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This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

The purpose of this paper is to carry out structural analysis of potential supply chain risks and performance measures in fresh food retail by applying interpretive structural modeling (ISM).

Inputs were taken from industry experts in identifying and understanding interdependencies among food retail supply chain risks on different levels (sourcing and logistics outside the retail stores; storage and customer interface at the stores). Interdependencies among risks and their impact on performance measures are structured into a hierarchy in order to derive subsystems of interdependent elements to derive useful insights for theory and practice.

Using the ISM approach the risks and performance measures were clustered according to their driving power and dependence power. Change in/inadequate government regulations’ are at the bottom level of the hierarchy implying highest driving power and require higher attention and focussed mitigation strategies. Risks like lack of traceability, transport delays/breakdowns and temperature abuse, cross-contamination in transport and storage have medium driver and dependence powers.

The approach is focussed on food retail supply chains in the Indian context and thereby limits the ability to generalize the findings. The academics and experts were selected on convenience and availability.

It gives managers a better understanding of the risks and performance measures that have most influence on others (driving performance measures) and those measures which are most influenced by others (dependent performance measures) in fresh food retail and also a tool to prioritize them. This kind of information is strategic for managers who can use it to identify which performance measures they should concentrate on managing the trade-offs between measures. The findings and the applicability for practical use have been validated by both experts and practicing managers in food retail supply chains.

The work is perhaps the first to link supply chain risks with performance and explains the propagation of risks in food retail supply chains. It contributes to theory by addressing a few research gaps and provides relevant managerial insights for practitioners.

Muslim consumers have been shocked with the news of cross-contamination issues in the Halal food that they consumed. These issues make them put more effort in ensuring the products that they purchased being monitored throughout the supply chain. In this case, food companies must be prepared to implement systematic traceability system to ensure the authenticity of Halal products and comprehend the importance of Halal industry environmental factors (HIEF) in enhancing integrity of Halal food supply chain and protect from any risk of cross-contaminations. This paper aims to clarify the relationship between the Halal traceability system adoption (HTSA) and HIEFs on Halal food supply chain integrity (HFSCIn).

The study opted quantitative research approach by using the self-administrated questionnaires. The questionnaires were distributed during Malaysia International Halal Showcase (MIHAS) 2014 and Halal Fiesta Malaysia (HALFEST) 2014. 127 Malaysian Halal food and beverages companies have been involved in the study. Most of the respondents are the general manager or owner of the company, Halal executives, quality assurance managers, operation managers and sales manager.

The study found that there is a significant relationship between HTSA and HIEF on HFSCIn. The study also found that the highest adoptions of Halal traceability system are among the producer and end user, while the highest contributions in influencing the HIEF are the economic and socio-cultural factors.

This study only focused on Halal food industry particularly the food and beverages category. Thus, future study can explore further on every category in food industry such as raw materials and ingredients; poultry, meat and dairy; fast food and premises and make comparison between pharmaceutical, cosmetics and health care in Halal industry. In addition, the sample size (N = 127) can be considered small; therefore, it is recommended that in future the subject matter be explored with a much larger sample to allow generalization of the result.

This study provided, perhaps for the first time, an analysis of the relationship between traceability adoptions and HIEF on HFSCIn.

This study aims to provide a practical solution to the relationship between supply chain (SC) integration and market responsiveness (MR). A method is proposed to integrate SC and MR parameters, namely, product supply and demand in the context of low-value commodities (e.g. cement).

Simulation and forecasting approaches are adopted to develop a potential procedure for addressing demand during lead time. To establish inventory measurements (safety stock and reorder level) and increase MR and the satisfaction of customer’s needs, this study considers a downstream SC including manufacturers, depots and central distribution centers that satisfies an unbounded number of customers, which, in turn, transport the cement from the industrialist.

The demand during lead time is shown to follow a gamma distribution, a rare probability distribution that has not been considered in previous studies. Moreover, inventory measurements, such as the safety stock, depending on the safety factor under a certain service level (SL), which enables the SC to handle different responsiveness levels in accordance with customer requests. In addition, the quantities of the safety stock and reorder point represent an optimal value at each position to avoid over- or understocking. The role of SC characteristics in MR has largely been ignored in existing research.

This study applies SC flexibility analyzes to overcome the obstacles of analytical methods, especially when the production process involves probabilistic variables such as product availability and demand. The use of an efficient method for analyzing the forecasting results is an unprecedented idea that is proven efficacious in investigating non-dominated solutions. This approach provides near-optimal solutions to the trade-off between different levels of demand and the SC responsiveness (SLs) with minimal experimentation times.

