Showing papers in "The International Journal of Logistics Management in 2018"

Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management: An empirical investigation

Abstract: Based on previous literature on big data analytics (BDA) and supply chain (SC) management, the purpose of this paper is to address the factors determining firms’ intention to adopt BDA in their daily operations. Specifically, this study classifies potential factors into four categories: technological, organizational, environmental factors, and SC characteristics.,Drawing on the innovation diffusion theory, a model consisted of direct technological and organizational factors as well as moderators was proposed. Subsequently, survey data was collected from 210 organizations. Then we used SPSS and SmartPLS to analyze the collected data.,The empirical results revealed that perceived benefits and top management support can significantly influence the adoption intention. And environmental factors, such as competitors’ adoption, government policy, and SC connectivity, can significantly moderate the direct relationships between driving factors and the adoption intention.,Given the fact that big data (BD) usage in logistics and SC management is still in the start-up stage, the interpretations toward BDA might vary from different perspectives, thus causing some ambiguity in understanding the meaning and potential BD has. In addition, we collected data through questionnaires completed by IT managers, whose viewpoint may not fully represent that of an organization.,This paper tests the organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.,This research helps top managers assess the benefits of BDA as well as how to adjust their business strategy along the changes of environment and SC maturity.,This paper contributes to the literature of organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.

An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management: A mixed research approach

Abstract: The Internet of Things (IoT) envisions a global infrastructure of networked physical objects that render radical transparency to supply chain management. Despite the perceived advantages of IoT, industry has still not widely adopted IoT-enabled logistics and supply chain management. The purpose of this paper is to understand the incentives and concerns behind firms’ decisions to adopt IoT, explore the determinant factors affecting IoT adoption in logistics and supply chain management.,This study uses mixed methods research to explore the determinants of IoT adoption intention in logistics and supply chain management. Qualitative analysis using the Grounded Theory methodology reveals the underlying perceptions regarding logistic innovation with IoT. Quantitative hypotheses are then developed based on qualitative investigation and adoption literature. Survey data were collected from the managerial staff of Taiwanese firms across various industries. Structural equation modeling with partial least square is used for data analysis.,The results of the qualitative study identify uncertainties and issues regarding firms’ intention to accept or reject IoT technology in logistics and supply chain management, including the benefit and cost aspects of adopting IoT, uncertainties about the trustworthiness of IoT technology, and the external motivating force to embrace IoT. The resulting quantitative model shows that perceived benefits, perceived costs, and external pressure are significant determinants of IoT adoption intention, while technology trust is not. However, technology trust does indirectly influence IoT adoption intention through perceived benefits.,The empirical findings of this study provide some guidelines for logistics and supply chain managers to evaluate IoT adoption in their firms. Likewise, IoT solution providers can also benefit from this study by improving their solutions to mitigate the IoT adoption concerns addressed herein.,This paper is among the first known to examine IoT adoption intention in logistics and supply chain management using mixed methods research. The mixed methods approach offers a better insight in understanding incentives behind firms’ decisions to adopt IoT vs the use of either a qualitative or quantitative method alone.

Impact of big data & predictive analytics capability on supply chain sustainability

Abstract: The purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.,The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.,The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support for H4. Although the authors did not find support for H4 (moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.,This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.

Big Data Analytics and IoT in logistics: a case study

Abstract: Purpose Advances in technology enable companies to collect and analyse data, which was previously not accessible, to either enhance existing business processes or create new ones. This research attempts to document the role and impact of Big Data Analytics (BDA), and the Internet of Things (IoT), in supporting a large logistics firm’s strategy to improve driver safety, lower operating costs, and reduce the environmental impact of their vehicles. Design/methodology/approach A single case with embedded units intrinsic case study method was adopted for this research, data was collected from a ‘real life’ situation, to create new knowledge about this emerging phenomenon. Findings Truck telematics were utilised in order to better understand, and improve, driving behaviours. Remote control centres monitor live sensor data from the company’s fleet of vehicles, capturing the likes of speed, location, braking and engine data, to inform future training programs. A combination of truck telematics and geo-information...

Big data and predictive analytics in humanitarian supply chains: Enabling visibility and coordination in the presence of swift trust

