Search results

The introduction of quality management Internet of things (QM IoT) can help food supply chain members to enhance real-time visibility, quality, safety and efficiency of products and processes. Current literature indicates three main research gaps, including a lack of studies in QM IoT in the food supply chain, the vagueness of integrative adoption of new technology framework and deficient research covering both adoption attitude and intention in the same model. This study aims to propose an analysis model based on the technological–organizational–environmental (TOE) framework and reinforced by the collaborative structure to capture the importance of the supply chain network.

The partial least square-structural equation modeling (PLS-SEM) was applied to test the impacts of the adoption factors on QM IoT adoption attitude and intention among 197 respondents in food manufacturing in Thailand.

The results indicated that compatibility, trialability, adaptive capacity, innovative capability, executive support, value chain partner pressure, presence of service provider and information sharing significantly impacted the attitude toward QM IoT adoption, while adaptive capability, innovative capability and information sharing directly influenced the QM IoT adoption intention. Furthermore, the attitude toward QM IoT adoption positively impacted the QM IoT adoption intention.

This study contributed to academicians by proposing a more solid adoption framework for QM IoT area. In addition, the business practitioners could actively prepare themselves for the QM IoT adoption, whereas the service providers could provide better and suitable service.

This research contributes to the building of a more solid framework and indicates significant factors that impact the attitude toward QM IoT adoption and adoption intention.

There are two aims of this research: one is to prove the interactive effect of supply chain integration (SCI) on performance and the other is to ascertain gaps in performance among levels of SCI. The population of this research is international freight forwarders and the collected data is used in testing hypotheses through various analytical methods such as factor analysis, Cronbach’s alpha, cluster analysis, ANOVA, MANOVA, ANCOVA, post hoc analysis and regression analysis. First, the interaction between internal integration and external integration improves customer performance and financial performance. The forwarders improve internal processes following information acquired from customers and the information is shared with logistics service providers, followed by high performance. Second, gaps in performance among levels of SCI are verified. Managers of the forwarders make strategic decision making on the basis of their recognition of environment and, as a result, the forwarders enjoy different performance.

This research empirically analyzes gaps in performance among development stages of integration in supply chain management (SCM). The used variables are integration such as internal and external and performance such as cost and service. The population is international freight forwarders in the Republic of Korea and the sample frame is the membership list of the Korean International Freight Forwarders Association. The used methodology in this research is various: Cronbach’s alpha, factor analysis, cluster analysis, analysis of variance and post hoc analysis. It is important to ascertain the position in which they are included and the position is concerned with internal integration and external integration because the aim of this research is to ascertain where the forwarders are in development stages of integration. According to prior research, development stages of integration are regarded as the flow from internal to external. However, this research suggests that development stages of integration do not explain the flow of the stages but explain the strategic choice concerned with their current decision-making.

The purpose of this paper is to investigate the economic feasibility of a three-echelon Halal Meat Supply Chain (HMSC) network that is monitored by a proposed radio frequency identification (RFID)-based management system for enhancing the integrity traceability of Halal meat products and to maximize the average integrity number of Halal meat products, maximize the return of investment (ROI), maximize the capacity utilization of facilities and minimize the total investment cost of the proposed RFID-monitoring system. The location-allocation problem of facilities needs also to be resolved in conjunction with the quantity flow of Halal meat products from farms to abattoirs and from abattoirs to retailers.

First, a deterministic multi-objective mixed integer linear programming model was developed and used for optimizing the proposed RFID-based HMSC network toward a comprised solution based on four conflicting objectives as described above. Second, a stochastic programming model was developed and used for examining the impact on the number of Halal meat products by altering the value of integrity percentage. The ε-constraint approach and the modified weighted sum approach were proposed for acquisition of non-inferior solutions obtained from the developed models. Furthermore, the Max-Min approach was used for selecting the best solution among them.

The research outcome shows the applicability of the developed models using a real case study. Based on the computational results, a reasonable ROI can be achievable by implementing RFID into the HMSC network.

This work addresses interesting avenues for further research on exploring the HMSC network design under different types of uncertainties and transportation means. Also, environmentalism has been becoming increasingly a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function.

The model can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management.

Although there were a few studies focusing on the configuration of a number of HMSC networks, this area is overlooked by researchers. The study shows the developed methodology can be a useful tool for designers to determine a cost-effective design of food supply chain networks.

Artificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of such a new advanced technology. The aim of the paper is to map the state-of-the-art of AI applications in agriculture, their advantages, barriers, implications and the ability to lead to new business models, depicting a future research agenda.

A structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.

