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1 – 10 of 16
Article
Publication date: 16 November 2021

Rajasshrie Pillai, Shilpi Yadav, Brijesh Sivathanu, Neeraj Kaushik and Pooja Goel

This paper aims to investigate the use of Industry 4.0 (I4.0) technology and its barriers in human resourcemanagement (HRM) for Smart HR 4.0 and its impact on HR performance.

Abstract

Purpose

This paper aims to investigate the use of Industry 4.0 (I4.0) technology and its barriers in human resourcemanagement (HRM) for Smart HR 4.0 and its impact on HR performance.

Design/methodology/approach

The research has been conducted using the grounded theory approach. Semi-structured interviews were conducted with 122 senior HR officers of national and multi-national companies in India after the extensive literature review. NVivo 8.0 software was used for the analysis of the interview data.

Findings

I4.0 technology is used for HRM functions by HR professionals. It is revealed that Smart HR 4.0 that emerged from the I4.0 technology has leveraged the HR performance. It is also found that usage barriers, traditional barriers and risk barriers affect the use of I4.0 technology in HRM.

Originality/value

A model is developed using the grounded theory approach for HR managers to understand the impact of I4.0 on HRM. This study reveals the barriers affecting the use of I4.0 technology in HRM. It also provides the model for HR performance that emerged through the use of I4.0 technology in HR and Smart HR 4.0. The research delivered key insights for the HR professionals, marketers of HR technology and technology developers.

Details

foresight, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-6689

Keywords

Article
Publication date: 19 February 2020

Rajasshrie Pillai and Brijesh Sivathanu

The purpose of this paper is to investigate the adoption of Internet of Things (IoT) in the agriculture industry by the farmers' in India using the theoretical lens of the…

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Abstract

Purpose

The purpose of this paper is to investigate the adoption of Internet of Things (IoT) in the agriculture industry by the farmers' in India using the theoretical lens of the behavioral reasoning theory (BRT).

Design/methodology/approach

A survey on farmers was conducted to examine the adoption of IoT in agriculture industry (IoT-A) using BRT. The data analysis of the primary survey was done by applying the structural equation modelling (SEM) technique.

Findings

The ‘reasons for’ adoption of IoT-A were as follows: Relative advantage, social influence, perceived convenience, and perceived usefulness. The ‘reasons against’ adoption were as follows: Image barrier, technological anxiety, perceived price and perceived risk. The BRT theory provides the platform to discuss the psychological processing of acceptance of IoT in agriculture industry by the farmers.

Practical implications

This research has unique implications as it studies the rural consumers’ behavior of innovation adoption namely IoT in agriculture. It provides the specific reasons ‘for’ and ‘against’ IoT adoption in agriculture, which will give directions to the marketers of IoT technology to develop suitable marketing strategies to improve the adoption in rural areas.

Originality/value

This research takes the first step in the direction toward deliberation of the adoption of IoT-A by farmers in an emerging Indian economy using the BRT theory, which discusses the ‘reasons for’ and ‘reasons against’ adoption in a proposed model.

Details

Benchmarking: An International Journal, vol. 27 no. 4
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 22 February 2022

Pooja Goel, Neeraj Kaushik, Brijesh Sivathanu, Rajasshrie Pillai and Jasper Vikas

The purpose of this study, a current systematic literature review, is to synthesize the extant literature on consumers’ adoption of artificial intelligence and robotics…

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Abstract

Purpose

The purpose of this study, a current systematic literature review, is to synthesize the extant literature on consumers’ adoption of artificial intelligence and robotics (AIR) in the context of the hospitality and tourism sector (HATS) to gain a comprehensive understanding of it. This study also outlines insights for academia, practitioners, AI marketers, developers, designers and policymakers.

Design/methodology/approach

This study used a content analysis approach to conduct a systematic literature review for the period of 10 years (2011–2020) of the various published studies themed around consumer’s adoption of AIR in HATS.

Findings

The synthesis draws upon various factors affecting the adoption of AIR, such as individual factors, service factors, technical and performance factors, social and cultural factors and infrastructural factors. Additionally, the authors identified four major barriers, namely, psychological, social, financial, technical and functional that hinder the consumer’s adoption of artificial intelligence and robots in the hospitality and tourism industry.

