Search Results (324)

The aim of the study was to evaluate the digital business transformation across EU countries and its relationship with key Sustainable Development Goals (SDGs): SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action). The Digital Business Transformation Index, developed from eleven digital technology indicators related to e-business and e-commerce, is constructed using Principal Component Analysis to provide a comprehensive framework for assessing digitalization at the enterprise level. The results reveal substantial disparities among member states, with northern and western countries leading, while southern and eastern countries are lagging behind. Regression analyses show a strong positive relationship between digital business transformation and SDG 9 and a negative association with SDG 13. Cluster analysis identifies six groups of countries with varying levels of digital and sustainability performance and emphasizes the need for tailored policy responses. Evidence confirms a digital–green trade-off in many EU countries; however, strategic policy integration can mitigate this challenge. The findings underline the importance of targeted investments in R&D, digital infrastructure, and ICT training, particularly in underperforming regions. Tailored measures are essential to ensure that digital business transformation aligns with inclusive and sustainable development across the EU. Full article

The development of E-commerce and digitalization drives the rapid change in logistics management practices and poses challenges to traditional talent training modes in logistics field. Nowadays, companies expect university graduates equipped with more practical logistics skills to connect tighter with the industry. This motivates universities to establish more practically relevant curriculums to enhance students’ career competitiveness. Under such background, industry–university collaboration courses are increasingly adopted in higher education institutes in logistics discipline. Due to the difference between this type of course and the traditionally taught courses, the learning outcome of it can be difficult to guarantee. Therefore, it is necessary to identify the influential factors of the learning outcomes of industry–university collaboration courses and establish the actionable strategies to enhance course quality. However, the current literature in logistics management education has little focus on this topic, resulting in gaps on clarifying the influential factors of learning outcomes of industry–university collaboration courses in this discipline. Applying a mixed method, this study conducted a case study for an industry–university collaboration course of a logistics discipline in a Chinese university. The interval-valued Pythagorean fuzzy (IVPF) numbers and the Weighted Aggregated Sum Product Assessment (WASPAS) methods were used. The results showed that there are 15 factors which can influence the outcomes of industry–university collaboration courses in logistics discipline. Among them, the most important factor is the working environment, followed by the students’ own ability. Also, the results indicated that students’ optimistic attitudes towards the course, whether students take the course seriously, and course evaluations can be influential factors for good learning outcomes. The sensitivity analysis was then conducted, showing that the results were robust. This study can contribute to the existing literature by providing a theoretical framework to understand and assess the quality of industry–university collaboration courses in logistics and relevant subjects, as well as offering new analytical tools for management educational studies. Moreover, this study can provide practical implications for educators to develop and maintain good industry–university collaboration courses and trainings. Specifically, a practical life-cycle view was suggested to put pertinent efforts in all periods before/during/after the course to achieve high course outcomes. Full article

As the Metaverse continues to evolve as a transformative digital ecosystem, its environmental implications remain insufficiently examined within academic discourse. Despite growing interest in its technological and societal impacts, there is a lack of comprehensive evaluations that synthesize existing knowledge on its sustainability potential. This interdisciplinary narrative review addresses this gap by critically exploring how Metaverse technologies intersect with environmental sustainability across key sectors, including education, healthcare, tourism, e-commerce, manufacturing, and urban development. Employing a narrative review methodology informed by a systematic selection of scholarly and industry sources, the study consolidates current practices, emerging opportunities, and notable trade-offs. While the Metaverse presents promising avenues for reducing material consumption, optimizing urban planning through digital twins, and lowering emissions via virtual alternatives to physical travel, it also raises pressing environmental concerns, particularly related to high energy consumption, short hardware lifespans, and the rebound effects of intensified digital engagement. The findings suggest that environmental sustainability within the Metaverse is not inherent to its virtual nature but hinges on deliberate design, regulatory foresight, and the broader energy systems it depends on. This review offers timely insights for policymakers, technology developers, and sustainability advocates seeking to align immersive digital innovation with ecological responsibility and long-term planetary health. Full article

With the rapid development of e-commerce, ensuring product quality on online platforms has become increasingly important, especially in developing countries where market regulations are still underdeveloped. By treating different sellers offering the same brand’s products as an industry, this study examines the impact of flagship store entry on online product quality by constructing a multiple period difference-in-difference model and conducts detailed empirical tests using full-category and large-span data from Taobao. The empirical results demonstrate that flagship store entry not only prompts the exit of incumbent sellers and deters potential new entrants due to the competition effect, but also facilitates the exit of low-quality sellers while attracting high-quality sellers as a result of a consumer-learning effect. Consequently, the overall quality of the industry is improved, and this effect is more pronounced in high-priced and durable goods industries. The findings of this study have important implications for market structure design and online quality governance in online marketplaces. Full article

