Purpose: Decision-making in logistics is an increasingly complex task for organizations as these involve decisions at strategic, tactical and operational levels coupled with the triple bottom line (TBL) of sustainability. Decision support systems (DSS) played a vital role in arguably solving the challenges associated with decision making in sustainable logistics. This review is a systematic attempt to explore the current state of the research in the domain of DSS for logistics while considering sustainability aspects.Design/methodology/approach: A systematic review approach using a set of relevant keywords with several exclusion criteria was adopted to identify literature related to DSS for sustainable logistics. A total of 40 papers were found from 1994 to 2015, which were then analysed along the dimensions of publishing trend, geographic distribution and collaboration, the most influential journals, affiliations and authors as well as the key themes of identified literature. The analysis was conducted by means of bibliometric and text mapping tools, namely BibExcel, gpsvisualizer, and VOSviewer. Findings:The bibliometric analysis showed that DSS for sustainable logistics is an emerging field; however, it is still evolving but at a slower pace. Furthermore, most of the contributing affiliations belong to the United States and the United Kingdom. The text mining and keyword analysis revealed key themes of identified papers. The inherent key themes were decision models and frameworks to address sustainable logistics issues covering transport, distribution and third party logistics. The most prominent sustainable logistics issue was carbon footprinting. Social impact has been given less attention in comparison to economic and environmental aspects. The literature has adequate room for proposing more effective solutions by considering various types of MCDA (multi-criteria decision analysis) methods and DSS configurations while simultaneously considering economic, environmental and social aspects of sustainable logistics. Moreover, the field has potential to include logistics from wide application areas including freight transport through road, rail, sea, air as well as inter-modal transport, port operations, material handling and warehousing. Originality/value: To the best of the authors' knowledge, this is the first systematic review of DSS for sustainable logistics using bibliometric and text analysis. The key themes and research gaps identified in this paper will provide a reference point that will encourage and guide interested researchers for future study, thus aiding both theoretical and practical advancements in this discipline.

The increasing importance of sustainability has put pressure on organisations to assess their supply chain sustainability performance, which requires a holistic set of key performance indicators (KPIs) related to strategic, tactical and operational decision making of firms. This paper presents a comprehensive set of KPIs for sustainable supply chain management using a mixed method approach including analysing data from the literature survey, content analysis of sustainability reports of manufacturing firms and expert interviews. A 3-level hierarchical model is developed by classifying the identified KPIs into key sustainability dimensions as well as key supply chain decision-making areas including strategic, tactical and operational. A novel multi-attribute decision-making (MADM) based sustainability assessment framework is proposed. The proposed framework integrates value focussed thinking (VFT), intuitionistic fuzzy (IF) Analytic Hierarchy Process (AHP) and IF Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The novelty of the research lies in (1) using a rigorous mixed method approach for KPIs identification and industrial validation (2) the development of a novel integrated intuitionistic sustainability assessment framework for decision making and (3) the innovative application of the proposed framework and associated methodologies in the context not explored before. The practical data on the performance ratings of various KPIs were obtained from the experts and a novel intuitionistic fuzzy TOPSIS was applied to benchmark the organisations for their sustainability performance. Furthermore, the case study shows the applicability of the proposed framework to evaluate and identify the problem areas of the organisations and yield guidance on KPIs by recognising the most significant areas requiring improvement. This research contributes to the practical implication by providing an innovative sustainability assessment framework for supply chain managers to evaluate and manage sustainability performance by making informed decisions related to KPIs.