Originality/value

To the best of the author’s/authors’ knowledge, this study is a first attempt to synthesize the factors that drive consumers’ adoption of artificial intelligence and robots in the hospitality and tourism industry. The present work also advances the tourism and consumer behavior literature by offering an integrated antecedent-outcome framework.

Visual abstract

Figure 2 The objective of the current systematic literature review is to synthesize the extant literature on consumer’s adoption of artificial intelligence and robotics (AIR) in the context of the hospitality and tourism sector (HATS) to gain a comprehensive understanding of it. For that purpose, authors conducted content analysis of extant literature on consumer’s adoption of AIR in HATS from 2011 to 2020. Authors presented an integrated antecedent outcome framework of the factors that drive consumer’s adoption of artificial intelligence and robots in the hospitality and tourism industry.

目的

这篇系统性文献综述的目的是综合现有关于消费者在酒店和旅游部门(HATS)中采用人工智能和机器人(AIR)的文献, 以便全面了解它。这项研究还概述了学术界、从业者、人工智能营销人员、开发人员、设计师和决策者的见解。

设计/方法论/方法

本研究使用内容分析方法对 10 年(2011–2020 年)期间的各种已发表研究进行系统的文献回顾, 主题围绕消费者在 HATS 中采用 AIR。

结果

本研究揭示了四大服务:自动化、定制、信息传播、旅游移动性和导航服务。 此外, 作者确定了阻碍消费者在酒店和旅游业采用人工智能和机器人的四大障碍, 即心理、社会、财务、技术和功能

原创性

本研究首次尝试综合推动消费者在酒店和旅游业中采用人工智能和机器人的因素。本文还通过提供一个综合的前因结果框架, 推进了旅游和消费者行为文献。

Resumen

Objetivo

El objetivo de la actual revisión sistemática literaria es sintetizar la literatura existente sobre la adopción de la inteligencia artificial y la robótica (IAR) por parte de los consumidores en el contexto del sector hotelero y turístico (SHT) para ganar un entendimiento comprensivo del mismo. Este estudio también traza visiones para los académicos, profesionales, comercializadores de AI, desarrolladores, diseñadores, y los elaboradores de las políticas a seguir.

Diseño/metodología/enfoque

El presente estudio siguió un enfoque de análisis de contenido para realizar una revisión sistemática de la literatura durante el período de 10 años (2011–2020) de los diversos estudios publicados y basados en la adopción de IAR en SHT, por parte de los consumidores.

Los hallazgos

Este estudio desvela cuatro grandes servicios: automatización, personalización, difusión de información, movilidad turística y servicios de navegación. Adicionalmente, los autores identificaron cuatro barreras principales, a saber; psicológicas, sociales, financieras, técnicas y funcionales, que impiden la adopción de la inteligenica artificial y la robótica por parte del consumidor, en la industria de la hospitalidad y el turismo.

Originalidad

Este estudio es un primer intento de sintetizar los factores que impulsan la adopción de la inteligencia artificial y la robótica por parte de los consumidores en la industria hotelera y turística. El presente trabajo también fomenta la literatura sobre el turismo y el comportamiento del consumidor, ofreciendo un marco integrado de resultados precedentes.

Article
Publication date: 29 April 2021

Rajasshrie Pillai and Brijesh Sivathanu

To understand human resource (HR) practices outcomes on HR decision making, strategic human resource management (HRM) and organizational performance by exploring the HR…

Abstract

Purpose

To understand human resource (HR) practices outcomes on HR decision making, strategic human resource management (HRM) and organizational performance by exploring the HR data quality along with descriptive and predictive financial and non-financial metrics.

Design/methodology/approach

This work utilizes the grounded theory method. After the literature was reviewed, 113 HR managers of multinational and national companies in India were interviewed with a semi-structured questionnaire. The collected interview data was analyzed with NVivo 8.0 software.

Findings

It is interesting to uncover the descriptive and predictive non-financial and financial metrics of HR practices and their influence on organizational performance. It was found that HR data quality moderates the relationship between the HR practices outcome and HR metrics. This study found that HR metrics help in HR decision-making for strategic HRM and subsequently affect organizational performance.