Abstract: The purpose of this paper is to understand how big data and predictive analytics (BDPA), as an organizational capability, can improve both visibility and coordination in humanitarian supply chains.,The authors conceptualize a research model grounded in contingent resource-based view where the authors propose that BDPA capabilities affect visibility and coordination under the moderating effect of swift trust. Using ordinary least squares regression, the authors test the hypotheses using survey data collected from informants at 205 international non-government organizations.,The results indicate that BDPA has a significant influence on visibility and coordination. Further, the results suggest that swift trust does not have an amplifying effect on the relationships between BDPA and visibility and coordination. However, the mediation test suggests that swift trust acts as a mediating construct. Hence, the authors argue that swift trust is not the condition for improving coordination among the actors in humanitarian supply chains.,The major limitation of the study is that the authors have used cross-sectional survey data to test the research hypotheses. Following Guide and Ketokivi (2015), the authors present arguments on how to address the limitations of cross-sectional data or use of longitudinal data that can address common method bias or endogeneity-related problems.,Managers can use this framework to understand: first, how organizational resources can be used to create BDPA, and second, how BDPA can help build swift trust and be used to improve visibility and coordination in the humanitarian supply chain.,This is the first research that has empirically tested the anecdotal and conceptual evidence. The findings make notable contributions to existing humanitarian supply chain literature and may be useful to managers who are contemplating the use of BDPA to improve disaster-relief-related activities.

Integration, supply chain resilience, and service performance in third-party logistics providers

Abstract: Purpose Supply chain resilience (SCR) is essential to the success of firms. However, very few studies have focused on the relationships between different types of integration, SCR and service performance from the perspective of third-party logistics providers (3PLs). The purpose of this paper is to develop and assesses a conceptual model for these relationships. Design/methodology/approach A total of 161 3PLs in Taiwan were surveyed and their responses were analyzed using partial least squares structural equation modeling (PLS-SEM/PLS). Findings The responses of respondents demonstrated that, of the three types of integration (internal integration, customer integration and logistics collaborator integration) used by 3PLs, internal integration had the greatest effect on SCR. Customer integration was found to have three fully mediating effects on the relationships between internal integration and service performance, between logistics collaborator integration and SCR, and between logistics collaborator integration and service performance. Originality/value This study provides useful information on how different types of integration manifest in the SCR and service performance of 3PLs.

An innovation diffusion perspective of e-consumers’ initial adoption of self-collection service via automated parcel station

Abstract: As an application of self-service technology, automated parcel station (APS) is emerging as a logistics innovation to address the inefficiency and delivery failure in conventional home delivery. However, the long-term viability of APS depends on the consumers’ acceptance of such concept. In response, the purpose of this paper is to conduct a behavioural study on consumers’ adoption of self-collection service via APS.,By synthesising theoretical insights from the innovation diffusion literature and attitude theories, a conceptual model is developed and empirically validated. Perceived characteristics of APS are present to directly influence the consumers’ adoption intention, or indirectly through attitude. A total of 170 valid responses are collected from a survey conducted in Singapore and the data are analysed using structural equation modelling.,Consumers’ favourable attitude and perceived relative advantage of APS directly lead to stronger adoption intention. On the contrary, consumers’ perceptions on compatibility and trialability and on complexity indirectly influence their adoption intention via attitude, in a positive and in a negative way, respectively. Additionally, attitude is found to be the most influential factor contributing to consumers’ adoption intention.,The scope of this paper is limited to e-consumers’ initial adoption decision. Future research should examine the consumers’ adoption behaviour further down the innovation adoption process, such as continuance and commitment.,This research conceptualises and validates the consumers’ adoption behaviour of APS from a synthesised view of innovation diffusion and attitude theories, theoretically and empirically contributing to the field of study on logistics innovations from the consumers’ perspective.

Supply chain resilience: a dynamic and multidimensional approach

Abstract: The purpose of this paper is to present a conceptual framework on resilience types in supply chain networks.,Using a complex adaptive systems perspective as an organizing framework, the paper explores three forms of resilience: engineering, ecological and evolutionary and their antecedents and links these to four phases of supply chain resilience (SCRES): readiness, response, recovery, growth and renewal.,Resilient supply chains need all three forms of resilience. Efficiency and system optimization approaches may promote quick recovery after a disruption. However, system-level response requires adaptive capabilities and transformational behaviors may be needed to move supply chains to new fitness levels after a disruption. The three resilience types discussed are not mutually exclusive, but rather complement each other and there are synergies and tradeoffs among these resilience types.,The empirical validation of the theoretical propositions will open up new vistas for supply chain research. Possibilities exist for analyzing and assessing SCRES in multiple and more comprehensive ways.,The findings of the research can help managers refine their approaches to managing supply chain networks. A more balanced approach to supply chain management can reduce the risks and vulnerabilities associated with supply chain disruptions.,This study is unique as it conceptualizes SCRES in multiple ways, thereby extending our understanding of supply chain stability.

