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Machine learning (ML) techniques are increasingly important in enabling business-to-business (B2B) companies to offer personalized services to business customers. On the other hand, humans play a critical role in dealing with uncertain situations and the relationship-building aspects of a B2B business. Most existing studies advocating human-ML augmentation simply posit the concept without providing a detailed view of augmentation. Therefore, the purpose of this paper is to investigate how human involvement can practically augment ML capabilities to develop a personalized information system (PIS) for business customers.

The authors developed a research framework to create an integrated human-ML PIS for business customers. The PIS was then implemented in the energy sector. Next, the accuracy of the PIS was evaluated using customer feedback. To this end, precision, recall and F1 evaluation metrics were used.

The computed figures of precision, recall and F1 (respectively, 0.73, 0.72 and 0.72) were all above 0.5; thus, the accuracy of the model was confirmed. Finally, the study presents the research model that illustrates how human involvement can augment ML capabilities in different stages of creating the PIS including the business/market understanding, data understanding, data collection and preparation, model creation and deployment and model evaluation phases.

This paper offers novel insight into the less-known phenomenon of human-ML augmentation for marketing purposes. Furthermore, the study contributes to the B2B personalization literature by elaborating on how human experts can augment ML computing power to create a PIS for business customers.

This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

The purpose of this study is to propose a research model based on the stimulus–organism–response (S–O–R) model to examine whether network externality, personalization and sociability as environmental feature antecedents to learners’ learning engagement (LE) can influence their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from learners who had experience in taking MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 371 usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that learners’ perceived network externality, personalization and sociability in MOOCs positively affected their cognitive LE, psychological LE and social LE elicited by MOOCs, which jointly led to their LP in MOOCs. The results support all proposed hypotheses, and the research model accounts for 76.2% of the variance in learners’ LP in MOOCs.

This study uses the S–O–R model as a theoretical base to construct learners’ LP in MOOCs as a series of the inner process, which is affected by network externality, personalization and sociability. It is worth noting that three psychological constructs including cognitive LE, psychological LE and social LE are used to represent learners’ organismic states of MOOCs usage. To date, hedonic/utilitarian concepts are more often adopted as organisms in previous studies using the S–O–R model, and psychological constructs have received lesser attention. Hence, this study’ contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners’ LP in MOOCs is well documented.

This paper aims to explore the intricate relationship between artificial intelligence (AI) and health information literacy (HIL), examining the rise of AI in health care, the intersection of AI and HIL and the imperative for promoting AI literacy and integrating it with HIL. By fostering collaboration, education and innovation, stakeholders can navigate the evolving health-care ecosystem with confidence and agency, ultimately improving health-care delivery and outcomes for all.

This paper adopts a conceptual approach to explore the intricate relationship between AI and HIL, aiming to provide guidance for health-care professionals navigating the evolving landscape of AI-driven health-care delivery. The methodology used in this paper involves a synthesis of existing literature, theoretical analysis and conceptual modeling to develop insights and recommendations regarding the integration of AI literacy with HIL.

Impact of AI on health-care delivery: The integration of AI technologies in health-care is reshaping the industry, offering unparalleled opportunities for improving patient care, optimizing clinical workflows and advancing medical research. Significance of HIL: HIL, encompassing the ability to access, understand and critically evaluate health information, is crucial in the context of AI-driven health-care delivery. It empowers health-care professionals, patients and the broader community to make informed decisions about their health and well-being. Intersection of AI and HIL: The convergence of AI and HIL represents a critical juncture, where technological innovation intersects with human cognition. AI technologies have the potential to revolutionize how health information is generated, disseminated and interpreted, necessitating a deeper understanding of their implications for HIL. Challenges and opportunities: While AI holds tremendous promise for enhancing health-care outcomes, it also introduces new challenges and complexities for individuals navigating the vast landscape of health information. Issues such as algorithmic bias, transparency and accountability pose ethical dilemmas that impact individuals’ ability to critically evaluate and interpret AI-generated health information. Recommendations for health-care professionals: Health-care professionals are encouraged to adopt strategies such as staying informed about developments in AI, continuous education and training in AI literacy, fostering interdisciplinary collaboration and advocating for policies that promote ethical AI practices.

