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Journal Articles | 2022

SEntFiN 1.0: Entity-aware sentiment analysis for financial news

Ankur Sinha, Satishwar Kedas, Rishu Kumar, and Pekka Malo

Journal of the Association for Information Science and Technology

Fine-grained financial sentiment analysis on news headlines is a challenging task requiring human-annotated datasets to achieve high performance. Limited studies have tried to address the sentiment extraction task in a setting where multiple entities are present in a news headline. In an effort to further research in this area, we make publicly available SEntFiN 1.0, a human-annotated dataset of 10,753 news headlines with entity-sentiment annotations, of which 2,847 headlines contain multiple entities, often with conflicting sentiments. We augment our dataset with a database of over 1,000 financial entities and their various representations in news media amounting to over 5,000 phrases. We propose a framework that enables the extraction of entity-relevant sentiments using a feature-based approach rather than an expression-based approach. For sentiment extraction, we utilize 12 different learning schemes utilizing lexicon-based and pretrained sentence representations and five classification approaches. Our experiments indicate that lexicon-based N-gram ensembles are above par with pretrained word embedding schemes such as GloVe. Overall, RoBERTa and finBERT (domain-specific BERT) achieve the highest average accuracy of 94.29% and F1-score of 93.27%. Further, using over 210,000 entity-sentiment predictions, we validate the economic effect of sentiments on aggregate market movements over a long duration.

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Journal Articles | 2022

Neither complements nor substitutes: Examining the case for coalignment of contract-based and relation-based alliance governance mechanisms in coopetition contexts

Rajnish Rai and Mitul Surana

Long Range Planning

Although the extant literature recognizes that the contract-based and relation-based alliance governance mechanisms (AGMs) play a significant role in the success of alliances, the nature of their interplay still remains ambiguous. In this study, we move away from the traditional debate between contract- and relation-based AGMs as substitutes versus complements. Instead, we offer the notion of “fit” or the “coalignment” as a more appropriate frame to explain the interplay between contract- and relation-based AGMs in the coopetition context. We conceptualize ‘Coalignment of Alliance Governance Mechanisms’ (CAGM) as a distinct higher-order construct and outline a methodological orientation to estimate the coalignment of the two forms of AGMs. We conduct a longitudinal study using primary data from 320 matched coopetition alliances in high-technology research-intensive sectors in India and find that the CAGM explains better the impact of governance mechanisms on value creation in coopetition alliances.

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Journal Articles | 2022

Women directors in corporate India, c. 1920–2019

Chinmay Tumbe

Business History

This paper provides a historical background of women’s representation on Indian corporate boards. It studies directory lists for benchmark years of the past century and other sources, to ascertain the trends and challenges over time. Women directors comprised less than 1% of all directors in the 200 leading firms of India until the 1990s, after which the share rose to 2% by 2000 and 5% in 2010. Due to a regulatory push in 2013, women’s representation on the boards of listed firms rose above 16% in 2019. The sharp reduction in board interlocks over time and the rise of public sector units, especially in banking, are some of the factors highlighted in bringing about more gender diversity in Indian corporate boardrooms before 2013. However, the principal mechanism through which women entered corporate boardrooms in India was through family ties, bound within specific castes and communities.

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Journal Articles | 2022

Big-4 auditors and audit quality: A novel firm life-cycle approach

Sonali Jain and Sobhesh Kumar Agarwalla

Meditari Accountancy Research

Purpose – Firm-specific factors such as size, profitability, growth, risk and complexity, in addition to agency-related issues determine both auditor selection and firm life-cycle stage. This paper aims to examine whether and how the effect of Big-4 auditors (B4As) on client firms’ audit quality varies across firms’ life-cycle stages. Design/methodology/approach – The sample comprises 1,813 firm-year observations in India’s emerging economy from 2011 to 2020. The Modified Jones model and Jones (signed, unsigned) model are used to compute discretionary accruals/audit quality. The authors use Koh et al.’s (2015) methodology to determine the firm life cycle. Findings – The authors’ key findings show that the client firms employing B4As have superior audit quality than those employing non-Big-4 auditors (NB4As). The authors also show that the life-cycle stage significantly impacts the relationship between B4As and a firm’s audit quality. Furthermore, B4A client firms report superior audit quality vis-à-vis NB4A firms only in the birth- and decline-stages. The audit quality of growth- and mature-stage B4A and NB4A client firms is not significantly different. Practical implications – Implications for managers include the decision to hire B4As. Given that B4As earn a significant fee premium, managers leading birth- and decline-stage firms should hire B4As, while managers of growth- and mature-stage firms should not. Originality/value – To the best of the authors’ knowledge, this is the first paper to examine the moderating effect of the firm life-cycle stage on the selection of B4As and their impact on audit quality.

