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This study investigates organizations' non-adoption intention towards the enterprise metaverse. The innovation resistance theory (IRT) is used as an underpinning theory to examine the impact of various risks on non-adoption intention towards the enterprise metaverse.

A total of 294 responses were collected to examine the proposed hypotheses. A structural equation modelling technique was used to investigate the hypotheses using SPSS AMOS and PROCESS MACRO.

The results of this study reveal that performance, security and psychological risks are significantly associated with non-adoption intention towards enterprise metaverse. Further, distrust significantly meditates the association between performance risk, social risk, technological dependence risk, security risk and psychological risk and non-adoption intention towards enterprise metaverse. Moreover, the results of moderated-mediation hypotheses indicate that the mediating effect of distrust on the association among performance risk, social risk, psychological risk and non-adoption intention towards enterprise metaverse is higher for individuals having high technostress compared to individuals having low technostress.

The study's findings will enrich the metaverse literature. Further, it provides a deeper understanding of enterprise metaverse adoption from a B2B perspective using the underpinnings of IRT. The study helps organizations understand the risks associated with the adoption of the enterprise metaverse.

Hempcrete has the potential to reduce both CO₂ emissions and energy usage in buildings. Hempcrete has a high sound absorption capacity, excellent moisture regulator and outstanding thermal insulation properties. However, hempcrete traditionally uses lime-based binders, which are carbon-intensive materials. The low-carbon binders to increase the sustainability of hempcrete are the current research gap. Geopolymer binders are low-carbon binders composed of aluminosilicate precursors dissolved in a high alkalinity solution. This study investigated the suitability of calcined clay and ground granulated blast furnace slag geopolymer binder as a low-carbon binder for hempcrete applications.

Two types of hemp hurds with different water absorption capacity and particle size distributions were used. Hempcrete properties tested were compressive strength, bulk density, sound absorption coefficient by a two-microphone impedance tube and thermal conductivity by a Hot Disk system.

The particle size distribution and water absorption capacity of hemp hurds did not affect the compressive strength of hempcrete when following a mixing procedure, ensuring the hurds in a saturated surface dry condition. The geopolymer hempcrete achieved a compressive strength about four times higher than the reference hydrated lime hempcrete. All hempcrete specimens achieved outstanding acoustic performance. The increase in bulk density led to the decrease in the maximum sound absorption coefficient. The geopolymer hempcrete achieved the lowest thermal conductivity.

The outcomes of this paper reveal that the low-carbon geopolymer binder appears to be a promising option for manufacturing hempcrete, achieving significantly higher compressive strength and lower thermal conductivity than the reference hydrated lime-based hempcrete.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

This study proposed an extended theory of planned behaviour (TPB), that is, considering that behavioural beliefs, normative beliefs and control beliefs (beliefs) will influence perceived service quality (PSQ) on food delivery services. PSQ (behavioural intention) will influence electronic word-of-mouth (EWOM) (behaviour). In addition, exogenous variables including information from online ratings and consumer groups will affect the strength of the relationship between received service quality and EWOM on food delivery service.

This study aimed to investigate the mediation (PSQ) and moderation (Online ratings and consumer groups) effects on the extended TPB for Taiwanese consumers (n = 823).

This study first found a positive relationship between different beliefs and PSQ (behavioural intention). In addition, there is a positive relationship between PSQ and EWOM. Online rating has a moderating effect between PSQ and EWOM. Consumer group has a moderating relationship between PSQ and EWOM.

This study first found that the three stages of beliefs-intention-behaviour for consumers on food delivery service are reciprocal with two paths, starting with offline-to-online in terms of generating the positive relationship between individual belies and PSQ. Next, it can generate positive power to return online with a behaviour of EWOM. In addition, online ratings can enhance and strengthen the positive effect between PSQ and EWOM.

Humanoid social robots (HSRs) are an innovative technology revitalizing various service sectors, such as the hospitality industry. However, limited research has explored how anthropomorphic features of HSRs influence user satisfaction with the services delivered by HSRs. To address this, a research model was proposed to evaluate how three distinct anthropomorphic features: appearance, voice and response, impact the perceived values (i.e. utilitarian, social and hedonic values) of HSRs, which, in turn, influence user satisfaction.

Data from an online survey of hotel customers was utilized to test the research model (N = 509).

The results indicated that appearance, voice, and response affect perceived utilitarian, hedonic and social values differently. The response feature of HSRs demonstrated the strongest impact on perceived utilitarian, social and hedonic values. In addition, voice affected all three perceived values, while appearance only affected perceived utilitarian and social values. Furthermore, perceived utilitarian, hedonic and social values showed positive impacts on user satisfaction, with hedonic value being the most influential factor.

This study contributes to the literature on HSRs and anthropomorphism by explaining how different anthropomorphic features affect users’ value perceptions and user satisfaction with HSR services by utilizing the stimulus-organism-response (SOR) framework.

Generative artificial intelligence (GAI) can disrupt how consumers search for information on retail products/services online by reducing information overload. However, the risk associated with GAI is high, and its widespread adoption for product/service information search purposes is uncertain. This study examined psychological drivers that impact consumer adoption of GAI platforms for retail information search.