The purpose of this paper is to analyse the dimensional structure of relationship value by comparing the results of one-dimensional versus multidimensional conceptualisation in the prediction of satisfaction and loyalty in a B2B context.

A survey was carried out and 219 responses were obtained from retail companies in the furniture sector in Spain. The model was estimated using the partial least squares (PLS) approach.

The results revealed that the multidimensional conceptualisation of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualisation.

Given the complexity involved in conceptualising relationship value, its study needs to be expanded to encompass other contexts.

Manufacturers should focus their efforts on improving each of the axes of relationship value, to ensure the satisfaction and loyalty of their retail customers.

This study integrates and justifies the measurement of relationship value and its axes in the nomological structure with other relational constructs.

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.

The purpose of this paper is to examine the concept of perishable food supply chain quality (PFSCQ) and to suggest a structural model that counts the influence of PFSCQ practices on organizational sustainable performance.

On the basis of comprehensive literature review, PFSCQ highly significant practices were examined and designated. These practices were classified into four dimensions: upstream quality (supplier quality), downstream quality (customer focus), internal quality (process and logistics quality) and support practices (top management leadership and commitment to quality, quality of human resource, quality of information and supply chain integration). The measurement instrument of organizational sustainable performance was also build on, containing three aspects: economic, environmental and social performance.

An inventive conceptual model that specifies a comprehensive image cover up core dimensions of PFSCQ and various aspects of organizational sustainable performance was suggested. This conceptual model can be used as “a directive” for theory developing and measurement instrument development of PFSCQ practices and organizational sustainable performance. More prominently, on the road to achieving additional insight, an extensive structural model that makes out direct and indirect relationships between PFSCQ practices and organizational sustainable performance was also developed. Practitioners can apply this model as “a path plan” for implementing PFSCQ practices to improve organizational sustainable performance.

The integration of quality and supply chain even now remains inadequate in the literature. Consequently, it is required to have a more focused approach in assessing quality issues inside the upstream, internal and downstream of the supply chain. This study concentrates on the practices which make better quality aspects of the supply chain, known as PFSCQ practices. Suggested research models in this paper contribute to conceptual frameworks for theory building in PFSCQ and sustainable organizational performance. It is also expected that this research can suggest a useful direction for determining and implementing PFSCQ practices as well as make possible further studies in this arena.

The purpose of this paper is to analyze and investigate analyzed core operational problems of aquatic products with food traceability system and their performance in the Taiwanese market and to develop the marketing strategies to solve these core operational problems.

Based on all of the core operational problems derived from the literature, the paper interviewed distributors and aquatic product producers and collected their ideas to resolve the above problems. Then, the study applies the TRIZ theory to find the improving and worsening parameters for those issues, based on which the study can develop strategies to improve the marketing model of aquatic products with food traceability systems to solve operational problems.

The findings of the study are of three fold: identified seven core problems of aquatic products with food traceability systems; identified seven strategies for improving marketing model to solve operational problems of aquatic products with food traceability systems and developed the new marketing model to solve operational problems for aquatic products with food traceability systems.

Promoting the food traceability certification comprehensively cannot only improve the food safety in Taiwan but also improve the competitiveness of Taiwanese industries as well as help to expand to the international market.

The contribution of this study lies in extending the body of knowledge of application of TRIZ methodology in marketing model for aquatic products with food traceability systems. The findings of this study can be used as a reference for aquaculture products with traceability systems in other countries, as food safety is a globally growing trend.

The purpose of this paper is to explore the sustainability of waste supply chains regarding the energy efficiency of first-mile waste collection systems and quality of waste. Roles of actors in the waste service triad are considered, particularly focusing on households.

Primary data are collected from respondents including municipality officers, waste service providers (WSPs) and households through brainstorming sessions, semi-structured interviews, site visits and a focus group. Secondary data are collected from official reports for validation.

Findings reveal tension between the energy efficiency of waste collection logistics and the quality of waste collected. Households are co-producers of logistic services providing important inputs in the form of sorting and moving waste and raw materials into new cycles of goods circulating in logistics systems. Other actors in the logistics service triad are the municipality as regulator and the WSP acting as a reverse-logistics service provider.

This study provides principles for policymakers and practitioners to evaluate the energy efficiency of waste management options, considering the quality of waste. Also, “logistics services” and “quality of waste” as concepts might provoke new thoughts on how to involve the consumer in resource recovery.

Few studies have focused on the end-consumer’s role in waste supply chains. By considering waste as a resource and the consumer as the supplier of this input, this study provides a new way to think about logistics services for waste collection.

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.