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This study aims to investigate how preservice teachers’ stages of concern, beliefs, confidence and interest in AI literacy education evolve as they deepen their understanding of AI concepts and AI literacy education.

AI literacy lessons were integrated into a technology integration course for preservice teachers, and the impacts of the lessons were evaluated through a mixed-methods study. The Concerns-Based Adoption Model was employed as the analytical framework to explore participants’ specific concerns related to AI.

Findings revealed that participants initially lacked AI knowledge and awareness. However, targeted AI literacy education enhanced preservice teachers’ awareness and confidence in teaching AI. While acknowledging AI’s educational benefits, participants expressed ongoing concerns after AI literacy lessons, such as fears of teacher displacement and the potential adverse effects of incorporating generative AI on students’ critical learning skills development.

Despite the importance of providing preservice teachers with AI literacy skills and knowledge, research in this domain remains scarce. This study fills this gap by enhancing the AI-related knowledge and skills of future educators, while also identifying their specific concerns regarding the integration of AI into their future classrooms. The findings of this study offer valuable insights and guidelines for teacher educators to incorporate AI literacy education into teacher training programs.

The adoption of artificial intelligence (AI) in frontline service encounters is a growing phenomenon in service marketing, which can lead to positive and negative results. In this context, this paper aims to review the literature on value cocreation and codestruction in AI-enabled service interactions.

A systematic literature review was carried out using the PRISMA protocol. Data were retrieved from the Web of Science and Scopus databases, from which 48 articles were selected for review. Data analysis, presentation of results and the research agenda followed the theory, context, characteristics and methodology (TCCM) framework.

The review especially revealed that: publications on AI-enabled value cocreation and codestruction are in the early stages of development; few articles have addressed value codestruction, and the main research emphasis is on value cocreation; interactions between human actors and AI-enabled autonomous nonhuman actors are resulting in value cocreation or value codestruction, or both, and these phenomena are also likely to occur when AI replaces more than one human actor in the service encounter; and AI is considered an increasingly independent nonhuman actor that integrates resources and interacts with other actors, yet prudence is necessary for its adoption.

This review fills a gap by jointly exploring the value cocreation and codestruction in the context of AI, presents an overview of the issues discussed and provides a research agenda with directions for future studies.

La adopción de la inteligencia artificial (IA) en los encuentros de servicio en primera línea es un fenómeno creciente en el marketing de servicios, que puede llevar a resultados positivos y negativos. En este contexto, el objetivo de este artículo es revisar la literatura sobre la cocreación y codestrucción de valor en las interacciones de servicio habilitadas por IA.

Se realizó una revisión sistemática de la literatura utilizando el protocolo PRISMA. Los datos se obtuvieron de las bases de datos Web of Science y Scopus, de las cuales se seleccionaron 48 artículos para su revisión. El análisis de los datos, la presentación de resultados y la agenda de investigación siguieron el marco de teoría, contexto, características y metodología (TCCM).

La revisión reveló especialmente que: (1) las publicaciones sobre la cocreación y codestrucción de valor habilitadas por IA están en las primeras etapas de desarrollo; (2) pocos artículos han abordado la codestrucción de valor, y el principal énfasis de la investigación está en la cocreación de valor; (3) las interacciones entre actores humanos y actores no humanos autónomos habilitados por IA están resultando en cocreación o codestrucción de valor, o ambas, y es probable que estos fenómenos también ocurran cuando la IA reemplaza a más de un actor humano en el encuentro de servicio; (4) la IA es considerada un actor no humano cada vez más independiente que integra recursos e interactúa con otros actores, pero se requiere prudencia en su adopción.

Esta revisión llena un vacío al explorar conjuntamente la cocreación y codestrucción de valor en el contexto de la IA, presenta una visión general de los temas discutidos y proporciona una agenda de investigación con direcciones para estudios futuros.

人工智能（AI）在前线服务接触中的应用已成为服务营销中的一个日益增长的现象, 这可能带来正面和负面的结果。在这一背景下, 本文旨在回顾关于人工智能驱动的服务互动中价值共创与共损的文献。

采用PRISMA协议进行了系统文献综述。数据从Web of Science和Scopus数据库中提取, 共选择48篇文章进行审阅。数据分析、结果呈现及研究议程遵循理论、背景、特征与方法论（TCCM）框架。

综述特别揭示了以下几点：(1) 关于AI驱动的价值共创与共毁的出版物尚处于发展初期; (2) 针对价值共损的文章较少, 主要研究重点集中在价值共创上; (3) 人类参与者与AI驱动的自主非人类参与者之间的互动, 可能导致价值共创或价值共损, 甚至同时发生, 特别是在AI替代多个服务接触中的人类参与者时; (4) AI被视为越来越独立的非人类参与者, 它整合资源并与其他参与者互动, 但在采用过程中需谨慎。

本综述填补了在AI背景下共同探讨价值共创与共损的空白, 概述了相关问题, 并提供了未来研究方向的议程。

This paper aims to explore the overall research question “How can artificial intelligence (AI) influence consumer information disclosure?”. It considers how anthropomorphism of AI, personalisation and privacy concerns influence consumers’ attitudes and encourage disclosure of their private information.

