IIMB Management Review最新文献

Robo-advisors are still in their nascent stages of use, and this technology has yet to find wider acceptance with investors. Our study extends the domain of technology acceptance to robo-advisors by identifying the drivers of investor adoption. Investment decisions carry high risks; thus, there is a greater need to understand investor behaviour to adopt robo-advisors. Trust, anxiety, performance expectancy, and preference for human advisors are used as variables to predict investors’ intentions. PLS-SEM is employed to examine the data with a sample size of 445 investors. Results suggest that all these variables play a significant role in determining the behavioural intention of investors towards the adoption of robo-advisors.

This research investigates how investor base affects the cost of equity capital (COE) in Indian companies, particularly in market conditions with weak investor protection and increased ownership concentration by promoters and families. Using ordinary least squares (OLS), panel fixed effects, and two-step system generalised method of moments (GMM) analysis on data spanning from 2016 to 2021, we discovered that a dispersed ownership structure is linked to a higher ex-ante COE. Our findings indicate that companies with dispersed shareholders have less motivation to monitor managers, which leads to the expropriation of minority shareholders and results in higher COE.

We analyse the effect of leverage components and banks’ ‘business model channels’ on risk-taking for Brazilian banks. Using a detailed dataset from the Brazilian financial system, the results show that the measurement of leverage components is relevant for determining banks’ risk. We highlight two important findings. First, we provide novel insights for the design of a generalised method of moments (GMM) estimation using external instruments. Second, the derivative and on-balance-sheet operations are risky for investment and foreign banks. These results provide important information for banking supervision and regulation and bring new insights regarding banks’ leverage behaviour.

The main aim of this paper is to explore the relationship between the nature of products tested to reveal dual quality and customers’ experiences, and for individual organisations to arrive at important guidelines for future solutions to the problem. The data used in this study were provided by the first nationwide survey conducted on a sample of 987 consumers throughout the Slovak Republic. Based on the experiences and opinions of consumers, recommendations were formulated for brand owners offering products with dual quality. Knowing the opinions of consumers will allow companies to adapt their offerings to the market.

In this paper, the autoregressive distributive lag (ARDL) model is used to examine the impact of global crude oil price on manufacturing output in India and the behaviour of consumer price index. Error correction model, co-integration and multivariate GARCH model models are used for the analysis. ARDL analysis shows a significant relation between consumer price index (CPI) and manufacturing index (MI). Also, a significant inverse relation is established between crude oil price with MI and a positive relation between MI and CPI. Despite an inconsistent short run relation between petrol price with CPI, rising fuel price shows dampening impact on manufacturing output in the long run.

The literature on the Indian pharmaceutical industry has examined the importance of product patents and the attempts policy has made to regulate them. However, it has not done the same for the question of brands. Our study addresses this gap. The Tariff Commission Report of 1968, a turning point in the price control policies of the 1960s, is examined. The examination revealed two important points: first, there were attempts to regulate brands through policies; and second, brands were of high importance to all the major industry players. This became evident in the industry's resistance to the government's regulatory efforts.

Management research in India has been strongly impacted by paradigms from the natural sciences. Further, most research in India is dominated by US-based theories that discourage indigenous research. This is an outcome of British impact on knowledge in India during the colonial era and US-driven neo-colonial influences on management knowledge in the post-colonial era. This is dysfunctional as managerial interventions are likely to be based on knowledge that is unsuitable for the context. There is an urgency to correct the situation as AI based tools are changing the way knowledge is created, disseminated, and learnt, hurting indigenous knowledge.