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Book part
Publication date: 20 June 2017

David Shinar

Free Access. Free Access

Abstract

Details

Traffic Safety and Human Behavior
Type: Book
ISBN: 978-1-78635-222-4

Available. Open Access. Open Access
Article
Publication date: 20 February 2025

Badrea Saleh Al-Oraini

This study investigated the factors that influence customer satisfaction with AI-driven services by focusing on chatbot agents. The conceptual model included psychological and…

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Abstract

Purpose

This study investigated the factors that influence customer satisfaction with AI-driven services by focusing on chatbot agents. The conceptual model included psychological and social factors, such as trust, perceived social presence, competence perception, social-oriented communication style, warmth perception, subjective norms and attachment anxiety.

Design/methodology/approach

A quantitative methodology was employed utilising a survey conducted among 525 consumers who interacted with chatbot services. The data were analysed using structural equation modelling (Smart-PLS 4.0) to test the proposed hypotheses.

Findings

The study revealed that social-oriented communication, perceptions of competence and warmth, trust and subjective norms significantly enhanced customer satisfaction with chatbots. Trust was critical in fostering satisfaction, whereas perceived social presence and attachment anxiety had minimal impact. The findings suggest that despite the emphasis on social presence, its influence on satisfaction may depend on contextual factors that were not captured in this study.

Originality/value

This study extended the Technology Acceptance Model and Stereotype Content Model by integrating factors such as perceived social presence, trust, competence perception, social-oriented communication style, warmth perception, subjective norm and attachment anxiety. Challenging conventional assumptions on the role of social presence and attachment anxiety, the study provides new insights into the complex dynamics of human–chatbot interactions, offering practical implications for improving chatbot design and enhancing user experience that emphasise the importance of trust, competence and social-oriented communication in customer satisfaction.

Details

Journal of Innovative Digital Transformation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2976-9051

Keywords

Available. Open Access. Open Access
Article
Publication date: 28 January 2020

Haotian Cao, Zhenghao Zhang, Xiaolin Song, Hong Wang, Mingjun Li, Song Zhao and Jianqiang Wang

The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.

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Abstract

Purpose

The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.

Design/methodology/approach

A total of 1,432 crashes and 19,714 baselines were collected for the Strategic Highway Research Program 2 naturalistic driving research. The authors used a case-control approach to estimate the prevalence and the population attributable risk percentage. The mixed logistic regression model is used to evaluate the correlation between different driver demographic characteristics (age, driving experience or their combination) and the crash risk regarding cell phone engagements, as well as the correlation among the likelihood of the cell phone engagement during the driving, multiple driver demographic characteristics (gender, age and driving experience) and environment conditions.

Findings

Senior drivers face an extremely high crash risk when distracted by cell phone during driving, but they are not involved in crashes at a large scale. On the contrary, cell phone usages account for a far larger percentage of total crashes for young drivers. Similarly, experienced drivers and experienced-middle-aged drivers seem less likely to be impacted by the cell phone while driving, and cell phone engagements are attributed to a lower percentage of total crashes for them. Furthermore, experienced, senior or male drivers are less likely to engage in cell phone-related secondary tasks while driving.

Originality/value

The results provide support to guide countermeasures and vehicle design.

Available. Open Access. Open Access
Article
Publication date: 30 August 2022

Francesca Magno and Giovanna Dossena

Many firms are investing in digital services to improve customer experiences. Virtual service agents, or “e-service agents” (“e-agents”) such as chatbots, are examples of these…

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Abstract

Purpose

Many firms are investing in digital services to improve customer experiences. Virtual service agents, or “e-service agents” (“e-agents”) such as chatbots, are examples of these efforts. Chatbots are types of virtual-assistant software programs that interact with users through speech or text. This paper aims to investigate whether the perceived hedonic and utilitarian attributes of chatbots can influence customer satisfaction and, consequently, their relationships with brands.

Design/methodology/approach

Data were collected through a questionnaire-based survey among a sample of Italian consumers. A convenience sampling technique was used. Data were then analyzed through Partial Least Squares Structural Equation Modeling to provide a prediction-oriented model assessment. The findings were then complemented with an importance–performance map analysis (IPMA) to gain more detailed insights and actionable guidelines for managers.

Findings

The findings highlighted that the perceived hedonic and utilitarian attributes of chatbots positively influenced customer satisfaction and improved customer relationships with the brands. However, the IMPA highlighted that the performance levels of two most important attributes – system quality and experience with chatbot – could be improved resulting in additional improvements of customer satisfaction.

Practical implications

This study suggests the importance of firms’ investments in and adoption of e-agents to strengthen consumer–brand relationships and of considering both the hedonic and utilitarian attributes of their e-agents.

Originality/value

This article attempts to enrich and consolidate the growing body of literature concerning the impacts of new technologies – and, specifically, chatbots – in service marketing.

Details

The TQM Journal, vol. 35 no. 5
Type: Research Article
ISSN: 1754-2731

Keywords

Available. Open Access. Open Access
Article
Publication date: 21 August 2019

Shaikh Shamim Hasan, Yue Zhang, Xi Chu and Yanmin Teng

Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast…

3297

Abstract

Purpose

Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast territory, huge population and widespread forest landscape of China, forest management is a complex system involving massive data and various management activities. To effectively implement sustainable forest management, the big data technology has been utilized to analyze China’s forestry resources. Thus, the purpose of this paper is to clarify the role of big data technology in China’s forest management.

Design/methodology/approach

In this paper, the authors revisited the roles of big data in forest ecosystem monitoring, forestry management system development, and forest policy implementation.

Findings

It demonstrates that big data technology has a great potential in forest ecosystem protection and management, as well as the government’s determination for forest ecosystem protection. However, to deepen the application of big data in forest management, several challenges still need to be tackled.

Originality/value

Thus, enhancing modern science and technology to improve big data, cloud computing, and information technologies and their combinations will contribute to tackle the challenges and achieve wisdom of forest management.

Details

Forestry Economics Review, vol. 1 no. 1
Type: Research Article
ISSN: 2631-3030

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