This research draws upon the personalisation-privacy paradox (PPP) and privacy calculus theory (PCT) to address the research question and examine how AI can influence consumer information disclosure. It is proposed that anthropomorphism of AI and personalisation positively influence consumer attitudes and intentions to disclose personal information to a digital assistant, while privacy concerns negatively affect attitude and information disclosure.

This paper develops a conceptual model based on and presents seven research propositions (RPs) for future research.

Building upon PPP and PCT, this paper presents a view on the benefits and drawbacks of AI from a consumer perspective. This paper contributes to literature by critically reflecting upon on the question how consumer information disclosure is influenced by AI. In addition, seven RPs and future research areas are outlined in relation to privacy and consumer information disclosure in relation to AI.

El papel del antropomorfismo, la personalización y los problemas de privacidad y perspectivas para la investigación futura

Resumen

Este artículo explora la pregunta general de investigación “¿Cómo puede influir la inteligencia artificial (IA) en la divulgación de información por parte de los consumidores? Se analiza cómo el antropomorfismo de la IA, la personalización y la preocupación por la privacidad influyen en la actitud de los consumidores y fomentan la revelación de su información privada.

Esta investigación se basa en la paradoja de la personalización y la privacidad y en la teoría del cálculo de la privacidad para abordar la pregunta de investigación y examinar cómo la IA puede influir en la revelación de información de los consumidores. Se propone que el antropomorfismo de la IA y la personalización influyen positivamente en las actitudes de los consumidores y en su intención de revelar información personal a un asistente digital, mientras que la preocupación por la privacidad afecta negativamente a la actitud y a la revelación de información.

Este artículo desarrolla un modelo conceptual basado en siete propuestas de investigación para el futuro.

Basándose en la paradoja de la personalización y la privacidad y en la teoría del cálculo de la privacidad, este artículo presenta un punto de vista sobre los beneficios e inconvenientes de la IA desde la perspectiva del consumidor. Este artículo contribuye a la literatura al reflexionar de forma crítica sobre la cuestión de cómo influye la IA en la revelación de información del consumidor. Además, se esbozan siete propuestas de investigación y futuras áreas de investigación en relación con la privacidad y la divulgación de información del consumidor en relación con la IA.

鼓励消费者分享他们的秘密？拟人化、个性化和隐私问题的作用以及未来研究的途径

摘要

本文探讨了 “人工智能如何影响消费者的信息披露？"这一总体研究问题。它考虑了人工智能（AI）的拟人化、个性化和隐私问题是如何影响消费者的态度并鼓励他们披露私人信息的。

本研究借鉴了个性化-隐私悖论和隐私计算理论来解决研究问题, 并研究人工智能如何影响消费者信息披露。本文提出, 人工智能的拟人化和个性化对消费者向数字助理披露个人信息的态度和意图有积极影响, 而隐私问题对态度和信息披露有消极影响。

本文在此基础上建立了一个概念模型, 并为未来的研究提出了七个研究命题。

在个性化-隐私悖论和隐私计算理论的基础上, 本文从消费者的角度提出了对人工智能的好处和坏处的看法。本文通过对消费者信息披露如何受到人工智能影响的问题进行批判性反思, 对文献做出了贡献。此外, 本文概述了与人工智能相关的隐私和消费者信息披露方面的七个研究命题和未来研究领域。

This paper aims to empirically examine the impact of psychological factors (i.e. privacy and intrusiveness concerns) on user intentions regarding artificial intelligence (AI)-enabled social commerce applications at their core through perceived usefulness. The theoretical model is supported by the theory of planned behaviour (TPB).

Data was gathered from 488 social media users in Saudi Arabia.

Privacy concerns significantly affect perceived usefulness. Furthermore, the link between privacy concerns and behavioural intentions was mediated by perceived usefulness.

