadequate for handling this complex problem. Multi-criteria decision-making (MCDM) emerges as a practical methodology for comparison and can be utilized to rank different CO2–NH3 interactions based on their environmental and biological performance. By employing MCDM methods, producers can effectively control the ratio of CO2 and NH3 concentrations, enabling them to identify the optimal range of operating parameters for various housing types, ensuring efficient pollutant mitigation. In this study, a multi-criteria decision-making (MCDM) approach was employed to support operation management. Specifically, influent CO2 and NH3 concentrations were optimized for three scenarios (the best biological, environmental, and overall performance), using a combination of two MCDM techniques. This study is anticipated to facilitate the system analysis and optimization of algae-based phytoremediation processes

Evaluation for Core Competence of Private Enterprises in Xuchang City Based on an Improved Dynamic Multiple-Attribute Decision-Making Model

Because Deng’s grey relational degree is inconspicuous, Deng’s relational degree with an exponential function is first presented. Then, we demonstrate that improved Deng’s relational degree is more conspicuous than the original model. Then, we construct a multiple-attribute decision-making model, based on improved Deng’s relational degree with multiple stages, and a method for determining the weight of the index is also developed. Finally, the core competence of private enterprises in Henan province is analyzed, illustrating the validity and feasibility of the improved model

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

Selection of safety officers in an indian construction organization by using grey relational analysis

Stakeholders are responsible for implementing the occupational health and safety provisions in an organization. Irrespective of organization, the role of safety department is purely advisory as it coordinates with all the departments, and this is crucial to improve the performance. Selection of safety officer is vital job for any organization; it should not only be based on qualifications of the applicant, the incumbent should also have sufficient exposure in implementing proactive measures. The process of selection is complex and choosing the right safety professional is a vital decision. The safety performance of an organization relies on the systems being implemented by the safety officer. Application of multi criteria decision-making tools is helpful as a selection process. The present study proposes the grey relational analysis(GRA) for selection of the safety officers in an Indian construction organization. This selection method considers fourteen criteria appropriate to the organization and has ranked the results. The data was also analyzed by using technique for order Preference by Similarity to an Ideal solution (TOPSIS) and results of both the methods are strongly correlate