Current Issue
Vol 1 No 3-4 (2020)
July 2020 - December 2020
Vol 1 No 3-4 (2020)
July 2020 - December 2020
Issue Information
Articles
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The objective of this paper is to provide an inventory of approaches to descriptively (as opposed to normatively) model logistics decisions within the context of freight transport modelling. Rather than taking transport modelling frameworks as a starting point, as has been the case in the literature so far, we depart from a framework of logistics decisions. The framework is developed by combining elements of over a dozen existing frameworks from the supply chain management literature. Based on this comprehensive framework, we review freight modelling approaches from the literature. We find that freight modelling can be extended by taking into account previously uncovered areas of logistics decisions, such as those related to marketing or logistics systems forecasting and planning, as well as in areas that are well known from an optimization perspective but not from a descriptive perspective, such as routing and scheduling decisions. We conclude with a systematic listing of such areas, which can be used by researchers and transport modelling practitioners to develop further those transport models that take agent decision making as a starting point.
The objective of this paper is to provide an inventory of approaches to descriptively (as opposed to normatively) model logistics decisions within the context of freight transport modelling. Rather than taking transport modelling frameworks as a starting point, as has been the case in the literature so far, we depart from a framework of logistics decisions. The framework is developed by combining elements of over a dozen existing frameworks from the supply chain management literature. Based on this comprehensive framework, we review freight modelling approaches from the literature. We find that freight modelling can be extended by taking into account previously uncovered areas of logistics decisions, such as those related to marketing or logistics systems forecasting and planning, as well as in areas that are well known from an optimization perspective but not from a descriptive perspective, such as routing and scheduling decisions. We conclude with a systematic listing of such...
The objective of this paper is to provide an inventory of approaches to descriptively (as opposed to normatively) model logistics decisions within the context of freight transport modelling. Rather than taking transport modelling frameworks as a starting point, as has been the case in the...
Lorant Tavasszy; Michiel de Bok, Zahra Alimoradi, Jafar Rezaei74-86 -
Classical logistic networks have long since struggled with the increasing demand for flexibility and responsiveness, driven by the emancipation of consumers and the globalization of our world. Hence, since 2010, researchers in the logistics domain propose the ‘Physical Internet’ (PI) as guiding vision for innovations in logistic networks. The PI model adopts concepts and ideas from the ‘Digital Internet’ (DI) world and applies these to the movement and storage of physical products. While researchers have been working with this analogy for the past decade, a debate has emerged about the value of the DI/PI analogy and its usefulness for guiding the design of the PI. Specifically, prior work has not focused on ascertaining the accuracy of the analogy, i.e., how well logistics researchers have adopted concepts from the Digital Internet, and how this may influence the value of the analogy in the current discourse. The aim of this paper is to help fill this gap, using a qualitative research approach. We use 15 semi-structured expert interviews, to determine how well the DI is understood among the experts working on the DI/PI analogy. We propose the Analogy Functionality Model to interpret the results and assess the current strength of the analogy. We find that the strength of the DI/PI analogy varies across functions. Its application value lies particularly in the persuasion of stakeholders, the accessible explanation of key concepts, and the gathering of inspiration for further design directions. This underlines the importance of the analogy for the PI innovation community. Researchers and logistics practitioners should, however, refrain from using the analogy as a blueprint for the design of PI systems. For implementation purposes, we recommend that researchers move to conceptually emancipate the PI from the DI.
Classical logistic networks have long since struggled with the increasing demand for flexibility and responsiveness, driven by the emancipation of consumers and the globalization of our world. Hence, since 2010, researchers in the logistics domain propose the ‘Physical Internet’ (PI) as guiding vision for innovations in logistic networks. The PI model adopts concepts and ideas from the ‘Digital Internet’ (DI) world and applies these to the movement and storage of physical products. While researchers have been working with this analogy for the past decade, a debate has emerged about the value of the DI/PI analogy and its usefulness for guiding the design of the PI. Specifically, prior work has not focused on ascertaining the accuracy of the analogy, i.e., how well logistics researchers have adopted concepts from the Digital Internet, and how this may influence the value of the analogy in the current discourse. The aim of this paper is to help fill this gap, using a...