Originality/value

This study has uniquely provided the descriptive and predictive non-financial and financial metrics of HR practices and their impact on HR decision making, strategic HRM and organizational performance. This study highlights the importance of data quality. This research offers insights to the HR managers, HR analysts, chief HR officers and HR practitioners to achieve organizational performance considering the various metrics of HRM. It provides key insights to the top management to understand the HR metrics' effect on strategic HRM and organizational performance.

Details

International Journal of Productivity and Performance Management, vol. 71 no. 7
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 15 May 2018

Brijesh Sivathanu and Rajasshrie Pillai

This paper aims to highlight the importance of Smart Human Resources 4.0 (Smart HR 4.0) and its role as a catalyst in the disruption process in the human resource domain…

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Abstract

Purpose

This paper aims to highlight the importance of Smart Human Resources 4.0 (Smart HR 4.0) and its role as a catalyst in the disruption process in the human resource domain. This paper illustrates the advantages of Smart HR 4.0 in the HR domain by using the example of Credit Suisse, which has extensively used people analytics to reduce employee attrition.

Design/methodology/approach

The paper discusses the role of Smart HR 4.0 as a disruptor in the human resource domain. With the help of the Smart HR 4.0 conceptual framework, this paper illustrates how Smart HR 4.0 disrupts the talent on-boarding, talent development, and talent off-boarding process.

Findings

An organization would require a successful Smart HR 4.0 strategy to cope up with the challenges of Industry 4.0 transformation. Emerging technologies such as Internet-of-Things, Big Data, and artificial intelligence will automate most of the HR processes, resulting in efficient and leaner HR teams. Both organization structure and leadership style changes would be required for efficient Smart HR 4.0 implementation that would allow HR departments to play a more strategic role in the overall organization growth.

Originality/value

This paper contributes to the existing literature and body of knowledge in the HR domain by developing a Smart HR 4.0 conceptual framework. This paper discusses how Smart HR 4.0 acts as a catalyst in the disruption of talent ion-boarding, talent development, and talent off-boarding process with the help of emerging technologies and change in the employee generation.

Details

Human Resource Management International Digest, vol. 26 no. 4
Type: Research Article
ISSN: 0967-0734

Keywords

Article
Publication date: 22 June 2018

Brijesh Sivathanu

The purpose of this paper is to utilize the novel approach of applying the behavioral reasoning theory (BRT) to examine the adoption of internet of things (IoT) based…

1717

Abstract

Purpose

The purpose of this paper is to utilize the novel approach of applying the behavioral reasoning theory (BRT) to examine the adoption of internet of things (IoT) based wearables for the healthcare of older adults and it aims to understand the relative effect of “reasons for” and “reasons against” adoption of IoT-based wearables for health care among older adults.

Design/methodology/approach

The hypothesized relationships were established using the BRT and empirically tested using a representative sample of 815 respondents. The data were analyzed using the PLS-SEM method.

Findings

The findings of this study demonstrate that adoption intention of IoT-based wearables for the health care of older adults is influenced by “reason for” and “reason against” adoption. The finding shows that “reasons for” adoption are ubiquitous, relative advantage, compatibility and convenience and “reasons against” adoption are usage barrier, traditional barrier and risk barrier. Value of “openness to change” significantly influences the “reasons for” and “reasons against” adoption of IoT-based wearables.

Research limitations/implications

This cross-sectional study is conducted only in the Indian context and future research can be conducted in other countries to generalize the results.

Practical implications

This research highlighted both the adoption factors—“for” and “against,” which should be considered while developing marketing strategies for IoT-based wearables for health care of older adults. Adoption of IoT-based wearables for healthcare of older adults will increase when marketers endeavor to minimize the effects of the anti-adoption factors.

Originality/value

This is a unique study that examines the adoption of IoT-based wearables for healthcare among older people using the BRT, by probing the “reasons for” and “reasons against” adoption in a single framework.

