Search results

This study examines the relationship between demand forecasting error and retail inventory management in an uncertain supplier yield context. Replenishment is segmented into off-season and peak-season, with the former characterized by longer lead times and higher supply uncertainty. In contrast, the latter incurs higher acquisition costs but ensures certain supply, with the retailer's purchase volume aligning with the acquired volume. Retailers can replenish in both phases, receiving goods before the sales season. This paper focuses on the impact of the retailer's demand forecasting bias on their sales period profits for both phases.

This study adopts a data-driven research approach by drawing inspiration from real data provided by a cooperating enterprise to address research problems. Mathematical modeling is employed to solve the problems, and the resulting optimal strategies are tested and validated in real-world scenarios. Furthermore, the applicability of the optimal strategies is enhanced by incorporating numerical simulations under other general distributions.

The study's findings reveal that a greater disparity between predicted and actual demand distributions can significantly reduce the profits that a retailer-supplier system can earn, with the optimal purchase volume also being affected. Moreover, the paper shows that the mean of the forecasting error has a more substantial impact on system revenue than the variance of the forecasting error. Specifically, the larger the absolute difference between the predicted and actual means, the lower the system revenue. As a result, managers should focus on improving the quality of demand forecasting, especially the accuracy of mean forecasting, when making replenishment decisions.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study aims to focus on building a conceptual closed-loop vaccine supply chain (CLVSC) to decrease vaccine wastage and counterfeit/fake vaccines.

Through a focused literature review, the framework for the CLVSC is described, and the system dynamics (SD) research methodology is used to build a causal loop diagram (CLD) of the proposed model.

In the battle against COVID-19, waste management systems have become overwhelmed, which has created negative environmental and extremely hazardous societal impacts. A key contributing factor is unused vaccine doses, shown as a source for counterfeit/fake vaccines. The findings identify a CLVSC design and transshipment operations to decrease vaccine wastage and the potential for vaccine theft.

This study contributes to establishing a pandemic-specific VSC structure. The proposed model informs the current COVID-19 pandemic as well as potential future pandemics.

A large part of the negative impact of counterfeit/fake vaccines is on human well-being, and this can be avoided with proper CLVSC.

This study develops a novel overarching SD CLD by integrating the epidemic model of disease transmission, VSC and closed-loop structure. This study enhances the policymakers’ understanding of the importance of vaccine waste collection, proper handling and threats to the public, which are born through illicit activities that rely on stolen vaccine doses.

Logistical facility location decisions can make a crucial difference in the success or failure of a company. Geographical Information Systems (GIS) have recently become a very popular decision support system to help deal with facility location problems. However, until recently, GIS methodologies have not been fully embraced as a way to deal with new facility location problems in business logistics. This research makes a framework for categorizing empirical facility location problems based on the intensity of the involvement of GIS methodologies in decision making. This framework was built by analyzing facility location models and GIS methodologies. The research results revealed the depth of the embracement of GIS methodologies in logistics for determining new facility location decisions. In the new facility location decisions, spatial data inputs are almost always coupled with the visualization of the problems and solutions. However, the usage of GIS capability solely (i.e. suitability analysis) for problem solving has not been embraced at the same level. In most cases, the suitability analysis is used together with special optimization models for choosing among the multiple alternatives.

The purpose of this paper is to provide an overview of the evolution of service supply chain management from a behavioural operations perspective, pointing out future research directions for scholars.

This study searched five databases for relevant literature published between 2009 and 2018, selecting 64 papers for this review. The selected literature was categorised according to two dimensions: a service supply chain link perspective and a behavioural factor perspective. Comparative analysis was used to identify gaps in the literature, and five future research agendas were proposed.

In terms of the perspective of service supply chain link, extant literature primarily focuses on service supply and service co-ordination management, and less on service demand and integration management. In terms of the behavioural factor’s perspective, most focus on classic behaviour factors, with less attention paid to emerging behaviour factors. This paper thus proposes five research agendas: demand-oriented management and integrated supply chain-oriented behavioural research; broadening the understanding of the scope of behavioural operations; integrating the latest backgrounds and trends of service industry into the research; greater attention to behavioural operations in service sub-industries; and multimethod combination is encouraged to be used to dig into the interesting research problems.

This study constitutes the first systematic review of service supply chain research from a behavioural perspective. By categorising the literature into two dimensions, the state of existing research is evaluated with an eye towards future research avenues.

This paper aims to provide a systematic literature review of the state-of-the-art applications of climate information in humanitarian relief efforts, to further the knowledge of how climate science can be better integrated into the decision-making process of humanitarian supply chains.

