IIMB Management Review最新文献

Predicting the success of a dyadic relationship during the very early stage of a relationship is quite critical since the existing SCDR elements have limited capabilities. Drawing on transaction cost economics and social exchange theory (SET), this study aims to explore and enhance the SCDR measurement tools that can likely predict putative relationship success. Using mixed methods in a longitudinal study, the research used qualitative interviews with an expert panel of supply chain practitioners and then surveys of selected dyads. Results show that culture matching is perceived to be a key element of the revised SCDR tool, one that will likely predict relationship success. The enhanced tool helps managers to comprehend the importance of organisational culture and its critical role in predicting the dyadic relationship success.

Do firms generate financial flexibility by retiring debt? Using Indian data, we document that firms channel approximately 39% of current cash flow to repay debt. This higher debt-cash flow sensitivity facilitates firms to maintain investment in the future. Firms prioritise reducing dependency on external finance, increasing investments, and saving cash in the short run. In the long run, firms enhance investments primarily through borrowing. Unlike in developed markets, we find that Indian firms respond symmetrically to positive and negative cash flow shocks by changing their borrowing.

The paper critically evaluates the bottlenecks inherent in India's low carbon value chain that is financed by green bonds and related debt securities. The paper identifies three cardinal limitations of the value chain viz. unviable carbon mitigation projects, insufficient market competitiveness of green bonds issued from India and the inability of refinancing institutions to securitise their liabilities and overcome the problem of asset-liability mismatch. It is argued that a climate financial architecture that overcomes these limitations provides important lessons to the ongoing global efforts to strengthen the financial mechanisms laid down by the Paris Agreement on Climate Change.

This study examines the effect of pandemic-induced uncertainty on cryptocoins (Bitcoin, Ethereum and Ripple). It employs the Westerlund and Narayan (2012, 2015) predictive model to examine the predictability of pandemic-induced uncertainty and our model's forecast performance. We examine the role of asymmetry in uncertainty and the sensitivity of our results to the recently-developed Salisu and Akanni (2020) Global Fear Index. Cryptocoins act as a hedge against uncertainty due to pandemics, albeit with reduced hedging effectiveness in the COVID-19 period. Accounting for asymmetry improves predictability and model forecast performance. Our results may be sensitive to the choice of measure of pandemic-induced uncertainty.

The purpose of this paper is to establish and estimate the extent of the volatility anomaly (VA). We examine the impact of the beta, variance, relative-beta, and relative-variance measures on the stock returns for NIFTY500 companies, for the 10-year period 2010-2020. Our empirical findings suggest that the VA is predominant in the medium to long-term, but seems to be negligible in the ultra-short and short time frames. The overall findings suggest that the VA is most significant when the time period considered is three years or more. These results can be highly useful for investors as well as portfolio managers.

We study the socio-cultural ecosystems, along with cross-country investments and global flow of foreign capital in a local milieu, India, having multiple stock exchanges and listed firms. India's varied investor profiles exhibit a marked preference for certain “special” days given their religious beliefs. This study tests the abstinence hypothesis to examine the “new moon day” effect, considered inauspicious by the local dominant investing community, and the duality of minds, based on India's annual festival, Diwali, considered auspicious to make investments and commence any wealth-generating activity (Muhurat trading). We find that the Indian markets generate a significant negative return on a Friday new moon day and a significant positive return on the Muhurat trading day. We propose a profit-making trading strategy that exploits the impact of the new moon day.

This study examines the impact of individual-level factors on organisations' escalation of commitment (EOC) using self-justification theory and institutional perspective. We use the Cox proportional hazard model on Indian Premier League (IPL) players’ data from 2008 to 2019 to test the proposed hypotheses. We find that player sunk cost (salary paid), reputation, and high status are positively related to the IPL team's EOC (player survival in the same team) for the particular player. Results show that player reputation and high status positively moderate the relationship between player level sunk cost and the IPL team's EOC for the particular player.

The VIX index is an indicator of the market's perception of risk, and an accurate forecast of the movements in VIX can be very useful for investment risk management. So, the aim of this study is to predict the day-to-day movement of the India VIX using six deep learning architectures. All six architectures performed well and achieved a higher level of accuracy with minor differences than in previous studies. The findings of the study are of great relevance for assessing short-term risk as well as long-term strategies for hedgers, risk-averse investors, volatility traders, investors, and financial researchers.