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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。

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

The purpose of this paper is to propose a framework to distinguish between various types of antecedents and consequences of impulse buying. The authors tested it using a meta-analytical approach.

The authors examined 12 databases and analyzed 178 relationships in 100 articles. For the quantitative data analysis, the authors used the coefficient of correlation r as a metric to measure the effect size of the studied scope variables.

The findings of this meta-analysis demonstrated significant relation of antecedents and consequences of the impulse buying behavior, such as consumer impulsiveness (r = 0.464), materialistic consumption (r = 0.344), purchase pleasure (r = 0.270), hedonic value (r = 0.311), income (r = 0.703), gender (r = 0.150), age (r = −0.062), store atmosphere (r = 0.166), decision-making (r = 0.703) and positive emotions (r = 0.323).

This meta-analysis reviewed relationships found worldwide in the literature, expanding and improving the current knowledge. The meta-analysis identified ways that research on impulse buying is lacking and presented suggestions for the elaboration of new studies to allow future researchers to better define their agendas.

This meta-analysis brings important questions, such as impulse buying behavior is associated not only with consumer impulsiveness but also with materialistic consumption.

This research tested the impact of the antecedents and consequences of impulse buying and presented important results through this meta-analytical review. This meta-analysis contributes to the marketing literature, with a set of empirical generalizations, including relationship coefficients and calculated fail-safe numbers.

Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant attraction in both industry and academia, there is no systematic understanding of DT from its development history to its different concepts and applications in disparate disciplines. The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area. Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies. The review also provides a comprehensive survey of DT applications from two perspectives: (1) applications in four product-lifecycle phases, i.e. product design, manufacturing, operation and maintenance, and recycling and (2) applications in four categorized engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering and Internet of things (IoT) applications. DT frameworks, characteristic components, key technologies and specific applications are extracted for each DT category in this paper. A comprehensive survey of the DT references reveals the following findings: (1) The majority of existing DT models only involve one-way data transfer from physical entities to virtual models and (2) There is a lack of consideration of the environmental coupling, which results in the inaccurate representation of the virtual components in existing DT models. Thus, this paper highlights the role of environmental factor in DT enabling technologies and in categorized engineering applications. In addition, the review discusses the key challenges and provides future work for constructing DTs of complex engineering systems.