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The purpose of this study is to explore to which extent data mining research would be associated with the library and information science (LIS) discipline. This study aims to identify data mining related subject terms and topics in representative LIS scholarly publications.

A large set of bibliographic records over 38,000 was collected from a scholarly database representing the fields of LIS and the data mining, respectively. A multitude of text mining techniques were applied to investigate prevailing subject terms and research topics, such as influential term analysis and Dirichlet multinomial regression topic modeling.

The findings of this study revealed the relationship between the LIS and data mining research domains. Various data mining method terms were observed in recent LIS publications, such as machine learning, artificial intelligence and neural networks. The topic modeling result identified prevailing data mining related research topics in LIS, such as machine learning, deep learning, big data and among others. In addition, this study investigated the trends of popular topics in LIS over time in the recent decade.

This investigation is one of a few studies that empirically investigated the relationships between the LIS and data mining research domains. Multiple text mining techniques were employed to delineate to which extent the two research domains would be associated with each other based on both at the term-level and topic-level analysis. Methodologically, the study identified influential terms in each domain using multiple feature selection indices. In addition, Dirichlet multinomial regression was applied to explore LIS topics in relation to data mining.

In this paper the authors aim to examine whether shareholder activism is associated with accounting reporting complexity (ARC).

The authors employ ordinary least squares (OLS) and a sample of 19,530 firm-year observations (representing 3,377 unique firms) over the 2010–2019 period to test the prediction.

The authors find that firms with shareholder activism provide more complex accounting reporting. Further, both types of activism (including Concern & Dispute and Control & Discussion) are positively associated with ARC. The authors also find that the association between shareholder activism and ARC is more pronounced when the firms have a higher level of litigation risk and a higher proportion of institutional ownership. Collectively, the findings suggest that firms with shareholder activism may be under more pressure to disclose more accounting items, leading to more complex accounting reporting.

The study may be informative to regulators considering the costs and benefits of shareholder activism in financial reporting.

The purpose of this study is to provide a holistic view of the emergence of shareholder activism (SA) in India. However, specifically, this study aims at fulfilling the research gap by discussing the policy and legal advancement in the area of SA and investigating the chronological evolution of SA, manifestations of SA, motives of SA, outcome of SAs and impact of SA on the financial performance of the firm.

This study used a mixed methodology (both qualitative and quantitative) to draw inferences, including content analysis, descriptive statistics, independent sample t-test and paired sample t-test. The data has been collected from the annual reports of the sample companies and the Prowess database. Return on assets and return on equity have been used as measures of financial performance while investigating the difference in financial performance between firms subjected to SA and firms not subjected to SA.

The findings of this study suggest that there has been significant growth in the occurrence of SA incidents in India in the past decade, with shareholders prominently manifesting by opposing the proposals at annual general meetings/extraordinary general meetings, mostly involving governance-related demands. The findings from the independent sample t-tests revealed that there has been a significant difference in the financial performance of the sample subjected to SA and firms not subjected to SA. Furthermore, the results of the paired sample t-test provide strong evidence of significant improvement in the financial performance of firms’ post-SA.

The findings of this study have implications for various stakeholders. The findings of this study suggest that SA has been relatively more successful in the Indian context and may encourage minority shareholders to follow active participation through shareholder proposals and votes rather than a passive strategy to trade and exit. For firms, it can provide valuable inferences about the emergence of SA and how it has a positive impact on the financial performance of the firm, which can lead to a change in the perception of investors and promoters who perceive SA as a threat (Gillan and Starks 2000; Hartzell and Starks, 2003). For policymakers, it can act as a tool to investigate whether the regulatory changes have been able to bring the intended transparency, accountability and enhanced shareholder participation. This will encourage policymakers to be more agile, as their efforts are bearing fruit. This will also act as a guide to formulating future policies and regulations.

This study is an effort to provide a holistic view of SA scenarios in a developing economy setting like India, where SA is a very recent phenomenon. Although there are studies in the area of SA, there is a dearth of studies that have investigated the various dimensions of SA in the Indian context in a very systematic and extensive manner, investigating all the different dimensions of SA. Furthermore, this study also intends to investigate the impact of SA, which is normally perceived as a threat to financial performance and provide valuable contrasting evidence.

In this study, we develop understanding of factors that shape the propensity of market incumbents to collaborate in response to the threat posed by new market entrants. We are particularly interested in instances when a market's competitive structure becomes unsettled by new entrants who engage in nonconforming strategic tactics. In such situations, we propose two factors – strategic similarity among competitors and market-share instability – will systematically shape competitors' collaborative response to new entrants. To test our theory, we use data on strategic tactics and collaborative dynamics in the US airline industry from 1989 to 2010. We demonstrate that greater strategic similarity among a market's incumbents increases the likelihood of cooperation in response to the threat of a nonconforming new entrant, while greater market-share instability reduces cooperative response. Through this study, we extend existing understanding of the contextual circumstances under which established competitors recognize their mutual interests and band together.

Sustainable management requires companies to build up new knowledge to acquire the competencies needed for action. This chapter aims to deliver knowledge about sustainability and knowledge for sustainability. Firstly, we systematically analyse the sustainability literature in the social sciences through a bibliographic analysis and topic modelling using VOSviewer and Mallet software. We outline research directions, themes and critical contributions for each research cluster identified. Additionally, we categorise over 30 definitions of sustainability identified by Meuer, Koelbel, and Hoffmann (2020). Secondly, we enumerate knowledge types needed for effective sustainability transitions of organisations. We trace typologies of sustainable business models and their distinct evaluations of sustainability. In this chapter, we argue that integrating the triad of social, ecological and economic goals is central for sustainability attempts as well as long-term thinking. Therefore, our research offers a comprehensive overview of sustainability in the social sciences supporting researchers and practitioners to navigate this miscellaneous and scattered field. Accordingly, our study is precious to young scholars researching sustainability who want to use the term in an informed and meaningful way.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.