Editorial

Greetings from the Editor’s desk!

While we bring 2024 to a close with the final issue of the year, it is my pleasure to wish all readers a very happy new year 2025. The IIMB Management Review team looks forward, with your support, to progress apace in the journey towards academic and research excellence and reaffirm its commitment to the highest standards of scholarship.

The journal also co-hosts the IMR Doctoral Conference (IMRDC), and we are happy to say that our review committees are in the process of selecting the papers for final presentation at the 16th edition of IMRDC, scheduled on the 17th and 18th of January, 2025. The highlights of IMRDC 2025 include a keynote address by Professor Viral Acharya, C.V. Starr Professor of Economics, New York University Stern School of Business (NYU-Stern) and former Deputy Governor of the Reserve Bank of India (RBI), and a panel discussion on the academic job market in India focussing on the opportunities for PhD students graduating from business schools. We welcome all of you to attend the conference as delegates, either in person or virtually. We invite you to visit the IMRDC 2025 website for more details at https://www.iimb.ac.in/imrdc2025/

Following is a brief introduction to the contents of this issue.

In the context of the surge in AI adoption in standard business processes in the recent past, in  Effect of automation of routine and non-routine tasks on labour demand and wages”, Arvind Upreti and V Sridhar explore the effects of automation of routine and non-routine tasks on the employment of low-skill and high-skill workers by constructing an agent-based model considering the profit-maximising behaviour of firms. Their model considers three types of agents – firms, high-skill workers, and low-skill workers. In the computational model, they consider four cases to study the employment effects of automation on low-skill and high-skill workers. These cases are positioned at the intersection of the firm’s strategy to either automate routine or non-routine tasks and the skill acquisition strategy of workers to cross-skill in tasks that have not been automated.

The simulations suggest that if the objective is to reduce wage inequality between the different classes of workers, the automation of non-routine tasks is preferable. However, if the objective is to increase the demand for both low-skill and high-skill workers, then automation of routine tasks is preferable, with no restrictions on different classes of workers competing amongst themselves to get the job.

This research indicates that extreme task automation without job mobility between low-skill and high-skill workers can negatively affect overall employment and wage inequality. Assisting workers in reskilling and performing tasks requiring more human-centric skills yields better overall labour market outcomes. Policymakers and industries should establish reskilling programmes for workers affected by automation to enhance labour well-being.

Vighneswara Swamy, Munusamy Dharani, and Fumiko Takeda underscore the role of investor sentiment in predicting stock markets, and the rise in the prominence of social media-based proxies for investor sentiment. In “Does Twitter happiness predict bullish markets? a study of the US stock markets,” they investigate whether Twitter happiness, measured by the Twitter Sentiment Index (TSI), predicts stock market performance across seven US indices. According to the Pew Research Center (2021), Twitter is the most popular social media app in the US. The TSI analyses sentiment in stock market related tweets to gauge investor contentment.

Using panel data for the period ranging from September 9, 2008 to April 30, 2018, they examine the two main hypotheses, namely (i) there exists a nonlinear effect of TSI on the stock market indices in the US and (ii) in the short run, Twitter happiness has a stronger effect and a relatively weak effect in the long run on the US stock market indices. The study applies cointegration techniques and a nonlinear autoregressive distributed lag model to capture both short-run and long-run effects of Twitter sentiment on stock markets.

The results establish the long-run association between the TSI and stock market indices. Two main findings are: (i) there exists a dynamic nonlinear cointegrating relationship between the social media content-based proxy of investor sentiment, that is, TSI and stock market index performance, and (ii) Twitter happiness significantly impacts stock market indices in the short run and has a comparatively weaker effect in the long run. The findings have implications for various stakeholders, including regulators, legislators, stock exchanges, investors, and the research community.

Sweta Tiwari, Chanchal Chatterjee, and Pooja Sengupta preface their study with the observation that firms often make strategic use of textual narratives while disclosing their financial reports in public. In “Effect of earnings management and cash holdings on annual report readability: Evidence from top Indian companies”, the authors explore the impact of earnings management (EM) on the readability of the Management Discussion and Analysis (MDA)  section of annual reports of 384 Indian firms listed in one of the Indian stock exchanges, for 1,160 firm-year observations, from 2014 to 2020. They develop the hypothesis that the financial condition of firms can be interpreted from the complexity of the financial disclosure. They employ multiple indices as proxies of readability and discretionary accruals obtained from the modified Jones model (1995) and the Raman and Shahrur (2008) model as proxy of EM.

The results suggest that Indian firms, which meet or just beat the prior year earnings-per-share  and manage earnings, make MDA more complex. This result holds when cash holding is included as an explanatory variable. Overall, they find that firms with less readable disclosures tend to maintain higher level of cash. They test the robustness of their findings by controlling the impact of different years, including the COVID-19 crisis period. The results are consistent across all years, including firm fixed effect and lagged EM variables. The authors contend that given the paucity of studies focusing on the readability of text in the Indian context their study provides new contribution to existing literature by adopting the obfuscation hypothesis.

In Electricity trade at exchanges of the world: Contextual analysis of Indian electricity exchanges”, Rajesh Gupta and Atulan Guha investigate the relationship between price and volume of the electricity traded at exchanges world over in the period ranging from 2015 to 2020. Additionally, they examine the operational mechanisms and dynamics at play within the Indian electricity exchanges. Their study makes a case for focusing on the consumer welfare perspective as the business of electricity progressively transitions towards exchanges.