Details

Journal of Enabling Technologies, vol. 12 no. 4
Type: Research Article
ISSN: 2398-6263

Keywords

Article
Publication date: 17 August 2020

Rajasshrie Pillai and Brijesh Sivathanu

Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI…

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Abstract

Purpose

Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.

Design/methodology/approach

This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.

Findings

This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.

Practical implications

This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.

Originality/value

This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.

Details

Benchmarking: An International Journal, vol. 27 no. 9
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 10 September 2020

Rajasshrie Pillai and Brijesh Sivathanu

This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in…

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Abstract

Purpose

This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.

Design/methodology/approach

To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.

Findings

As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.

Practical implications

This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.

Originality/value

This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.

Details

International Journal of Contemporary Hospitality Management, vol. 32 no. 10
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 30 June 2022

Mahek Mahtta, Rajasshrie Pillai, Angappa Gunasekaran, Brijesh Sivathanu and Neeraj Kaushik

In the postpandemic era, organizations have planned a combination of on-site and virtual work to portray the “New Normal”. The authors aim to analyze the effect of virtual…

Abstract

Purpose

In the postpandemic era, organizations have planned a combination of on-site and virtual work to portray the “New Normal”. The authors aim to analyze the effect of virtual team (VT)-building strategies on virtual team performance and HR performance in the “New Normal” context. This study aims to explore the drivers and barriers to VT performance and its contribution to HR performance.

Design/methodology/approach

The study utilized the grounded theory approach. Semistructured interviews with 114 VT leaders of national and multinational companies in India were conducted and NVivo 8.0 software was used to analyze data.

Findings

VT-building strategies contribute to VT collaboration and subsequently to VT performance. It was found that VT-building strategies catalyze VT collaboration which is impacted by the drivers and barriers of VTs, affecting VT performance and HR performance.

Practical implications

The primary contribution of this work is the development of a framework that delivers important insights to VT leaders, talent managers, HR professionals and academicians.

Originality/value

This study uniquely examines the VT-building strategies and VT performance through the “New Normal” paradigm lens. This study proposes a conceptual model for VT performance and HR performance. It also provides the team-building strategies, drivers and barriers for VT performance. This work offers the roadmap to achieve VT performance and HR performance. This research also contributes to the human resource management literature by discussing the VT performance and HR performance in the “New Normal” paradigm. It provides insights to VT leaders, talent managers, HR professionals and academicians.

Details

Journal of Organizational Effectiveness: People and Performance, vol. 9 no. 4
Type: Research Article
ISSN: 2051-6614

Keywords

Article
Publication date: 15 September 2022

Brijesh Sivathanu, Rajasshrie Pillai and Bhimaraya Metri

The purpose of this study was to investigate the online shopping intention of customers by watching artificial intelligence (AI)–based deepfake video advertisements using…

Abstract

Purpose

The purpose of this study was to investigate the online shopping intention of customers by watching artificial intelligence (AI)–based deepfake video advertisements using media richness (MR) theory and Information Manipulation Theory 2 (IMT2).

Design/methodology/approach

A conceptual model was developed to understand customers' online shopping intention by watching deepfake videos. A quantitative survey was conducted among the 1,180 customers using a structured questionnaire to test the conceptual model, and data were analyzed with partial least squares structural equation modeling.

Findings

The outcome of this research provides the antecedents of the online shopping intention of customers after watching AI-based deepfake videos. These antecedents are MR, information manipulation tactics, personalization and perceived trust. Perceived deception negatively influences customers' online shopping intention, and cognitive load has no effect. It also elucidates the manipulation tactics used by the managers to develop AI-based deepfake videos.

Practical implications

The distinctive model that emerged is insightful for senior executives and managers in the e-commerce and retailing industry to understand the influence of AI-based deepfake videos. This provides the antecedents of online shopping intention due to deepfakes, which are helpful for designers, marketing managers and developers.

Originality/value

The authors amalgamate the MR and IMT2 theory to understand the online shopping intention of the customers after watching AI-based deepfake videos. This work is a pioneer in examining the effect of AI-based deepfakes on the online shopping intention of customers by providing a framework that is empirically validated.

Details

International Journal of Retail & Distribution Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-0552

Keywords

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