Food cold chain management: From a structured literature review to a conceptual framework and research agenda

Abstract: Since last few years, cold chain management (CCM) has gained growing interest among practitioners, policymakers, researchers and academicians. The purpose of this paper is to provide a review focused on food cold chain management (FCCM) over the last 16 years to identify state of the art in the literature, highlight research gaps and define appropriate research questions (RQs) for future research.,The paper analyzes the content of 89 research articles published on the topic of food cold chain (FCC) from 2001 to 2016 within different journals. The Scopus and Web of Science databases were taken into consideration to shortlist research articles. Henceforth, the authors scrutinized the FCC industry to offer some effective strategies to tackle the chain complexities. The authors also draw interwoven between FCC infrastructure, integration, stakeholders’ interest, value addition, partners’ performance and overall food cold chain performance (FCCP) into a conceptual framework.,This paper identifies four research gaps in the literature of FCC concerning the most popular approaches used for the FCCP measurement, the performance measurement metrics, the factors which negatively affect the FCCP and the main sustainability issues in FCC.,This study identifies RQs which represent possible areas of investigation to improve the body of the FCCP evaluation and management. Furthermore, the FCC practitioners, food authorities and researchers might find this review useful, as it draws a clear picture of research in the respective domain.

Role of cloud ERP on the performance of an organization: Contingent resource-based view perspective

Abstract: Cloud-based enterprise resource planning (ERP) enables an organization to pay for the services they need and removes the need to maintain information technology infrastructure. The purpose of this paper is to empirically test the role of cloud-based ERP services on the performance of an organization. Here, the performance is categorized as supply chain performance and organizational performance that comprises of financial performance and marketing performance. Contingent resource-based view (RBV) theory was used to develop a theoretical framework in which supply base complexity (SBC) acts as a moderating variable on the relationship between cloud ERP and the performance.,Contingent RBV theory is used to explain the relationship between all identified variables in this paper. Partial least squares (PLS) based on structural equation modeling (SEM) is used to empirically test our theoretical framework.,The PLS-SEM analysis of 154 respondents supports the contingent RBV theory. Six hypotheses – out of the eight hypotheses formulated in this paper – are supported by data.,Given this study was conducted in India where the potential of cloud ERP has not been fully implemented yet, the results may reflect more of perceived usefulness of this technology. The authors have attempted to understand the effect of SBC as a moderator in the relationship between cloud ERP and organizational performance which may not be the only moderator affecting this relationship among other potential moderators.,This paper empirically validates the theoretical framework based on the contingent RBV theory as it mitigates the static nature of the resource-based view approach suggested in the seminal article of Barney (1991).

Decision-making in cold chain logistics using data analytics: a literature review

Abstract: The purpose of the paper is to identify the multiple types of data that can be collected and analyzed by practitioners across the cold chain, the ICT infrastructure required to enable data capture and how to utilize the data for decision making in cold chain logistics,Content analysis based literature review of 38 selected research articles, published between 2000 and 2016, was used to create an overview of data capture, technologies used for collection and sharing of data, and decision making that can be supported by the data, across the cold chain and for different types of perishable food products,There is a need to understand how continuous monitoring of conditions such as temperature, humidity, and vibration can be translated to support real-time assessment of quality, determination of actual remaining shelf life of products and use of those for decision making in cold chains Firms across the cold chain need to adopt appropriate technologies suited to the specific contexts to capture data across the cold chain Analysis of such data over longer periods can also unearth patterns of product deterioration under different transportation conditions, which can lead to redesigning the transportation network to minimize quality loss or to take precautions to avoid the adverse transportation conditions,The findings need to be validated through further empirical research and modeling There are opportunities to identify all relevant parameters to capture product condition as well as transaction data across the cold chain processes for fish, meat and dairy products Such data can then be used for supply chain (SC) planning and pricing products in the retail stores based on product conditions and traceability information Addressing some of the above research gaps will call for multi-disciplinary research involving food science and engineering, information technologies, computer science and logistics and SC management scholars,The findings of this research can be beneficial for multiple players involved in the cold chain like food processing companies, logistics service providers, ports and wholesalers and retailers to understand how data can be effectively used for better decision making in cold chain and to invest in the specific technologies, which will suit the purpose To ensure adoption of data analytics across the cold chain, it is also important to identify the player in the cold chain, which will drive and coordinate the effort,This paper is one of the earliest to recognize the need for a comprehensive assessment for adoption and application of data analytics in cold chain management and provides directions for future research

Big data analytics and demand forecasting in supply chains: a conceptual analysis

Abstract: Purpose Demand forecasting is a challenging task that could benefit from additional relevant data and processes. The purpose of this paper is to examine how big data analytics (BDA) enhances forecasts’ accuracy. Design/methodology/approach A conceptual structure based on the design-science paradigm is applied to create categories for BDA. Existing approaches from the scientific literature are synthesized with industry knowledge through experience and intuition. Accordingly, a reference frame is developed using three steps: description of conceptual elements utilizing justificatory knowledge, specification of principles to explain the interplay between elements, and creation of a matching by conducting investigations within the retail industry. Findings The developed framework could serve as a guide for meaningful BDA initiatives in the supply chain. The paper illustrates that integration of different data sources in demand forecasting is feasible but requires data scientists to perform the job, an appropriate technological foundation, and technology investments. Originality/value So far, no scientific work has analyzed the relation of forecasting methods to BDA; previous works have described technologies, types of analytics, and forecasting methods separately. This paper, in contrast, combines insights and provides advice on how enterprises can employ BDA in their operational, tactical, or strategic demand plans.