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Journal Articles | 2022

Disentangling reciprocal relationships between R&D intensity, profitability and capital market performance: A panel VAR analysis

Amit Karna, Christos Mavis, and Ansgar Richter

Long Range Planning

Research and development (R&D) investments are strategic choices that firms make to create and sustain competitive advantage. Extant literature proposes that firms’ R&D investments and their profitability and capital market performance are reciprocally related. However, the direction of these relationships and their temporal nature are unclear. We take a real options perspective to argue that the long-run firm performance effects of R&D investments are better than their short-term ones, and that the initial level of R&D intensity influences the nature of these relationships. We apply panel vector autoregression (P-VAR) to a sample of 6623 U.S. firms over the 1990–2020 period in order to test our hypotheses. Our results indicate that increases in R&D intensity have negative effects on profitability in the short term, yet these effects diminish relatively quickly. The effects of increases in R&D intensity on capital market performance are positive and persist over time. Consistent with our predictions, they are contingent on the initial levels of R&D intensity and performance. The findings are fundamentally in line with the real options perspective employed here, yet they add important nuance to our understanding of when, how, and under which conditions R&D investments and firm performance affect one another.

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Journal Articles | 2022

How Do MNEs and Domestic Firms Respond Locally to a Global Demand Shock? Evidence from a Pandemic

Arzi Adbi, Chirantan Chatterjee, and Anant Mishra

Management Science

Global shocks bring unanticipated changes in the business environment of foreign multinational enterprises (MNEs) and rival domestic firms. We examine whether there is a difference between how MNEs and domestic firms react in heterogeneous local or subnational markets to a global demand shock. Leveraging the 2009–2010 H1N1 influenza pandemic as a source of exogenous variation in global demand for influenza vaccines, we investigate the role of subnational heterogeneity in economic resources, industry infrastructure, and political alignment within an emerging economy on the behavior of incumbent MNEs and rival domestic firms. We find that following the pandemic, MNE market share in the influenza vaccine market relative to the noninfluenza vaccine markets declines more in regions with lower government health spending per capita and also, in regions unaligned with the federal government. Additional analyses suggest that these changes in market share are not caused by a reduction in MNE revenues. Rather, they are caused by domestic firms that were already present in noninfluenza vaccine markets diversifying by entering the highly related influenza vaccine market. Finally, a granular examination of the differential responses reveals that such responses are not related to preshock differences in regional coverage of MNEs and domestic firms. This study contributes to the extant literature by suggesting that the direct costs or opportunity costs of new market and region entry are relatively greater for MNEs than for domestic firms, particularly in regions that have inadequate health infrastructure and are politically not aligned.

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Journal Articles | 2022

A two-stage integer programming model considering transaction equivalence for privacy preservation

Srikumar Krishnamoorthy

Computers and Operations Research

Preserving privacy is one of the fundamental requirements of firms that share data with their business partners for building advanced data mining models. Firms often aim to protect the disclosure of sensitive knowledge or information discovered during the data mining process. In this study, we investigate the problem of Frequent Itemset Hiding (FIH) which aims to hide sensitive itemset relationships present in a transactional database. We propose a two-stage integer programming model that maximizes the proportion of unaltered transactions in the sanitized database and protects sensitive itemset relationships. The model exploits the concept of transactional equivalence and significantly reduces the size of the FIH problem. In addition, our model enables the identification of solutions with minimal side effects. We conduct an experimental evaluation on both real and synthetic databases to show that our approach is scalable and produces a sanitized database with maximum accuracy. The generated solution is also found to have lower side effects (itemset information loss) compared to other state-of-the-art methods. Our experiments on very large problem instances show problem size reductions of one to three orders of magnitude. The proposed approach is quite attractive and practically useful for solving large-scale FIH problem instances and preserving privacy in increasingly shared and big data-driven organizational environments.

