A Modified Super-Efficiency in the Range Directional Model

The range directional model (RDM) relaxes the assumption of non-negativity of inputs and outputs in the conventional data envelopment analysis (DEA) with the aim of evaluating the efficiency of a decision-making unit (DMU) when some data are negative. Although the concept of super-efficiency in the RDM contributes to enhancing discriminatory power, the formulated model may lead to the infeasibility problem for some efficient DMUs. In this paper, we modify the super-efficiency RDM (SRDM) model to overcome the infeasibility problem occurring in such cases. Our method leads to a complete ranking of the DMUs with negative data for yielding valuable insights that aid decision makers to better understand the findings from a performance evaluation process. The contribution of this paper is fivefold: (1) we detect the source of infeasibility problems of SRDM in the presence of negative data, (2) the proposed model in this study yields the SRDM measures regardless of feasibility or infeasibility of the model, (3) when feasibility occurs, the modified SRDM model results in the scores that are the same as the original model, (4) we differentiate the efficient units to improve discriminatory power in SRDM, and (5) we provide two numerical examples to elucidate the details of the proposed method

An Integrated Fuzzy Clustering Cooperative Game Data Envelopment Analysis Model with application in Hospital Efficiency

Hospitals are the main sub-section of health care systems and evaluation of hospitals is one of the most important issue for health policy makers. Data Envelopment Analysis (DEA) is a nonparametric method that has recently been used for measuring efficiency and productivity of Decision Making Units (DMUs) and commonly applied for comparison of hospitals. However, one of the important assumption in DEA is that DMUs must be homogenous. The crucial issue in hospital efficiency is that hospitals are providing different services and so may not be comparable. In this paper, we propose an integrated fuzzy clustering cooperative game DEA approach. In fact, due to the lack of homogeneity among DMUs, we first propose to use a fuzzy C-means technique to cluster the DMUs. Then we apply DEA combined with the game theory where each DMU is considered as a player, using Core and Shapley value approaches within each cluster. The procedure has successfully been applied for performances measurement of 288 hospitals in 31 provinces of Iran. Finally, since the classical DEA model is not capable to distinguish between efficient DMUs, efficient hospitals within each cluster, are ranked using combined DEA model and cooperative game approach. The results show that the Core and Shapley values are suitable for fully ranking of efficient hospitals in the healthcare systems

Sustainable Value-Sharing Mechanisms of the Industrial Internet of Things Platforms:A Case Study of Haier’s Service-Oriented Transformation

Ensuring fairness and equity in value distribution is crucial for the sustainability of platform ecosystems. However, existing approaches to distributing benefits among cooperative entities often find it difficult to accurately assess each stakeholder’s contributions. This paper tackles this challenge through a case study of the Haier COSMOPlat IIoT platform. By analyzing its value creation and value distribution processes, the research uncovers how platform enterprises can overcome existing limitations by quantifying and revealing intangible customer relationships alongside financial metrics. This revised value-sharing mechanism encourages a shift from “post-event value-sharing” to “mid-event adjustment”, promoting a fair and equitable profit distribution framework that motivates stakeholders toward sustainable value co-creation