Business leaders should raise users’ awareness about the effectiveness of AI-powered tools that can influence their behavioural intentions. Furthermore, managers must be aware of the regulations that protect user privacy, track online activity and offer secure communication channels.

This paper expands on TPB by bridging the theoretical and practical divide. It further develops a theoretical framework for practitioners to better understand customers’ physiological aspects of using AI-powered social commerce platforms.

Este artículo examina empíricamente el impacto de los factores psicológicos (es decir, preocupaciones de privacidad e intrusión) en las intenciones de los usuarios con respecto a las aplicaciones de comercio social habilitadas con inteligencia artificial (IA) en su núcleo a través de la utilidad percibida. El modelo teórico se sustenta en la teoría del comportamiento planificado (TPB).

Los datos se recopilaron de 488 usuarios de redes sociales en Arabia Saudita.

Las preocupaciones sobre la privacidad afectan significativamente la utilidad percibida. Además, el vínculo entre las preocupaciones por la privacidad y las intenciones de comportamiento estuvo mediado por la utilidad percibida.

Los líderes empresariales deberían concienciar a los usuarios sobre la eficacia de las herramientas impulsadas por la IA que pueden influir en sus intenciones de comportamiento. Además, los gerentes deben conocer las regulaciones que protegen la privacidad de los usuarios, rastrear la actividad en línea y ofrecer canales de comunicación seguros.

Este artículo amplía el TPB cerrando la brecha teórica y práctica. Además, desarrolla un marco teórico para que los profesionales comprendan mejor los aspectos fisiológicos de los clientes al utilizar plataformas de comercio social impulsadas por IA.

本文透過實證研究了心理因素 (即隱私和侵入性問題) 對人工智慧 (AI) 驅動的社交商務應用程式的使用者意圖的影響, 其核心是透過感知有用性。 此理論模型得到計劃行為理論 (TBP) 的支持。

資料收集自沙烏地阿拉伯的 488 名社群媒體用戶。

隱私問題顯著影響感知的用處。 此外, 隱私問題和行為意圖之間的連結是透過感知有用性來調節的。

企業領導者應該提高使用者對人工智慧工具有效性的認識, 這些工具可以影響他們的行為意圖。 此外, 管理人員必須了解保護用戶隱私、追蹤線上活動並提供安全通訊管道的法規。

本文透過彌合理論和實踐鴻溝，對 TPB 進行了擴展。 它進一步為從業者開發了一個理論框架，以便更好地了解使用人工智慧驅動的社交商務平台的客戶的生理方面。

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

The purpose of the study was to evaluate the impact of generative artificial intelligence (GenAI) on students' learning experiences and perceptions through a master’s-level course. The study specifically focused on student engagement, comfort with GenAI and ethical considerations.

The study used an action research methodology employing qualitative data collection methods, including pre- and post-course surveys, reflective assignments, class discussions and a questionnaire. The AI-Ideas, Connections, Extensions (ICE) Framework, combining the ICE Model and AI paradigms, is used to assess students' cognitive engagement with GenAI.

The study revealed that incorporating GenAI in a master’s-level instructional design course increased students' comfort with GenAI and their understanding of its ethical implications. The AI-ICE Framework demonstrated most students were at the initial engagement level, with growing awareness of GenAI’s limitations and ethical issues. Course reflections highlighted themes of improved teaching strategies, personal growth and the practical challenges of integrating GenAI responsibly.

The small sample size poses challenges to the analytical power of the findings, potentially limiting the breadth and applicability of conclusions. This constraint may affect the generalizability of the results, as the participants may not fully represent the broader population of interest. The researchers are mindful of these limitations and suggest caution in interpreting the findings, acknowledging that they may offer more exploratory insights than definitive conclusions. Future research endeavors should aim to recruit a larger cohort to validate and expand upon the initial observations, ensuring a more robust understanding.

The study is original in its integration of GenAI into a master's-level instructional design course, assessing both the practical and ethical implications of its use in education. By utilizing the AI-ICE Framework to evaluate students' cognitive engagement and employing action research methodology, the study provides insights into how GenAI influences learning experiences and perceptions. This approach bridges the gap between theoretical understanding and the real-world application of GenAI, offering actionable strategies for its responsible use in educational settings.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

This study aims to examine the trends and advancements in AI-supported language learning over the past decade. By analyzing 15 empirical research articles, the study seeks to fill the gap in understanding the effectiveness and challenges of AI-assisted language learning for both first- and second-language learners.

The research utilizes activity theory, which includes seven components: tool, subject, object, rules, community, division of labor and outcome. This theoretical framework helps to reveal the dynamic interactions and contradictions among these elements. The selection and screening process for relevant articles followed the PRISMA method, ensuring a systematic and comprehensive review.

