Search Results (107)

Japan’s 8.5 million vacant homes (Akiyas) represent a paradox of scarcity amid surplus: while rural depopulation leaves properties abandoned, housing shortages and bureaucratic inefficiencies hinder their reuse. This study proposes AKI2ALL, an AI-blockchain framework designed to automate the circular repurposing of Akiyas into ten high-value community assets—guesthouses, co-working spaces, pop-up retail and logistics hubs, urban farming hubs, disaster relief housing, parking lots, elderly daycare centers, exhibition spaces, places for food and beverages, and company offices—through smart contracts and data-driven workflows. By integrating circular economy principles with decentralized technology, AKI2ALL streamlines property transitions, tax validation, and administrative processes, reducing operational costs while preserving embodied carbon in existing structures. Municipalities list properties, owners select uses, and AI optimizes assignments based on real-time demand. This work bridges gaps in digital construction governance, proving that automating trust and accountability can transform systemic inefficiencies into opportunities for community-led, low-carbon regeneration, highlighting its potential as a scalable model for global vacant property reuse. Full article

With rising environmental awareness, numerous firms are transitioning to green investment, such as low-carbon production. However, the consumer adoption of low-carbon products remains low due to transparency concerns. Many firms are leveraging blockchain to address information asymmetry in the supply chain, thereby building consumer confidence in low-carbon products. The purpose of this work is to provide decision support for business firms by analyzing the strategic choices regarding the manufacturer’s green investment and the e-retailer’s adoption of blockchain technology. Three strategy combinations are considered, including the baseline strategy combination without green investment and blockchain technology (NN), the strategy combination with only green investment (LN), and the strategy combination with both green investment and blockchain technology (LB). The optimal pricing and green level decisions are derived, and the conditions under which green investment and blockchain technology are beneficial to the supply chain members are examined. The findings suggest that the e-retailer can obtain the highest profit without adopting blockchain technology if it holds a substantial or extremely low market share, if the consumers’ low-carbon preference is at a low to medium level, or if the consumer green trust coefficient is high when the manufacturer implements the green investment strategy. When consumers exhibit a weak preference for low-carbon products, the strategy combination NN is optimal for the supply chain members. The strategy combination LB becomes optimal if the consumer green trust coefficient is near or below the moderate threshold, if the market share of a channel is neither extremely high nor low, or if consumers exhibit a strong preference for low-carbon products. Full article

As environmental issues are of worldwide concern and consumers grow more concerned about the environment, green investments have emerged as a key factor in attracting consumers. To enhance consumer trust in enterprise investments in green and sustainable practices, blockchain technology, with its tamper-resistant and traceable characteristics, is being adopted by an increasing number of enterprises. However, the resulting spillover effect may lead to adverse consequences in a co-opetitive supply chain. This study examines a green supply chain comprising Brand O, a high brand value entity, and a contract manufacturer (CM) with lower brand value. The two parties collaborate through outsourced production while competing in the retail market. Three decision-making models were constructed, namely, without blockchain, Brand O adopting blockchain, and the CM adopting blockchain, and equilibrium solutions were derived to facilitate analysis. We find that Brand O tends not to introduce blockchain in order to avoid the loss of brand value and the spillover of consumer trust. The CM tends to introduce blockchain to enhance its products’ environmental impact and gain an exclusive competitive advantage, targeting the high-end market. These findings guide managers and practitioners in a co-opetitive green supply chain: high brand value retailers should cautiously evaluate blockchain’s impact, staying alert to risks hidden beneath benefits; upstream manufacturers can prioritize blockchain adoption for competitive advantage. Full article

In the digital age, consumer complaints have become significant indicators of operational vulnerabilities, with social media amplifying their impact. Mishandling such complaints has the potential to escalate minor issues into full-scale organizational crises, damaging brand reputation and eroding consumer trust. This study employs a case study approach to examine the Patiswiss Chocolate crisis, where a single consumer complaint led to widespread backlash, executive resignation, and boycotts. The crisis is analyzed through three key frameworks of analysis: communication, marketing, and ethics, offering a comprehensive understanding of its evolution. The findings reveal that defensive or dismissive responses exacerbate reputational damage, triggering the Streisand effect, where attempts to suppress criticism amplify its spread. Ethical concerns, including misleading corporate claims and governance issues, intensified consumer backlash. From a marketing perspective, brand trust declined as consumer activism influenced purchasing behavior and retailer decisions. This study emphasizes that organizations must adopt strategic, ethical, and consumer-centric approaches to crisis management to maintain long-term brand resilience. Full article