Modeling big data enablers for operations and supply chain management

Abstract: The purpose of this paper is to identify and analyse the interactions among various enablers which are critical to the success of big data initiatives in operations and supply chain management (OSCM).,Fourteen enablers of big data in OSCM have been selected from literature and consequent deliberations with experts from industry. Three different multi criteria decision-making (MCDM) techniques, namely, interpretive structural modeling (ISM), fuzzy total interpretive structural modeling (fuzzy-TISM) and decision-making trial and evaluation laboratory (DEMATEL) have been used to identify driving enablers. Further, common enablers from each technique, their hierarchies and inter-relationships have been established.,The enabler modelings using ISM, Fuzzy-TISM and DEMATEL shows that the top management commitment, financial support for big data initiatives, big data/data science skills, organizational structure and change management program are the most influential/driving enablers. Across all three different techniques, these five different enablers has been identified as the most promising ones to implement big data in OSCM. On the other hand, interpretability of analysis, big data quality management, data capture and storage and data security and privacy have been commonly identified across all three different modeling techniques as the most dependent big data enablers for OSCM.,The MCDM models of big data enablers have been formulated based on the inputs from few domain experts and may not reflect the opinion of whole practitioners community.,The findings enable the decision makers to appropriately choose the desired and drop undesired enablers in implementing the big data initiatives to improve the performance of OSCM. The most common driving big data enablers can be given high priority over others and can significantly enhance the performance of OSCM.,MCDM-based hierarchical models and causal diagram for big data enablers depicting contextual inter-relationships has been proposed which is a new effort for implementation of big data in OSCM.

Characterizing supply chain visibility – a literature review

Abstract: Purpose The purpose of this paper is to present a literature review that aims to provide insight into the characteristics and effectiveness of supply chain visibility (SCV), as well as to identify metrics that capture these aspects in business processes. Design/methodology/approach A systematic review of the supply chain literature is conducted to identify the characteristics and the effectiveness of SCV. The synthesis of SCV effectiveness and its metrics are based on the process-oriented approach which relates the effectiveness of SCV to improved business performance. Findings This study reveals that the characteristics of SCV can be captured in terms of the accessibility, quality, and usefulness of information. The benefits of SCV are found to extend beyond improvements to operational efficiency of business processes or to the strategic competencies of an organization. Practical implications This study underlines that clear agreements between all players involved in the SC can help to solve problems caused by information completeness (type and amount of information), and unlock the full potential of SCV projects. Originality/value By using a process-oriented approach, this review provides a comprehensive explanation of the functions of SCV, as well as its first-order effects, in terms of automational, informational, and transformational characteristics.

Big data analytics in supply chain and logistics: an empirical approach

Abstract: The purpose of this paper is to recognise the current state of big data analytics (BDA) on different organisational and supply chain management (SCM) levels in Brazilian firms. Specifically, the paper focuses on understanding BDA awareness in Brazilian firms and proposes a framework to analyse firms’ maturity in implementing BDA projects in logistics/SCM.,A survey on SCM levels of 1,000 firms was conducted via questionnaires. Of the 272 questionnaires received, 155 were considered valid, representing a 15.5 per cent response rate.,The knowledge of Brazilian firms regarding BDA, the difficulties and barriers to BDA project adoption, and the relationship between supply chain levels and BDA knowledge were identified. A framework was proposed for the adoption of BDA projects in SCM.,This study does not offer external validity due to restrictions for the generalisation of the results even in the Brazilian context, which stems from the conducted sampling. Future studies should improve the comprehension in this research field and focus on the impact of big data on supply chains or networks in emerging world regions, such as Latin America.,This paper provides insights for practitioners to develop activities involving big data and SCM, and proposes functional and consistent guidance through the BDA-SCM triangle framework as an additional tool in the implementation of BDA projects in the SCM context.,This study is the first to analyse BDA on different organisational and SCM levels in emerging countries, offering instrumentalisation for BDA-SCM projects.

A resilience model for cold chain logistics of perishable products

Abstract: Most of the extant literature on resilience builds on normative, conceptual or silo approaches, thereby lacking an integrative approach to cold chain logistics risks (CCLRs) and resilience. The purpose of this paper is to bridge the current research gap by developing a model, based on broad empirical evidence, of the interplay between CCLRs, resilience and firm performance (FP) in perishable product supply chains (PPSCs).,A mixed method approach is used with qualitative data from interviews and quantitative data from a survey across the supply chain. The analysis is framed by contingency theory and resource-based theory.,Four significant sources of CCLRs and six resources used to build resilience are identified. Then, supply chain resilience (SCR) as a moderator of the negative relationship between CCLRs and FP is corroborated.,The findings will help improve managerial understandings of critical sources of risks in cold chain logistics and resources indispensable to build resilience. The scope of the research is cold chain logistics for PPSCs, which has relevance to other cold supply chains as well.,While some theoretical frameworks suggest resilience being a moderator in the negative relationship between cold chain risks and a firm’s performance, this study empirically tests this relationship using the survey across the entire supply chain. A new empirically and theoretically driven definition of SCR is also developed.

