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The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province.

The clustering process is divided into two stages. In the first stage, grey cloud clustering coefficient vectors are obtained by grey cloud clustering. In the second stage, with the help of the weight kernel clustering function, the general representation of the weight vector group of kernel clustering is given. And a new coefficient vector of kernel clustering that integrates the support factors of the adjacent components was obtained in this stage. The entropy resolution coefficient of grey cloud clustering coefficient vector is set as the demarcation line of the two stages, and a two-stage grey cloud clustering model, which combines grey and randomness, is proposed.

This paper demonstrates that 18 cities in Henan Province are divided into five categories, which are in accordance with five drought hazard levels. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical and effective new method for drought risk assessment and, then, provides theoretical support for the government and production departments to master drought information and formulate disaster prevention and mitigation measures.

The model in this paper not only solves the problem that the result and the rule of individual subjective judgment are always inconsistent owing to not fully considering the randomness of the possibility function, but also solves the problem that it’s difficult to ascertain the attribution of decision objects, when several components of grey clustering coefficient vector tend to be balanced. It provides a new idea for the development of the grey clustering model. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

The purpose of this paper is to appraise the efficiency, effectiveness, and performance of 27 public sector banks (PSBs) operating in India by using a two‐stage performance evaluation model.

Using the cross‐sectional data for the financial year 2006/2007, the technique of data envelopment analysis has been used for computing the efficiency and effectiveness scores for individual PSBs. The overall performance scores have been derived by taking the product of efficiency and effectiveness scores.

The empirical results reveal that high efficiency does not stand for high effectiveness in the Indian PSB industry. A positive and strong correlation between effectiveness and performance measures has been noted. Further, on the efficiency front, State Bank of Travancore appears as an ideal benchmark, while State Bank of Bikaner and Jaipur, and State Bank of Mysore emerge as ideal benchmarks on the effectiveness front.

The practical implication of the research findings is that in their drive to improve overall performance, Indian PSBs should pay more attention to their income‐generating capabilities (i.e. effectiveness) relative to their ability to produce traditional outputs such as advances and investments (i.e. efficiency).

This paper is perhaps the first to evaluate the performance of Indian banks by considering simultaneously the aspects of efficiency and effectiveness.

This paper aims to identify the relationship between efficiency and profitability by using data from Greek meat processing companies over the period 1994‐2007.

The relationship of efficiency and profitability is studied, by applying a new performance decomposition model. This method is capable of making valid and consistent inferences about the performance of a two‐stage production system, as well as the main sources of inefficiencies within a company.

A poor performance over the study period is observed in the sample companies. The low performance is mainly due to the low profitability. The results do not confirm the existence of a positive strong correlation between efficiency and profitability. The companies that have the capability of producing their products with the best practices are not always capable of generating the maximum profits.

The need for the improvement of performance has two aspects: first, it is a demand for the effective use of resources, and simultaneously, it is an urgent requirement for the generation of profits. According to the study findings, the long‐term survival of firms in our sample seems to require adopting mainly profitability‐enhancing strategies.

This paper provides one of the first evaluations of performance focusing on efficiency and profitability, by applying an innovative performance decomposition approach that has not yet been applied in Greek industries.

The purpose of this study is to investigate customer satisfaction and its effect on image, trust, and customer loyalty for Islamic banks.

The study uses data from Islamic banks and dual‐window Islamic banks, pertaining to two different customer segments (Muslims and non‐Muslims).

The results indicate that customer satisfaction has a significant relationship with image, image has a significant relationship with trust, and trust has a significant relationship with customer loyalty for both customer segments. Furthermore, significant differences occur in the effect of customer satisfaction on image, image on trust, and trust on customer loyalty between Muslim and non‐Muslim customers.

The findings suggest that Muslim customers establish relationships with Islamic banks because they trust that Islamic banks are Shariah compliant. Therefore, providing secure banking products that are fully compliant with Islamic principles are necessary.

