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Article
Publication date: 15 September 2023

Tooraj Karimi and Mohamad Ahmadian

Competition in the banking sector is more complex than in the past, and survival has become more difficult than before. The purpose of this paper is to propose a grey methodology…

Abstract

Purpose

Competition in the banking sector is more complex than in the past, and survival has become more difficult than before. The purpose of this paper is to propose a grey methodology for evaluating, clustering and ranking the performance of bank branches with imprecise and uncertain data in order to determine the relative status of each branch.

Design/methodology/approach

In this study, the two-stage data envelopment analysis model with grey data is applied to assess the efficiency of bank branches in terms of operations. The result of grey two-stage data envelopment analysis model is a grey number as efficiency value of each branch. In the following, the branches are classified into three grey categories of performance by grey clustering method, and the complete grey ranking of branches are performed using “minimax regret-based approach” and “whitening value rating”.

Findings

The results show that after grey clustering of 22 branches based on grey efficiency value obtained from the grey two-stage DEA model, 6 branches are assigned to “excellent” class, 4 branches to “good” class and 12 branches to “poor” class. Moreover, the results of MRA and whitening value rating models are integrated, and a complete ranking of 22 branches are presented.

Practical implications

Grey clustering of branches based on grey efficiency value can facilitate planning and policy-making for branches so that there is no need to plan separately for each branch. The grey ranking helps the branches find their current position compared to other branches, and the results can be a dashboard to find the best practices for benchmarking.

Originality/value

Compared with traditional DEA methods which use deterministic data and consider decision-making units as black boxes, in this research, a grey two-stage DEA model is proposed to evaluate the efficiency of bank branches. Furthermore, grey clustering and grey ranking of efficiency values are used as a novel solution for improving the accuracy of grey two-stage DEA results.

Details

Grey Systems: Theory and Application, vol. 14 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 26 May 2022

Md Kamal Hossain, Vikas Thakur and Yigit Kazancoglu

The study aims to identify and analyse the drivers of resilient healthcare supply chain (HCSC) preparedness in emergency health outbreaks to prevent disruption in healthcare…

Abstract

Purpose

The study aims to identify and analyse the drivers of resilient healthcare supply chain (HCSC) preparedness in emergency health outbreaks to prevent disruption in healthcare services delivery in the context of India.

Design/methodology/approach

The present study has opted for the grey clustering method to identify and analyse the drivers of resilient HCSC preparedness during health outbreaks into high, moderate and low important grey classes based on Grey-Delphi, analytic hierarchy process (AHP) and Shannon's information entropy (IE) theory.

Findings

The drivers of the resilient HCSC are scrutinised using the Grey-Delphi technique. By implementing AHP and Shannon's IE theory and depending upon structure, process and outcome measures of HCSC, eleven drivers of a resilient HCSC preparedness are clustered as highly important, three drivers into moderately important, and two drivers into a low important group.

Originality/value

The analysis and insights developed in the present study would help to plan and execute a viable, resilient emergency HCSC preparedness during the emergence of any health outbreak along with the stakeholders' coordination. The results of the study offer information, rationality, constructiveness, and universality that enable the wider application of AHP-IE/Grey clustering analysis to HCSC resilience in the wake of pandemics.

Details

International Journal of Emerging Markets, vol. 18 no. 6
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 28 November 2023

Huan Wang, Daao Wang, Peng Wang and Zhigeng Fang

The purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to…

Abstract

Purpose

The purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.

Design/methodology/approach

A novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.

Findings

The methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.

Originality/value

This study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.

Details

Grey Systems: Theory and Application, vol. 14 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 12 July 2023

Naiming Xie and Yuquan Wang

This paper aims to investigate the grey scheduling, which is the combination of grey system theory and scheduling problems with uncertain processing time. Based on the interval…

Abstract

Purpose

This paper aims to investigate the grey scheduling, which is the combination of grey system theory and scheduling problems with uncertain processing time. Based on the interval grey number and its related definitions, properties, and theorems, the single machine scheduling with uncertain processing time and its general forms are studied as the research object. Then several single machine scheduling models are reconstructed, and an actual production case is developed to illustrate the rationality of the research.

