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Article
Publication date: 17 July 2018

Jau Yang Liu, William Shiue, Fu Hsiang Chen and Ai Ting Huang

Corporate social responsibility has gradually become an essential enterprise responsibility under stakeholders’ expectations. Employee care strategies involve both qualitative and…

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Abstract

Purpose

Corporate social responsibility has gradually become an essential enterprise responsibility under stakeholders’ expectations. Employee care strategies involve both qualitative and quantitative factors and are receiving special attention with the advent of the information age. In previous studies, a company’s policy of employee care may not fit with the needs of the employees. Consequently, the purpose of this paper is to investigate enterprises’ employee care from the employee’s perspective by adopting a hybrid multiple attribute decision making (MADM) model.

Design/methodology/approach

This study is based on 159 interviews with senior employees and/or department managers using a survey questionnaire. This study uses the MADM model to conduct the analysis. First, this research study used Decision-Making Trial and Evaluation Laboratory (DEMATEL) to construct an influential network relations map of the 4 dimensions and 13 criteria of employee care. Second, this study uses DEMATEL-based Analytic Network Process to conduct a weight analysis for each dimension and criterion. Third, this study uses VIKOR to calculate employees’ level of satisfaction as well as the gap from the “aspired level.”

Findings

The results of the study revealed the critical factors influencing employee care and proposed a systematic plan to be used as a reference for improvement. The improvement sequence revealed the following order: Equal employment opportunities→Good industrial relations and benefits→Responsibility to train and educate employees→Occupational health and safety. The empirical results showed there was still 35 percent room for improvement in the enterprises’ implementation policy of employee care.

Originality/value

The implementation of employee care has become an important issue for corporations since it helps to sustain and to increase an enterprise’s competitiveness in the business environment. However, the extant literature on employee care comes from enterprises’ perspectives instead of from employees’ perspectives. This research investigates the key factors of employee care and successfully shows MADM to be an effective model for the planning and implementation of corporate social responsibilities’ employee care from the perspective of employees.

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Article
Publication date: 2 November 2020

Shu-Hao Chang

Defining key artificial intelligence (AI) technologies is especially fundamental because AI applications involve the development of multiple technical fields and have the…

685

Abstract

Purpose

Defining key artificial intelligence (AI) technologies is especially fundamental because AI applications involve the development of multiple technical fields and have the potential to generate numerous business opportunities in the future. However, most related studies have examined patent grants granted by or patent applications filed to major patent offices; few studies have employed the perspective of standard-essential patents (SEPs) from a holistic technical view. In addition, because few studies have explored the status signals of countries in relation to SEPs, the present study integrated “country” into the model and determined differences among countries in terms of their technological focus.

Design/methodology/approach

In this study, through patent technological network analysis in various periods, the author not only observed the focus fields of AI-related SEPs but also examined temporal trends to determine technical development trends.

Findings

This study identified technologies that have been key players in the SEP network in recent years; these technologies were centered on electric digital data processing, recognition of data and transmission of digital information. Moreover, many of these technologies have been applied in areas such as management and commerce and radio navigation. Furthermore, the USA plays a crucial role in the global development of AI technical network.

Originality/value

This study constructs a technical network model to identify key technologies and trends that can serve as a reference for national research and development resource allocation.

Details

Data Technologies and Applications, vol. 55 no. 1
Type: Research Article
ISSN: 2514-9288

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Publication date: 28 March 2022

C. Ganeshkumar, Arokiaraj David and D. Raja Jebasingh

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were…

Abstract

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

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Article
Publication date: 29 April 2022

Khoa The Do, Huy Gip, Priyanko Guchait, Chen-Ya Wang and Eliane Sam Baaklini

While robots have increasingly threatened frontline employees’ (FLEs) future employment by taking over more mechanical and analytical intelligence tasks, they are still unable to…

1748

Abstract

Purpose

While robots have increasingly threatened frontline employees’ (FLEs) future employment by taking over more mechanical and analytical intelligence tasks, they are still unable to “experience” and “feel” to occupy empathetic intelligence tasks that can be handled better by FLEs. This study, therefore, aims to empirically develop and validate a scale measuring the new so-called empathetic creativity as being creative in practicing and performing empathetically intelligent skills during service encounters.