Practitioners understanding of big data and its applications in supply chain management

Abstract: Big data poses as a valuable opportunity to further improve decision making in supply chain management (SCM). However, the understanding and application of big data seem rather elusive and only partially explored. The purpose of this paper is to create further guidance in understanding big data and to explore applications from a business process perspective.,This paper is based on a sequential mixed-method. First, a Delphi study was designed to gain insights regarding the terminology of big data and to identify and rank applications of big data in SCM using an adjusted supply chain operations reference (SCOR) process framework. This was followed by a questionnaire-survey among supply chain executives to elucidate the Delphi study findings and to assess the practical use of big data.,First, big data terminology seems to be more about data collection than of data management and data utilization. Second, the application of big data is most applicable for logistics, service and planning processes than of sourcing, manufacturing and return. Third, supply chain executives seem to have a slow adoption of big data.,The Delphi study is explorative by nature and the questionnaire-survey rather small in scale; therefore, findings have limited generalizability.,The findings can help supply chain managers gain a clearer understanding of the domain of big data and guide them in where to deploy big data initiatives.,This study is the first to assess big data in the SCOR process framework and to rank applications of big data as a mean to guide the SCM community to where big data is most beneficial.

Supplier transparency: scale development and validation

Abstract: The purpose of this paper is to create an instrument for conducting future supply chain transparency research by developing and validating a measure of supplier transparency. Specifically, the research develops a two-dimensional measure of supplier transparency that builds on previous studies that independently examine visibility and traceability in supply chain management (SCM)/logistics.,The scale development process is carried out over three stages (item generation, scale purification, scale validation). Survey methods are used with two separate data collection phases involving a total of 358 managers from multiple and diverse industries.,The new supplier transparency measure is a concise, two-dimensional scale that has the potential for significant usage in the development and testing of SCM theory.,This study implemented a purposefully general sampling procedure. However, different industries may have additional, specific constraints regarding what it means to be a transparent supplier. Additional opportunities for future research include applying the new supplier transparency measure to examine supply chain frameworks, regulatory compliance, supply chain relationships and the implementation of information technology.,Firms are under increasing pressure to be transparent about partner sourcing, resource utilization and other transactional issues related to the products and processes in their supply chains. The new measure may be utilized to address these issues as well as the interaction between supply chain operations and stakeholders by facilitating a quantitative assessment of supplier transparency.,Drawing on the established constructs of supply chain visibility and traceability, a measure of supplier transparency is developed, supported by a review of the literature, input from subject matter experts and interviews with supply chain managers. Suggestions are made for future validation of supplier transparency within established supply chain frameworks.

Supply chain information integration, flexibility, and operational performance: An archival search and content analysis

Abstract: Supply chain flexibility is crucial for firms to respond to uncertain circumstances caused by environmental factors, such as the diversity of customer demands, problems of product safety, and adjustments of industrial policies. To investigate the approach to enhance supply chain flexibility, the purpose of this paper is to propose that both internal and external information integration contribute to reactive and proactive supply chain flexibilities, which elicit high operational performance.,Using a sample of 84 food companies that have been listed three years in China and content analysis based on their annual reports, evidence was collected to test the hypotheses through hierarchical regressions.,The results reveal that external information integration results in both reactive and proactive flexibilities, which further improve operational performance. Internal information integration positively affects both reactive and proactive flexibilities, but its mediating role was not determined in the study.,The research provides insights into how supply chain flexibility mediates the effect of supply chain information integration on operational performance in the context of the Chinese food industry.

Last-mile distribution planning for fruit-and-vegetable cold chains

Abstract: The purpose of this paper is to formulate and solve a last-mile distribution plan problem with concern for the quality of fruits and vegetables in cold chains.,The vehicle routing problem with time windows (VRPTW) is extended based on the characteristics of fruit-and-vegetable cold chains. The properties of multiple perishable foods, continuing decline in quality, various requirements for quality levels and optimal temperature settings during vehicle transportation are considered in the VRPTW. The product quality level is defined by the estimation of residual shelf life, which changes with temperature, and is characterized by a stepped decrease during the transportation process as time goes on. A genetic algorithm (GA) is adapted to solve the problem because of its convincing ability to solve VRPTW-related problems. For this purpose, solution encoding, a fitness function and evolution operators are designed to deal with the complicated problem herein.,A distribution plan including required fleet size, vehicle routing sequence and what quality level should be shipped out to account for the quality degradation during vehicle transportation is generated. The results indicate that the fulfillment of various requirements of different customers for various fruits and vegetables and quality levels can be ensured with cost considerations.,This study presents a problem for last-mile delivery of fresh fruits and vegetables which considers multiple practical scenarios not studied previously. A solution algorithm based on a GA is developed to address this problem. The proposed model is easily applied to other types of perishable products.