Design/methodology/approach

In this paper, the authors first summarize the definitions and properties related to interval grey numbers, especially the transitivity of the partial order of interval grey numbers, and give an example to illustrate that the transitivity has a positive effect on the computational time complexity of multiple interval grey number comparisons. Second, the authors redefine the general form of the single machine scheduling problem with uncertain processing time according to the definitions and theorems of interval grey numbers. The authors then reconstruct three single machine scheduling models with uncertain processing time, give the corresponding heuristic algorithms based on the interval grey numbers and prove them. Finally, the authors develop a case study based on the engine test shop of K Company, the results show that the proposed single machine scheduling models and algorithms with uncertain processing time can provide effective guidance for actual production in an uncertain environment.

Findings

The main findings of this paper are as follows: (1) summarize the definitions and theorems related to interval grey numbers and prove the transitivity of the partial order of interval grey numbers; (2) define the general form of the single machine scheduling problem with interval grey processing time; (3) reconstruct three single machine scheduling models with uncertain processing time and give the corresponding heuristic algorithms; (4) develop a case study to illustrate the rationality of the research.

Research limitations/implications

In the further research, the authors will continue to summarize more advanced general forms of grey scheduling, improve the theory of grey scheduling and prove it, and further explore the application of grey scheduling in the real world. In general, grey scheduling needs to be further combined with grey system theory to form a complete theoretical system.

Originality/value

It is a fundamental work to define the general form of single machine scheduling with uncertain processing time used the interval grey number. However, it can be seen as an important theoretical basis for the grey scheduling, and it is also beneficial to expand the application of grey system theory in real world.

Details

Grey Systems: Theory and Application, vol. 13 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

Abstract

Purpose

The aim of this research was to evaluate the maturity level of strategic communication management implemented by Brazilian startups.

Design/methodology/approach

This study employed the analytic hierarchy process (AHP), survey and Grey Fixed Weight Clustering modeling techniques. Three experts with extensive academic and practical experience in the subject participated in the AHP process, providing their opinions on the relative importance of eight variables associated with the topic under investigation, thus enabling their prioritization. Concurrently, data were collected through a survey from 23 respondents who have extensive knowledge about the realities of Brazilian startups. The weights derived from the AHP and the survey data were utilized in the Grey Fixed Weight Clustering modeling.

Findings

Based on the opinions of the 23 respondents, the level of implementation of practices related to strategic management, brand management, external image management and internal communication management is superficial. In addition, according to the majority of experts, Brazilian startups exhibited a medium level of maturity to address the key challenges related to communication management. Furthermore, this study reveals that the variables “financial resources allocation,” “stakeholder relationship” and “brand management” were deemed the most significant for the model.

Originality/value

The contributions presented herein can be beneficial for both researchers and startup managers seeking to enhance communication strategies in their organizations. This research also contributes by highlighting how grey systems theory can be extremely useful for conducting decision-making analyses in the context of startups, which is characterized by uncertainty and imprecise information.

Details

Grey Systems: Theory and Application, vol. 14 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 6 October 2023

Jie Yang, Manman Zhang, Linjian Shangguan and Jinfa Shi

The possibility function-based grey clustering model has evolved into a complete approach for dealing with uncertainty evaluation problems. Existing models still have problems…

Abstract

Purpose

The possibility function-based grey clustering model has evolved into a complete approach for dealing with uncertainty evaluation problems. Existing models still have problems with the choice dilemma of the maximum criteria and instances when the possibility function may not accurately capture the data's randomness. This study aims to propose a multi-stage skewed grey cloud clustering model that blends grey and randomness to overcome these problems.

Design/methodology/approach

First, the skewed grey cloud possibility (SGCP) function is defined, and its digital characteristics demonstrate that a normal cloud is a particular instance of a skewed cloud. Second, the border of the decision paradox of the maximum criterion is established. Third, using the skewed grey cloud kernel weight (SGCKW) transformation as a tool, the multi-stage skewed grey cloud clustering coefficient (SGCCC) vector is calculated and research items are clustered according to this multi-stage SGCCC vector with overall features. Finally, the multi-stage skewed grey cloud clustering model's solution steps are then provided.

Findings

The results of applying the model to the assessment of college students' capacity for innovation and entrepreneurship revealed that, in comparison to the traditional grey clustering model and the two-stage grey cloud clustering evaluation model, the proposed model's clustering results have higher identification and stability, which partially resolves the decision paradox of the maximum criterion.

Originality/value

Compared with current models, the proposed model in this study can dynamically depict the clustering process through multi-stage clustering, ensuring the stability and integrity of the clustering results and advancing grey system theory.

