6 research outputs found
Decision Support Systems for Sustainable Logistics: A Review and Bibliometric Analysis
Get PDFPurpose: 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
Decision support systems for sustainable logistics: A review and bibliometric analysis
Get PDFPurpose: 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
Decision support for centralizing cargo at a Moroccan airport hub using stochastic multicriteria acceptability analysis
No full textThe geographical location of Morocco places it at the heart of important sea, air, rail and motorway transport routes between four continents. In this study we evaluate different alternatives to centralize multimodal cargo at a Moroccan airport hub. The choice depends on different socio-economical criteria, the geographical location, and the environmental impacts. Some of the criteria can be measured quantitatively, while for others only qualitative assessment is feasible. Furthermore, significant uncertainty is present in both the criteria measurements and the preferences. We aided this decision process using Stochastic Multicriteria Acceptability Analysis (SMAA). SMAA is a method that allows the representation of a mixture of different kinds of uncertain, imprecise and partially missing information in a consistent way. The results indicated that two of the alternatives, Benslimane and Casablanca, were superior. As a result of the analysis, the National Airport Authority of Morocco started negotiations with investors to develop the hub at Benslimane.Transportation Air cargo hub Decision support Stochastic multicriteria acceptability analysis
σ-µ efficiency analysis: A new methodology for evaluating units through composite indices
Get PDFWe propose a new methodology to employ composite indicators for performance analysis of units
of interest using Stochastic Multiattribute Acceptability Analysis. We start evaluating each unit by
means of weighted sums of their elementary indicators in the whole set of admissible weights. For
each unit, we compute the mean, µ, and the standard deviation, σ, of its evaluations. Clearly, the
former has to be maximized, while the latter has to be minimized as it denotes instability in the evaluations
with respect to the variability of weights. We consider a unit to be Pareto-Koopmans efficient
with respect to µ and σ if there is no convex combination of µ and σ of the rest of the units with a
value of µ that is not smaller, and a value of σ that is not greater, with at least one strict inequality.
The set of all Pareto-Koopmans efficient units constitutes the first Pareto-Koopmans frontier. By removing
this set and computing the efficiency frontier for the rest of the units, one could obtain the
second Pareto-Koopmans frontier. Analogously, the third, fourth and so on Pareto-Koopmans frontiers
can be defined. This permits to assign each unit to one of this sequence of Pareto-Koopmans
frontiers. We measure the efficiency of each unit not only with respect to the first Pareto-Koopmans
frontier, as in the classic Data Envelopment Analysis, but also with respect to the rest of the frontiers,
thus enhancing the explicative power of the proposed approach. To illustrate its potential, we
apply it to a case study of world happiness based on the data of the homonymous report, annually
produced by the United Nations’ Sustainable Development Solutions Network
σ-µ efficiency analysis: A new methodology for evaluating units through composite indices
Get PDFWe propose a new methodology to employ composite indicators for performance analysis of
units of interest using and extending the family of Stochastic Multiattribute Acceptability
Analysis. We start evaluating each unit by means of weighted sums of their elementary indicators
in the whole set of admissible weights. For each unit, we compute the mean, �, and
the standard deviation, �, of its evaluations. Clearly, the former has to be maximized, while
the latter has to be minimized as it denotes instability in the evaluations with respect to
the variability of weights. We consider a unit to be Pareto-Koopmans efficient with respect
to � and � if there is no convex combination of � and � of the rest of the units with a value of
� that is not smaller, and a value of � that is not greater, with at least one strict inequality.
The set of all Pareto-Koopmans efficient units constitutes the first Pareto-Koopmans frontier.
In the spirit of context-dependent Data Envelopment Analysis, we assign each unit
to one of the sequences of Pareto-Koopmans frontiers. We measure the local efficiency of
each unit with respect to each frontier, but also its global efficiency taking into account all
feasible frontiers in the