Design/methodology/approach

This study adopts a multistage design to develop the scale. Phase 1 combines a literature review with text mining from 3,737 service robots-related YouTube comments to generate 16 items capturing this new construct. Phase 2 assesses both face and content validity of those items, while Phase 3 recruits Prolific FLEs sample to evaluate construct validity. Phase 4 checks this construct’s nomological validity using PLS-SEM and Phase 5 experiments dedicated effort (vs natural talent) as an effective approach to foster FLEs’ perceived empathetic creativity.

Findings

The final scale is comprised of 13 refined items that capture three dimensions (social, interactive and emotional) of empathetic creativity. This research provides timely implications to help FLEs in high-contact services stay competitive.

Originality/value

This study introduces the new construct of empathetic creativity, which goes beyond the traditional definition of creativity in services and highlights the importance of empathetic intelligence for FLEs in future employment. This study also develops a multi-item scale to measure this construct, which can be applied to future service management research.

Details

Journal of Service Management, vol. 34 no. 3
Type: Research Article
ISSN: 1757-5818

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Article
Publication date: 3 May 2022

Nurhafihz Noor, Sally Rao Hill and Indrit Troshani

Service providers and consumers alike are increasingly adopting artificial intelligence service agents (AISA) for service. Yet, no service quality scale exists that can fully…

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Abstract

Purpose

Service providers and consumers alike are increasingly adopting artificial intelligence service agents (AISA) for service. Yet, no service quality scale exists that can fully capture the key factors influencing AISA service quality. This study aims to address this shortcoming by developing a scale for measuring AISA service quality (AISAQUAL).

Design/methodology/approach

Based on extant service quality research and established scale development techniques, the study constructs, refines and validates a multidimensional AISAQUAL scale through a series of pilot and validation studies.

Findings

AISAQUAL contains 26 items across six dimensions: efficiency, security, availability, enjoyment, contact and anthropomorphism. The new scale demonstrates good psychometric properties and can be used to evaluate service quality across AISA, providing a means of examining the relationships between AISA service quality and satisfaction, perceived value as well as loyalty.

Research limitations/implications

Future research should validate AISAQUAL with other AISA types, as they diffuse throughout the service sector. Moderating factors related to services, the customer and the AISA can be investigated to uncover the boundary conditions under which AISAQUAL is likely to influence service outcomes. Longitudinal studies can be carried out to assess how ongoing use of AISA can change service outcomes.

Practical implications

Service managers can use AISAQUAL to effectively monitor, diagnose and improve services provided by AISA while enhancing their understanding of how AISA can deliver better service quality and customer loyalty outcomes.

Originality/value

Anthropomorphism is identified as a new service quality dimension. AISAQUAL facilitates theory development by providing a reliable scale to improve the current understanding of consumers’ perspectives concerning AISA services.

Details

European Journal of Marketing, vol. 56 no. 5
Type: Research Article
ISSN: 0309-0566

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Article
Publication date: 17 April 2023

Prasetyo Adi Nugroho, Nove E. Variant Anna and Noraini Ismail

This study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two…

885

Abstract

Purpose

This study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two topics during the coronavirus pandemic.

Design/methodology/approach

The study gathered secondary data from the Scopus website using the keywords “AI,” “library” and “repository,” from 1993 to 2022. Data were re-analyzed using the bibliometric software VOSviewer to examine the trending country's keyword relations and appearance and Biblioshiny to study the publication metadata.

Findings

Index keywords, such as “human,” “deep learning,” “machine learning,” “surveys” and “open-source software,” became popular during 2020, being closely related to digital libraries. Additionally, the annual scientific production of papers increased significantly in 2021. Words related to data mining also had the most significant growth from 2019 to 2022 because of the importance of data mining for library services during the pandemic.

Practical implications

This study provides insight for librarians for the implementation of AI to support repositories during the pandemic. Librarians can learn how to maximize the AI-based repository services in academic libraries during the pandemic. Furthermore, academic libraries can create policies for repository services using AI.

Social implications

This study can lead researchers, academicians and practitioners in conducting research on AI in library repositories.

Originality/value

As research on AI and digital repositories remains limited, the study identifies themes and highlights the knowledge gap existing in the field.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Available. Content available

Abstract

Details

Journal of Hospitality and Tourism Technology, vol. 13 no. 3
Type: Research Article
ISSN: 1757-9880

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Article
Publication date: 28 September 2020

Man Lai Cheung, Wilson K.S. Leung and Haksin Chan

Young consumers have increasingly adopted wearable health-care technology to improve their well-being. Drawing on generation cohort theory (GCT) and the technology acceptance…

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Abstract

Purpose

Young consumers have increasingly adopted wearable health-care technology to improve their well-being. Drawing on generation cohort theory (GCT) and the technology acceptance model (TAM), this study aims to illuminate the major factors that drive the adoption of health-care wearable technology products by Generation Z (Gen-Z) consumers in Hong Kong.

