Ranking efficient DMUs using cooperative game theory

The problem of ranking Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) has been widely studied in the literature. Some of the proposed approaches use cooperative game theory as a tool to perform the ranking. In this paper, we use the Shapley value of two different cooperative games in which the players are the efficient DMUs and the characteristic function represents the increase in the discriminant power of DEA contributed by each efficient DMU. The idea is that if the efficient DMUs are not included in the modified reference sample then the efficiency score of some inefficient DMUs would be higher. The characteristic function represents, therefore, the change in the efficiency scores of the inefficient DMUs that occurs when a given coalition of efficient units is dropped from the sample. Alternatively, the characteristic function of the cooperative game can be defined as the change in the efficiency scores of the inefficient DMUs that occurs when a given coalition of efficient DMUs are the only efficient DMUs that are included in the sample. Since the two cooperative games proposed are dual games, their corresponding Shapley value coincide and thus lead to the same ranking. The more an ef- ficient DMU impacts the shape of the efficient frontier, the higher the increase in the efficiency scores of the inefficient DMUs its removal brings about and, hence, the higher its contribution to the overall discriminant power of the method. The proposed approach is illustrated on a number of datasets from the literature and compared with existing methods

A new model for continuous evaluation of suppliers with real execution data

Supplier evaluation is a significant work for a company in order to enhance productivity and profitability. When a well-managed supplier evaluation is developed, this has a significant impact on the competitiveness of the entire supply chain. By examining the literature, it was seen that a great deal of papers are related to evaluation during new supplier selection process. However, there is a scarcity of studies that evaluate performance depending on the difficulty. The purpose of this paper is to focus on performance evaluation of the suppliers that are being currently worked with. In this context, Enterprise Resource Planning usage is investigated in order to collect and track real-time data for supplier evaluation systems, especially examined small- to medium-sized enterprises. With this in mind, this study conducts a questionnaire on the small- to medium-sized enterprises. Subsequently, by referring to the results of this study, a new evaluation model with dynamic structure is developed utilizing Enterprise Resource Planning, which constantly reviews suppliers at each delivery. Moreover, the developed model has been implemented in a medium-sized machine manufacturing company, integrating it into the purchasing module of its Enterprise Resource Planning system. The managers of the company have confirmed the proposed model and the manufacturing company is continuously doing a systematic evaluation with this model, thus facilitating to attain the goals of supply chain management such as reduction of inventory cost, increasing profit margin and customer satisfaction

DEA-based Nash bargaining approach to merger target selection

Mergers and Acquisitions (M&amp;As) are important business strategies in any industry, as they allow the parties involved to achieve, for example, higher market share, profits and influence in one or more industries. In any M&amp;A activity, the key challenge for an acquirer company is to select the target company that can most improve its performance through synergy. The goal of this research is thus to help acquirer companies model and optimally solve their merger target selection problems (MTSPs) in both horizontal integration and vertical integration settings. We apply both a data envelopment analysis (DEA) based performance evaluation framework and the Nash bargaining solution concept to mathematically model an acquirer company's MTSPs under the two types of integration settings. To the best of our knowledge, the proposed new models are the first DEA-based Nash bargaining models in the literature to help acquirer companies obtain their most desired target companies. Finally, this research provides numerical examples, including real-life examples, to illustrate various aspects and implementation details of the two types of models.</p