Search Results (226)

This paper proposes an innovative, intelligent shopping cart system with an interdisciplinary approach using Bluetooth low energy (BLE) beacons. The research integrates online and offline retail strategies by presenting campaigns and ads to the customers during in-store navigation. In a testing environment, BLE beacons are strategically positioned to monitor the purchasing process and deliver relevant insights to retailers. The technology anonymously logs customers’ locations and the duration of their browsing at each sales shelf. Through the analysis of client movement heatmaps, retailers may discern high-traffic zones and modify product placement to enhance visibility and sales. Additionally, the system provides an additional revenue model for store owners through location specific targeted ads displayed on a tablet mounted on the cart. Unlike previous BLE-based tracking solutions, this research bridges the gap between customer movement analytics and real-time targeted advertising in retail settings. The system achieved an accuracy of 82.4% when the aisle partition length was 3.00 m and 91.7% when the aisle partition length was 6.00 m. This system, which can generate additional income for store owners by generating 0.171 USD in a single test simulation as a result of displaying ads to three test customers in a two-partitioned aisle layout, offers a new and scalable business model for modern retailers. Full article

The chilled ready meal market in New Zealand has witnessed substantial growth, fuelled by the increasing demand for convenient food options. This study integrates the theory of consumption value (TCV) with the theory of planned behaviour (TPB) to explore how lifestyle, consumer knowledge, sensory properties, subjective norms, consumer choice behaviour, consumption habits, and perceived behavioural control influence the purchase intention of meat-based chilled ready meals. Partial least squares path modelling (PLSPM) was used to verify the conceptual model using data from an online survey of 464 meat-based ready meal consumers from New Zealand. The results revealed that consumer attitudes towards meat-based chilled ready meals were positively influenced by lifestyle, consumer knowledge, and sensory properties, but these attitudes negatively impacted purchase intention, emphasising the complexity of consumer decision-making. Subjective norms, particularly social influences, significantly shaped consumers’ intentions. Furthermore, consumer choice behaviour, including conditional value, epistemic value, and emotional value, significantly influenced purchase intentions, with consumption habits emerging as the strongest predictor. Price had the highest influence on perceived behavioural control, while packaging information had little direct effect on perceived behavioural control. The findings of this study provide actionable insights for businesses to tailor marketing strategies and enhance consumer acceptance by improving product quality and sensory appeal of meat-based chilled ready meals in New Zealand. Full article

During the COVID-19 pandemic, the tourism sector encountered multiple challenges. Numerous governments chose to lock down their cities and countries. Despite this, many companies found their online businesses making the greatest leaps in their portfolios, and social media platforms became one of the most valuable sources of information for purchase decisions. There have been numerous studies on the effects of social media reviews—a form of electronic word-of-mouth (eWOM)—on consumer behavior. Few were found to be related to their impact on group package tours (GPTs) while considering mixed eWOM, that is, both the positive and negative forms present in word-of-mouth communication. As the tourism sector gradually revives, the need to further explore how tourism and hospitality service providers can adapt to changes in post-pandemic consumer behavior has become imperative. The influence of social media reviews on consumers’ value perceptions of a GPT to Japan, allowing for the influence of the marketing mix element of advertised price, was examined through online experiments in this study. Positive, negative, and mixed eWOM were examined. It was found that eWOM was more influential on consumers’ value perceptions than the advertised price for all price acceptability levels. Mixed eWOM was found to negatively affect consumers’ final price perceptions which override the impact of quality perceptions in value formations. The value perceptions of the GPT became less acceptable when eWOM was mixed compared to when eWOM was absent or was positive. Mixed eWOM had a negative effect on value perceptions but not as great as when negative eWOM was present, and this was consistently found to apply for all price acceptability levels of the GPT. This study’s contribution to eWOM research and implications for the post-pandemic recovery of tourism and hospitality service providers are made, together with suggested strategies using innovative technologies and communications to enhance their adaptive resilience in the new normal. Full article

Road freight e-commerce platforms, as a specialized form of e-commerce in the road transportation sector, face complex operational risks due to their unique service positioning and business models. This study employs a comprehensive methodology to examine the risk framework of these platforms. Through the development of three distinct questionnaires, 20 critical risk factors are identified, which were subsequently analyzed using a combination of Decision-making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) approaches. Furthermore, a systematic risk assessment is conducted by integrating the Analytic Hierarchy Process (AHP) with Fuzzy Comprehensive Evaluation (FCE) methods. The research reveals that the 20 core risk factors affecting road freight e-commerce platforms exhibit a systematic and hierarchical structure, with clearly defined transmission pathways between different levels of risk factors. This investigation uncovers the internal interaction mechanisms among these risk factors. The study demonstrates that a thorough consideration of risk factor mechanisms, coupled with a systematic risk assessment, can significantly enhance the effectiveness and precision of risk control strategy formulation. This methodological approach not only provides a robust framework for understanding the complex risk landscape of online freight platforms but also offers practical insights for developing targeted risk mitigation strategies in this evolving sector. Full article