Their analysis of electricity exchanges in 20 countries found that increasing the share of exchange-traded electricity in the country is crucial for reaping the price advantage expected from the mechanism of a commodity exchange. Despite being declared a power surplus  economy and having electricity exchanges for the last 13 years, electricity tariffs have been higher  in India than in many developed countries and continue to rise. The creation of power exchanges in India has not yet translated into competition. Electricity exchanges in India seem to benefit private electricity producers and distribution companies (DISCOMs) at the cost of consumers.

Policymakers interested in the design of the electricity markets grapple with the question of the efficacy of exchanges as a market mechanism to improve social welfare. This study offers two probes to test this efficacy: the rate of increase of the share of electricity traded at exchanges and the relationship of changes in the day-ahead-market price with the change in exchange-traded electricity (as a share in the total electricity procured in the country). Debate around these issues can generate much needed awareness about the role of electricity exchanges in emerging economies in general and in India.

Geographical indication (GI), a form of collective intellectual property rights that identifies a good originating in a particular geographical region, has been actively promoted by governments in developing countries for agricultural goods,  as a tool for regional socio-economic development as also for its presumed positive effect on agricultural exports. Observing that the literature studying GI and its impacts has been limited within the Indian context, mainly restricted to a few product-specific case studies, in “Blessing of geography: Impact of geographical indications on agricultural exports in India”, Manu Bansal and Rahul Singh study the effect of GIs on agricultural exports for the full spectrum of agricultural commodities in India.

They combine a dataset of state-product-year level exports with data on registered GIs for agricultural products from 2004 to 2016. They rely on a difference-in-differences framework comparing the changes in exports for GI-registered state products (treated) with other state-product observations that do not receive GI registration (control).

Their key finding is that GIs on agricultural products do have a significant positive effect on state-product level exports. Further, the effect of GI on exports is differentially higher for states with better judicial efficiency, better road and rail infrastructure, and government-owned GIs. They also observe a shift in cropping pattern in favour of crops with the GI tag as a potential explanation for the increased production of GI products. The results add to the ongoing discussion over the impact of GIs, indicating that the effect of market expansion is more pronounced compared to the market power effect in the context of GIs.

In “Nightmare in remote mode – Evidence of remote abusive supervision in Indian organisations”, Munmun Goswami and Lalatendu Kesari Jena aim to address whether and how abusive supervision occurs remotely in the Indian context.  On the basis of the conservation of resources theory and the cognitive appraisal theory, they attempt to investigate how the employee's experience of remote abusive supervision increases obsessive work passion, which spills over to their life domain, causing work-to-life conflict thus adversely impacting their life satisfaction. They  also focus on the moderating role of ICT usage in the above relations through the underpinning of self-determination theory.

They envisage that remote abusive supervision drains resources (environmental factor), forcing an individual to work harder and longer (perception), resulting in obsessive work passion (action–coping). Focusing more on work creates strain in their personal life (resource drain), thus resulting in work-life conflict; this, in turn, lessens their life satisfaction experiences. ICT usage during nonworking hours at home is a negative deterrent, as time is spent (a limited resource), which could be used to attend to demands in the life domain.

They collected data during the third wave (early 2022) of the Covid19 pandemic in India. Hypotheses were tested using structural equation modelling SEM from 236 adults working from home in an Indian ITES company. Results supported their hypothesised model. Remote abusive supervision was found to be negatively related to life satisfaction, and the relationship was positively mediated by obsessive work passion and work-to-life conflict. Additionally, ICT usage moderates between obsessive work passion and work-to-life conflict and satisfaction.

In “Freelancing: A journey towards personal and organisational triumph”, Monica Kunte, Sonali Bhattacharya, and Netra Neelam explore the work restructuring that has happened in various organisations in the new normal adopted in the post-pandemic world, along with its enablers and challenges. The decisions made during restructuring are explained through the theory of rational choice, where both individuals and organisations tend to make choices which give them optimum returns. They propose an integrated model, taking cues from the psychological capital theory, which defines how employees’ psychological resources can be capitalised to achieve work resiliency and performance. Notably, initiated interdependency and received interdependency are the exogenous constructs that form the resource input. Learning orientation and work resiliency, on the other hand, are the mediating constructs that form the nodes of process pathway. Personal vision refers to the work performance related outcome construct.

They use covariance-based structural equation modelling to analyse the cause-and-effect relationship between their constructs. They collate data from 120 large, medium, and small manufacturing and IT companies in India, with a total of 886 responses, obtaining a response rate of 88.6%. The study found that initiated work interdependence does increase learning orientation, which in turn aids in developing work resilience and personal vision. Although initiated interdependence has an inverse relationship with work resilience, by mediating through learning orientation, it effectively strengthens work resilience and personal vision. The key feature of work restructuring was found to be the emergence of the gig economy, with conducive internal and external business environments as its facilitators.

Looking forward to your continued engagement with the journal,

With best wishes,

Sushanta Kumar Mishra

Editor-in-Chief

IIMB Management Review

Email address: eic@iimb.ac.in

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