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1 – 10 of 262Xiaoyu Wang, Mengxi Chen, Zhiyan Wang, Chun Hung Roberts Law and Mu Zhang
This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs).
Abstract
Purpose
This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs).
Design/methodology/approach
Purposive and referral samplings methods were used to conduct 28 semistructured interviews with hotel FLEs, and the transcribed manuscript was analyzed based on grounded theory.
Findings
The study identifies six dimensions of SR affordances: physical, sensory, task, safety, social and emotional affordances. The main effects of SR affordances on FLEs involve reducing work stress and mental fatigue and increasing positive emotions in the psychological aspects of FLEs. In terms of behavioral aspects, shifts in task priorities and enhancements in SR usage behaviors were observed. Accordingly, a mechanistic framework was revealed through which SR affordances influence FLEs via direct and indirect interactions between FLEs and SRs.
Originality/value
This paper expands robotics research from a supply-side perspective and is one of the few studies to investigate SR affordances in the field of hospitality research. Findings of this study provide practical guidelines for designing and implementing SRs to support hotel FLEs in their daily work.
研究目的
本研究旨在调查酒店中服务机器人(SR)的可供性及其对一线员工(FLEs)的影响。
研究方法
本研究采用目的性和推荐抽样方法, 对酒店一线员工进行了28次半结构化访谈, 并根据扎根理论对转录的手稿进行了分析。
研究发现
本研究确定了服务机器人的六个可供性维度:物理、感官、任务、安全、社会和情感可供性。服务机器人可供性对一线员工的主要影响包括减少工作压力和心理疲劳, 以及在心理方面增加积极情绪。在行为方面, 观察到任务优先级的变化和服务机器人使用行为的增强。因此, 研究揭示了一种机制框架, 通过一线员工与服务机器人的直接和间接互动, 服务机器人可供性影响一线员工。
研究创新
本文从供给侧视角扩展了机器人研究, 是少数几篇研究酒店业中服务机器人可供性的研究之一。本研究结果为设计和实施服务机器人以支持酒店一线员工的日常工作提供了实践指南。
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This study investigates human behavior, specifically attitude and anxiety, toward humanoid service robots in a hotel business environment.
Abstract
Purpose
This study investigates human behavior, specifically attitude and anxiety, toward humanoid service robots in a hotel business environment.
Design/methodology/approach
The researcher adopted direct observations and interviews to complete the study. Visitors of Henn-na Hotel were observed and their spatial distance from the robots, along with verbal and non-verbal behavior, was recorded. The researcher then invited the observed hotel guests to participate in a short interview.
Findings
Most visitors showed a positive attitude towards the robot. More than half of the visitors offered compliments when they first saw the robot receptionists although they hesitated and maintained a distance from them. Hotel guests were also disappointed with the low human–robot interaction (HRI). As the role of robots in hotels currently remains at the presentation level, a comprehensive assessment of their interactive ability is lacking.
Research limitations/implications
This study contributes to the HRI theory by confirming that people may treat robots as human strangers when they first see them. When a robot's face is more realistic, people expect it to behave like an actual human being. However, as the sample size of this study was small and all visitors were Asian, the researcher cannot generalize the results to the wider population.
Practical implications
Current robot receptionist has limited interaction ability. Hotel practitioners could learn about hotel guests' behavior and expectation towards android robots to enhance satisfaction and reduce disappointment.
Originality/value
Prior robot research has used questionnaires to investigate perceptions and usage intention, but this study collected on-site data and directly observed people's attitude toward robot staff in an actual business environment.
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Dessy Harisanty, Nove E. Variant Anna, Tesa Eranti Putri, Aji Akbar Firdaus and Nurul Aida Noor Azizi
This study investigates the level of artificial intelligence (AI) awareness among library leaders, practitioners and scientists of Indonesian academic libraries to elucidate the…
Abstract
Purpose
This study investigates the level of artificial intelligence (AI) awareness among library leaders, practitioners and scientists of Indonesian academic libraries to elucidate the benefits of AI implementation and its necessary infrastructure and challenges.