Classical logistic networks have long since struggled with the increasing demand for flexibility and responsiveness, driven by the emancipation of consumers and the globalization of our world. Hence, since 2010, researchers in the logistics domain propose the ‘Physical Internet’ (PI) as...
Sharon van Luik, Tobias Fiebig, Patrick Fahim, Pieter de Waard, Lorant Tavasszy87-103 -
This paper is dedicated to applying ontology alignment systems to the heterogeneity problem in logistics. The primary motivation for doing so is to enable interoperability among different IT systems in logistics, all with their own database scheme. We first analyze different standards for logistics interoperability, which are implemented by XML schema definition (XSD) or Electronic Data Interchange (EDI) with implicit and inconsistent semantics across these open standards. To analyze the applicability of ontology alignment, we create two ontologies from two well-known standards that are rich in terms of semantic relations between entities. These ontologies are subjected to the state-of-the-art alignment systems, applying matching with and without logistics background knowledge. Our experimental analyses show that the alignment using background knowledge with some annotations finds better mappings between the given logistics standards and is thus applicable to real-world situations under particular conditions.
This paper is dedicated to applying ontology alignment systems to the heterogeneity problem in logistics. The primary motivation for doing so is to enable interoperability among different IT systems in logistics, all with their own database scheme. We first analyze different standards for logistics interoperability, which are implemented by XML schema definition (XSD) or Electronic Data Interchange (EDI) with implicit and inconsistent semantics across these open standards. To analyze the applicability of ontology alignment, we create two ontologies from two well-known standards that are rich in terms of semantic relations between entities. These ontologies are subjected to the state-of-the-art alignment systems, applying matching with and without logistics background knowledge. Our experimental analyses show that the alignment using background knowledge with some annotations finds better mappings between the given logistics standards and is thus applicable to real-world...
This paper is dedicated to applying ontology alignment systems to the heterogeneity problem in logistics. The primary motivation for doing so is to enable interoperability among different IT systems in logistics, all with their own database scheme. We first analyze different standards for...
Majid Mohammadi, Wout Hofman, Yao-Hua Tan104-117 -
Returns management, especially in apparel e-commerce, has gained increased attention due to the ecological and economic implications it imposes. However, research which explores the relationship between (i) reasons which drive customers’ apparel returns and (ii) customer-based instruments designed to reduce online apparel returns, has not yet been empirically examined in literature, especially from the point of view of customers. This research aims to examine the customers’ technology acceptance of four technological alternatives designed to prevent unnecessary apparel returns. To determine the customers’ technology acceptance, the Technology Acceptance Model (TAM) is used. To operationalize TAM, a Multi-Criteria Decision-Analysis (MCDA) approach is applied, wherein the Bayesian group Best-Worst Method (BWM) is used to infer the weights of the indicators (i.e. criteria) that contribute to the customers’ (users’) technology acceptance. This is done within the context of apparel e-commerce and with the application of qualitative tools such as an online BWM survey and expert interviews. The results show that reliable fit & size information is the most important sub-indicator contributing to the customers’ technology acceptance. Furthermore, it seems that whilst per subsequent alternative, the reliability of information provision regarding apparel attributes increases, the perceived user-friendliness (ease of use) of the technologies decreases, privacy and security concerns increase and the managerial implications increase as well.
Returns management, especially in apparel e-commerce, has gained increased attention due to the ecological and economic implications it imposes. However, research which explores the relationship between (i) reasons which drive customers’ apparel returns and (ii) customer-based instruments designed to reduce online apparel returns, has not yet been empirically examined in literature, especially from the point of view of customers. This research aims to examine the customers’ technology acceptance of four technological alternatives designed to prevent unnecessary apparel returns. To determine the customers’ technology acceptance, the Technology Acceptance Model (TAM) is used. To operationalize TAM, a Multi-Criteria Decision-Analysis (MCDA) approach is applied, wherein the Bayesian group Best-Worst Method (BWM) is used to infer the weights of the indicators (i.e. criteria) that contribute to the customers’ (users’) technology acceptance. This is done within the context of...
Returns management, especially in apparel e-commerce, has gained increased attention due to the ecological and economic implications it imposes. However, research which explores the relationship between (i) reasons which drive customers’ apparel returns and (ii) customer-based instruments...
Ruchika Kalpoe118-137