Digital transformation (DT) has become an important engine for the development of the digital economy and an important means of reshaping corporate culture, business processes, management models, and so on. Different social communities at different levels have different needs and understandings of digital transformation. Therefore, this paper proposes to explore the communication themes of digital transformation on social media. This study’s main objective is to uncover underlying thematic structures and core ideas from large amounts of textual data in different social media communities to better understand the significance of the communication themes. This paper also aims to reveal the characteristics of diffusion patterns of DT themes by opinion-themed mining. This study uses text mining and social network analysis methods to mine DT themes, theme structure, and the statistical characteristics of hot words across various online communities. The main findings of this study are as follows. The Huawei forum discusses the technological drivers of the digital economy from a micro level. Sohu News explores business operation strategies at a macro level. The Zhihu forum discusses the elements of digital development at the micro level. Moreover, the hot words’ degree centrality and betweenness centrality across various online communities exhibited a power law distribution. In conclusion, this research paper studies and analyzes DT themes of different social media platforms to discover the opinions and attitudes of various social groups in the digital transformation era and deeply interprets social trends and public opinions in order to provide valuable decision-making theoretical support for managers, enterprises, and governments. Full article

Adaptive reuse of vacant houses in Japan offers an innovative and sustainable solution to the increase in vacant houses. This approach aligns with principles of sustainable architecture and the circular economy by reducing waste, lowering energy consumption, and extending the lifecycle of existing structures. This study uses purposive sampling, analyzing 262 adaptive reuse cases across Japanese prefectures through partial surveys, municipal records, and online maps. K-prototype clustering identified three distinct patterns. Cluster 1 emphasizes modern businesses, such as food, beverage, and accommodation services, within urban areas to address the needs of densely populated regions and tourist hubs. Cluster 2 blends urban and rural contexts, balancing historical preservation with modern functionality. Cluster 3 highlights rural and scenic accommodations that cater to tourists seeking cultural immersion and authentic experiences, despite challenges like low population density and limited accessibility. These findings contribute to the theoretical understanding of adaptive reuse as a key strategy for repurposing underutilized spaces, promoting both economic and social resilience. In practical terms, it demonstrates how adaptive reuse advances circular economy objectives by preserving cultural heritage, enhancing environmental sustainability, and creating economic opportunities. Further investigation is needed to unlock the unexplored potential of adaptive reuse in broader contexts and functions. Full article

Malware has emerged as a significant threat to end-users, businesses, and governments, resulting in financial losses of billions of dollars. Cybercriminals have found malware to be a lucrative business because of its evolving capabilities and ability to target diverse platforms such as PCs, mobile devices, IoT, and cloud platforms. While previous studies have explored single platform-based malware detection, no existing research has comprehensively reviewed malware detection across diverse platforms using machine learning (ML) techniques. With the rise of malware on PC or laptop devices, mobile devices and IoT systems are now being targeted, posing a significant threat to cloud environments. Therefore, a platform-based understanding of malware detection and defense mechanisms is essential for countering this evolving threat. To fill this gap and motivate further research, we present an extensive review of malware detection using ML techniques with respect to PCs, mobile devices, IoT, and cloud platforms. This paper begins with an overview of malware, including its definition, prominent types, analysis, and features. It presents a comprehensive review of machine learning-based malware detection from the recent literature, including journal articles, conference proceedings, and online resources published since 2017. This study also offers insights into the current challenges and outlines future directions for developing adaptable cross-platform malware detection techniques. This study is crucial for understanding the evolving threat landscape and for developing robust detection strategies. Full article

