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Article
Publication date: 6 August 2021

Farheen Mujeeb Khan and Yuvika Gupta

This study aims to contribute to literature on mobile learning (m-learning) by proposing four research clusters whereby scholars can expand m-learning research to facilitate…

Abstract

Purpose

This study aims to contribute to literature on mobile learning (m-learning) by proposing four research clusters whereby scholars can expand m-learning research to facilitate effective learning experiences for students.

Design/methodology/approach

This study reviews student-centric literature on m-learning since 2010 and presents insights on m-learning while applying well-established bibliometric techniques. Consequently, 722 articles published in the past decade were evaluated by identifying key research areas, most influential authors, countries, journals and organisations. Most influential studies based on number of citations were also examined.

Findings

Through article co-citation analysis, four clusters representing m-learning literature were identified: concept of m-learning, application of m-learning in education, designing framework for model learning/acceptance and emerging technologies.

Originality/value

As mobile learning (m-learning) has undergone an evolution from being an emerging field to a significant teaching and research tool, it is pertinent to explore and identify the trends of m-learning research.

Article
Publication date: 5 April 2024

Yuvika Gupta and Farheen Mujeeb Khan

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular…

Abstract

Purpose

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

Design/methodology/approach

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Findings

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

Research limitations/implications

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

Practical implications

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

Originality/value

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 7 September 2023

Yuvika Gupta, Farheen Mujeeb Khan, Anil Kumar, Sunil Luthra and Maciel M. Queiroz

With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research…

Abstract

Purpose

With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research in this domain is limited. Accordingly, the present research seeks to understand how big data analytics capabilities (BDAC) add value to tourism supply chains (TSCs) and can dynamic capabilities (DC) improve the triple bottom line.

Design/methodology/approach

Data from 218 valid responses were collected from different Indian tourism industry units. Confirmatory factor analysis (CFA) was applied to confirm the constructs, followed by partial least squares structural equation modelling (PLS-SEM) to check the mediating effect of DC on TSCs performance.

Findings

The findings show that BDAC significantly influence the performance of TSCs and that DC plays a critical role in strengthening the impact of BDAC on TSCs' economic performance. These results corroborate that DC plays a key moderating role.

Research limitations/implications

This study contributes significantly to the tourism sector in India, where tourism is a key contributor to the country's gross domestic product. Theoretically, this study contributes to the resource-based view (RBV) and practically encourages professionals in the tourism sector to promote the use of BDAC to enhance the performance of TSCs.

Originality/value

The originality of the study is that it has tried to comprehend the moderating role of dynamic capabilities which impact BDAC to improve TSC performance.

Details

The International Journal of Logistics Management, vol. 35 no. 2
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 28 June 2023

Vishal Goel, Balakrishnan R. Unny, Samik Shome and Yuvika Gupta

This study aims to conduct a systematic literature review and bibliometric analysis on the topic of digital labour. The study also identifies the future research directions for…

Abstract

Purpose

This study aims to conduct a systematic literature review and bibliometric analysis on the topic of digital labour. The study also identifies the future research directions for the topic.

Design/methodology/approach

In total, 118 research papers were identified and reviewed from 11 established research databases and A*, A and B category journals from the ABDC journal list. The papers covered a timespan between 2006 and 2023. Bibliometric analysis was conducted to identify key research hotspots.

Findings

The emergent themes and associated sub-themes related to digital labour were identified from the literature. The paper found three significant themes that include digital labour platform, gig economy and productivity. This study also acts as a platform to initiate further research in this field for academicians, scholars, industry practitioners and policymakers. The future research scope in the topic is also presented.

Originality/value

The present study is unique in its nature as it approaches the topic of digital labour from all relevant perspectives.

Details

International Journal of Organizational Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1934-8835

Keywords

Article
Publication date: 12 August 2021

Mansi Tiwari, Yuvika Gupta, Farheen Mujeeb Khan and Amit Adlakha

The purpose of this paper is to identify the viability of the extended Unified Theory of Acceptance and Use of Technology Model 3 (UTAUT3) model among the teachers especially…

Abstract

Purpose

The purpose of this paper is to identify the viability of the extended Unified Theory of Acceptance and Use of Technology Model 3 (UTAUT3) model among the teachers especially during COVID-19 towards the use of technology.

Design/methodology/approach

An extensive primary survey has been conducted through a well-structured tool under UTAUT3 model. The survey is conducted among 450 teachers from various institutions taken for the study. The data was collected from the Northern India. The data analysis will be done through the SmartPLS software with application of structural equation modelling (SEM).

Findings

The results are strong for educators and policy makers. It was found that performance expectancy is positively related to the behavioural intentions among teachers. Teachers consider that usage of technology will boost their job and task performance.

Practical implications

This study has a very strong implications in the field of education in case or replacement of traditional teaching patterns with modern one during pandemic times. It will be effective if teachers would prioritize their work. There will be more effective teaching and learning system in future.

Originality/value

The study validates the constructs of UTAUT3 model in understanding teachers' behaviour and attitude towards technology acceptance. Furthermore, the study invites research from different viewpoint to investigate the role of UTAUT3 model in an individuals' behaviour and attitude towards technology acceptance.

Details

Information Discovery and Delivery, vol. 50 no. 3
Type: Research Article
ISSN: 2398-6247

Keywords

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