Findings underline the multiple uses and advantages of AI in agriculture and the potential impacts for farmers and entrepreneurs, even from a sustainability perspective. Several applications and algorithms are being developed and tested, but many barriers arise, starting from the lack of understanding by farmers and the need for global investments. A collaboration between scholars and practitioners is advocated to share best practices and lead to practical solutions and policies. The promising topic of new business models is still under-investigated and deserves more attention from scholars and practitioners.

The paper reports the state-of-the-art of AI in agriculture and its impact on the development of new business models. Several new research avenues have been identified.

The purpose of this paper is to review the food supply chain management (FSCM) in terms of systems and implementations so that observations and lessons from this research could be useful for academia and industrial practitioners in the future.

A systematical and hierarchical framework is proposed in this paper to review the literature. Categorizations and classifications are identified to organize this paper.

This paper reviews total 192 articles related to the data-driven systems for FSCM. Currently, there is a dramatic increase of research papers related to this topic. Looking at the general interests on FSCM, research on this topic can be expected to increase in the future.

This paper only selected limited number of papers which are published in leading journals or with high citations. For simplicity without generality, key findings and observations are significant from this research.

Some ideas from this paper could be expanded into other possible domains so that involved parties are able to be inspired for enriching the FSCM. Future implementations are useful for practitioners to conduct IT-based solutions for FSCM.

As the increasing of digital devices in FSCM, large number of data will be used for decision-makings. Data-driven systems for FSCM will be the future for a more sustainable food supply chain.

This is the first attempt to provide a comprehensive review on FSCM from the view of data-driven IT systems.

Agri-food firms face many challenges when assessing and managing their performance. The purpose of this research is to determine important factors for an integrated agri-food supply chain performance measurement system.

This research uses the Peruvian kiwicha supply chain as a meaningful context to examine critical factors affecting agri-food supply chain performance. The research uses interpretative structural modelling (ISM) with fuzzy MICMAC methods to suggest a hierarchical performance measurement model.

The resulting kiwicha supply chain performance management model provides insights for managers and academic theory regarding managing competing priorities within the agri-food supply chain.

The model developed in this research has been validated by cooperative kiwicha associations based in Puno, Peru, and further refined by experts. Moreover, the results obtained through ISM and fuzzy MICMAC methods could help decision-makers from any agri-food supply chain focus on achieving high operational performance by integrating key performance measurement factors.

During the COVID-19 crisis in Victoria, Australia the complexity of school leadership increased greatly for school principals. This study focused on the lived experiences of early career principals in the independent school sector from March to November 2020 in Victoria, Australia. It investigates transformative work that was undertaken by these leaders in leading their schools over a protracted crisis.

The study builds on constructs of crisis leadership, adaptive leadership, agile leadership and emotional intelligence, exploring the leadership approaches undertaken by twenty-two early career principals in Victoria, Australia. Using a narrative inquiry approach, across three temporal points in 2020, storied productions drawn from the findings present four emergent types of emotionally intelligent leadership approaches undertaken by these principals. These leadership approaches are presented as the commander-leader, the conductor-leader, the gardener-leader and the engineer-leader with each approach demonstrating both organisational leadership approaches as well as individual leadership styles used by these principals as they led their schools.

The findings have direct implications for professional development programs focusing on aspiring principals and early career principals with emphasis on the importance of developing emotionally intelligent skillsets in principals for use during periods of rapid change or high crisis in schools. The findings present insight into the support useful for early career principals in the first five years of principalship.

This study uses a unique emotional intelligence approach to understand school leadership during and after a crisis.

In this paper, the authors integrate the psychological ownership theory with the concept of commitment to contribute to the discussion on agricultural supply chain management. The purpose of this study is to examine how farmers experience their commitment to the business relationship with the processor and how this is conveyed through the routes of psychological ownership.

The empirical data are based on 14 in-depth face-to-face Finnish farmer interviews. To understand the farmers’ routes to psychological ownership, the critical incidents technique was used.

According to the three routes to psychological ownership – control, profound knowledge and self-investment – the authors argue that farmers mainly consider their routes to be more or less blocked because of the asymmetrical power and information distribution in the business relationship with the processor. Furthermore, based on farmers’ perceptions of psychological ownership, the authors provide a farmer typology that reflects in the farmers’ willingness to commit to the business relationship. The identified types are named as satisfied, captives and leavers.

By integrating the theory of psychological ownership with the concept of commitment, this study provides a more robust understanding of how farmers experience their commitment to the business relationship, thus, contributing to the literature on supply chain management in the agri-food business context. Implementation of these findings can help business partners to proactively improve their business relationships through the perceived level of commitment and to deal with critical incidents influencing the effectiveness of the whole chain.