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 of sustainability. Decision support systems (DSS) played a vital role in arguably solving the challenges associated with decision making in sustainable logistics. The purpose of this paper is 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 analyzed 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 USA and the UK. 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 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.

Sustainability is a growing concern for manufacturing companies, as they are major contributors to pollution and consume a substantial portion of the world´s natural resources. Sustainable manufacturing can reduce waste, conserve energy and increase resource efficiency. However, one of the main challenges facing manufacturing organisations to put sustainability into practice is the lack of understanding of the cause-and-effect relationships between critical indicators of sustainable manufacturing. To overcome this challenge, a novel, rigorous and integrated framework, composed of four quantitative methods, is proposed to analyse critical indicators of sustainable manufacturing. The analysis is based on responses from both academic and industry experts. These four methods including DEMATEL (decision-making trial and evaluation laboratory), the MMDE (maximum mean de-entropy) algorithm, ISM (interpretive structural modelling) and SEM (structural equation modelling) are uniquely integrated to present statistically validated relationships between critical indicators using information on varying degrees of relationship between them. The final cause-and-effect models for the respondent groups (i.e., researchers and industry experts) are further validated through gathering the viewpoints of a researcher and an industry practitioner for its robustness. The novelty of our research lies in: (1) proposing a novel and integrated rigorous quantitative framework combined with qualitative research method; (2) applying the proposed framework to analyse contextual relationships between critical indicators of implementing sustainability, in the manufacturing sector as a whole, which to the best of authors’ knowledge is the first of its kind; and (3) comparing and contrasting results of researchers and industry practitioners’ groups along with a check of their validation and robustness.