Design/methodology/approach
The study adopted a purposive sampling technique to select the 38 participants and thematic analysis to analyze the data, identifying eight themes: understanding of AI, AI adoption, benefits of AI, competencies needed to support AI, facilities to support AI, factors supporting AI adoption, AI-inhibiting factors and expectations of AI.
Findings
Different viewpoints provided full awareness among library stakeholders and sufficient information to begin AI initiatives in Indonesian libraries as leaders, practitioners and scientists had a favorable, open and encouraging outlook on AI.
Research limitations/implications
The study does not investigate variations in perspectives between the participants, but it examines their understanding of AI and elaborates the results into the concept of an intelligent library. Moreover, this study only uses samples from academic libraries.
Practical implications
Libraries can take these results into consideration before implementing AI, especially in technology and facilities, librarian competency with regard to AI and leadership roles in AI projects.
Social implications
Library boards and library associations can use this research as a source to create guidelines about AI implementation in academic libraries.
Originality/value
The study addresses the gap in the research on university libraries' readiness and awareness to implement AI, especially in developing countries.
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Yuhao Li, Shurui Wang and Zehua Li
This study aims to apply the predictive processing theory to examine the influence of artificial intelligence (AI)-driven robotic performers on audience emotions and the…
Abstract
Purpose
This study aims to apply the predictive processing theory to examine the influence of artificial intelligence (AI)-driven robotic performers on audience emotions and the audience’s resulting electronic word-of-mouth (eWOM) behaviors during tourism service encounters.
Design/methodology/approach
Using a quantitative research methodology, survey responses from 339 regular customers of performing arts in tourism destinations were analyzed. The respondents were recruited through Prolific, a professional data collection platform. SPSS 23.0 was used for the preliminary analysis, from which a research model to achieve the aim was proposed. SmartPLS 3 was used for partial least squares structural equation modeling to test the model.
Findings
Interactive and novel robotic performances significantly encouraged the consumers to share their experiences online, thereby enhancing eWOM. However, melodic resonance had no significant impact on eWOM intentions. The consumers’ emotional responses fully mediated the relationship of the novelty and interactivity of the performances to the consumers’ eWOM intentions but did not mediate the relationship of the musical elements to their eWOM intentions.
Originality/value
This study enriches the understanding of how AI-driven performances impact consumers’ emotional engagement and sharing behaviors. It extends the application of the predictive processing theory to the domain of consumer behavior, offering valuable insights for enhancing audience engagement in performances through technological innovation.
研究目的
本研究旨在运用预测处理理论, 考察人工智能(AI)驱动的机器人表演对观众情感及其在旅游服务接触中的电子口碑(eWOM)行为的影响。。
研究方法
采用定量研究方法, 分析了339名经常观看旅游景点表演艺术的常客的调查问卷。受访者通过专业数据收集平台Prolific招募。初步分析使用SPSS 23.0进行, 从中提出了实现研究目标的研究模型。使用SmartPLS 3进行偏最小二乘结构方程模型测试该模型。
研究发现
互动性和新颖性的机器人表演显著鼓励消费者在线分享他们的体验, 从而增强电子口碑。然而, 旋律共鸣对电子口碑意图没有显著影响。消费者的情感反应完全中介了表演的新颖性和互动性与消费者电子口碑意图之间的关系, 但没有中介音乐元素与电子口碑意图之间的关系。
研究创新
本研究丰富了对AI驱动表演如何影响消费者情感参与和分享行为的理解。将预测处理理论的应用扩展到消费者行为领域, 为通过技术创新增强观众参与度提供了宝贵的见解。
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This study tries to examine the effect of artificial intelligence (AI) drivers on the willingness to adopt the human capital supply chain (HCSC) in manufacturing firms (MFs) in…
Abstract
Purpose
This study tries to examine the effect of artificial intelligence (AI) drivers on the willingness to adopt the human capital supply chain (HCSC) in manufacturing firms (MFs) in developing countries (DCs) including Jordan, Saudi Arabia, Bahrain, Qatar and the United Arab Emirates, which are listed in the Chambers of Industry of these countries.