Food loss and waste is a recurring issue of discussion that food processing companies can no longer avoid. Society, stakeholders, and directives are demanding more and more communication on sustainability issues. However, only just under half of food processing companies stated that they provide consumer information on food waste. However, consumer information is only one way of communicating about food waste. The aim of this study is to identify key themes for relevant online communication on food waste that companies should be communicating to support the German National Strategy for the Reduction of Food Waste and to determine whether companies are already using these themes online. For this purpose, national strategy experts were asked through a questionnaire which topics were relevant according to the national strategy. The websites of 105 food processing companies were analyzed using content analysis to determine the status quo of food waste communication and assessed for relevance according to the national strategy. This paper presents five prioritized clusters of topics for relevant online communication on food waste for companies. The top priorities for communication, Cluster 1, are “Business Goals”, “Business Strategy”, “Process”, “Consumer Information”, “In-house Transparency”, and “Utilization of Remaining Materials”. The status quo shows that 43.8% of the companies provided online content regarding food waste. Through theory-driven content analysis, the three most common topics were identified in relation to food waste, namely the following: “Business Goals”, “Product and Packaging”, and “Consumer Information”. Companies communicated in line with the priority clusters. However, the frequency of topics and the way they are communicated varies widely. Only “Consumer Information” and “Business Goals” from Cluster 1 are commonly communicated. During the COVID-19 pandemic and the war in Ukraine, there was a decline in publications on food waste, and afterward, more consumer-oriented content was published rather than communicating the relevant topics. Companies are expected to have two objectives in their communication: to communicate with consumers and to be transparent about their targets, data, and utilization of food waste. The results also show differences between subsectors, the occurrence of the topics over time, and examples. The findings are aimed at policymakers, researchers, and companies as a starting point for improving the consistency and transparency of food waste communication in line with the national strategy. The results are also of international interest due to the common challenges of food waste and international food companies. Full article

The evolving capabilities of Geographic Information Systems (GISs) are transforming various industries, including e-commerce, by providing enhanced spatial analysis and precision in customer targeting, and improving the ability of recommender systems. This paper proposes a novel framework that integrates mobile agents with GISs to deliver real-time, personalized recommendations in e-commerce. By utilizing the OpenStreetMap API for geographic mapping and the Java Agent Development Environment (JADE) platform for mobile agents, the system leverages both geospatial data and customer preferences to offer highly relevant product suggestions based on location and behaviour. Mobile agents enable real-time data collection, processing, and interaction with customers, facilitating dynamic adaptations to their needs. The combination of GISs and mobile agents enhances the system’s ability to analyze spatial data, providing tailored recommendations that align with user preferences and geographic context. This integrated approach not only improves the online shopping experience but also introduces new opportunities for location-specific marketing strategies, boosting the effectiveness of targeted advertising. The validation of this system highlights its potential to significantly enhance customer engagement and satisfaction through context-aware recommendations. The integration of GISs and mobile agents lays a strong foundation for future advancements in personalized e-commerce solutions, offering a scalable model for businesses looking to optimize marketing efforts and customer experiences. Full article

This study examines the factors that lead students to consider or avoid a career in sales, focusing on behaviors and preferences during the transition period following the peak of the COVID-19 pandemic. Conducted in 2021, the study captures how the pandemic has changed traditional aspects of sales work, such as face-to-face interaction, and explores the lasting impact of these changes on young professionals. A sample of 671 business and engineering students participated in an online survey; data analysis was performed by using Partial Least Squares Structural Equation Modeling (SEM-PLS). Results show that intrinsic and social motivations enhance the perceived attractiveness of a sales career, which, in turn, impacts career intentions. Although empathy and COVID-19-related fears lack a direct effect on the intention to pursue a sales career, digital skills reinforce the connection between job attractiveness and career intentions in a digital-centric environment, having a moderating role. These findings emphasize the evolving nature of sales careers, highlighting the need to align career development strategies with young people’s intrinsic motivation and digital competencies. This study adds to the understanding of motivational factors in sales career decisions and offers valuable insights for employers seeking to attract motivated talent in a shifting industry landscape. Full article

Adopting advanced e-commerce practices is essential for enhancing user engagement and business performance, particularly in tourism. This study evaluates the e-commerce adoption of Kazakhstan’s tourism websites using an innovative Integrated Multi-Criteria Decision Analysis (IMCDA) methodology. Traditional evaluation methods overlook the interplay between website functionality, user experience, and strategic objectives. To address this gap, the IMCDA framework integrates qualitative and quantitative approaches by combining advanced Multi-Criteria Decision-Making (MCDM) techniques, including SPOTIS, ESP-COMET, RANCOM, and SITW, with content analysis and logistic regression. The study assessed 77 tourism websites, categorized into Online Travel Agencies (OTAs), Official Tourism Websites (OTWs), and Attraction Websites (AWs), based on 34 e-commerce features grouped into dimensions such as product information, functionality, reservations, payment systems, and customer relationship management (CRM). The findings reveal that OTAs significantly outperform OTWs and AWs in most dimensions, especially in online booking and CRM functionalities. At the same time, AWs lag in key e-commerce features like reservations and payment systems. This research highlights critical gaps in Kazakhstan’s tourism e-commerce ecosystem. It provides actionable recommendations, including enhancing CRM tools, integrating advanced booking systems, and leveraging collaborations with local financial technology providers like Kaspi Pay. The IMCDA framework offers a robust, adaptable evaluation model with practical implications for digital transformation and competitiveness in the tourism industry. This study contributes to advancing digital maturity in Kazakhstan’s tourism sector by addressing these gaps. It sets the foundation for future research to explore innovative strategies in e-commerce adoption across various regions and industries. Full article