The rapid growth of live e-commerce, a sector valued at over USD 100 billion worldwide, demonstrates its transformative impact on the retail industry, especially in markets like China, where platforms such as Taobao Live and TikTok Shop have markedly altered consumer interaction. This transition is further expedited by Netflix-like entertainment marketing methods, which have demonstrated the capacity to enhance consumer retention by as much as 40%. As organizations adjust to this evolving landscape, it is essential to optimize supply chain strategies to align with these dynamic, consumer-centric environments. This paper examines the complexity of decision-making in live e-commerce supply chains, specifically regarding Netflix-inspired marketing strategies. The primary aim of this study is to design a game-theoretic framework that examines the interactions between producers and online celebrity retailers (OCRs) across different power dynamics. As live commerce integrates digital retail with immersive experiences, businesses must optimize pricing, quality, and marketing strategies in real-time. We present engagement-driven marketing as a strategic variable and incorporate consumer regret and switching costs into the demand function. To illustrate practical trade-offs in strategy, we incorporate a multi-criteria decision-making (MCDM) layer with AHP-TOPSIS, assessing profit, consumer surplus, engagement score, and channel efficiency. The experiment results indicate that Netflix-style marketing markedly increases demand and profit in retailer-led frameworks, whereas centralized tactics enhance overall channel performance. TOPSIS analysis prioritizes high-effort, high-engagement methods, whereas the Stackelberg experiment underscores the influence of power dynamics on profit distribution. This study presents an innovative integrative decision-making methodology for enhancing live-streaming commerce tactics in data-driven and consumer-focused markets. Full article

The integration of artificial intelligence (AI), big data analytics, and blockchain technologies within the digital economy presents transformative opportunities for promoting low-carbon urban development. However, a systematic understanding of how these digital innovations influence urban carbon mitigation remains limited. This study addresses this gap by proposing two research questions (RQs): (1) What are the key success factors for artificial intelligence, big data, and blockchain in urban carbon emission reduction? (2) How do these technologies interact and support the transition to low-carbon cities? To answer these questions, the study employs a hybrid methodological framework combining the decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques. The data were collected through structured expert questionnaires, enabling the identification and hierarchical analysis of twelve critical success factors (CSFs). Grounded in sustainability transitions theory and institutional theory, the CSFs are categorized into three dimensions: (1) digital infrastructure and technological applications; (2) digital transformation of industry and economy; (3) sustainable urban governance. The results reveal that e-commerce and sustainable logistics, the adoption of the circular economy, and cross-sector collaboration are the most influential drivers of digital-enabled decarbonization, while foundational elements such as smart energy systems and digital infrastructure act as key enablers. The DEMATEL-ISM approach facilitates a system-level understanding of the causal relationships and strategic priorities among the CSFs, offering actionable insights for urban planners, policymakers, and stakeholders committed to sustainable digital transformation and carbon neutrality. Full article

In today’s competitive environment of online service industries, particularly e-commerce, meeting consumer expectations is essential for service providers to ensure service quality. However, service failures are unavoidable, leading to unfavorable consequences for businesses. Understanding the mechanisms for customer recovery after negative service experiences is crucial. Using cognitive–emotional personality systems theory and benign violation theory, this study constructed a theoretical model. A total of 351 samples were collected through a situational simulation experiment for a linear regression analysis. A self-mocking response strategy positively influenced brand trust through perceived brand authenticity regarding the dimensions of credibility, integrity, and symbolism. Simultaneously, brand trust was identified as a key driver of post-recovery satisfaction. This study proposes a chain mediation model, which incorporates perceived authenticity and brand trust, to fully comprehend the mechanisms underlying consumers’ satisfaction after service recovery. Our findings provide empirical evidence for the effects of self-mockery on post-recovery satisfaction, as well as suggestions for marketers seeking efficient means to meet consumers’ emotional and cognitive demands during service recovery situations. Full article

In response to the challenges of urbanization, digitalization, and the e-commerce surge intensified by the COVID-19 pandemic, Smart Urban Logistics (SUL) has become a key framework for addressing last-mile delivery issues, congestion, and environmental impacts. This study introduces a System Dynamics (SD)-based approach to investigate how urban logistics and access management policies may interact. At the center, there is a Causal Loop Diagram (CLD) that illustrates dynamic interdependencies among fleet composition, access regulations, logistics productivity, and environmental externalities. The CLD is a conceptual basis for future stock-and-flow simulations to support data-driven decision-making. The approach highlights the importance of route optimization, dynamic access control, and smart parking management systems as strategic tools, increasingly enabled by Industry 4.0 technologies, such as IoT, big data analytics, AI, and cyber-physical systems, which support real-time monitoring and adaptive planning. In alignment with the Industry 5.0 paradigm, this technological integration is paired with social and environmental sustainability goals. The study also emphasizes public–private collaboration in designing access policies and promoting alternative fuel vehicle adoption, supported by specific incentives. These coordinated efforts contribute to achieving the objectives of the 2030 Agenda, fostering a cleaner, more efficient, and inclusive urban logistics ecosystem. Full article