Design/methodology/approach
The quantitative methodology with a simple random sampling method was adopted using a questionnaire survey-based approach to collect data from 233 out of 1,055 participants (human resource (HR) managers and information technology (IT) senior managers) from various MFs (private and commercial), representing a 22% response rate. Covariance-based structural equation modeling (CB-SEM) was used to analyze the raw data using Amos V.25.
Findings
The results of this study showed that there are positive and statistically significant direct association effects between the reliability of use (RoU), competitive pressures (CPs) and user confidence (UC) factors on the willingness to adopt AI in HCSC in the MFs in DCs. At the same time, there is no significant effect on a firm’s infrastructure readiness (FIRs), in addition to the indirect effect of UC in the relationship between CPs and FIRs on the willingness to adopt AI in HCSC.
Originality/value
Such findings of this study can provide insightful implications for stakeholders and policymakers regarding the importance of using predictive AI drivers' effect on willingness to adopt the HCSC in the MFs in DCs as emerging economies. Additionally, the managers might focus on the existence of a significant positive indirect effect of UC as a mediating factor in the relationship between FIRs and willingness to adopt AI and its applications in HCSC systems and departments.
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Ernesto Cardamone, Gaetano Miceli and Maria Antonietta Raimondo
This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation…
Abstract
Purpose
This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation targeted to the general audience. The proposed conceptual model suggests that innovation fits well with more abstract language because of the association of innovation with imagination and distal construal. Moreover, communication of innovation may benefit from greater adherence to the narrativity arc, that is, early staging, increasing plot progression and climax optimal point. These effects are moderated by content variety and emotional tone, respectively.
Design/methodology/approach
Based on a Latent Dirichlet allocation (LDA) application on a sample of 3225 TED Talks transcripts, the authors identify 287 TED Talks on innovation, and then applied econometric analyses to test the hypotheses on the effects of abstractness vs concreteness and narrativity on engagement, and on the moderation effects of content variety and emotional tone.
Findings
The authors found that abstractness (vs concreteness) and narrativity have positive effects on engagement. These two effects are stronger with higher content variety and more positive emotional tone, respectively.
Research limitations/implications
This paper extends the literature on communication of innovation, linguistics and text analysis by evaluating the roles of abstractness vs concreteness and narrativity in shaping appreciation of innovation.
Originality/value
This paper reports conceptual and empirical analyses on innovation dissemination through a popular medium – TED Talks – and applies modern text analysis algorithms to test hypotheses on the effects of two pivotal dimensions of language on user engagement.
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The goal of this study is to better understand the driving force behind the use of artificial intelligence (AI) in pharmaceutical manufacturing firms (PMFs) that are recognized as…
Abstract
Purpose
The goal of this study is to better understand the driving force behind the use of artificial intelligence (AI) in pharmaceutical manufacturing firms (PMFs) that are recognized as developing countries in the Middle East and North Africa (MENA) region that are listed by the Chambers of the Industries of Jordan, the Kingdom of Saudi Arabia, Morocco, and Algeria. Furthermore, the effect of adopting and using AI in managing raw materials (RMs), products, parts, and components for PMFs through supply chains (SCs).
Design/methodology/approach
A self-administrated questionnaire survey was used to gather data from 95 out of 511 participating managers (e.g. manufacturing, supplying, IT, operational, and logistical managers) utilizing a quantitative technique with a random sample size. In fact, 18.8% of the 89 different manufacturing firms (MFs) in the MENA area responded, with five to six managers from each company. The raw data was analyzed using partial least squares structural equation modeling (PLS-SEM).
Findings
The study’s findings show that the readiness to embrace artificial intelligence (AI) in the production management supply chain performance (PMSCP) of pharmaceutical manufacturing firms in the Middle East and North Africa (MENA) is positively and significantly influenced directly and indirectly by sustainable strategic supplier reliability (SSSR), shipping process dependability (SPD), technological factors (TFs), and infrastructure transformational development capability (ITDC).
