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This study aims to reveal the implications that trust, as a key driver of consumer behaviour, might have on consumer acceptance of front-of-pack labels (FOPLs) and policy effectiveness. By conducting three studies on 1956 European consumers with different levels of exposure to FOPLs, this study offers additional theoretical and experimental support through a deep investigation of the central role of trust in consumers’ decision-making towards healthier and more informed food choices.

Study 1 used structural equation modelling to assess whether trust is a relevant mediator of the relationship between attitude and behavioural intention (BI), thus upgrading the front-of-pack acceptance model (FOPAM); Study 2 tested the model by comparing two labels at the extremes of the current European scheme (NutrInform Battery [NiB], Nutri-Score [NS]); Study 3 assessed the effect in cases where the connection between trust and algorithms is made transparent and evaluated trust dimensions, focusing on the perception of an algorithm presence behind FOPLs information.

Study 1 strengthens the FOPAM model with the mediating role of trust in FOPLs, demonstrating a positive effect of attitude on trust and, in turn, on BI, and resulting in a higher model fit with all the significant relationships; Study 2 revealed that the relative performance of the different labels on the FOPAM can be explained by the trust dimension; Study 3, investigating the dynamics of trust in the FOPAM, revealed that the NS is less effective than the NiB on attitude, BI and trust.

The sample was limited to Italian, French and English respondents, and two labels at the extreme of the spectrum were examined. Furthermore, the research has relevance to the issue of trust. Other moderators used in previous studies on technology acceptance model, such as actual use versus perceptual use, user experience level or type of users and type of use might be investigated.

The investigation of trust, with the upgrade of FOPAM, enhances understanding of consumers’ decision-making processes when aided by food labels and makes a new contribution to the European Union “Inception Impact Assessment” in preparation for the finalization of the “From-Farm-to-Fork Strategy”, providing new insights into the role of trust by assessing the relative performance of FOPLs in consumers’ acceptance of food-related information. Furthermore, this study revealed that consumers’ perception of FOPLs worsens when they realize that they are the result of an algorithmic calculation. Finally, the new FOPAM represents a reliable theoretical model for future research on FOPL.

This study increases the knowledge about the performance of different FOPLs on several dimensions of food decision-making, positions the upgraded FOPAM as a valid alternative to existing theoretical models to assess the relative performance of labels, also extending the literature in the context of algorithm-based FOPL, and could be used as a valid support to policymakers and industry experts in their decision towards a unified label at European level.

Food banks play an increasingly important role in society by mitigating hunger and helping needy people; however, research aimed at improving food bank operations is limited.

This systematic review used Web of Science and Scopus as search engines, which are extensive databases in Operations Research and Management Science. Ninety-five articles regarding food bank operations were deeply analyzed to contribute to this literature review.

Through a systematic literature review, this paper identifies the challenges faced by food banks from an operations management perspective and positions the scientific contributions proposed to address these challenges.

This study makes three main contributions to the current literature. First, this study provides new researchers with an overview of the key features of food bank operations. Second, this study identifies and classifies the proposed optimization models to support food bank managers with decision-making. Finally, this study discusses the challenges of food bank operations and proposes promising future research avenues.

The present study aims to identify the most critical elements of resilience in the management of supply chains of Brazilian companies and, in the sequence, debate possible digital technologies mentioned by literature to enhance them.

To identify the most critical elements, the information provided by qualified academics was used. Data analysis was performed through Cronbach’s alpha coefficient, hierarchical cluster analysis and Fuzzy TOPSIS approach.

Comparatively, the results pointed out three elements of resilience as the most critical in managing supply chains. They are the decision-making (understood as the definitions from the layout of the chain’s operations network to the choice of warehouse locations, distribution centres and manufacturing facilities), human resources (understood as management for human resources development and knowledge management through training) and security (understood as issues related to information technology for data security). For each of them, bibliographic research was performed to identify technologies that enhance these elements of supply chain management resilience.

The results presented here can significantly contribute to the expansion of debates associated with resilience in managing supply chains of Brazilian companies and directing researchers in the area.

Since Islamic markets are growing substantially, there is an urgent need to gain a better understanding of how Muslim consumers perceive products from a religious perspective. The purpose of this paper is to investigate the brain responses of Muslim consumers to Halal and non-Halal products using a functional magnetic resonance imaging (fMRI) technology.

The research model is a simplified version of the theory of planned behavior. The initial experiment began by asking participants to divide a set of images into two groups: Halal and non-Halal products. The fMRI experiment uses a blocked design approach to capture brain activities resulting from presenting the two groups of images to participants, and to record the strength of their attitudes toward purchasing the products.

Across all participants, the level of brain activation in the ventromedial prefrontal cortex increased significantly when Halal images were presented to them. The same results emerged when the Halal images showed raw and cooked meat. The variations in the results may be due to the high emotional sensitivity of Muslim consumers to using religious products.

This study uses a unique approach to monitor brain activity to confirm that consumers from specific market segments respond differently to market products based on their internal beliefs. Findings from this study provide evidence that marketing managers targeting Muslim markets should consider the sensitivity of presenting products in ways that reflect religious principles, in order to gain higher acceptance in this market segment.