Agroecology has traditionally been implemented using conventional methods. However, the integration of precision equipment, advanced methodologies, and digital technologies (DT) is now essential for transitioning to a more modern and efficient approach. While agroecological principles remain fundamental for planning and managing sustainable food systems by optimizing natural resources, technological tools can significantly support their implementation and adoption by farmers. This transition, however, must also consider socioeconomic factors and policy frameworks to ensure that technological advancements lead to meaningful improvements in farms and agroecosystems. Across both industrialized and emerging economies, various initiatives, such as precision agriculture, digital platforms, and e-commerce, are driving the digitalization of agroecology. These innovations offer clear benefits, including enhanced knowledge generation and direct improvements to the food supply chain; however, several barriers remain, including limited understanding of digital tools, high-energy demands, insufficient financial resources, economical constrains, weak policy support, lack of infrastructure, low digital learning by framers, etc. to facilitate the transition. This review looks for the understanding of how digitalization can align or conflict with local agroecological dynamics across distinct political frameworks and reality contexts because the information about DT adoption in agroecological practices is limited and it remains unclear if digital agriculture for scaling agroecology can considerably change power dynamics within the productive systems in regions of Europe and Latin America. In South America, among countries like Ecuador, with strong potential for agroecological development, where 60% of farms are less than 1 ha, and where farmers have expressed interest in agroecological practices, 80% have reported lacking sufficient information to make the transition to digitalization, making slow the adoption progress of these DT. While agroecology is gaining global recognition, its modernization through DT requires further research in technical, social, economic, cultural, and political dimensions to more guide the adoption of DT in agroecology with more certainty. Full article

Amid the rapid growth of social media and live streaming platforms, streamers, who serve as a crucial link between products and users, have garnered significant attention from both academia and industry. This study explores the impact of the streamer’s social capital (S) on user stickiness (R), as well as the mediating roles of perceived value and flow experience (O) in light of the Stimuli-Organism-Response (SOR) framework and social capital theory. A total of 322 valid samples were analyzed through Structural Equation Modeling (SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA). The results from the SEM indicate that the structural capital, cognitive capital, and relational capital of streamers in e-commerce live streaming significantly influence users’ perceived value, while structural capital and relational capital substantially impact users’ flow experience. Furthermore, both perceived value and flow experience are found to have a significant effect on user stickiness, with chained mediating effects observed between perceived value and flow experience. The fsQCA results further identify three configurational paths influencing user stickiness: the perceived value-oriented path, the flow experience-oriented path, and a hybrid path. This study offers valuable insights and practical implications for e-commerce merchants and companies involved in live streaming activities. Full article

In recent years, the rapid development of the agricultural product e-commerce and logistics industry has generated a large amount of express packaging waste. The way in which to promote the reuse of express packaging and reduce carbon emissions has become an important issue, and the current research on consumers’ willingness to express packaging recycling is still in its infancy. This study, based on the theory of Extended Planned Behavior, constructed a factor model observing the influence of consumers’ willingness to participate in the e-commerce of agricultural products’ recyclable packaging recovery. Using partial least squares structural equation modeling to process and analyze 659 questionnaire data, the results show that policy promotion and perceived benefits had the highest degree of positive influence on recycling willingness, and there was a relatively weak positive effect of packaging performance and subjective norm on consumers’ willingness to recycle in terms of packaging performance and the subject norm of recycling willingness. The attitude towards recycling had the smallest impact on the willingness to recycle. Therefore, in order to promote the production and use of recyclable packaging, government policies should be strengthened, and consumers’ perceived benefits and subjective norm should be improved, as well as the packaging performance of recyclable packaging. This study provides new insights into Chinese consumers’ participation in the recycling and promotion of recyclable packaging for e-commerce agricultural products. Full article

Interaction with mobile platforms changes users’ emotional and cognitive engagements through various stimuli cues that respond to behavioural intentions. Emerging technologies such as artificial intelligence (AI) and augmented reality (AR) foster more engagements and transform a new user–platform interaction paradigm in the e-commerce industry. This study signifies the effects of artificial intelligence and augmented reality in assessing user experience for mobile platforms. In this paper, we develop an interaction–engagement–intention model that considers users’ continuance intention based on perceived user experience. The proposed model uniquely explains a nuanced understanding of how the user–platform interactions evolve interactivity, product fit, artificial intelligence-driven recommendation, and online reviews in perceiving spatial presence and subjective norm. This paper explores the importance of attitude and trust as emotional states that influence the user’s behavioural responses. We validate the consequences of user–platform interactions toward continuance intention by conducting an online questionnaire survey and assessing user experience in augmented reality environments. The results contribute to adopting the co-created values of user–platform interactions through cognitive and emotional engagements that affect users’ continuance intention. The platform industry can apply the research outcomes by considering user experience and its implications to enhance the platforms’ capability with a broader aspect. Full article