The Deposit-Return System for Recyclable Packaging (DRS) has recently been implemented in many countries to improve packaging waste management and support circular economy objectives. However, this mechanism has encountered many difficulties. The present study analyses the effectiveness of the DRS in the first 10 months of its operation in Romania, focusing on the spatial inequalities in recycling behaviour, the socioeconomic factors that influence the level of user participation, and user perceptions of waste management effectiveness. Combining cartographic analysis, socioeconomic indicators correlations, and media sentiment analysis, we discover key barriers to DRS implementation in rural areas, infrastructure limits, and public trust challenges. The results show a correlation between recycling rates and factors such as educational attainment, economic well-being, and urbanisation. The study also points out waste management inefficiencies related to poor infrastructure, costs to retailers, and operational difficulties of the recycling system. To enhance DRS performance, we suggest expanding the collection infrastructure in uncovered areas, providing dedicated financial assistance to retailers, and increasing transparency communication in waste processing outcomes. These findings contribute to discussions on optimising deposit-return schemes, reducing waste generation, and improving recycling efficiency in emerging circular economies. Full article

With the development of electronic retailing in C2C e-commerce platforms, the issue of trust loss from sellers has worsened. It is urgent for platform operators to learn how to retain quality sellers and improve their trust. Based on institutional trust theory, we combine formal institutions (structural assurance) and informal institutions (cultural factors), intending to examine the direct effects of masculinity, uncertainty avoidance, and long-term orientation on platform trust, the moderating effects of website quality, institutional guarantee and security systems, and the relationships among cultural factors. A total of 2970 valid responses were collected and analyzed from individual sellers on Taobao, which is one of the most representative C2C e-commerce platforms in China. The results reveal that uncertainty avoidance is negatively associated with platform trust, while masculinity and long-term orientation are positively associated with platform trust. Significant associations are also found among cultural factors. Website quality and institutional guarantee weaken the negative correlation between uncertainty avoidance and platform trust, while the security system strengthens it. Details of theoretical and managerial implications are discussed. Full article

This study aims to assess the influence of various factors on young customers’ intention to purchase renewable energy products by extending the Theory of Planned Behavior (TPB) model. Based on data collected from 690 respondents, the results of the SEM model analysis revealed that the intention to purchase renewable energy products is influenced by all three primary TPB constructs: attitude toward renewable energy products, perceived behavioral control, and subjective norm. Furthermore, knowledge of sustainable development goals significantly affects perceived behavioral control, attitude toward renewable energy products, and intention to purchase renewable energy products. Additionally, perceived government policies uncertainty emerged as a significant barrier to the intention to purchase renewable energy products. Conversely, trust in retailers has no impact on the purchasing intention. Notably, this study identifies the indirect effect of sustainable development goals (SDGs) knowledge on the intention to purchase renewable energy products through the mediating roles of attitude toward renewable energy products and perceived behavioral control. Based on these findings, this study makes both theoretical and practical contributions, proposing several implications for businesses and policymakers. Full article

In the rapidly evolving digital landscape, integrating blockchain technology into retail banking has emerged as a pivotal strategy for operational efficiency and competitive differentiation. This study employs the Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology to explore the relationships among the main factors shaping blockchain adoption, highlighting their direct and indirect effects on banks’ implementation efforts. The findings reveal that technology cost exerts the strongest causal influence on blockchain adoption, significantly affecting all other factors. Moreover, the interaction between technology cost and blockchain scalability is mediated by regulatory requirements, customer acceptance, and industry collaboration. Specifically, regulatory compliance obligations and associated uncertainties can magnify the cost barrier, while higher expenses may discourage customer engagement and limit large-scale adoption. Simultaneously, collaborations among banks and technology partners can alleviate cost burdens, thereby promoting more widespread implementation. These findings highlight the need for careful financial planning, strategic investment, and regulatory engagement to manage the high costs inherent in blockchain projects. Furthermore, banks should consider proactive customer education to convey the benefits of blockchain-driven innovations, thereby building trust and encouraging utilization. Full article