We conducted 31 in-depth, semi-structured interviews with the lead GAI users regarding product/service information search. The data were analysed using a grounded theory paradigm and thematic analysis.

Results show that consumers experience uncertainty about GAI’s functioning. Their trust in GAI impacts the adoption and usage of this technology for information search. GAI provides unique settings to investigate potential additional factors, leveraging UTAUT as a theoretical basis. This study identified three overarching themes – technology characteristics, technology readiness and information characteristics – as possible drivers of adoption.

Consumers seek exhaustive and reliable information for purchase decisions. Due to the abundance of online information, they experience information overload. GAI platforms reduce information overload by providing synthesized and customized product/service search results. However, its reliability, trustworthiness and accuracy have been questioned. The functioning of GAI is opaque; the popular technology adoption model such as UTAUT is general and is unlikely to explain in totality the adoption and usage of GAI. Hence, this research provides the adoption drivers for this unique technology context. It identifies the determinants/antecedents of relevant UTAUT variables and develops an integrated conceptual model explaining GAI adoption for retail information search.

This study uses the pleasure–arousal–dominance (PAD) theory to explore how users’ emotional engagement with ChatGPT drives their continued adoption of ChatGPT and word-of-mouth (WOM) behaviour in the context of travel-related service.

This study obtained reliable data from 428 Chinese respondents who used ChatGPT for travel-related purposes. Structural equation modelling was used to test a series of hypotheses based on the PAD framework.

This study identifies three key features of human–artificial intelligence (AI) interaction, namely, service ubiquity, entertainment and anthropomorphism, which significantly influence users’ emotional responses, including pleasure, arousal and dominance. Dominance and pleasure are found to enhance emotional experiences, driving continued adoption and positive WOM recommendations for ChatGPT, whereas arousal influences WOM but does not affect continued adoption. The results also confirm that users’ perceived pleasure from interacting with ChatGPT has the strongest effect. These findings advance theoretical understanding by clarifying the emotional mechanisms underlying human–AI interactions in the tourism context.

This study examines the emerging trend of tourists’ continuous adoption of ChatGPT for travel-related services. The results highlight how different emotions in human–AI interaction influence long-term use of AI-powered tool for travel-related services.

本研究基于愉悦-兴奋-支配（PAD）理论, 探讨在旅行相关服务中, 用户对 ChatGPT 的情感投入如何推动其持续使用该技术, 并激发口碑行为。

本研究基于428名使用过ChatGPT进行旅游相关服务的中国受访者所提供的可靠数据, 运用结构方程模型（SEM）, 结合PAD框架, 对一系列假设进行了验证。

本研究确定了用户与人工智能互动的三个关键特征：服务无处不在、娱乐性和拟人化, 这些特征对用户的情感反应（包括愉悦感、兴奋感和主导感）产生了显著影响。研究发现, 主导性和愉悦感增强了用户的情感体验, 推动了对ChatGPT的持续采用和积极的口碑推荐（WOM）, 而兴奋感仅影响口碑推荐, 但不影响持续采用。研究结果还证实, 用户在与ChatGPT互动中感知到的愉悦感具有最强的影响力。这些发现阐明了旅游业中人与人工智能互动的情感机制, 推动了相关理论的深入理解。

本研究探讨了游客持续采用ChatGPT进行旅游相关服务的这一新兴趋势。研究结果突显了在人机交互中, 不同情感如何影响游客对人工智能驱动工具在旅游服务中的长期使用。

Propósito: El estudio emplea la teoría del placer-despertar-dominio (PAD) para explorar cómo el compromiso emocional de los usuarios con ChatGPT impulsa su adopción continuada de ChatGPT y el comportamiento boca a boca en el contexto de un servicio relacionado con los viajes.

Este estudio recopiló datos fiables de 428 participantes chinos que utilizaron ChatGPT para fines relacionados con viajes. Se empleó el modelado de ecuaciones estructurales para evaluar una serie de hipótesis fundamentadas en el marco PAD.

Este estudio identifica tres características clave de la interacción entre humanos e IA: la ubicuidad del servicio, el entretenimiento y el antropomorfismo, que influyen significativamente en las respuestas emocionales de los usuarios, como el placer, la excitación y la dominación. La dominación y el placer mejoran las experiencias emocionales, impulsando la adopción continuada y las recomendaciones boca a boca positivas de ChatGPT, mientras que la excitación solo influye en las recomendaciones boca a boca, sin afectar la adopción continuada. Los resultados también confirman que el placer percibido por los usuarios al interactuar con ChatGPT es el factor con mayor impacto. Estos hallazgos contribuyen a la comprensión teórica al esclarecer los mecanismos emocionales que subyacen en las interacciones entre humanos e IA en el contexto del turismo.

Este estudio analiza la tendencia emergente de la adopción sostenida de ChatGPT por parte de los turistas en el ámbito de los servicios de viaje. Los resultados subrayan cómo las diversas emociones generadas en la interacción humano-IA inciden en el uso prolongado de herramientas basadas en IA para servicios turísticos.