Collaboration in urban distribution of online grocery orders

Abstract: Population growth, urbanisation and the increased use of online shopping are some of the key challenges affecting the traditional logistics model The purpose of this paper is to focus on the distribution of grocery products ordered online and the subsequent home delivery and click and collect services offered by online retailers to fulfil these orders These services are unsustainable due to increased operational costs, carbon emissions, traffic and noise The main objective of the research is to propose sustainable logistics models to reduce economic, environmental and social costs whilst maintaining service levels,The authors have a mixed methodology based on simulation and mathematical modelling to evaluate the proposed shared logistics model using: primary data from a major UK retailer, secondary data from online retailers and primary data from a consumer survey on preferences for receiving groceries purchased online Integration of these three data sets serves as input to vehicle routing models that reveal the benefits from collaboration by solving individual distribution problems of two retailers first, followed by the joint distribution problem under single decision maker assumption,The benefits from collaboration could be more than 10 per cent in the distance travelled and 16 per cent in the time required to deliver the orders when two online grocery retailers collaborate in distribution activities,The collaborative model developed for the online grocery market incentivises retailers to switch from current unsustainable logistics models to the proposed collaborative models

Explaining logistics social responsibility from a dynamic capabilities perspective

Abstract: So far, most of the literature on logistics social responsibility (LSR) has prioritized the examination, classification of and adaption toward positive LSR practices instead of investigating necessary logistics service providers’ capabilities to implement LSR strategies. Therefore, the purpose of this paper is to contribute to theory by an assessment of LSR and its linkages to dynamic capabilities theory to gain insights into how logistics service providers can foster an enhanced application of LSR practices.,The paper is conceptual and grounded on dynamic capabilities theory. Relevant literature from logistics management, supply chain management and sustainable supply chain management (SSCM) as well as dynamic capabilities was examined to build upon existing theory by conceptualizing LSR from a dynamic capabilities perspective. In addition, propositions for future research are presented based on the conceptual model.,With regards to the controversial discussion in the literature about the direct link between dynamic capabilities and competitive advantage as well as the necessary degree of heterogeneity of dynamic capabilities, the conceptualization of LSR from a dynamic capabilities perspective adds new elements to this discussion. Considering long-term or even sustainable competitive advantage, the current degree of homogeneity across logistics services might hinder a sustainable advantage in the long run and demands for more advanced logistical capabilities. In this line, it is important to understand and utilize the causal relationships between different logistical resources and capabilities to achieve a unique long-term advantage allowing logistics service providers to further enhance LSR practices.,Due to the current role of logistics service providers, they should not just foster their resources focusing on the relationship to the focal firm, but they should also develop and implement new logistical capabilities derived from SSCM-related dynamic capabilities to design alternative service portfolio extensions and new business models.,Although dynamic capabilities have been studied intensively in the last two decades, the causal relationships between different logistical resources and necessary dynamic capabilities to achieve advantages by enhancing LSR practices still lack conceptualization. To build on the understanding of LSR, the paper at hand presents a conceptual framework explaining LSR and SSCM practices through the lens of dynamic capabilities theory.

How logistics performance is affected by supply chain relationships

Abstract: The purpose of this paper is to evaluate the effect of logistics collaboration, meetings, relationship history, and supplier selection on the logistics performance of shippers, carriers, and logistics services providers. Rather than focusing on collaboration and performance, the research provides a wide analysis of how logistics collaboration and performance interact with other organizational practices.,To investigate the interaction among the constructs, the authors proposed a structural equation model to understand the influence of meetings, relationship history, supplier selection, and collaboration on logistics performance. The data were obtained through a survey of 199 managers of Brazilian companies in the retail sector.,Supplier selection has the strongest effect on logistics collaboration, and relationship history has the strongest effect on logistics performance. Rather than meetings and operational features, the elements of interpersonal skills, organizational culture, and communication appear to be the most important contributors to logistics performance achievements; relationship history leads to better performance.,This study contributes to our understanding of how and with whom to collaborate by highlighting the relationships among supplier selection, relationship history, meetings, and logistics collaboration and logistics performance.

