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1 – 10 of over 1000Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle…
Abstract
Purpose
Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.
Design/methodology/approach
Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.
Findings
The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.
Practical implications
The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.
Originality/value
The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.
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Assembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and…
Abstract
Purpose
Assembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and capacity forecasting the most troublesome problems for production managers. In this paper, uncertain man-hours are represented as interval grey numbers, and the optimization problem of production line balance in the case of interval grey man-hours is studied to better evaluate the production line capacity.
Design/methodology/approach
First, this paper constructs the basic model of assembly line balance optimization for the single-product scenario, and on this basis constructs an assembly line balance optimization model under the multi-product scenario with the objective function of maximizing the weighted greyscale production line balance rate, second, this paper designs a simulated annealing algorithm to solve problem. A neighborhood search strategy is proposed, based on assembly line balance optimization, an assembly line capacity evaluation method with interval grey man-hour characteristics is designed.
Findings
This paper provides a production line balance optimization scheme with uncertain processing time for multi-product scenarios and designs a capacity evaluation method to provide managers with scientific management strategies so that decision-makers can scientifically solve the problems that the company's design production line is quite different from the actual production situation.
Originality/value
There are few literary studies on combining interval grey number with assembly line balance optimization. Therefore, this paper makes an important contribution in this regard.
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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.
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Shaoguang Zhang, Sifeng Liu, Zhigeng Fang, Qin Zhang and Jingru Zhang
Financial performance has been paid attention at an unprecedented level, which can be confirmed as a fact that the quantitative expansion of financial performance evaluation work…
Abstract
Purpose
Financial performance has been paid attention at an unprecedented level, which can be confirmed as a fact that the quantitative expansion of financial performance evaluation work. The purpose of this study is to propose a more appropriate model for financial performance evaluation under the unbalanced development.
Design/methodology/approach
This paper introduces the differentiation criteria to eliminate the deviation caused by the same principle for multiple performance evaluation objects whose development are unbalanced; Then the generalized grey number is adopted to describe the value of performance evaluation index; and the information entropy weight is used to obtain the index weight to reduce the artificial judgment error; Finally, the generalized grey information entropy weight TOPSIS evaluation model is constructed.
Findings
Empirical research shows that in the new evaluation model, the differentiated possibility function effectively eliminates the deviation caused by the same principle, the application of information entropy weight reduces the human judgment error, and the value of generalized grey number further enhances the closeness of the results. Moreover, it is also found that in different scenarios, an adaptive performance evaluation model should be selected to match scientifically reasonable results.
Originality/value
The proposed model offers a solution for financial performance evaluation considering unbalanced development among cities. It can be realized by determining the differentiation possibility function matrix, and then the information entropy weight TOPSIS evaluation model can be constructed. This model reflects the actual situation, improves the performance evaluation accuracy, and can be used under similar conditions.
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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.
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Keywords
Na Zhang, Haiyan Wang and Zaiwu Gong
Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of…
Abstract
Purpose
Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.
Design/methodology/approach
Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.
Findings
The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.
Originality/value
To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.
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Thiago Rodrigues Timóteo, Gustavo Tietz Cazeri, Gustavo Hermínio Salati Marcondes de Moraes, Tiago F.A.C. Sigahi, Lucas Gabriel Zanon, Izabela Simon Rampasso and Rosley Anholon
The aim of this research was to evaluate the maturity level of strategic communication management implemented by Brazilian startups.
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.
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Santonab Chakraborty, Rakesh D. Raut, T.M. Rofin and Shankar Chakraborty
Supplier selection along with continuous evaluation of their performance is a crucial activity in healthcare supply chain management for effective utilization of scarce resources…
Abstract
Purpose
Supplier selection along with continuous evaluation of their performance is a crucial activity in healthcare supply chain management for effective utilization of scarce resources while providing quality service at an affordable price, and minimizing chances of stock-out, avoiding serious consequences on the illness or fatality of the patients. Presence of both qualitative and quantitative evaluation criteria, set of potential suppliers and participation of different stakeholders with varying interest make healthcare supplier selection a challenging task which can be effectively solved using any of the multi-criteria decision making (MCDM) methods.
