Community partition is a significant task in social network analysis. For some interest networks, the interest of nodes may influence the formation of community. Considering the cooperation relation among nodes, we pro-pose a cooperative social network partition approach by using the technique of data envelopment analysis. In this approach, the interest relationship among decision making units (DMUs) is identified by measuring the increased revenue of two cooperative DMUs, and then, a weighted interest network is constructed correspondingly. In this interest network, each node would like to cooperate with others to gain more benefits. Regarding each node as a player, the formation of community can be achieved by a cooperative game. We employ Shapley value mech-anism mainly including five algorithms, i.e., maximum Shapley value of each node, expand algorithm, check stability, update, and merge process, to achieve community partition. Finally, the proposed method is applied to mineral resource of 31 provinces in Chinese mainland.

Identifying role models from a large-scale sample is critical for improving the performance of the society or large organizations because it is an effective way to spread positive ideologies, attitudes, and the best behaviors. To find role models from a large-scale sample, this study proposes a social network data envelopment analysis method by integrating data envelopment analysis (DEA) and social network analysis (SNA), where DEA is non-parametric data-driven technique for evaluating the relative performance of peer decision making units (DMUs) and SNA seeks to understand network structure and characteristic through the relationships between nodes. A pairwise evaluation process is constructed to explore the performance of each DMU relative to another based on the DEA method. Then, the pairwise evaluation matrix that reflects the reference relationship between any two DMUs is obtained. Based on this matrix, the social network is established, and role models in the large-scale sample are identified by calculating the in-degree centrality values of all DMUs. More importantly, based on the indicator weights in DEA models, the strengths of role models are analyzed in detail. Finally, we construct the experiments with the online diagnostic data of 10599 doctors in 55 departments on the Chunyu Doctor platform in China to validate our proposed social network DEA method.

This paper uses the data envelopment analysis (DEA) approach to solve the issue of allocating fixed costs among a set of decision-making units (DMUs) with two-stage network structure. Fixed cost allocation is a prominent issue that is encountered by organizations, and it is one of the most important applications of DEA. It exists not only in single-stage systems but in two-stage network systems, such as bank systems in real situations, which comprises the deposits process and lending process. However, branch banks often compete with one another out of self-interest. The objective of this paper is to design a fair allocation scheme for two-stage network systems and considering the noncooperative game relationship among DMUs. The idea of satisfaction degree and noncooperative game theory is integrated into the proposed allocation model. In the noncooperative framework, we define a DMU’s payoff as the product of two substage satisfaction degree, and every member is noncooperative and selfishly seeks to maximize its own payoff. The allocation plan to DMUs and substages is determined by the final competition payoff. A real case is analyzed to illustrate the applicability of the proposed approaches.

Abstract Mergers and acquisitions (M&A) are important parts of banking reform, which can increase the synergies and reduce the costs of the banks. To analyze the effect and importance of the M&A in the reform period, we measure the productivity change of China’s banks who completed M&A during 2004– 2018, by using a two-stage data envelopment analysis (DEA) method. First, we incorporate the process of deposits producing and the process of profit earning as a two-stage structure of bank’s system. Then, we construct a slacks-based measure (SBM) model considering the weak disposability of undesirable outputs to measure the productivity of 14 M&A banks in China. Particularly, we adopt the global Malmquist index (GMI) to evaluate the productivity change of the banks, and analyze the efficiency change (EC) and technical change (TC) for the whole system and individual stages. Additionally, to facilitate making M&A plans, we classify the M&A banks to obtain the process they need to improve and the trend they could adopted: (i) We classify them into four categories by the productivity of two individual stages; (ii) We also classify them into four categories by EC and TC. Finally, the policy recommendations for M&A banks are given.

Allocating fixed cost among a group of entities is becoming increasingly important in management. Numerous studies have addressed this issue in single-stage systems based on data envelopment analysis (DEA). However, these studies frequently ignored the internal structure of systems, and in many real applications, enterprises with multiple stage processes cooperate with one another. Taking this issue into account in the allocation process, we approach fixed-cost allocation issues of two-stage systems by considering a cooperative relationship among decision making units (DMUs). We integrate cooperative game theory and the DEA methodology to generate a unique and fair allocation plan. The results confirm that each DMU can maximize its relative efficiency to one by a series of optimal variables after the fixed cost allocation. Based on these results, a unique nucleolus solution can be generated through a feasible computation algorithm. Finally, we apply the proposed approach to a random dataset and an empirical commercial bank application in China.

Fixed cost allocation among groups of entities is a prominent issue in numerous organisations. Addressing this issue has become one of the most important topics of the data envelopment analysis (DEA) methodology. In this study, we propose a fixed cost allocation approach for basic two-stage systems based on the principle of efficiency invariance and then extend it to general two-stage systems. Fixed cost allocation in cooperative and noncooperative scenarios are investigated to develop the related allocation plans for two-stage systems. The model of fixed cost allocation under the overall condition of efficiency invariance is first developed when the two stages have a cooperative relationship. Then, the model of fixed cost allocation under the divisional condition of efficiency invariance wherein the two stages have a noncooperative relationship is studied. Finally, the validation of the proposed approach is demonstrated by a real application of 24 nonlife insurance companies, in which a comparative analysis with other allocation approaches is included. (C) 2019 Elsevier B.V. All rights reserved.