Multi-activity Data Envelopment Analysis Research Articles

Is there a trade-off between social and financial performance of public commercial banks in India? A multi-activity DEA model with shared inputs and undesirable outputs

Indian public commercial banks play a crucial role in the financial support for the economic development, poverty alleviation, and women's empowerment. As social banks, they have dual performance objectives of financing the vulnerable sections of society as well as providing mainstream financial services. Balancing these twin missions is the biggest challenge for these hybrid enterprises. To date, no study has been published giving evidence on whether these banks are efficient in both facets of their dual goals. For this reason, this paper adds to the literature by measuring the social and financial efficiency of a sample of 26 Indian public banks over 2011–2014 by using an innovative Multi-activity Data Envelopment Analysis (MDEA) model with shared inputs and undesirable outputs. Our study also examines whether there is a conflict or trade-off between socially responsible and for-profit banking practices. We find that Indian public banks have managed their dual mission relatively well, but on average, they have been much more efficient in social (99.4%) than conventional banking (81.9%) activity. Moreover, this study shows a significant synergy effect between social and financial performance. However, when regional differences across India are considered by comparing the social and financial efficiency scores for different degrees of economic and human development in Indian states, the significant synergy effect is only confirmed in those public banks located in less more economically developed Indian states.

Measuring departmental and overall regional performance: applying the multi-activity DEA model to Taiwan׳s cities/counties

This study measures the departmental and overall efficiency in Taiwan׳s counties/cities by applying a multi-activity data envelopment analysis (MADEA) model. The model overcomes the problems of panel data, undesirable outputs, shared inputs, and environmental variables and intertemporal efficiency changes (productivity) by applying the Malmquist–Luenberger (ML) index. We include data on the economic development, social welfare, police and security, and education departments for 20 counties/cities in Taiwan for the period 1999–2013. We find that the police security department is the most efficient in most counties/cities in the period 1999–2013, and the economic development department is the second efficient one in 2002–2005 and after 2009. Furthermore, there exist urban–rural gaps in the efficiency scores between counties and cities, between service-type and non-service-type counties/cities, and among different regions. With regard to the efficiencies over time (ML indices and their decompositions), we find that the production frontiers of the social welfare and education departments in Taiwan׳s counties/cities expanded continuously during this period. Finally, we also find that urban–rural gaps and gaps between service-type and non-service-type counties/cities exist in terms of technological changes and ML productivity indices in the social welfare and education departments. The area differences of technological changes exist in 4 departments and in overall. Our results will help the mayors of counties/cities understand the strengths and weaknesses of the regions they govern.

Türkiye’de kamu üniversitelerinin eğitim-araştırma etkinlikleri ve etkinlik artışında stratejik önceliklerin rolü: Çok-aktiviteli VZA uygulaması

In this study, the research and teaching efficiencies of 45 selected state universities in Turkey are measured by using the Multi-Activity Data Envelopment Analysis (MA-DEA) model for the year 2010. Universities are institutions which face multiple production functions simultaneously, therefore they can be considered as carrying out mainly research and teaching activities using common resources. The mathematical formulation of MA-DEA is capable of objectively assigning the shared variables to different activities. Hence, the model is adapted to the problem by assuming a suitable production process for the Turkish Higher Education System. Results first show that the MA-DEA model generates different efficiency scores for universities and hence “research efficient” and “teaching efficient” universities have been identified. In addition, since the structure of MA-DEA model allows each university can give different priorities to different activities, scenario analyses have been applied on this priorities and it is shown that by assigning higher priorities to the activities which they are more efficient, universities can reach higher total efficiencies. The importance of this result related with performance analysis and strategic planning is then emphasized.

Measuring the performance of financial holding companies

Financial institutions have become larger and engage in a wider array of financial activities due to continuing consolidation. Since the financial holding companies face multiple production functions simultaneously, the traditional data envelopment analysis (DEA) approach is not suitable for investigating their efficiency. This study applies the multi-activity DEA model to explore the relative efficiency of 12 financial holding companies in Taiwan. The results show that the multi-activity DEA model is obviously more capable of identifying sources of inefficiency, thereby potentially yielding greater managerial insights into organisational improvements.

Productive efficiency, environmental efficiency and their determinants in farrow-to-finish pig farming in Taiwan

Two sub-technologies, pig production and wastewater control, in pig farm operation are considered. This paper develops a multi-activity DEA (data envelopment analysis) model to simultaneously measure productive efficiency (PE) and environmental efficiency (EE) in farrow-to-finish pig production in Taiwan, and to explore several theorized causal relationships between performance and farm-specific knowledge. The empirical results prove that the estimated PE and EE do not belong to the same distribution. That suggests that using an identical ‘technical efficiency’ index to represent PE and EE would get a biased result when undesirable outputs are considered. PE is higher than EE, but the two are positively correlated. Analytical results support the presence of economies of scale in sample farms. Providing training to farmers and computerizing farm operations are critical determinants of PE; providing training to operators of wastewater control facilities and the operator's education level showed a positive impact on EE. Such information is valuable for both farmers and the authorities in making decisions to enhance productivity and environmental protection in the pig sector in Taiwan.

Measuring the Cost Effectiveness of Multimode Bus Transit in the Presence of Accident Risks

This study employs the directional graph distance function and the multiactivity data envelopment analysis (DEA) approach, which incorporates both desirable and undesirable outputs, in order to provide a more complete representation of the multimode bus production technology from which environmentally and risk-sensitive cost effectiveness measures can be generated. We treat accident cost as the risky output in the sense that we wish to increase desirable outputs and decrease risky output and inputs. The approach is applied to the problem of measuring the cost effectiveness of 24 bus companies in Taiwan. An empirical illustration suggests that the overall cost effectiveness rankings turn out to be very sensitive to whether or not the graph multiactivity DEA approach is adopted. This implies that the conventional DEA cost effectiveness measure may be seriously misleading if it ignores the cost effectiveness of organizations that carry out various activities whilst sharing common resources.

The efficiency of the Spanish police service: an application of the multiactivity DEA model

In this paper the efficiency of the Spanish Police Service is analysed using Data Envelopment Analysis (DEA). The analysis concentrates on the police activities related to the solving of crimes. The theoretical and empirical study of the police production function under this dimension leads to a consideration of the units analysed as centres which carry out their activities with nonidentical technologies and using common inputs. Accordingly, the multiactivity DEA model developed by Mar Molinero (Journal of the Operational Research Society, 47, 1996, 1273-9) is applied, one that is designed to estimate the efficiency of institutions which face several production functions using shared inputs. The results demonstrate the important differences that exist between the centres with respect to the distinct activities analysed, both as regards the efficiency rates and the factors which determine them.