Although the literature reports considerable research on Muslim consumers’ behavior, most of the previous studies utilize conventional data collection approaches to target broad segments of consumers by using traditional products. This paper is the first to track the reactions of the Muslim consumer segment to specific types of market products.

Packaging and labelling have become essential to how food manufacturers generate and deliver value to customers. The information displayed on the packaging can be used to communicate to customers the properties and unique characteristics of a food product (e.g. nutrients, calories and country of origin). To achieve communication goals effectively, manufacturers need to understand how consumers evaluate products based on their attributes. In particular, companies should be aware of which specific product attributes affect consumer buying behaviour and which product attributes are more critical during food assessment. So, the paper aims to investigate consumer's behaviuor linked to typical product attributes indicated on the packaging.

The present study examines consumer willingness to pay (WTP) for a cherry jam with different attributes (brand, type of production method and price) on a sample of 2,166 Italian respondents through a choice experiment using a random parameter logit-error component model.

The results showed that WTP for jams can be affected by attributes such as brand, price and production methods; precisely, they indicated that the level of naturalness in the production process constitutes the main element for the consumer’s choice; however, the considerable weight that price and brand have in influencing the purchasing behaviour of the food consumer was still confirmed: in fact, a p-value of less than 0.05 was found in all cases.

To the best of the authors’ knowledge, this is the first study that assesses the effect of different types of production on WTP for food products. In addition, this study also reflects on the importance of the level of education for consumer choice.

The purpose of this paper is to propose a concept of cloud auction robot (CAR) and its execution platform for transforming perishable food supply chain management. A new paradigm of goods-to-person auction execution model is proposed based on CARs. This paradigm can shift the management of traditional manual working to automated execution with great space and time saving. A scalable CAR-enabled execution system (CARES) is presented to manage logistics workflows, tasks and behavior of CAR-Agents in handling the real-time events and associated data.

An Internet of Things enabled auction environment is designed. The robot is used to pick up and deliver the auction products and commends are given to the robot in real-time. CARES architecture is proposed while integrating three core services from auction workflow management, auction task management, to auction execution control. A system prototype was developed to show its execution through physical emulations and experiments.

The CARES could well schedule the tasks for each robot to minimize their waiting time. The total execution time is reduced by 33 percent on average. Space utilization for each auction studio is improved by about 50 percent per day.

The CAR-enabled execution model and system is simulated and verified in a ubiquitous auction environment so as to upgrade the perishable food supply chain management into a new level which is automated and real-time. The proposed system is flexible to cope with different auction scenarios, such as different auction mechanisms and processes, with high reconfigurability and scalability.

To develop a roadmap of sustainability practices and assessment mechanisms to advance in the sustainable supply chain (SSC) performance assessment in the food supply chain. The analysis is grounded on the contingency and stakeholder theories.

The study follows a multiple case study approach analyzing the sustainability practices implementation and assessment across different supply chain stages in the food industry in Italy. The set of cases comprises 12 companies in the fresh fruit and vegetables (FFV), and seven companies in the “Balsamic Vinegar of Modena” (BVM) supply chains.

The sustainability practices and assessment in each company in both supply chains according to their objectives are identified. Different stakeholder pressures for sustainability implementation and assessment are analyzed. The contingency factors that foster sustainability assessment are outlined as well. Finally, the study develops a roadmap with five levels of progress considering the groups of practices implemented and the type of assessment applied.

The roadmap is a decision-making tool for planning and monitoring progress on SSC performance along five possible levels of progress. While identifying the assessment mechanisms implemented for different kind of sustainability practices, companies can develop a strategy according to their aims and capabilities and stakeholder's expectations.

The novelties in this study are threefold. First, the roadmap with five levels of progress. Second, investigating two different food supply chains that allowed for a broader view regarding sustainability practices and assessment. Third, the adoption of stakeholder and contingency theories in SSC studies.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

The purpose of this study is to examine the trend toward purchasing locally grown food and evaluate if tourists visiting Hawai'i are willing to pay more for locally produced foods that are more ecologically sustainable.

A research questionnaire was developed in order to investigate the attitudes and behaviors of tourists from the continental United States visiting Hawai'i in purchasing locally grown food in Hawai'i. The final sample includes 454 valid survey responses collected via Momentive, a market research services company.

According to the findings of this study, there are economic prospects to expand the use of locally cultivated food into the tourists' experience, as well as a willingness for tourists to support these activities financially. The Contingent Valuation study revealed that tourists from the continental United States were ready to pay a higher price to purchase food that is locally grown, signifying that tourists to Hawai'i are willing to aid the local agriculture business by increasing their restaurant/hotel meal bill, which will help Hawai'i become a more sustainable tourist destination.

While tourists from the United States mainland, which is the “an islands” top tourist market, have agreed with paying extra or an additional fee for locally grown food products, this study might not accurately represent the attitudes and behaviors of international tourists visiting Hawai'i. Future research should focus on the international tourist markets which may have different social norms or cultural differences thus could provide a broader spectrum of the current study's findings.

The results of this study provided quantitative evidence that tourists from the United States are interested in purchasing locally grown food items in Hawaii in addition to their willingness to pay an additional fee for these locally grown food products at a restaurant or a hotel dining room, thus addressing a gap in the tourism research.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.