Originality/value
As the studied countries are growing economies, such study findings might offer insightful consequences for stakeholders and policymakers regarding the significance of using artificial intelligence system adoptions in pharmaceutical manufacturing enterprises in the MENA region. The managers may also concentrate on the strong positive direct and indirect links between SSSR, SPD, TFs, and ITDC preparedness to accept AI adoption and its applications and systems in supply chain and production management departments and the consequences of informational and product delivery.
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Rob Law, Katsy Jiaxin Lin, Huiyue Ye and Davis Ka Chio Fong
The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.
Abstract
Purpose
The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.
Design/methodology/approach
This study adopts the theory-context-methods framework to systematically review 100 AI-related articles recently published (i.e. from 2021 to April 2023) in three top-tier hospitality journals, namely, the International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management.
Findings
Findings suggest that studies of AI applications in hospitality are mostly theory-driven, whereas most AI methods research adopts a data-driven approach. State-of-the-art AI applications research exhibits the most interest in service robots. In AI methods research, little attention was paid to the amid-service/experience.
Research limitations/implications
This study reveals inadequacies in theory, context and methods in contemporary AI research. More research from hospitality suppliers’ perspectives and research on generative AI applications are advocated in response to the unveiled research gaps and recent AI developments.
Originality/value
This study classifies the most recent AI research in hospitality into two main streams – AI applications research and AI methods research – and discusses the gaps in each research stream and latest AI developments. The paper then suggests future research directions to guide researchers in advancing AI research in hospitality.
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Given its ability to improve user interaction and labor productivity, ease human workloads and cut maintenance costs, public sectors are using AI-based robotic technology (AI-RT…
Abstract
Purpose
Given its ability to improve user interaction and labor productivity, ease human workloads and cut maintenance costs, public sectors are using AI-based robotic technology (AI-RT) at an accelerated rate. There is, however, little knowledge about the variables affecting citizens' participation when services backed by AI-RT are offered. In order to better understand the elements that influence AI-RT citizens' involvement and the moderating function of trusts in governmental organizations, this article draws on ideas from the Consumer Value Theory.
Design/methodology/approach
Out of 500 survey forms that were distributed to Indonesian people who had experience in using AI-RT devices in public service hall (e.g. airport’s Auto Gate), 367 returned the completed feedbacks. Data analysis used a step-by-step hierarchical moderated regression examination using SPSS 24 version.
Findings
Citizens’ involvement is positively correlated with esthetics and customization and adversely correlated with period expended using the AI-RT. Additionally, the findings imply that citizens who have greater levels of faith in governmental institutions are more likely to benefit favorably from the customization and esthetics of AI-RT.
Practical implications
The AI-RT must be capable of customizing the distribution of the appropriate materials to the appropriate individual at the appropriate moment, and public managers should guarantee that it is esthetically pleasing. Additionally, they ought to place a high priority on winning the trust of the populace in order to increase citizens’ involvement.
Originality/value
This paper was among the initial efforts that discover the determinants of citizens’ involvement in the AI-RT and the moderating effect of trusts in governmental organizations on the links between predictors and predicted variable, especially in an emerging country such as Indonesia.
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Khurram Shahzad, Shakeel Ahmad Khan, Abid Iqbal and Asfa Muhammed Din Javeed
This study aimed to identify the university librarians’ readiness to adopt artificial intelligence (AI) for innovative learning experiences and smart library services.
Abstract
Purpose
This study aimed to identify the university librarians’ readiness to adopt artificial intelligence (AI) for innovative learning experiences and smart library services.
Design/methodology/approach
Quantitative research design followed by a survey method was applied. Data were collected from 174 professional librarians of 58 university libraries in Punjab province, Pakistan.
Findings
The findings of the study revealed that the adoption of AI enhances innovative learning. The results displayed that AI adoption assists librarians in the provision of smart library services to end users.
Originality/value
The study has offered practical recommendations in light of the evidence-based data for the efficient adoption and sustainability of AI applications in university libraries for innovative learning and smart library services. It contributes to the theoretical understanding by expanding the existing knowledge base. It offers managerial insights and has a societal impact. The study has provided a framework based on the empirical findings for efficiently adopting AI tools in academic settings for the provision of innovative learning experiences and sustainable smart library services.
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