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The purpose of this paper is to investigate ways to improve operational efficiency of outbound retail logistics considering retailers and consumers by using clustering approach. The retailers are allocated to serve a cluster of consumers. This study demonstrates economic and environment benefits that are achieved in terms of reduced delivery time, transportation cost and carbon emissions.

This study is based on modeling the outbound logistics of a retail chain by using Kohonen self-organizing map (KSOM). KSOM is an unsupervised learning and data analysis method for vector quantization, which is based on Euclidean distance method to form clusters.

Appropriate clustering of retailers and consumers provides efficient locations of retailers that are identified using the KSOM training algorithm. It provides optimum distance with lesser delivery time, transportation cost and carbon emissions.

The implication of research includes modeling of operational procedures in a retail supply chain, which is a crucial task for a business. These operations positively affect the reduction in inventory and distribution costs, improvement in customer service and responsiveness to the ever-changing markets of consumer durables. Overall results are insightful and practical in the sense that implementation would result in consumer convenience, eco-friendly environment, etc.

There is not enough research available on outbound retail logistics considering retailers and consumers using clustering approach.

Benchmarking is an approach to understand and evaluate the current position of different entities like third-party logistics (3PLs) service providers with respect to the best practices. The purpose of this paper is to develop an integrated approach to benchmark the 3PLs and minimize the transportation cost, operational cost, total carbon emissions and improve vehicle capacity utilization rate and demand management in an efficient manner.

Conventional data envelopment analysis (DEA) is extended to develop an integrated approach involving DEA and adaptive linear neuron network (ADALINE). The proposed methodology is dichotomized to the benchmarking of DMUs using Charnes, Cooper, Rhodes ratio and, in the process, helps to suggest ways to reduce inefficiencies.

The approach also supports the decision makers to understand ways to increase the efficiency of decision-making units (DMUs) that are relatively inefficient for a set of 3PLs considered in this study. This is one of the potential researches as it studies how to improve the efficiency of inefficient DMUs.

The proposed approach would help the decision makers to better understand the complexities associated with the low-performing 3PLs. The application of the proposed DEA-ADALINE methodology is illustrated using a range of data set for 3PLs.

The paper examines and explains the value added to the conventional DEA model for obtaining the relative efficiencies with reference to the most efficient DMUs without any loss to the original characteristics of DEA and ADALINE.

The purpose of this paper is to model the enablers of an integrated logistics. The integration is accounted for incorporating sustainability, thereby aiming in its theory building. Existing models have focused on enablers of sustainable supply chain independently which lacks a holistic view in understanding the integrated logistics for sustainable supply chain.

An extensive literature review, expert opinion from both industry and academia based on questionnaire survey, is conducted to find the relevant enablers. The modeling of these enablers is done using total interpretive structural modeling (TISM). Finally, TISM along with its respective fuzzy-matriced impact croises multiplication applique (fuzzy-MICMAC) analysis is depicted.

The result of the survey and TISM model with its respective fuzzy-MICMAC has been used to evolve the mutual relationships among the important enablers of integrated logistics of consumer durables. The strategic factors obtained from TISM are integration and collaboration in the supply chain, vehicle type, and capacity; reduction in average length of haul; and real-time information system. Route selection and scheduling, reduction of fuel consumption, customer relationship management, green technology, cost reduction, etc., are some of the operational factors. Sustainable environment performance is obtained as the performance factor. Fuzzy-MICMAC is more responsive than the traditional MICMAC analysis.

The study has limitation for the development of a conceptual framework for integrated logistics in uncertain environments. So it can be extended by combining soft computing methodologies. There is a lack of mathematical quantification of the proposed model where the enablers of sustainability can be measured.

The study on integrated logistics for sustainable supply chain is itself a new area to be explored, as very few studies on this relevant topic exist. The research concentrates on TISM for the integrated logistics and the movement of consumer durables through different distribution channels of a supply chain. The study has implications for practitioners, academicians, and policy makers. For practitioners, it provides a list of strategic factors, operational factors, and performance factors. For academicians, this methodology can be opted to conduct an exploratory study by identifying the essential enablers. For policy makers, the regulations can be developed using the above model.

It is an effort to model the important enablers and establish sustainability in integrated logistics of consumer durables.