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This study aimed to develop the integration of the multiperiod production-distribution model in a closed-loop supply chain involving carbon emission and traceability. The developed model was for agricultural food (agri-food) products, considering the reverse flow of food waste from the disposal center (composting center) to producers.

The results indicate that integrating the production and distribution model considering food waste recycling provides low carbon emissions in lower total costs. The sensitivity analysis also found that there are trade-offs between production and distribution rate and food waste levels on carbon emission and traceability.

This study focuses on the mathematical modeling of a multiperiod production-distribution formulation for a closed-loop supply chain.

The model of the agri-food closed-loop supply chain in this study that considers food recycling and carbon emissions would help stakeholders involved in the agri-food supply chain to reduce food waste and carbon emissions.

This study focuses to develop a common humanitarian supply chain process model (HSCPM) that enables effective enterprise resource planning (ERP) systems for NGOs, and the study also investigates the role of modularity as a dynamic capability that supports creating such model.

A multifocus group study was performed as part of a larger project, the Frontline Humanitarian Logistics Initiative, aiming to establish a common data model that would serve as the backbone of humanitarian ERP systems. Fourteen international humanitarian organizations (IHOs) participated in the process, reaching a consensus on the structure of the process model.

An HSCPM was proposed based on the consensus reached across IHOs. Four degrees of customization differentiating between “generic,” “tailored,” “specific,” and “unique” processes are presented and discussed.

The findings show modularity applied to process as a mean to create dynamic efficiencies and position the modular process model within the dynamic capabilities framework, supporting supply chain responsiveness and expanding the literature on supply chain management (SCM), dynamic capabilities, and humanitarian logistics.

This research proposes a consensus-based data model, facilitating the advancement of ERP systems in the humanitarian context and lays a foundation for interoperability among ERP systems across diverse IHOs.

First attempt to elucidate the specific characteristics and unique processes defining an HSCPM, this study reached an unprecedented consensus for the humanitarian sector, setting the base toward an industry standard.

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

This paper tries to project population distribution by modeling geo-homophily in OSNs.

This paper aims to investigate how organizational learning (OL) affects the development of anticipatory adaptation to climate change in companies. Because the need to learn increases in circumstances of greater uncertainty such as the case of climate change, one of the processes that can explain different levels of anticipatory adaptation to climate change (AACC) by companies is OL.

The research uses a case study design. Following the procedures of qualitative sampling, an exemplary case of organizational adaptation to climate change in a sector that is extremely affected by the impacts of weather events was chosen. Empirical data collection includes semi-structured interviews and the collection of private and public documents. Such data were analyzed through thematic analysis.

The process of OL for anticipatory adaptation to climate change presents substantial differences from the traditional OL process presented by the specialized literature. In particular, the concepts of single- and double-loop learning were challenging to fit into the learning processes required for AACC.

Organizations have historically been working towards the adaption to external unforeseen events, but anticipatory adaptation to climate change presents new challenges and requires new forms of learning. Previous research has examined the interplay between learning and climate change adaptation, especially at the inter-organizational level. By developing research at the organizational level, this paper addresses a gap in the literature and shows that the required learning to adapt to climate change differs from the traditional learning, described in the management literature.

Due to the globalization of trade, hundreds of millions containers pass every year through world ports. Such a situation is extremely challenging in terms of securing freight transport operations. However, costs and lead-times are still very important components of supply chains' performance models. Therefore, the drive for enhanced safety and security cannot be made at the expense of these other two factors of competitiveness, and the processes implemented by the global supply chain links, including the maritime port one, should tend to a joint optimization of trade facilitation and operational safety / security.

The research on which this paper feeds back falls within the frame of this mixed performance requirement. More specifically, the paper presents a decision-support system dedicated to managing the risks associated with land and maritime container transportation; this system is based on the modeling of the knowledge of a group of experts, and covers the three phases of risk identification, assessment and avoidance / mitigation.