Lean supply chain practices: an exploratory study on their relationship

Abstract: The purpose of this paper is to empirically investigate the relationships among the implementation of LSC practices. Particularly, the authors examine the adoption level of 27 LSC practices, which were identified in a literature review, within 113 manufacturing companies from different sectors located in Southern Brazil.,Data collected were analyzed by means of multivariate techniques (partial correlation analysis) and two control variables were used: level of onshore suppliers and company’s experience on lean manufacturing implementation.,The results showed that the relationship among practices may not always be synergic, since there are pairs of practices that, when concurrently implemented they tend to conflict, hindering their benefits.,The use of partial correlations between pairs of LSC practices provides means to better understand specific associations, disregarding the implementation effect of the whole set of practices. The research also provides managers and practitioners arguments to better comprehend how practices interact with each other under specific contexts.

Estimating transportation network impedance to last-mile delivery a case study of Maribyrnong City in Melbourne

Abstract: Purpose The purpose of this paper is to measure and map the potential transportation network impedance to last-mile delivery (LMD) using spatial measures representing attributes of road network and planning controls. Design/methodology/approach The transport network impedance is estimated as the potential hindrance to LMD as imposed by the characteristics of the built and regulatory environment. A matrix of key transport and planning measures are generated and overlaid in geographical information systems to compute and visualise the levels of transportation network impedance to LMD using a composite indexing method. Findings The mapped outputs reveal significant spatial variation in transportation network impedance to LMD across different part of the study area. Significant differences were detected along the road segments that connect key industrial hubs or activity centres especially along tram routes and freight corridors, connecting the Port of Melbourne and logistic hub with the airport and the Western Ring Road. Research limitations/implications The use of static measures of transport and urban planning restricts the robustness of the impedance index, which can be enhanced through better integration of dynamic and real-time movements of business-to-business LMD of goods. Spatial approach is valuable for broader urban planning at a metropolitan or council level; however, its use is somewhat limited in assisting the daily operational planning and logistics decision making in terms of dynamic routing and vehicle scheduling. Practical implications The built and regulatory environment contributes to the severity of LMD problem in urban areas. The use of land use controls as instruments to increase city compactness in strategic nodes/hubs is more likely to deter the movement of urban freight. The mapped outputs would help urban planners and logisticians in mitigating the potential delay in last-mile deliveries through devising localised strategies such as dedicated freight corridors or time-bound deliveries in congested areas of road network. Originality/value This is the first study that measured the potential transport network impedance to LMD and improved understanding of the complex interactions between urban planning measures and LMD. Micro-scale mapping of transportation network impedance at the street level adds an innovative urban planning dimension to research in the growing field of city logistics.

The influence of the Digital Divide on Big data generation within supply chain management

Abstract: The purpose of this paper is to examine the influence of the Digital Divide (DD) and digital alphabetization (DA) on the Big Data (BD) generation process, to gain insight into how BD could become a useful tool in the decision-making process of supply chain management (SCM). Similarly, the paper aims to recognize and understand, from a value-creation perspective, the correlation between DD and BD generation and between DD and SCM.,The approach utilized in the present study consists of two steps: first, a systematic literature review was conducted aiming at finding out to determine the existing relationship between “Big Data Analytics” (BDA), “SCM” and the “DD”. A total of 595 articles were considered, and analysis showed a clear relationship among BDA, SCM, and DD. Next, the Vector autoregressive (VAR) approach was applied in a case study to prove the correlation between DD (as part of internet usage) and internet acquisitions, and in general terms the relationship between DD and Trade. Internet usage and internet acquisition in imports and exports at the European level were considered as variables in an empirical study of European trade. The novelty of this two-tiered approach consists in its application of a systematic literature review, the first of its kind, to generate inputs for the longitudinal case study of imports and exports at the EU level. In turn, the case study tested the accuracy of the theorized relationship among the main variables.,By analyzing the connection between DD and internet acquisitions, a positive and long-lasting impulse response function was revealed, followed by an ascending trend. This suggests that a self-multiplying effect is being generated, and it is reasonable to assume that the more individuals use the internet, the more electronic acquisitions occur. We can thus reasonably conclude that the improvement of the BD and SCM process is strongly dependent on the quality of the human factor. Tackling DA is the new reading key in the decision-making process: quantifying the added value of the human factor in SCM is challenging and is an ongoing process, based on the opportunity cost between automation in decision-making or relying on the complexity of human factors.,One of the biggest limits in our research is the lack of the time series available on consumer orientations and preferences. Data on the typology of customer preferences, and how they are shaped, modified, or altered, were non-accessible, though big companies may have access to this data. The present longitudinal study on European trade helps clarify how and to what extent BDA, SCM, and DD are inter-related. The modeling of the theoretical framework likewise highlights several identifiable benefits for companies of adopting BDA in their business processes.,Understanding the obstacles to DD in trade companies and states, and identifying their influence on firm performance, serves to orient the decision-making process in SCM toward reducing DD to generate important economic benefits. Enhancing internet usage may accelerate longer-term investments in human resources, offering developing countries unprecedented opportunities to enhance their educational systems and to improve their economic policies, widening the range of opportunities for businesses and poor states.,BD generation will undeniably influence microeconomic decisions: they will become evaluation tools of more efficient economic progress in small and/or large economies. However, an economically efficient society will be achievable only in those countries in which qualified human resources can generate and manage BD, to unlock its potential. This twofold effect will surely affect the socio-economic and geopolitical situation. The economic progress of conventional countries may vacillate if it is not adequately flanked by qualified human resources able to progress the information and communication technology (ICT) prevalent in contemporary economies. Consequently, the social impact of investments in ICT capacity building will necessarily affect future socio-economic scenarios. New indicators will become necessary to measure the conventional progress, and one of them will surely be DD.,The novelty of the present study is twofold: first, it is the first meticulous meta-analysis developed using a very wide analysis of the published literature to highlight a previously hidden relationship among DD, BD, and SCM. This comparative approach made it possible to build a theoretical framework for the real evaluation of the impact of BDA on different organizational elements, including SCM. Second, the research emphasizes the need to reform and reshape the studies on BDA, convincing companies that it is necessary to understand that the obstacles (DD and DA, i.e. internet usage) must be addressed with conscious decision-making processes, strategically and resolutely, to transform points of weakness into opportunities.