To enhance AI literacy and integrate it with HIL, health-care professionals are encouraged to adopt several key strategies. First, staying abreast of developments in AI technologies and their applications in health care is essential. This entails actively engaging with conferences, workshops and publications focused on AI in health care and participating in professional networks dedicated to AI and health-care innovation. Second, continuous education and training are paramount for developing critical thinking skills and ethical awareness in evaluating AI-driven health information (Alowais et al., 2023). Health-care organizations should provide opportunities for ongoing professional development in AI literacy, including workshops, online courses and simulation exercises focused on AI applications in clinical practice and research.

This paper lies in its exploration of the intersection between AI and HIL, offering insights into the evolving health-care landscape. It innovatively synthesizes existing literature, proposes strategies for integrating AI literacy with HIL and provides guidance for health-care professionals to navigate the complexities of AI-driven health-care delivery. By addressing the transformative potential of AI while emphasizing the importance of promoting critical thinking skills and ethical awareness, this paper contributes to advancing understanding in the field and promoting informed decision-making in an increasingly digital health-care environment.

The proliferation of non-fungible token (NFT)-based crypto-art platforms has transformed how creators manage, own and earn money through the creation, assets and identity of their digital works. Despite this, no studies have examined the drivers of continuous content contribution behavior (CCCB) toward NFTs. Hence, this study draws on the theory of relational bonds to examine how various relational bonds affect feelings of psychological ownership, which, in turn, affects CCCB on metaverse platforms.

Using structural equation modeling and importance-performance matrix analysis, an online survey of 434 content creators from prominent NFT platforms empirically validated the research hypotheses.

Financial, structural, and social bonds positively affect psychological ownership, which in turn encourages CCCBs. The results of the importance-performance matrix analysis reveal that male content creators prioritized virtual reputation and social enhancement, whereas female content creators prioritized personalization and monetary gains.

We examine Web 3.0 and the NFT creators’ network that characterizes the governance practices of the metaverse. Consequently, the findings facilitate a better understanding of creator economy and meta-verse commerce.

The widespread integration of artificial intelligence (AI)-enabled personalization has sparked a need for a deeper understanding of its transformative potential. To address this, this study aims to investigate the mental models held by consumers from diverse cultures regarding the impact and role of AI-enabled personalization in their lives (i.e. individual well-being) and in society (i.e. societal well-being).

This paper uses the theories-in-use approach, collecting qualitative data via the critical incident technique. This data encompasses 487 narratives from 176 consumers in two culturally distinct countries, Belgium and Pakistan. Additionally, it includes insights from a focus group of six experts in the field.

This research reveals that consumers view AI-enabled personalization as a dual-edged sword: it may both extend and restrict the self and also contribute to an affluent society as well as an ailing society. The particular aspects of the extended/restricted self and the affluent/ailing society that emerge differ across respondents from different cultural contexts.

This cross-cultural research contributes to the personalization and well-being literature by providing detailed insight into the transformative potential of AI-enabled personalization while also having important managerial and policy implications.

Artificial intelligence (AI) is revolutionizing product recommendations, but little is known about consumer acceptance of AI recommendations. This study examines how to improve consumers' acceptance of AI recommendations from the perspective of product type (material vs experiential).

Four studies, including a field experiment and three online experiments, tested how consumers' preference for AI-based (vs human) recommendations differs between material and experiential product purchases.

Results show that people perceive AI recommendations as more competent than human recommendations for material products, whereas they believe human recommendations are more competent than AI recommendations for experiential products. Therefore, people are more (less) likely to choose AI recommendations when buying material (vs experiential) products. However, this effect is eliminated when is used as an assistant to rather than a replacement for a human recommendation.

This study is the first to focus on how products' material and experiential attributes influence people's attitudes toward AI recommendations. The authors also identify under what circumstances resistance to algorithmic advice is attenuated. These findings contribute to the research on the psychology of artificial intelligence and on human–technology interaction by investigating how experiential and material attributes influence preference for or resistance to AI recommenders.

This study aims to chart the impact of technological advancements on tourism from the post–Second World War era to the present and forecast their influence until 2050. It assesses how technologies have reshaped travel experiences and operations, with a focus on upcoming innovations such as the metaverse, Web 3.0 and AI, and their implications for sustainable and ethical tourism.

This study uses a hybrid approach, combining historical analysis and future projections. It analyzes archival data, industry reports and academic literature.

This study identifies crucial technological milestones that have significantly impacted tourism, including the rise of commercial aviation, the internet and AI. Future trends suggest emerging technologies will further transform the sector. Challenges in sustainability, ethics and inclusivity are highlighted as critical considerations for future development.