The different bargaining power of actors is a long-standing problem in the fruit and vegetable supply chain, where buyers (e.g., retailers, industry, and wholesalers) have more power than agricultural producers and are, therefore, able to engage in commercial practices that may be perceived as unfavorable or even unfair by the weaker part. This study explores how producers perceive the quality of commercial relations. The methods include a focus group discussion with sales managers of producer organizations and a survey of agricultural producers in Italy. We measure their willingness to change buyer and their stated overall satisfaction with the commercial relation by analyzing ninety-eight commercial relations and five dimensions of quality in the relationship. We identify four clusters of relationships characterized by different quality levels. The satisfaction and willingness to change buyers significantly differ across the clusters; economically favorable commercial relations are associated with a low willingness to change buyers, even when the producer is not satisfied with the overall quality of the relationship. The highest levels of satisfaction and the lower willingness to change buyers are reached for commercial relations that are not only economically favorable but also include positive relational aspects such as trust and mutual commitment. Full article

This study examines the interplay of consumer trust, return policies, and risk perception in shaping satisfaction with online shopping experiences in a business to consumer e-commerce context. Employing a conceptual model tested through Partial Least Squares-Structural Equation Modeling (PLS-SEM), it evaluates how these factors individually and collectively influence consumer satisfaction. The findings confirm that consumer trust reduces perceived risk and enhances shopping satisfaction. Contrary to expectations, attractiveness of free returns has no significant impact on either risk perception or satisfaction, while clear return policies positively influence satisfaction but not risk perception. Additionally, the study reveals a quadratic relationship between risk perception and satisfaction, suggesting that an optimal level of perceived risk maximizes satisfaction, deviating from prior research advocating for minimal perceived risk. These results offer new insights into consumer behavior in online retail, highlighting the nuanced role of risk and emphasizing the strategic importance of trust and return policies. The paper concludes by discussing managerial implications and suggesting directions for future research. Full article

Background: Food insecurity is a major global problem, with over 2.8 billion people reported as unable to afford a healthy diet in 2022. While charitable food assistance programs (CFAPs) play an important role in improving food access, ensuring the quality and safety of donated foods is crucial for safeguarding needy communities from food-related illnesses. This study evaluated the safety and quality of food donations at a food bank warehouse in the eThekwini District using a novel methodology. Methods: In March 2024, a five-day audit was conducted at a food bank warehouse in the eThekwini District, KwaZulu-Natal, South Africa. A mobile device was utilized to document comprehensive information on all incoming deliveries, including the type of food, product details (such as brand, name, and variety), donor information, weight, and date markings. The audit assessed 1037 items, totaling 64,818 kg of donated food, against established food safety standards. Each item was visually inspected upon arrival and classified as ‘unsuitable’, ‘potentially unsafe’, or ‘unsafe’ for human consumption. Results: Out of the 64,818 kg of donated food, 95.5% (61,886 kg) was deemed satisfactory. However, 4.5% of the total, which amounts to 2932 kg, was categorized as either unsafe (355 kg), potentially unsafe (1182 kg), or unsuitable (1395 kg) for consumption. Retail supermarkets donated the largest weight of food, and also of the food classified as unsafe or unsuitable. Conclusions: The study highlights an urgent need for improved quality control and safety measures in food donations to CFAPs. Stricter handling and inspection guidelines are essential to ensure the quality of charitable food, reduce health risks, and build public trust in donation programs. Full article

A recent study by the Food and Agriculture Organization (FAO) reveals that approximately 40% of India’s food production is wasted each year due to inefficient and fragmented supply chain management. An effective supply chain is essential to ensure the efficient use of resources and to maximize profitability. A platform is required to enhance communication, facilitate contract agreements, and streamline collaboration among stakeholders to reach their target destinations. In some cases, suppliers of raw materials often struggle to find buyers, which create gaps in the system. To address these issues, we have developed a unique methodology. We designed a platform that connects all stakeholders in the supply chain through a transparent, two-way communication channel, while ensuring high levels of authenticity and trust. Additionally, we created a comprehensive framework that includes profiles for farmers, retailers, manufacturers, and distributors. This application aims to bridge communication gaps and improve the overall efficiency of the system. To ensure the application’s integrity with the database, we conducted tests with various databases for optimal performance and authentication. During our evaluation, one of our observations on databases was that the Postgres database system utilized 48.3% of the total processing time and a latency of 10,941.3 milliseconds. At the same time, PgBouncer used 5.4% of the time consumed and required 1230.75 milliseconds before data processing started. Considering the authentication as a parameter, we also considered the Firebase (NoSQL) database for our application. It optimizes database operations to enhance the platform’s speed and efficiency, which has the potential for performance improvements in the supply chain management system. Full article