With the rapid development of e-commerce and the logistics industry, the importance of logistics packaging defect detection as a key link in product quality control is becoming increasingly prominent. However, existing target detection models often face the problems of difficulty in improving detection accuracy and high model complexity when dealing with small-scale targets in logistics packaging. For this reason, an improved target detection model, DScanNet, is proposed in this paper. To address the problem that the model’s detailed feature extraction for small target defects is not sufficient and thus leads to low detection accuracy, the MEFE module, the local feature extraction module (LFEM Block), and the PCR module of the multi-scale convolution and feature enhancement strategy are proposed to enhance the model’s capability of capturing defective features and focusing on specific features, and to improve the detection accuracy. To address the problem of excessive model complexity, a Mamba module incorporating a channel attention mechanism is proposed to optimize the model via its linear complexity. Through experiments on its own dataset, BIGC-LP, DScanNet achieves a high accuracy of 96.8% on the defect detection task compared with the current mainstream detection algorithms, while the number of model parameters and the computational volume are effectively controlled. Full article

(1) Background: With the deep integration of e-commerce and video technology, live-streaming marketing has emerged globally and maintained rapid growth. However, most of the current research on live-streaming e-commerce marketing focuses on merchants’ sales strategies and consumers’ purchase intentions, and there is relatively little research related to the risks of live-streaming e-commerce marketing. Nevertheless, with the development of live-streaming e-commerce marketing and its integration with technologies such as artificial intelligence and virtual reality (VR), live-streaming e-commerce marketing still faces challenges such as unclear subject responsibility, difficulty in verifying the authenticity of marketing information, and uneven product quality. It also harbors problems such as the ethical misbehavior of AI anchors and the excessive beautification of products by VR technology. (2) Methods: This study systematically analyzes the scenarios of live-streaming marketing to elucidate the mechanisms of risk formation. Utilizing fault tree analysis (FTA) and risk checklist methods, risks are identified based on the three core elements of live-streaming marketing: “people–products–scenes”. Subsequently, the Delphi method is employed to refine the initial risk indicator system, resulting in the construction of a comprehensive risk indicator system comprising three first-level indicators, six second-level indicators, and 16 third-level indicators. A hesitant fuzzy multi-attribute group decision-making method (HFMGDM) is then applied to calculate the weights of the risk indicators and comprehensively assess the live-streaming marketing risks in live broadcast rooms of three prominent celebrity anchors in China. Furthermore, a detailed analysis is conducted on the risks associated with the six secondary indicators. Based on the risk evaluation results, targeted recommendations are proposed. This study aims to enhance consumers’ awareness of risk prevention when conducting live-streaming transactions and pay attention to related risks, thereby safeguarding consumer rights and fostering the healthy and sustainable development of the live-streaming marketing industry. (3) Conclusions: The results show that the top five risk indicators in terms of weight ranking are: Ethical Risk of the AI Anchor (A4), VR Technology Promotion Risk (F3), Anchor Reputation (A1), Product Quality (D1), and Logistics Distribution Service Quality (D2). The comprehensive live-streaming marketing risk of each live broadcast room is Y > L > D. Based on the analysis results, targeted recommendations are provided for anchors, MCN institutions, merchants, supply chains, and live-streaming platforms to improve consumer satisfaction and promote sustainable development of the live-streaming marketing industry. Full article

This study addresses the multi-robot task allocation (MRTA) problem for logistics robots operating in zone-picking warehouse environments. With the rapid growth of e-commerce and the Fourth Industrial Revolution, logistics robots are increasingly deployed to manage high-volume order fulfillment. However, efficiently assigning tasks to multiple robots is a complex and computationally intensive problem. To address this, we propose a five-step optimization framework that reduces computation time while maintaining practical applicability. The first step calculates and stores distances and paths between product locations using the A* algorithm, enabling reuse in subsequent computations. The second step performs hierarchical clustering of orders based on spatial similarity and capacity constraints to reduce the problem size. In the third step, the traveling salesman problem (TSP) is formulated to determine the optimal execution sequence within each cluster. The fourth step uses a mixed integer linear programming (MILP) model to allocate clusters to robots while minimizing the overall makespan. Finally, the fifth step incorporates battery constraints by optimizing the task sequence and partial charging schedule for each robot. Numerical experiments were conducted using up to 1000 orders and 100 robots, and the results confirmed that the proposed method is scalable and effective for large-scale scenarios. Full article