Details

Grey Systems: Theory and Application, vol. 14 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 15 June 2023

Yaru Huang, Yaojun Ye and Mengling Zhou

This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological…

Abstract

Purpose

This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.

Design/methodology/approach

This study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.

Findings

The results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.

Practical implications

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

Social implications

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

Originality/value

the new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.

Details

Grey Systems: Theory and Application, vol. 13 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 1 November 2022

Qian Tang, Yuzhuo Qiu and Lan Xu

The demand for the cold chain logistics of agricultural products was investigated through demand forecasting; targeted suggestions and countermeasures are provided. This paper…

Abstract

Purpose

The demand for the cold chain logistics of agricultural products was investigated through demand forecasting; targeted suggestions and countermeasures are provided. This paper aims to discuss the aforementioned statement.

Design/methodology/approach

A Markov-optimised mean GM (1, 1) model is proposed to forecast the demand for the cold chain logistics of agricultural products. The mean GM (1, 1) model was used to forecast the demand trend, and the Markov chain model was used for optimisation. Considering Guangxi province as an example, the feasibility and effectiveness of the proposed method were verified, and relevant suggestions are made.

Findings

Compared with other models, the Markov-optimised mean GM (1, 1) model can more effectively forecast the demand for the cold chain logistics of agricultural products, is closer to the actual value and has better accuracy and minor error. It shows that the demand forecast can provide specific suggestions and theoretical support for the development of cold chain logistics.

Originality/value

This study evaluated the development trend of the cold chain logistics of agricultural products based on the research horizon of demand forecasting for cold chain logistics. A Markov-optimised mean GM (1, 1) model is proposed to overcome the problem of poor prediction for series with considerable fluctuation in the modelling process, and improve the prediction accuracy. It finds a breakthrough to promote the development of cold chain logistics through empirical analysis, and give relevant suggestions based on the obtained results.

Details

Kybernetes, vol. 53 no. 1
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 22 September 2023

Weiliang Zhang, Sifeng Liu, Junliang Du, Liangyan Tao and Wenjie Dong

The purpose of this study is to advance a novel evaluation index system and evaluation approach for ability of older adults in China.

Abstract

Purpose

The purpose of this study is to advance a novel evaluation index system and evaluation approach for ability of older adults in China.

Design/methodology/approach

This study constructed a comprehensive older adult ability evaluation index system with 4 primary indicators and 17 secondary indicators. Grey clustering analysis and entropy weight method are combined into a robust evaluation model for the ability of older adults.

Findings

The result demonstrates that the proposed grey clustering model is readily available to calculate the disability level of elderly individuals. The constructed index system more comprehensively considers all aspects of the disability of the elderly.

Originality/value

This study provides a quantitative method and a more reasonable index system for the determination of the disability level of the elderly.

Details

Journal of Modelling in Management, vol. 19 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 14 November 2023

Flavian Emmanuel Sapnken, Mohammed Hamaidi, Mohammad M. Hamed, Abdelhamid Issa Hassane and Jean Gaston Tamba

For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic…

36

Abstract

Purpose

For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic growth and the ambitious projects underway. Therefore, one of the state's priorities is the mastery of electricity demand. In order to get there, it would be helpful to have reliable forecasting tools. This study proposes a novel version of the discrete grey multivariate convolution model (ODGMC(1,N)).

Design/methodology/approach

Specifically, a linear corrective term is added to its structure, parameterisation is done in a way that is consistent to the modelling procedure and the cumulated forecasting function of ODGMC(1,N) is obtained through an iterative technique.

Findings

Results show that ODGMC(1,N) is more stable and can extract the relationships between the system's input variables. To demonstrate and validate the superiority of ODGMC(1,N), a practical example drawn from the projection of electricity demand in Cameroon till 2030 is used. The findings reveal that the proposed model has a higher prediction precision, with 1.74% mean absolute percentage error and 132.16 root mean square error.

Originality/value

These interesting results are due to (1) the stability of ODGMC(1,N) resulting from a good adequacy between parameters estimation and their implementation, (2) the addition of a term that takes into account the linear impact of time t on the model's performance and (3) the removal of irrelevant information from input data by wavelet transform filtration. Thus, the suggested ODGMC is a robust predictive and monitoring tool for tracking the evolution of electricity needs.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

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