This study aims to examine the factors that influence profit–loss sharing (PLS) financing in Indonesian Islamic banks from the perspective of Islamic banks’ employees. Islamic banks have important role in influencing the amount of PLS financing distribution through their screening process.

This study uses questionnaires in collecting data that are distributed to the employees who process or handle PLS financing in Islamic banks in Yogyakarta, Indonesia. The independent variables are risk, financing screening process, analysis of financial statement and competency of the employees of Islamic banks. The data are processed using multiple regression.

This study finds that risk, the quality of financing screening process and the analysis of financial statement have positive influence on the PLS financing, whereas competency of employees of Islamic banks does not influence PLS financing.

The results of this study are expected to give contribution to increase the role of Islamic banks in encouraging PLS financing. The adequate screening, controlling and monitoring system in Islamic banks should be strengthened to encourage the quality of financing distributed.

Primary data are used in this study to know the perspective of Islamic bank employees in the financing division on the PLS financing. This study attempts to identify the perspective of employees who have direct relationship with the decision of financing in Islamic banks.

The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout.

A queuing framework that operates under two distinct regimes is formulated to analyze service rates that represent system capacity to vaccinate (under the first regime) and hesitancy-induced throughput (under the second regime). These supply- and hesitancy-constrained regimes form the focus of the present paper, as the former reflects the inherent ability of the nation in its various jurisdictions to mobilize, whereas the latter reflects a critical area for public policy to protect the population’s overall health and safety.

The two-regime framework analysis provides insights into the capacity to vaccinate and hesitancy-constrained demand, which is found to vary across the country primarily by politics and region. The framework also allows analysis of the end-to-end supply chain, where it is found that the ability to vaccinate was likely constrained by last-mile administration issues, rather than the capacity of the manufacturing and transportation steps of the supply chain.

This study presents a new framework to consider end-to-end supply chains as dynamic systems that exhibit different regimes because of unique supply- and demand-side characteristics and estimate rollout capacity and underlying determinants at the national, state and county levels.

Food supply chain (FSC) in Greece is dominated by small and medium-sized enterprises (SMEs), who face several challenges in adopting green practices. The purpose of this paper is to identify the key drivers and barriers influencing the environmental performance of SMEs within the Greek dairy supply chain (SC).

Descriptive research methodology attempts to prioritize the drivers and barriers for improving the environmental sustainability performance. Analytical hierarchy process and sensitivity analysis are used to understand the complex nature of the influencing factors.

The analysis identifies five barriers and six drivers for the implementation of green practices within the dairy SC. While external drivers significantly influence the market structure and logistics network, government, competitors and customers are the driving factors for improving environmental performance.

The study contributes to filling the literature gap on key factors influencing the implementation of green practices within the FSC. The identified influential factors will contribute toward building a framework for improving sustainability performance within the Greek dairy SC.

The study is expected to benefit the Greek and European SMEs by driving their environmental practices within the perishable SC network.

The paper provides directions for researchers, practitioners and policy makers in understanding the challenges for implementing green practices in the dairy SC. The holistic approach followed in this paper is a building block for a conceptual framework on implementing environmental sustainability within the FSC. Apart from contributing to the current literature by extending the research horizon to SMEs’ green adoption capability, this study also provides better understanding of the pivotal role of internal and external key factors in influencing sustainability performance.

Demand for express parcel delivery has been greatly increasing in South Korea due to the growth of B2C e-commerce activities. It is imperative that parcel carriers have good insights into the performance of their distribution networks with different levels of demand and plan ahead for the adaptations in order to be able to meet future changes in demand. This paper proposes a framework to evaluate the likelihood of parcels arriving on-time to their destinations (local service reliability) with a strong focus being placed on their spatial distribution. The resulting maps of local service reliability allow us to identify specific locales that would suffer the most from a capacity overflow in the networking system, thus pointing to areas that need immediate attention. Furthermore, this paper attempts to identify potential factors which could affect the spatial variation of local service reliability.