18,676 research outputs found
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 eļ¬cient DMUs and the characteristic function represents the increase in the discriminant power of DEA contributed by each eļ¬cient DMU. The idea is that if the eļ¬cient DMUs are not included in the modiļ¬ed reference sample then the eļ¬ciency score of some ineļ¬cient DMUs would be higher. The characteristic function represents, therefore, the change in the eļ¬ciency scores of the ineļ¬cient DMUs that occurs when a given coalition of eļ¬cient units is dropped from the sample. Alternatively, the characteristic function of the cooperative game can be deļ¬ned as the change in the eļ¬ciency scores of the ineļ¬cient DMUs that occurs when a given coalition of eļ¬cient DMUs are the only eļ¬cient 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- ļ¬cient DMU impacts the shape of the eļ¬cient frontier, the higher the increase in the eļ¬ciency scores of the ineļ¬cient 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 hybrid performance evaluation approach for urban logistics using extended cross-efficiency with prospect theory and OWA operator
Urban logistics performance evaluation can provide reference for further
improving its level. However, most performance evaluation for
urban logistics premises that decision-makers (DMs) are completely
rational, which may not conform to the actual situation. Therefore,
this article aims to consider the DMsā psychological factors in the performance
evaluation of urban logistics. Specifically, the cross-efficiency
evaluation (CEE) method with the DMsā psychological factors
is used to measure the urban logistics efficiency in the central area of
Yangtze River Delta (YRD) urban agglomeration in China in 2019. The
main contributions in this article are to propose a hybrid CEE method
with prospect theory and ordered weighted average (OWA) operator
for urban logistics industry and to expand the evaluation perspectives
of urban logistics performance. The main conclusions are
obtained: (1) The DMsā optimism level can indeed affect the efficiency
value and ranking of urban logistics. (2) The aggregation
based on the OWA operator is fair and reasonable because it can
make all self-evaluation efficiencies play the same role. (3) To make
the efficiencies and rankings of urban logistics in the central area of
the YRD have credibility and discrimination, the DMsā optimism level
range is best between 0.8 and 0.8177
Stimulating innovation in Russia: the role of institutions and policies
This paper examines the potential role of innovation policy in enhancing long-term productivity growth in Russia. It begins by exploring the role of framework conditions for business in encouraging innovative activities, particularly with respect to intellectual property rights and competition. Realising Russiaās innovation potential will also require reform of the large public science sector. This raises issues pertaining to the organisation and financing of public research bodies and, in particular, to the incentives and opportunities they face in commercialising the results of their research. Finally, the paper looks at the potential role of direct interventions, such as special economic zones and technoparks, as well as the scope for improving the tax regime for private-sector R&D
Processes, information, and accounting gaps in the regulation of Argentina's private railways
Almost a decade after Argentina began privatizing its railways, resolution of conflicts between regulators, users, and operators continues to take longer, and to be more difficult, than expected. The authors contend that many of these conflicts arose because there are no rules for interactions between the key stakeholders: government, regulators, users, unions, and the media. One result of inexperience in setting up concession agreement has been that the agreements did not clearly define the information needed for oversight and regulation. Argentine rail concession contracts were supposed to be specific about the way tariffs, quality, investment, exclusivity, and so on, would change over time. And the newly created regulatory bodies were given some discretion about adjusting the contracts in the face of unforeseen developments. However, initial privatization were carried out in such a way that there was no time to refine terms, so many loopholes remained. Those unforeseen events have happened, and the regulatory agency, the National Commission for Transport Regulation (CNRT), has had to adapt its procedures and decisions to available information. In some cases, alleged modifications of the operating environment have led to renegotiations. Changes have been introduced in the approach to furnishing information to the government for oversight and regulatory accounting. The changes center on clearer definitions in connection with four major issues: a) The measurement of efficiency; b) access prices; and c) the financial model. Circumstances in the Argentine rail industry early in 2001 did not favor dramatic changes, but current renegotiations could be used to adjust information requirements to reflect what has been learned through six yearsof experience.Environmental Economics&Policies,Knowledge Economy,Labor Policies,Decentralization,Financial Intermediation,Environmental Economics&Policies,Financial Intermediation,Banks&Banking Reform,Education for the Knowledge Economy,Knowledge Economy
Disaster Management Cycle-Based Integrated Humanitarian Supply Network Management
While logistics research recently has placed increased focus on disruptionmanagement, few studies have examined the response and recovery phases in post-disaster operations. We present a multiple-objective, integrated network optimizationmodel for making strategic decisions in the supply distribution and network restorationphases of humanitarian logistics operations. Our model provides an equity- or fairness-based solution for constrained capacity, budget, and resource problems in post-disasterlogistics management. We then generate efficient Pareto frontiers to understand the trade-off between the objectives of interest.Next, we present a goal programming-based multiple-objective integratedresponse and recovery model. The model prescribes fairness-based compromise solutionsfor user-desired goals, given limited capacity, budget, and available resources. Anexperimental study demonstrates how different decision making strategies can beformulated to understand important dimensions of decision making.Considering multiple, conflicting objectives of the model, generating Pareto-optimal front with ample, diverse solutions quickly is important for a decision maker tomake a final decision. Thus, we adapt the well-known Non-dominated Sorting GeneticAlgorithm II (NSGA-II) by integrating an evolutionary heuristic with optimization-basedtechniques called the Hybrid NSGA-II for this NP-hard problem. A Hypervolume-basedtechnique is used to assess the algorithmās effectiveness. The Hazards U.S. Multi-Hazard(Hazus)-generated regional case studies based on earthquake scenarios are used todemonstrate the applicability of our proposed models in post-disaster operations
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