The rapid advancement and widespread adoption of artificial intelligence (AI) across diverse industries, including healthcare, finance, manufacturing, and retail, underscore the transformative potential of AI technologies. This necessitates the development of viable AI model marketplaces that facilitate the development, trading, and sharing of AI models across the pervasive industrial domains to harness and streamline their daily activities. These marketplaces act as centralized hubs, enabling stakeholders such as developers, data owners, brokers, and buyers to collaborate and exchange resources seamlessly. However, existing AI marketplaces often fail to address the demands of modern and next-generation application domains. Limitations in pricing models, standardization, and transparency hinder their efficiency, leading to a lack of scalability and user adoption. This paper aims to target researchers, industry professionals, and policymakers involved in AI development and deployment, providing actionable insights for designing robust, secure, and transparent AI marketplaces. By examining the evolving landscape of AI marketplaces, this paper identifies critical gaps in current practices, such as inadequate pricing schemes, insufficient standardization, and fragmented policy enforcement mechanisms. It further explores the AI model life-cycle, highlighting pricing, trading, tracking, security, and compliance challenges. This detailed analysis is intended for an audience with a foundational understanding of AI systems, marketplaces, and their operational ecosystems. The findings aim to inform stakeholders about the pressing need for innovation and customization in AI marketplaces while emphasizing the importance of balancing efficiency, security, and trust. This paper serves as a blueprint for the development of next-generation AI marketplaces that meet the demands of both current and future application domains, ensuring sustainable growth and widespread adoption. Full article

Resource Dependence Theory suggests that (a) power balance with resource interdependency, (b) formal/informal procedures for resource exchange, and (c) matching in goals and operational philosophies positively affect partnering implementation (information exchange and joint decision-making). Additionally, improved partnering implementation positive affects commitment fulfillment and dispute resolution. In a setting where SMEs supply to small local retailers, the SMEs do not suffer from low bargaining power and rely on informal contracts, and both firms are compatible. The small trading partners in this study predominantly have face-to-face and telephonic interactions with each other (possible due to the small number). Knowledge of one another and a simple transaction process reduces risk and uncertainty, and leads to trust. In this study, trust is a contextual factor, and we aim to determine if there is a positive effect of (a), (b), and (c) on partnering implementation, and if the effect strengthens with an increase in the level of trust. Survey data are used to calibrate and validate a structural equation model independently. Through empirical research, we aim to identify deviations in results, determine the cause of deviation in the study characteristics, and add explanatory power to research findings. Except for the influence of trust on the positive relationship between informal procedures and partnering implementation, the finding fits with the theoretical bases. With a high level of trust, clarity in time, accuracy, and relevance of information exchanged may be lacking, compromising decision-making and adding to the ambiguity of partnering implementation with an informal agreement. Full article

Artificial intelligence (AI) is fundamentally transforming the marketing landscape, enabling significant progress in customer engagement, personalization, and operational efficiency. The retail sector has been at the forefront of the AI revolution, adopting AI technologies extensively to transform consumer interactions, supply chain management, and business performance. Given its early adoption of AI, the retail industry serves as an essential case context for investigating the broader implications of AI for consumer behavior. Drawing on 404 articles published between 2000 and 2023, this study presents a comprehensive bibliometric and content analysis of AI applications in retail marketing. The analysis used VOSviewer (1.6.20.0 version) and Bibliometrix (version 4.3.1) to identify important contributors, top institutions, and key publication sources. Co-occurrence keyword and co-citation analyses were used to map intellectual networks and highlight emerging themes. Additionally, a focused content analysis of 50 recent articles was selected based on their relevance, timeliness, and citation influence. It revealed six primary research streams: (1) consumer behavior, (2) AI in retail marketing, (3) business performance, (4) sustainability, (5) supply chain management, and (6) trust. These streams were categorized through thematic relevance and theoretical significance, emphasizing AI’s impact on the retail sector. The contributions of this study are twofold. Theoretically, it integrates existing research on AI in retail marketing and outlines future research in areas such as AI’s role in the domain of consumer behavior. From an empirical standpoint, the study highlights how AI can be applied to enhance customer experiences and improve business operations. Full article