This research is important as it clearly demonstrates that the loyalty of Muslim and non‐Muslim customers to Islamic banks is influenced by customers being satisfied, as well as the image of and trust in Islamic banks. In this context, when customers are unwilling to trust Islamic banks, they are also unwilling to be loyal.

The purpose of the study is to investigate the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust on mobile website satisfaction.

A total of 302 valid questionnaires were collected to empirically test the research model. Structural equation modeling (SEM) was performed to evaluate the reliability and validity of the measurement model and structural models.

The results show that there is a positive relationship between PEOU, PU and mobile users’ satisfaction. PU is positively related to trust and mobile users’ satisfaction. Moreover, trust positively influences mobile users’ satisfaction.

Drawing on the technology acceptance model and trust theory, this study develops and empirically examines a model for consumers’ satisfaction to use mobile services. This study contributes new insights concerning the marketing literature by examining the impact of PU, PEOU and trust on mobile users’ satisfaction.

The contribution of the study is significant for both mobile marketers and academicians in the era of the third-generation environment. This study is among the first few attempts to integrate the TAM with trust to determine mobile user satisfaction.

This paper aims to identify the determinants of the intention to use mobile banking services among Islamic Banking customers in Sri Lanka. The study was carried out based on the Unified Theory of Acceptance and Use of Technology (UTAUT 2). The predictor variables of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation and habit were used to predict the variable of behavioural intention to use. The moderating variables entail age, gender and experience.

Quantitative method with questionnaire survey was used. Data collection relied on the questionnaire survey method of which items were derived and adapted from past literatures. The responses were captured using the seven-point Likert scale. The study population consisted of Islamic Banking customers in Sri Lanka. A total of 594 questionnaires were returned of which 582 were found usable for analysis. Data analysis was conducted using the partial least square structural equation modelling along with SmartPLS 3.

The analysis results demonstrated the significant effect of all the variables on the Islamic Banking customers’ intention to use m-banking services along with the significant effect of the moderating variables as initially hypothesized.

As the first study of its kind in the context of Islamic banking customers in Sri Lanka, this study offers decision makers valuable guidelines for when they intend to re-engineer their m-banking applications and promote them to the public.

Following a comprehensive literature review, this study is identified as the pioneering effort in the investigation of m-banking usage intention among Islamic Banking customers in Sri Lanka. Therefore, this study contributes new knowledge and insights to the existing body of literature by confirming the viability of the UTAUT2 model in driving m-banking usage adoption among Islamic Banking customers in Sri Lanka.

It is always of great importance for managers in organizations to evaluate their staff members and create incentive systems, using instruments such as Data Envelopment Analysis (DEA) and DEA-R (DEA models based on ratio analysis). The purpose of this paper is to propose a two-stage network incentives system for commercial banks.

Centralized Resource Allocation (CRA) models make it possible to project all decision-making units (DMUs) onto the efficient frontier by solving a single linear programming model. In this paper, we use our proposed DEA-R-based CRA models to evaluate commercial banks in a two-stage case when the only ratios available are the assets-to-costs and income-to-assets vectors.

Thirteen commercial banks modeled as two-stage networks were evaluated by the models proposed in two different cases of ratio data. Results suggest that the proposed methodology yields more accurate efficiency scores, thus allowing better discrimination among DMUs. Furthermore, evaluating the DMUs when they are structured as two-stage (or even three-stage) networks makes it possible to examine the incentives system in more detail. Therefore, the use of incentive systems by managers would allow a better focus on the priority activities of commercial banks and a faster movement toward the frontier of best practices.

The super-efficiency scores of a number of commercial banks are evaluated based on the CRA model, as a cornerstone criterion for the two-stage evaluation in DEA-R, thus allowing the rank of each commercial bank in terms of the incentives system rather on the performance of the productive process.

In multi-criteria decision-making with interval grey number information, decision makers usually take a risk to rank or choose some very similar alternatives. Additionally, when evaluating only one alternative, decision makers can only obtain a specific value using traditional decision-making methods and may find it hard to cluster the alternatives to the “correct class” because these methods lack predetermined reference points. To overcome this problem, this paper aims to propose a two-stage grey decision-making method.

