The current paper aims to develop an effective and integrated MCDM model for the evaluation of the sustainability practices in the banking services, employing a multi‐stage, fuzzy MCDM model that integrates the Balanced Scorecard, fuzzy AHP and fuzzy TOPSIS. The approach aims to evaluate sustainability from the following four perspectives: financial stability, customer relationship management, internal business process and environment‐friendly management system. A real implementation dealing with the six largest commercial banks in India is discussed. The results highlights the critical aspects of the evaluation criteria and the issues in improving sustainable banking performances. Regarding the sustainability issues, it is shown that the environment‐friendly management system takes a back seat compared with the other criteria. Furthermore, the results show that there is a misunderstanding of the role that corporate social responsibility plays with respect to environmental issues. The developed evaluation model offers a valuable management tool for banks' administrators by assisting them in strategic choices in order to achieve their objective of sustainability and sustainable banking. Moreover, it offers a measuring tool with unique features that complements the emerging trend of integrated reporting considering uncertainty. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment

Home care services are an alternative answer to hospitalization, and play an important role in reducing the healthcare costs for governments and healthcare practitioners. To find a valid plan for these services, an optimization problem called the home healthcare routing and scheduling problem is motivated to perform the logistics of the home care services. Although most studies mainly focus on minimizing the total cost of logistics activities, no study, as far as we know, has treated the patients' satisfaction as an objective function under uncertainty. To make this problem more practical, this study proposes a bi-objective optimization methodology to model a multi-period and multi-depot home healthcare routing and scheduling problem in a fuzzy environment. With regards to a group of uncertain parameters such as the time of travel and services as well as patients' satisfaction, a fuzzy approach named as the Jimenez's method, is also utilized. To address the proposed home healthcare problem, new and well-established metaheuristics are obtained. Although the social engineering optimizer (SEO) has been applied to several optimization problems, it has not yet been applied in the healthcare routing and scheduling area. Another innovation is to develop a new modified multi-objective version of SEO by using an adaptive memory strategy, so-called AMSEO. Finally, a comprehensive discussion is provided by comparing the algorithms based on multi-objective metrics and sensitivity analyses. The practicality and efficiency of the AMSEO in this context lends weight to the development and application of the approach more broadly.

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Growing food demand, environmental degradation, post-harvest losses and the dearth of resources encourage the decision makers from developing nations to integrate the economic and environmental aspects in food supply chain network design. This paper aims to develop a bi-objective decision support model for sustainable food grain supply chain distribution system considering an entire network of procurement centres, central, state and district level warehouses, and fair price shops. The model seeks to minimize the cost and carbon dioxide emission simultaneously. The model covers several problem peculiarities such as multi-echelon, multi-period, multi-modal transportation, emission caused due to various motives, heterogeneous capacitated vehicles and limited availability, multiple sourcing and distribution, and capacitated warehouses. Several different realistic problem instances are solved using the two Pareto based multi-objective algorithms. Sensitivity analysis results imply that the decision makers should establish the sufficient number of warehouses in each producing and consuming states by maintaining the suitable balance between the two objectives. Multiple policymakers like Food Corporation of India, logistics providers and state government agencies will be benefited from this research study.

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