Design/methodology/approach
To deal with various qualitative criteria, like cost, quality, delivery performance, reliability, responsiveness and flexibility, this paper proposes integration of grey system theory with a newly developed MCDM tool, i.e. mixed aggregation by comprehensive normalization technique (MACONT) to identify the best performing supplier for pharmaceutical items in a healthcare unit from a pool of six competing alternatives based on the opinions of three healthcare professionals.
Findings
While assessing importance of the six evaluation criteria and performance of the alternative healthcare suppliers against those criteria using grey numbers, and exploring use of three normalization procedures and two aggregation operations of MACONT method, this integrated approach singles out S5 as the most compromised healthcare supplier for the considered problem. A sensitivity analysis of its ranking performance against varying values of both balance parameters and preference parameters also validates its solution accuracy and robustness.
Originality/value
This integrated approach can thus efficiently solve healthcare supplier selection problems based on qualitative evaluation criteria in uncertain group decision making environment. It can also be deployed to deal with other decision making problems in the healthcare sector, like supplier selection for healthcare devices, performance evaluation of healthcare units, ranking of physicians etc.
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Mahsa Sadeghi, Amin Mahmoudi, Xiaopeng Deng and Leila Moslemi Naeni
The aim of this article states that in each stage of the industrial revolution, only a few initiatives have been real game changers. In Industry 3.0, “Internet of Information” has…
Abstract
Purpose
The aim of this article states that in each stage of the industrial revolution, only a few initiatives have been real game changers. In Industry 3.0, “Internet of Information” has transformed the business landscape via connectivity and communications. Enterprises could come together to spur innovation in a cooperative or competitive manner. In Industry 4.0, the “Internet of Value” has shown considerable benefits; and, blockchain technology is expected to touch all layers of a business ecosystem, and the construction industry is not an exception.
Design/methodology/approach
This study aims to answer the “How do enterprise blockchain solutions contribute to the vibrancy of the construction ecosystem from social, economic, and environmental aspects?” Following a comprehensive literature review, the Grey Ordinal Priority Approach (OPA-G) is employed in multiple criteria decision analysis (MCDA). OPA-G can select functionally rich enterprise blockchain solutions that meet the needs of the future construction industry, while there is uncertainty in the input data.
Findings
The results from the case study show that organization under observation welcomes an enterprise blockchain solution that delivers services related to “renewable energy certificates” in the context of “smart cities and built environment”. Employing high-ranked blockchain solutions brings vibracy and sustainability to construction ecosystem in terms of “C6. decentralized finance and investment,” “C3. multi-party and cross-industry collaboration,” and “C8. data-driven value creation”.
Originality/value
At the micro level, blockchain solutions automate processes, streamline operations, and build new capacities on a new business model. At the macro level, blockchain creates a vibrant ecosystem based on transparency, decentralization, consensus-based democracy, interoperability, etc. Indeed, the capability of blockchain solutions at an enterprise scale (enterprise blockchain solutions) can shape a new construction ecosystem. The practical implications of current research are preparing executives for a fundamentally different next normal in construction.
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Sifeng Liu, Ningning Lu, Zhongju Shang and R.M. Kapila Tharanga Rathnayaka
The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series…
Abstract
Purpose
The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series of new grey relational degree model for cross sequences.
Design/methodology/approach
The definitions of cross sequences and area elements have been proposed at first. Then the concept of difference degree between sequences has been put forward. Based on the definition of difference degree between sequences, various modified grey relational degree models for cross sequences have been proposed to solve the measurement problem of cross sequence correlation relationships.
Findings
(1) The new definition of cross sequences; (2) The area element; (3) Various modified grey relational degree models for cross sequences based on the definition of difference degree between sequences.
Practical implications
The grey relational analysis model of cross sequences is a difficult problem in grey relational analysis. The new model proposed in this article can effectively avoid the calculation deviation of grey relational analysis model for cross sequences, and reasonably measure the correlation between cross sequences. The new model was used to analyse the food consumer price index in Shaanxi Province, clarifying the relationship between different types of food consumer price indices, some interesting results that are not completely consistent with general economic theory were obtained.
Originality/value
The new definition of cross sequences, the area element and various modified grey relational degree models for cross sequences were proposed.
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