First, a new type of clustering method for interval grey numbers is designed by proposing a new possibility function for grey numbers. Based on this clustering method, a new grey clustering evaluation model for interval grey numbers is proposed by which decision makers can obtain the grade rating information of each alternative. Then, according to the grey clustering evaluation model, a new two-stage decision-making method is introduced to solve the problem that some alternatives are very similar by designing a grey comprehensive decision coefficient of alternatives.

The authors propose a new grey clustering evaluation model to deal with interval grey numbers. They design a new model to obtain the membership degree for the interval grey numbers and then propose a new grey clustering evaluation model, which can evaluate only one alternative by predefined grey classes. Then, by the grey comprehensive decision coefficient, a two-stage grey evaluation decision-making method is put forward to solve the problem that some alternatives are very close and hard to be distinguished.

A new grey clustering evaluation model is proposed, which can evaluate only one alternative by predefined grey classes. A two-stage grey evaluation decision-making method is given to solve the problem that some alternatives are very close and hard to be distinguished.

Banking is the key industry to guarantee the core leading role of finance in the process of economic development. It is important to study the bank efficiency and optimal allocation of bank’s resources. The purpose of our paper is to study the optimal allocation of resources between the bank savings system and loan system under the premise of environmental heterogeneity.

We use a two-stage meta-frontier Data Envelopment Analysis model to solve the relative efficiency of each city branch and use the multivariate statistical tools to analyze the empirical results.

This paper measures the relative efficiency of 16 Bank Branches of a state-owned bank in Anhui province considering regional heterogeneity. Based on the optimal resource allocation, we get the two-stage operation performance of all banks under group-frontier and meta-frontier and analyze the impact of the technical differences between the branches.

This study has a positive guiding significance for the banking industry to improve its operational efficiency in various business practices in the new era of big data. It will also provide practical suggestions and support for the government and relevant departments in the process of formulating macro-policies to ensure the healthy and stable development of the banking industry.

Each production unit is responsible for the protection of the environment. The restricted undesirable production effects lower environmental damage. This paper emphasizes a proportional reduction of the undesirable outputs, and it supports the growth of desirable outputs as much as possible as well. The two-stage proposed model not only considers the viewpoint of the managers to follow the environmental regulations but also it assigns some bounds on producing undesirable factors according to international environmental protocols. Additionally, the restricted bounds on the undesirable outputs, in both stages, enhance the discriminatory ability of the model.

Two-stage network structure based on Data Envelopment Analysis (DEA) is applied as the main methodology for this paper. The advantages of the proposed model are appointed to assess the environmental units.

Comparing with the existing models, the proposed approach presents a new two-stage model to deal with the environmental issues. Furthermore, the discriminatory ability of the efficiency scores is improved. The distribution of this model is greater than the existing ones.

This paper is fully written, submitted and revised during limitations caused by coronavirus .

The proposed method is employed in two different cases. The efficiency scores of 25 power plants and 13 poultry farms are determined. In fact, the undesirable outputs never meet zero in the process of production but they can be reduced. The results of this research support the effect of the undesirable factors' restriction on the reduction scenario. Both of the examples show that imposing the upper bounds for the undesirable products provide low-efficiency results in comparison with the existing model. On the other hand, the results cover the arguments of sustainability in the evaluation of environmental efficiency.

In the production process, desirable outputs and undesirable factors are produced jointly so undesirable factors never meet zero. This paper develops a new two-stage method to reduce the undesirable outputs at each stage. First, the model confirms the reduction of undesirable outputs. Second, this model imposes restrictions on intermediate and final undesirable outputs according to environmental rights and the concerns of the managers. The model increases the discrimination of the efficiency assessment of real-life two-stage environmental systems as well. Then it focuses on the production of desirable outputs. The new objective function is defined according to the aim of the proposed model that not only declares better efficiency decomposition to the individual system but also the efficiency score is evaluated for each stage.