Indian Institute of Management Tiruchirappalli

Abstract: 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.

Abstract: The COVID-19 pandemic has forced many organisations to undergo significant transformation, rethinking key elements of their business processes and use of technology to maintain operations whilst adhering to a changing landscape of guidelines and new procedures. This study offers a collective insight to many of the key issues and underlying complexities affecting organisations and society from COVID-19, through an information systems and technological perspective. The views of 12 invited subject experts are collated and analysed where each articulate their individual perspectives relating to: online learning, digital strategy, artificial intelligence, information management, social interaction, cyber security, big data, blockchain, privacy, mobile technology and strategy through the lens of the current crisis and impact on these specific areas. The expert perspectives offer timely insight to the range of topics, identifying key issues and recommendations for theory and practice.

Abstract: Mobile banking (m-banking) has emerged dynamically over the years due to consumers' increased use of mobile technologies, their ever-growing lifestyle choices and also the several different economic factors. This paper proposes a new research model by extending the DeLone & McLean information systems (D&M IS) success model to understand users’ actual usage of m-banking. The research model was tested and validated using data collected by survey from 227 Omani residents. This study employed a two-staged analytical approach by combining structural equation modeling and neural network analysis. The results divulge that satisfaction and intention to use stand as two important precedents of actual usage, and the satisfaction also mediates the relationship between service quality, information quality and trust with intention to use m-banking and negates with that of system quality. We have provided the theoretical as well as practical implications of the findings.

Abstract: Due to green legislations, industries track the used products through reverse logistics contractors. A reverse logistics programme offers significant cost savings in procurement, transportation, disposal and inventory carrying. Since reverse logistics operations and the supply chains they support are considerably more complex than traditional manufacturing supply chains, it can be offered to third party contractors. But availability of more number of contractors make evaluating and selecting the most efficient Reverse Logistics Contractor (RLC) a challenging task and treated as a multi-criteria decision making problem. In this paper, a hybrid method using Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is proposed. AHP is used to obtain the initial weights and Fuzzy TOPSIS is used to get the final ranking. A case study demonstrates the application of the proposed method. Finally sensitivity analysis is carried out to confirm the robustness.

Abstract: We extend the “institutional voids” perspective on business groups by examining the value-adding potential of two of the characteristic features of business groups: their diverse portfolio and multi-entity organizational form. We maintain that portfolio diversity affords affiliates privileged access to opportunities hidden by incomplete strategic factor markets. We hypothesize that the multi-entity organizational form enables superior sensing and seizing of these growth opportunities by affiliate firms. We further suggest that, in the context of institutional reforms, these characteristics strengthen business group affiliates' ability to capitalize on the expanded set of opportunities made available by the reform program. Empirical analyses on a sample of Indian firms over the period 1994–2010 support our hypotheses. Implications for theory and future directions are discussed