The study found that AI-supported technology shows promise in enhancing language learning, particularly in areas such as writing quality, scoring accuracy and learner engagement. However, challenges remain in terms of dialogic competence and the necessity of teacher intervention in pedagogical design. While AI-supported systems can effectively aid in language acquisition, improvements are needed to foster language use for communication and collaborative design.

The review highlights the need for more empirical studies on the pedagogical impacts of AI-supported language learning and the engagement levels of both learners and teachers. It also underscores the importance of investigating the application of AI-assisted language learning in actual classroom environments.

The implications of this study offer significant insights for both educational practice and future research in AI-supported language learning. As AI technologies continue to evolve, their potential to enhance learning outcomes and support teachers’ efforts becomes increasingly apparent. However, effective implementation requires not only the availability of technological tools but also proper pedagogical integration and teacher intervention. Furthermore, AI presents unique opportunities to personalize learning and foster collaboration among learners, aligning with the growing trend of hybrid learning environments.

This paper addresses the need for a comprehensive review of AI’s role in language education, providing insights into emerging trends and identifying areas for future research. It emphasizes the importance of integrating AI tools with educational theories and the necessity of teacher configuration in enhancing AI-supported language learning.

The influence of technology on marketing communications is rising in both applications and value created. Artificial intelligence (AI) and, as a result, smart speakers are benefiting both brands and customers at many levels. In particular, AI opens up the possibility to establish human-like dialogs with customers and to advertise brands in a new and engaging way. Therefore, the purpose of this paper is to understand why and how consumers would accept receiving advertising (ad) via AI-enabled devices such as smart speakers.

A total of 326 individuals participated in a study that explored the factors influencing ad acceptance in smart devices. A partial least squares-structural equation model technique was used to validate the results.

The findings show that customer acceptance of ads via smart assistants is influenced by smart assistant usefulness and hedonic motivations. However, privacy risk moderates the relationship between smart speaker ease of use and smart speaker usefulness.

This paper explores the main drivers of ad acceptance via smart speakers and goes beyond the existing knowledge of smart speaker acceptance to further explore how this can become an important channel for brands to communicate.

La influencia de la tecnología en las comunicaciones de marketing está aumentando tanto en las aplicaciones desarrolladas como en el valor creado. La inteligencia artificial (IA) y, en consecuencia, los altavoces inteligentes están beneficiando tanto a las marcas como a los clientes a muchos niveles. En particular, la IA abre la posibilidad de establecer diálogos similares a los humanos con los clientes y de publicitar las marcas de una manera nueva y atractiva. Por lo tanto, es necesario entender por qué y cómo los consumidores aceptarían recibir publicidad (anuncios) a través de dispositivos con IA, como los altavoces inteligentes.

Un total de 326 personas participaron en un estudio que exploró los factores que influyen en la aceptación de la publicidad en los dispositivos inteligentes. Se utilizó una técnica PLS-SEM para validar los resultados.

Los resultados muestran que la aceptación de los anuncios a través de los asistentes inteligentes por parte de los clientes está influenciada por la utilidad del asistente inteligente y las motivaciones hedónicas. Sin embargo, el riesgo para la privacidad modera la relación entre la facilidad de uso del altavoz inteligente y su utilidad.

El artículo explora los principales impulsores de la aceptación de la publicidad a través de los altavoces inteligentes y va más allá del conocimiento existente sobre la aceptación de los altavoces inteligentes para explorar más a fondo cómo esto puede convertirse en un canal importante para que las marcas se comuniquen.

科技对营销传播的影响在应用和价值创造方面都在上升。人工智能（AI）以及智能音箱在很多层面都对品牌和客户有益。尤其是, 人工智能开辟了与客户建立类似人类对话的可能性, 并以一种新颖的、有吸引力的方式宣传品牌。因此, 了解消费者为什么以及如何接受通过人工智能设备（如智能音箱）接收广告（广告）是有必要的。

本研究的326名参与者探讨了影响智能设备中广告接受度的因素。PLS-SEM技术被采用以对结果进行验证。

研究结果显示, 客户通过智能助手接受广告会受智能助手有用性和享乐动机的影响。然而, 隐私风险调节了智能音箱的易用性和智能音箱的有用性之间的关系。

本文探讨了通过智能音箱接受广告的主要驱动因素, 并超越了现有的关于智能音箱接受度的知识, 进一步探讨了这如何能成为品牌沟通的重要渠道。