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This study aims to investigate the impact of consumer ethnocentrism on consumers' evaluation of blockchain-based traceability information. It also examined how the use of quick response (QR) codes for traceability affects consumers' evaluation of traceable food products.

An online choice experiment was conducted to determine consumers' evaluation of the blockchain-based traceability of Feta cheese with a quota sample of 715 Greek consumers. Pearson bivariate correlation and mean comparison were used to examine the relationship between consumer ethnocentrism and QR use behaviour. Random parameter logit models were employed to examine consumers’ valuation of the examined attributes and interaction terms.

The results show that ethnocentric consumers are willing to pay more for blockchain-based traceability information. Ethnocentric consumers tend to scan QR codes with traceability information. Spending more time reading traceability information embedded in QR codes does not lead to a higher willingness-to-pay (WTP) for traceable food products.

The findings suggest that patriotic marketing messages can draw consumers' attention to blockchain-based traceability information. The modest WTP for and low familiarity with blockchain-based traceability systems raise the need for educating consumers regarding the benefits of blockchain in traceability systems.

This is the first study to provide timely empirical evidence of a positive WTP for blockchain-based traceability information for a processed dairy product. This study is the first to attempt to distinguish the effects of the intention to scan QR codes and reading information embedded in QR codes on consumers’ valuation of food attributes.

This study aims to examine the factors influencing consumers’ intentions to use QR code menus in the post-COVID-19 pandemic using the unified theory of acceptance and use of technology and rational choice theory as the theoretical foundations.

Using a survey method, 200 data are collected from consumers who had used QR code menus in the past. Partial least squares structural equation modelling is used to analyse the data.

Our findings show that performance expectancy, effort expectancy, social influence, habit and perceived privacy protection have a significant positive influence on intentions. However, facilitating conditions, hedonic motivation and perceived privacy risk do not have a significant influence on intentions.

This study further extends the work of previous studies by using the unified theory of acceptance and use of technology model, with additional two new predictors, namely perceived privacy protection and perceived privacy risk, to understand consumers’ intentions to use QR code menus.

The purpose of this paper is to explore how the technology acceptance model (TAM) and structural equation modeling (SEM) might be used to assess customer acceptance of financial apps aiming at paving the road for enabling a cashless society in the Kingdom of Bahrain.

Using a convenience sample of 600 users of the BenefitPay app in the Kingdom of Bahrain, this study used the quantitative research approach to obtain 427 usable responses. Following a descriptive study to establish a framework for the data and a subsequent inferential analysis using SEM with confirmatory factor analysis, the research hypotheses were tested.

The results of this study back up what is claimed in the TAM theory literature, which shows that banking customers in the Kingdom of Bahrain who use e-payment methods are more likely to use BenefitPay if it is both easy to use and useful. BenefitPay systems behavioral intention to use was also highly influenced by aspects like ease of use and usefulness, which enable the development of cashless societies.

This research work contribution is described through exploring how a cashless society is developed using electronic apps by studying the case of the Kingdom of Bahrain. The Kingdom of Bahrain is unique, and hence the knowledge obtained from studying it cannot be applied mechanically to any other nation. Instead, the paper seeks to explain the motivations behind Bahrain’s move toward a cashless society, to analyze the difficulties and potential benefits of this transition and to spark much-needed conversations on how having less cash or none would affect the economies. Bahrain’s BenefitPay systems can be seen as a current pushing force toward cashless society; thus, understanding how people in the Kingdom of Bahrain adopt e-payment techniques is vital.

The TAM conceptual model is experimentally validated in this study using cutting-edge methods like SEM with value creation for banking sector management, making it stand out from similar research. This research may prove useful in laying the groundwork for a cashless society in the Kingdom of Bahrain by analyzing the key elements that affect the BenefitPay app.

The study aimed to investigate consumers’ views on criteria to be claimed for organic processed foods and information to be communicated.

An online survey was carried out among 439 adults living in Italy, users of processed organic food, to gather opinions on criteria that processing of organic food should meet and on the terms that best define “careful” processing. Next, a conjoint design was applied to examine the effects of five independent factors on consumers' ideal concept of “organic”; these were potential information on packaging, processing, additives and product quality, and the type of food product. Three products with different processing level were selected: an ultra-processed and multi-ingredient product (vegetable burger), a processed product preserved by canning (peas in glass jar) and a minimally processed product (bagged salad).

The findings highlight that consumers attach more importance to the organic food carrier than the informational messages. Information on the processing and packaging follows, with messages on quality and on additives seemingly of minor importance. Three clusters of respondents were identified: those driven primarily by the type of organic food (24.6%), those placing more emphasis on product processing (21.3%), and a third larger cluster (54.1%) who expressed almost equal importance to all the factors considered. As for the processing of organic products, “eco-friendly” was the best message.

This paper offers insights into what best outlines the ideal concept of “processed organic food” as seen by organic food consumers, to be communicated to better guide their purchasing decisions.

Know your customer (KYC), accounting standards, issuance, clearing, and trade settlement became the major barrier to implement accounting, accountability and assurance process in supply chain finance (SCF). Blockchain technology features have the potential to solve accounting problems. This research focuses on exploring how blockchain technology provides solutions to overcome the barriers of accounting process in SCF. The benefits, opportunities, costs and risks related to blockchain adoption are also explored.