This paper offers a unique longitudinal perspective on technology’s influence on tourism, bridging past trends with future projections.

本研究采取混合方法, 融合历史分析与未来趋势预测。研究分析了丰富的档案数据、行业报告以及学术文献。

旨在勾勒从二战后至今技术进步对旅游业的影响, 并展望至2050年的潜在影响。本研究着重评估技术如何重塑旅游体验和运作, 特别是对元宇宙、网络3.0和人工智能等即将到来的创新技术及其对可持续和伦理旅游的意义。

识别了旅游业中关键的技术里程碑, 包括商业航空、互联网和人工智能的崛起。研究指出, 未来趋势显示新兴技术将继续深刻改变旅游业。同时强调, 可持续性、伦理和包容性是未来发展中不可忽视的关键要素。

本文从独特的纵向视角出发, 深入探讨了技术对旅游业的历史与未来影响, 将过去发展趋势与未来展望紧密结合。

Este estudio emplea un enfoque híbrido que combina el análisis histórico y las proyecciones de futuro. Analiza datos de archivo, informes del sector y bibliografía académica.

La investigación pretende trazar el impacto de los avances tecnológicos en el turismo desde la era posterior a la Segunda Guerra Mundial hasta la actualidad y prever su influencia hasta 2050. Evalúa cómo las tecnologías han reconfigurado las experiencias y las operaciones de viaje, centrándose en las próximas innovaciones como el Metaverso, la Web 3.0 y la IA, y sus implicaciones para un turismo sostenible y ético.

El estudio identifica hitos tecnológicos cruciales que han tenido un impacto significativo en el turismo, como el auge de la aviación comercial, Internet y la IA. Las tendencias futuras sugieren que las tecnologías emergentes transformarán aún más el sector. Los retos en sostenibilidad, ética e inclusividad se destacan como consideraciones críticas para el desarrollo futuro.

Este artículo ofrece una perspectiva longitudinal única sobre la influencia de la tecnología en el turismo, tendiendo un puente entre las tendencias pasadas y las proyecciones futuras.

This research aims to enhance the operational excellence and continuous improvement of the retail supply chain in the Saudi Thobe Factory through an integrated approach of Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) with artificial intelligence (AI).

The study identified the tailoring department as the department with maximum defects by using voice of customer and critical to quality tools. An AI-integrated Six Sigma approach was applied to identify and eliminate nonproductive stages, and a new facility layout was designed to enhance productivity and customer satisfaction.

The use of the factor rating method and simulation using Arena software led to an improved sigma level from 1.597 to 2.237, representing an increment of about 40%. Additionally, the defects per million opportunities reduced from 461,538 to 230,769. The study can help production industry management to optimize facility layouts and improve overall production line efficiency.

This study addresses the lack of published research on the use of an integrated approach of Six Sigma DMAIC with AI in the retail and distribution sector of Saudi Arabia, particularly for small and medium-sized enterprises (SMEs). The study demonstrates how this approach may significantly boost SMEs’ performance and provides a basis for future research in this area.

This study provides a practical example of how an integrated approach of Six Sigma DMAIC with AI can be used in the retail and distribution sector of Saudi Arabia to enhance operational excellence and continuous improvement. The study highlights the potential benefits of this approach for SMEs in the region and provides a framework for future research.

The purpose of this study is to review the application of semantic technologies in cultural heritage (STCH) to achieve interoperability and enable advanced applications like 3D modeling and augmented reality by enhancing the understanding and appreciation of CH. The study aims to identify the trends and patterns in using STCH and provide insights for scholars and policymakers on future research directions.

This research paper uses a bibliometric study to analyze the articles published in Scopus and Web of Science (WoS)-indexed journals from 1999 to 2022 on STCH. A total of 580 articles were analyzed using the Biblioshiny package in RStudio.

The study reveals a substantial increase in STCH publications since 2008, with Italy leading in contributions. Key research areas such as ontologies, semantic Web, linked data and digital humanities are extensively explored, highlighting their significance and characteristics within the STCH research domain.

This study only analyzed articles published in Scopus and WoS-indexed journals in the English language. Further research could include articles published in other languages and non-indexed journals.

This study extensively analyses the research published on STCH over the past 23 years, identifying the leading authors, institutions, countries and top research topics. The findings provide guidelines for future research direction and contribute to the literature on promoting, preserving and managing the CH globally.