A systematic literature review was conducted using a combination of key search terms developed from both climate science and humanitarian logistics literature. Articles from four major databases were retrieved, reduced and analyzed.

The study illustrates the status of application of climate information in humanitarian work, and identifies usability, collaboration and coordination as three key themes.

By delivering an overview of the current applications and challenges of climate information, this literature review proposes a three-phase conceptual framework.

This paper aims to examine the integration of lateral transshipment and road vulnerability into the humanitarian relief chain in light of affected area priority to address equitable distribution and assess the impact of various parameters on the total average inflated distance traveled per relief item.

After identifying comprehensive critical criteria and subcriteria, a hybrid multi-criteria decision-making framework was applied to obtain the demand points’ weight and ranking in a real-life earthquake scenario. Direct shipment and lateral transshipment models were then presented and compared. The developed mathematical models are formulated as mixed-integer programming models, considering facility location, inventory prepositioning, road vulnerability and quantity of lateral transshipment.

The study found that the use of prioritization criteria and subcriteria, in conjunction with lateral transshipment and road vulnerability, resulted in a more equitable distribution of relief items by reducing the total average inflated distance traveled per relief item.

To the best of the authors’ knowledge, this study is one of the first research on equity in humanitarian response through prioritization of demand points. It also bridges the gap between two areas that are typically treated separately: multi-criteria decision-making and humanitarian logistics.

This is the first scholarly work in Shiraz focused on the equitable distribution system by prioritization of demand points and assigning relief items to them after the occurrence of a medium-scale earthquake scenario considering lateral transshipment in the upper echelon.

The paper clarifies how to prioritize demand points to promote equity in humanitarian logistics when the authors have faced multiple factors (i.e. location of relief distribution centers, inventory level, distance, lateral transshipment and road vulnerability) simultaneously.

The purpose of this paper is to explore the current trends, implications and challenges of information systems (IS) related to omni-channel logistics.

An exploratory survey study is conducted with 23 Swedish retail companies transforming to omni-channel logistics. The study investigates the retailers’ current situations regarding logistics IS as well as their perceptions of the future development.

From the perspective of leading Swedish retailers, omni-channel requirements drive the implementation of new IS to support effective and efficient material handling across the network and in the respective nodes. The shifting roles and increase in the number of handlings nodes will require flexible IS platforms that can support multiple flows and integrated inventory. The major increase in the implementation of new, critical functionalities is related to real-time, multi-criteria decision making on order allocation to different handling nodes. More advanced IS functionality is also required in material-handling nodes to support the increased degree of automation and continuous improvements with the aim to shorten order-to-delivery lead times. A number of challenges are identified that must be addressed during the transformation to omni-channel logistics, especially related to the growing complexity and decentralization of networks, tougher lead-time requirements and larger product assortments.

To support further theory development, 11 propositions related to trends and a schematic framework conceptualizing implications and challenges are submitted for testing in future research.

The study highlights several aspects related to logistics IS that are important for practitioners to consider as they undergo the transition to omni-channels. It provides insights into IS functionalities that are likely to grow in use and criticality for supporting material handling and inventory management in increasingly complex and decentralized networks. In particular, the authors stress the need to implement functionality that works across previously separated handling nodes and decision areas. Managers can also use the propositions to reflect on what the near future holds and as input for their own scenario analyses.

Previous research has primarily focused on technology that supports the front-end customer experience. This study is original in that it explores the trends, implications and challenges for logistics IS in omni-channels – an area that has not been explored in detail previously. It also studies both perceived and expected changes over time related to the transformation toward omni-channel logistics.

The purpose of this paper is to provide a method to formalize information security control descriptions and a decision support system increasing the automation level and, therefore, the cost efficiency of the information security compliance checking process. The authors advanced the state-of-the-art by developing and applying the method to ISO 27002 information security controls and by developing a semantic decision support system.

The research has been conducted under design science principles. The formalized information security controls were used in a compliance/risk management decision support system which has been evaluated with experts and end-users in real-world environments.

There are different ways of obtaining compliance to information security standards. For example, by implementing countermeasures of different quality depending on the protection needs of the organization. The authors developed decision support mechanisms which use the formal control descriptions as input to support the decision-maker at identifying the most appropriate countermeasure strategy based on cost and risk reduction potential.

Formalizing and mapping the ISO 27002 controls to the security ontology enabled the authors to automatically determine the compliance status and organization-wide risk-level based on the formal control descriptions and the modelled environment, including organizational structures, IT infrastructure, available countermeasures, etc. Furthermore, it allowed them to automatically determine which countermeasures are missing to ensure compliance and to decrease the risk to an acceptable level.