The obstacles to cold chain implementation in developing countries: insights from Vietnam

Abstract: The purpose of this paper is to identify the obstacles that impede cold chain implementation in developing countries.,A grounded theory methodology was employed to execute this research. Eight semi-structured, in-depth interviews were conducted with senior managers in Vietnam. In addition, consistent with grounded theory guidelines, the authors utilized archival data to facilitate theory development.,The results of the analysis revealed a total of ten key obstacles: deficient professional skills, lack of quality and safety-control measures, high concentration of intermediaries, poor infrastructure, lack of information systems, high cost of installation and operation, inadequate education and training at farmer level, deficiency of standardization, lack of government support for local businesses and social norms.,Although many authors have recognized the enormity of food wastage and limited employment of cold chain in developing countries compared to developed countries, few efforts have been made to explore the reasons for the limited use of cold chains in developing countries. There are several noteworthy theoretical and managerial contributions that emerged from addressing this gap.

Developing the fifth generation port concept model : an empirical test

Abstract: The purpose of this paper is to test the 5GP concept with measurement of the performance of Busan, Hong Kong, Singapore and Shanghai ports, employing a hybrid method of consistent fuzzy preference relation (CFPR), VIsekriterijumska Optimizacija i KOmpromisno Resenje (VIKOR) and PROMETHEE.,The authors developed the concept of the fifth generation ports (5GPs), and apply CFPR, VIKOR and preference ranking organization method for enrichment evaluations (PROMETHEE) to evaluate the 5GPs.,The performance of the ports of Hong Kong and Singapore is close to meet the definition of 5GP criteria. On the contrary, ports of Busan and Shanghai are still behind the 5GP stage in light of the majority of the evaluation criteria’s performance.,This paper studies four ports. More empirical tests are needed to verify the applicability of the 5GP concept toward other ports.,The findings provided port managers with the insight of how to improve their port to meet the criteria of 5GP.,New criteria and higher expectations of existing requirements present challenges to port managers for a need to raise the bar of service standards and develop new competencies.,The authors developed the concept of the 5GPs. Newly developed 5GP contributes to expanding the concepts of first to fourth generation ports developed by UNCTAD.

Hidden potentials in open-loop supply chains for remanufacturing

Abstract: The circular economy grows in popularity in sustainability-oriented environments. Remanufacturing contributes to circularity though it faces challenges regarding reverse supply chains (SCs). Literature focusses on closed-loop supply chains (CLSCs) for reverse flows of products. However, alternative SCs and different market actors provide used components (cores) for remanufacturing through “open-loops”. The purpose of this paper is to investigate the influence of independent actors on core supply and how especially middlemen implement supplier relationship management to address supply shortages in automotive remanufacturing.,The study follows a qualitative research approach to compare remanufacturing SCs in Europe and North America. The analysis aims to identify managerial leverage to reduce supply shortages.,Reduction of information asymmetries and transaction costs is crucial for “open-loop supply chains” to compete with more integrated CLSCs. The study identifies an e-procurement solution that addresses these issues and helps to increase the supply through “open-loops”. Furthermore, regulation may hinder or facilitate supply.,It needs to be further investigated to what extent e-procurement and supplier relationship management can reduce shortages. Middlemen who can collaborate with the research would provide further research opportunities.,If supplier relationship management adapts to the requirements of remanufacturing, it can increase the supply potential through “open-loop” SCs. The e-procurement solution could serve SCs beyond automotive remanufacturing. Policy makers need to revise legislation hindering these SCs.,The study provides novel findings regarding independent actors, their supplier relationship management and their potential to reduce shortages in independent SCs for remanufacturing.