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Journal Articles | 2022

The impact of social reputation features in innovation tournaments: Evidence from a natural experiment

Swanand J. Deodhar and Samrat Gupta

Information Systems Research

This study examines how a change in an online reputation system, specifically the addition of a social reputation feature, affects contestant performance in innovation tournaments. Drawing from the literature on peer recognition and social evaluation anxiety, we project competing effects whereby the feature could either enhance or diminish contestant performance. Furthermore, we hypothesize a series of contingent effects involving the soft reserve, a competitive dynamic that unfolds in tournaments, and a determinant of performance in its own right. Specifically, we hypothesize that the direct influence of the social reputation feature on contestant performance would be predicated on the level of two types of soft reserves in an innovation tournament: that created by the focal contestant and that created by competitors. We test these hypotheses leveraging a natural experiment, where an innovation tournament platform (Kaggle.com) introduced a social reputation feature, allowing contestants to follow other contestants unilaterally. Estimates obtained using a panel data set bracketed within a narrow time window (15 days) around the feature launch reveal that the feature significantly improves the performance. We further report that the two types of soft reserves significantly moderate the positive effect of the social reputation feature on contestant performance, whereby the higher the soft reserve, the weaker the effect of the social reputation feature on contestant performance. These findings have several theoretical and practical implications for managing innovation tournaments.

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Journal Articles | 2022

How COVID-19 lockdown has impacted the sanitary pads distribution among adolescent girls and women in India

Karan Babbar, Niharika Rustagi, and Pritha Dev

Journal of Social Issues

This paper empirically explores the impact of COVID-19 pandemic and its accompanying lockdown on adolescent girls’ and women's access to sanitary pads in India. We have used the National Health Mission's Health Management Information System (NHM-HMIS) data for the study, which provides data on pads' distribution on a district level. The empirical strategy used in the study exploits the variation of districts into red, orange, and green zones as announced by the Indian Government. To understand how lockdown severity impacts access to sanitary pads, we used a difference-in-difference (DID) empirical strategy to study sanitary pads' access in red and orange zones compared to green zones. We find clear evidence of the impact of lockdown intensity on the provision of sanitary pads, with districts with the strictest lockdown restrictions suffering the most. Our study highlights how sanitary pads distribution was overlooked during the pandemic, leaving girls and women vulnerable to managing their menstrual needs. Thus, there is a requirement for strong policy to focus on the need to keep sanitary pads as part of the essential goods to ensure the needs of the girls and women are met even in the midst of a pandemic, central to an inclusive response.

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Journal Articles | 2022

Impostor phenomenon and identity-based microaggression among hispanic/Latinx Individuals in Science, Technology, Engineering, and Mathematics: A Qualitative Exploration

Devasmita Chakraverty

Violence and Gender

Impostor phenomenon is defined as a psychological condition when some successful people do not fully ascribe their success to ability or competence, but attribute it to luck, generosity from others, or misjudgment, thereby experiencing an internal conflict. Microaggression is defined as subtle disparaging behavior that consciously or unconsciously discriminates people based on their background, personal identity, and group membership. Both impostor phenomenon and microaggression are commonly experienced in science, technology, engineering, and mathematics (STEM) fields, especially by women and BIPOC individuals—black, indigenous, or other person of color. Hence, the connection between microaggression and impostor phenomenon among BIPOC individuals needs deeper exploration. This qualitative study examined the research question: How do Hispanic/Latinx PhD students and postdoctorates in STEM describe impostor phenomenon and microaggression based on ethnic identity? U.S.-based participants were recruited using convenience sampling and snowball sampling. Semistructured interviews were conducted with 29 participants who self-reported experiencing impostor phenomenon. Interview transcripts were coded and analyzed inductively using constant comparison to develop themes. Twenty-two of the participants (18 women) experienced microaggression during training based on their Hispanic/Latinx identity. Microaggressive comments were made by faculty members, peers, and others in academia. Microaggression and impostor phenomenon were related through “othering” or feeling like outsiders, creating a sense of (un)belonging in STEM fields.

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