Design/methodology/approach

A self-administrated online survey was used to collect data from a sample of Gen-Z consumers in Hong Kong with experience in using health-care wearable technology. Data analysis was performed using partial least-squares-structural equation modeling to verify four hypotheses.

Findings

The results reveal that consumer innovativeness (CI) and electronic word-of-mouth referral (EWOM) are significant predictors of perceived credibility, perceived ease of use and perceived usefulness, which subsequently drive online engagement intention and adoption intention (AI).

Practical implications

This research provides practical guidance for marketers of health-care wearable technology products. In particular, CI and EWOM hold the key to young consumers’ product perceptions (and thereby their online engagement and AIs).

Originality/value

This research leverages the insights of GCT to enrich the TAM, specifically by including CI and EWOM as antecedents and online engagement as a consequence in the context of health-care wearable technology. The results of an empirical study enhance theoretical understanding of Gen-Z consumers’ perceptions and behavioral intentions toward health-care wearable technology. They also point to actionable recommendations for marketing this new technology to young consumers.

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Article
Publication date: 12 November 2024

Aleksandar Radic, Sonali Singh, Nidhi Singh, Antonio Ariza-Montes, Gary Calder and Heesup Han

This study illustrates the conceptual framework that expands the knowledge of the fundamental components that describe how AI-driven servant leadership (SEL) influences the job…

130

Abstract

Purpose

This study illustrates the conceptual framework that expands the knowledge of the fundamental components that describe how AI-driven servant leadership (SEL) influences the job resources (JR), work engagement (WE) and job performance (JP) of tourism and hospitality employees.

Design/methodology/approach

The empirical study was conducted on a sample of 953 international tourism and hospitality employees who were selected via a purposive and snowball sampling approach in a cross-sectional survey. The analysis was performed using a partial least square-structural equation modeling.

Findings

The results of this study confirmed the positive impact of AI-driven SEL on employee JR with the boundary conditions of AI-driven SEL.

Practical implications

This study finding assists tourism and hospitality practitioners in understanding that in the near future, AI will have a major effect on the nature of work, including the impact on leadership styles. Hence, AI-driven SEL holds both positive (through direct impact on JR) and negative (via boundary conditions) impacts on employees’ JP and ultimately organizational success. Accordingly, managers should employ AI-driven SEL to increase employees’ JR, and once employees achieve high WE, they should constrict AI-driven SEL boundary conditions and their influence between JR and WE and WE and JP.

Originality/value

This study offers a novel and original conceptual model that advances AI-driven social theory, SEL theory and job demands-resources (JD-R) theory by synthesizing, applying and generalizing gained knowledge in a methodical way.

Details

Journal of Hospitality and Tourism Insights, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9792

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Article
Publication date: 22 December 2022

Jung-Kuei Hsieh, Werner H. Kunz and Ai-Yun Wu

This study aims to investigate the factors that affect an audience's purchase decisions on a new type of social media, namely live video streaming platforms.

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Abstract

Purpose

This study aims to investigate the factors that affect an audience's purchase decisions on a new type of social media, namely live video streaming platforms.

Design/methodology/approach

This study is based on data from an online survey providing 488 valid responses. These responses are used to test the research model by employing partial least squares (PLS) modeling.

Findings

Three antecedents (consumer competitive arousal, gift design aesthetics and broadcaster's image) influence the audience's purchase decisions (impulse buying and continuous buying intention). Chinese impression management (mianzi) acts as a moderator. Self-mianzi, mutual mianzi and other mianzi (i.e. three subtypes of mianzi) moderate the effects of consumer competitive arousal, gift design aesthetics and broadcaster's image on impulse buying.

Practical implications

The findings encourage practitioners developing marketing strategies for live video streaming platforms in the Chinese cultural context to consider peer influence, gift appearance, broadcaster's image and mianzi.

Originality/value

Drawing on the community gift-giving model and face-negotiation theory, this study provides an integrated research model to investigate a new type of social media (live video streaming). It offers insight into virtual gifting behaviors by confirming the effects of three antecedents on the audience's purchase decisions, with mianzi acting as a moderator.

Details

Internet Research, vol. 33 no. 4
Type: Research Article
ISSN: 1066-2243

Keywords

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