Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policyYogesh K. Dwivedi, Laurie Hughes, Elvira Ismagilova et al.|International Journal of Information Management|2019 As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial, intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision-making, engendering new opportunities for continued innovation. The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, realistic assessment of impact, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: business and management, government, public sector, and science and technology. This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.
Applications of text mining in services management: A systematic literature reviewSunil Kumar, Arpan Kumar Kar, P. Vigneswara Ilavarasan|International Journal of Information Management Data Insights|2021 The importance of text mining is increasing in services management as the access to big data is increasing across digital platforms enabling such services. This study adopts a systematic literature review on the application of text mining in services management. First, we analyzed the literature on which has used text mining methods like Sentiment Analysis, Topic Modeling, and Natural language Processing (NLP) in reputed business management journals. Further, we applied visualization tools for text mining and the topic association to understand the dominant themes and relationships. The analysis highlighted that social media analysis, market analysis, competitive intelligence are the most dominant themes while other themes like risk management and fake content detection are also explored. Further, based on the analysis, future research agenda in the field of text mining in services management has been indicated.
Perceived usefulness, ease of use and user acceptance of blockchain technology for digital transactions – insights from user-generated content on TwitterPurva Grover, Arpan Kumar Kar, Marijn Janssen et al.|Enterprise Information Systems|2019 Although blockchain has attracted a great deal of attention from academia and industry there is a lack of studies on acceptance drivers. This study explores blockchain acceptance by mining the collective intelligence of users on Twitter. It maps blockchain user acceptance drivers to technology acceptance constructs. The analysis shows that users are attracted by security, privacy, transparency, trust and traceability aspects provided by blockchain. On Twitter more discussions on blockchain benefits than on drawbacks. Initial coin offering (ICO) is extensively discussed. The study provides guidelines for managers and concludes by presenting the limitations of the study along with future research directions.
Search engine marketing is not all gold: Insights from Twitter and SEOClerksReema Aswani, Arpan Kumar Kar, P. Vigneswara Ilavarasan et al.|International Journal of Information Management|2017 Social media content and product co-creation: an emerging paradigmPurpose – The purpose of this paper is to conceptualise and discuss the possible insights that can be generated for product development by analysing the user-generated content available from various social media platforms. Design/methodology/approach – The paper reviews the role of user generated content in developing products and its features (e.g. appearance and shape). It delineates the directions in which the relationship between social media content and customer oriented concepts evolve while developing successful new products. Findings – The review and arguments presented in this paper suggest that the social media approach adds more value than the traditional approaches for obtaining insights about the products. Availability of users’ opinions and information about existing products provide insights for the improvement in the product design process. Co-creation and self-construal are important components that are based on customer engagement and customer behaviour, respectively, in the product design and development. Practical implications – As social media creates new ways of communication with users, businesses can include users into the product development process to improve and refine their products or for making the next generation of products. Originality/value – This paper suggests a new approach in getting useful insights about the products from user-generated contents. This way of using social media helps businesses to move forward from the traditional product development paradigms.