The hospitality business model has undergone profound changes influenced by successive waves of technological advances and platforms. This paper explores how different waves of technologies and platforms are shaping the evolution of the hospitality business model. Employing a systematic literature review, this research analyzes how platform innovation has driven significant shifts in the industry. The analysis yielded four key findings. Firstly, the incorporation of digital technologies resulted in a radical transformation of conventional business models, prompting substantial alterations in marketing strategies, distribution processes, and consumer behavior patterns. Secondly, the industry has undergone five significant technological revolutions, evolving from steam-powered transportation to the integration of artificial intelligence (AI) and the Internet of Things (IoT), thereby driving a shift towards innovation-centric business models. Thirdly, the advent of digital platforms, most notably online travel agencies (OTAs), posed a challenge to traditional hospitality models by introducing personalized experiences and disrupting established market norms. While digital platforms offer advantages such as enhanced convenience and customization, they also present challenges, including intensified competition and declining profit margins. Nonetheless, technological advancements such as AI, virtual reality (VR), and augmented reality (AR) present a potential avenue for redefining value propositions and enhancing customer experiences. Fourth, the future of the hospitality business model is poised for further disruption, influenced by the emergence of new virtual platforms and services. This could potentially result in a reshaping of the industry’s value chain and value proposition. Full article

Businesses are leveraging digital technology through e-commerce platforms as a strategy to continue operating following the movement control order (MCO). Online shopping, a subset of e-commerce platforms, allows consumers to browse, select, and purchase products using digital interfaces. Unfortunately, there is a lack of understanding of how this platform can impact customer behavior. Therefore, this study aims to develop new knowledge of customer behavior and assess the relationship between consumer behavior and e-service quality in online shopping to better understand the e-service quality provided by the vendor in Malaysia. A novel model of e-service quality and consumer behavior has been developed and investigated. Survey questionnaires were distributed and tested using structural equation modeling (SEM) to 200 customers who had experienced online shopping during COVID-19. The finding revealed that website design, security/privacy, and fulfillment are statistically correlated with e-service quality. However, customer service is not significantly correlated with e-service quality. Meanwhile, the quality of e-services is statistically significantly related to customer behavior. This study shows that e-service quality can provide good customer behavior post-COVID-19. Online shopping is therefore predicted to boost the economy of the country, but consumers also want high-quality e-services to continue. Retailers can improve their storefronts, engage customers, and promote responsible consumption. Full article

With the rapid development of e-commerce, malicious accounts have become a threat, especially in the business field. Therefore, how to efficiently detect malicious accounts has become one an important issue requiring resolution. Present research on malicious detection mainly uses the basic statistics of the original data to build models, and ignores malicious activities in the business field. To address the context-independent nature of business activities and their lack of social structure, this study constructs an online model for detecting malicious accounts in the business field based on a stacking ensemble strategy with BiGRU-Conv1D-Capsule, XGBoost, and LightGBM as individual learners and AdaBoost as a meta-learner. Experimental results show that the stacking ensemble model constructed in this study has better predictive power than the typical shallow learning and baseline deep learning models. In addition to the basic feature, the behavior sequence of users is also applied in the proposed model. Overall, our experiments based on a real dataset from a financial platform show that the TPR, AUC, and F1 of the stacking ensemble model can reach 0.8258, 0.9860, and 0.8922 respectively, which outperforms all baseline models. Full article

This study focuses on the quality of beauty product reviews as online information, aiming to determine their impact on encouraging continued product purchases by users and to explore the simultaneous ripple effects. This study derived a total of 9 hypotheses, examining the relationship between online review information quality, product purchase, and influencers who create reviews, using the expectation confirmation model and the quality–value–satisfaction–loyalty mechanism. Simultaneously, this study sought to examine the process by which the formation of trust in influencers impacts the intention to purchase other products they recommend. The research results indicate that online review quality positively influences perceived value, satisfaction, and repurchase intention when the expectations for a product match reality. Furthermore, both the confirmation of online reviews and satisfaction with the product facilitate the transition from online to offline and back, which in turn generates ripple effects. The results of this study not only add clarity to the interrelationship between online and offline contexts but also provide implications for businesses in formulating strategies to leverage influencers for product sales. Full article