Multi-case study and qualitative methods are used with a framework based on blockchain role to overcome the accounting process barriers. Ten blockchain projects in SCF and 29 interviews of participants as a unit of analysis are considered.

The findings indicate that blockchain technology offers solutions to solve accounting, accountability and assurance problems in SCF. Validity, verification, smart contracts, automation and enduring data on trade transactions potentially solve those barriers. However, it is also necessary to consider costs such as implementation, technology, education and integration costs. Then there are possible risks such as regulatory compliance, operational, code development and scalability risk. This finding reflects the current status of blockchain technology roles in SCF.

This study unveils blockchain's SCF accounting potential, emphasizing multi-case method limitations and future research prospects. Diverse contexts challenge findings' applicability, warranting cross-industry studies for deeper insights. Addressing selection bias and integrating quantitative measures can enhance understanding of blockchain's accounting impact.

Accounting professionals can get an idea of the future direction and impact of blockchain technology on accounting, accountability and assurance processes.

This study provides initial findings on the potential, costs and risks of blockchain that is beneficial for parties involved in SCF, especially for banks and insurance underwriters. In addition, the findings also provide direction for the contribution of blockchain technology to accounting theory in the future.

Amidst pressing environmental concerns, the service industry has increased its focus on sustainable production and consumption patterns. This study aims to explore whether Generation Z’s perceived value of plant-based food influences feelings of guilt as a result of consuming meat instead of plant-based food and/or pride from consuming plant-based foods, which might then lead to decisions to purchase alternative plant-based products at restaurants.

A survey was conducted measuring a range of variables and their relationships. The hypothesized model was tested using covariance-based structural equation modeling.

Results showed that perceived social value significantly influenced guilt and pride with perceived emotional value only influencing pride. Both guilt and pride significantly influenced the decision to switch eating patterns from conventional meat to plant-based protein at restaurants. And, finally, environmental concern significantly moderated the effect of emotional value on guilt.

To achieve sustainable goals, food producers should promote plant-based menu items by increasing the awareness of social approval through marketing communications.

This study bridges a gap in the literature by investigating how consumers’ perceived value affects their anticipated emotional feelings of guilt and pride leading to the switch from meat-based to plant-based diets at restaurants.

This study aims to investigate Generation Z’s perception of and experience with restaurant service robots.

Established on the servicescape theoretical framework and following Zaltman Metaphoric Elicitation Technique, 34 in-depth interviews were conducted with Generation Z consumers.

The results showed that Generation Z consumers had a generally positive attitude toward the usage of service robots in restaurants. Research participants also indicated aspects that can be improved: the service robot’s appearance design and functionality, and the human service facilitating the robotic service process.

This paper provides a holistic understanding of the Generation Z’s mind maps about robot service restaurants presenting practical suggestions for restaurants.

This research offers an in-depth understanding of how the young consumption power perceives and expects the innovative service robots employed in restaurants. The research findings provide industry practitioners with timely guidelines to improve the usage of robotic services in restaurants to satisfy the emerging consumer group of Generation Z.

The current research contributes to the servicescape literature by extending this long-standing theory to the emerging robotic service contexts for updating discoveries. Particularly, the study focuses on the young consumers of Generation Z, shedding lights on the generational cohort research.

本研究调查了 Z 世代对餐厅服务机器人的看法和体验。

建立在服务场景理论框架之上, 并遵循 Zaltman 隐喻启发技术, 对 Z 世代消费者进行了 34 次深入访谈。

结果表明, Z 世代消费者对在餐厅使用服务机器人持普遍积极态度。 研究参与者还指出了可以改进的方面：服务机器人的外观设计和功能, 以及促进机器人服务过程的人工服务。

这项研究深入了解了年轻的消费力量如何看待和期望在餐厅使用的创新服务机器人。 研究结果为行业从业者提供了及时的指导方针, 以改善机器人服务在餐厅的使用, 以满足 Z 世代的新兴消费群体。

当前的研究通过将这一长期存在的理论扩展到新兴的机器人服务环境以更新发现, 从而为服务景观文献做出贡献。 特别是, 该研究侧重于 Z 世代的年轻消费者, 阐明了世代队列研究。

The main aim of this study is to identify and prioritize the factors that influence the adoption of big data analytics (BDA) within the supply chain (SC) of the food industry in India.

The study is carried out in two distinct phases. In the first phase, barriers hindering BDA adoption in the Indian food industry are identified. Subsequently, the second phase rates/prioritizes these barriers using multicriteria methodologies such as the “analytical hierarchical process” (AHP) and the “fuzzy analytical hierarchical process” (FAHP). Fifteen barriers have been identified, collectively influencing the BDA adoption in the SC of the Indian food industry.

The findings suggest that the lack of data security, availability of skilled IT professionals, and uncertainty about return on investments (ROI) are the top three apprehensions of the consultants and managers regarding the BDA adoption in the Indian food industry SC.

This research has identified several reasons for the adoption of bigdata analytics in the supply chain management of foods in India. This study has also highlighted that big data analytics applications need specific skillsets, and there is a shortage of critical skills in this industry. Therefore, the technical skills of the employees need to be enhanced by their organizations. Also, utilizing similar services offered by other external agencies could help organizations potentially save time and resources for their in-house teams with a faster turnaround.

The present study will provide vital information to companies regarding roadblocks in BDA adoption in the Indian food industry SC and motivate academicians to explore this area further.

This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.

A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.

Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.

The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.