On Predicting ESG Ratings Using Dynamic Company Networks

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Ang, Gary; Guo, Zhiling; Lim, Ee-Peng

Abstract: Environmental, social and governance (ESG) considerations play an increasingly i ... Expand

Abstract: Environmental, social and governance (ESG) considerations play an increasingly important role due to the growing focus on sustainability globally. Entities, such as banks and investors, utilize ESG ratings of companies issued by specialized rating agencies to evaluate ESG risks of companies. The process of assigning ESG ratings by human analysts is however laborious and time intensive. Developing methods to predict ESG ratings could alleviate such challenges, allow ESG ratings to be generated in a more timely manner, cover more companies, and be more accessible. Most works study the effects of ESG ratings on target variables such as stock prices or financial fundamentals of companies, but few works study how different types of company information can be utilized to predict ESG ratings. Previous works also largely focus on using only the financial information of individual companies to predict ESG ratings, leaving out the different types of inter-company relationship networks. Such inter-company relationship networks are typically dynamic, i.e., they evolve across time. In this paper, we focus on utilizing dynamic inter-company relationships for ESG ratings prediction, and examine the relative importance of different financial and dynamic network information in this prediction task. Our analysis shows that utilizing dynamic inter-company network information, based on common director, common investor and news event-based knowledge graph relationships, can significantly improve ESG rating prediction performance. Robustness checks over different time-periods and different number of time-steps in the future further validate these insights. Collapse

Topics: shapley additive explanation knowledge graph database system missing data network effect

Methods: machine learning econometric modeling longitudinal research Granger causality robustness check

Extended Generativity Theory on Digital Platforms

2023 | Information Systems Research | Citations: 2

Authors: Fürstenau, Daniel; Baiyere, Abayomi; Schewina, Kai; Schulte-Althoff, Matthias; Rothe, Hannes

Abstract: The assumption that generativity engenders unbounded growth has acquired an almo ... Expand

Abstract: The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growth in the context of a digital platform. To do this, we synthesize the literature on generativity into two views, social interaction (expansion of ecosystem boundaries) and product view (expansion of product boundaries), that jointly and individually relate to user base growth. Both views help us explain how opening a platform relates to the emergence and resolution of conflicting expectations in a platform ecosystem that result in new functions and expanded use. We adopt a panel vector autoregressive approach combining data from six large transaction platforms that engaged with open-source developer communities. We found that the dominant narrative of generativity engendering growth, although generally supported by our analysis, obscures the fact that the inverse is also true; that is, growth can lead to expansion of product boundaries (inverse generativity) and that generativity can be bounded; that is, growth can stabilize ecosystem boundaries (bounded generativity). Against this background, we propose an extended generativity theory that presents generativity and growth in an integrative view and raises awareness about the limitations of the “unbounded growth” claim. We conclude that there is value in separating the two views of generativity conceptually and analytically, along with their relationship to user base growth, and we call for research on the pathways through which generativity produces growth. History: Ola Henfridsson, Senior Editor; Robert Wayne Gregory, Associate Editor. Collapse

Topics: digital platform innovation management open source electronic commerce accounting

Methods: longitudinal research Granger causality time series analysis Student's t-test parametric test

Innovation Novelty and Firm Value: Deep Learning based Text Understanding

2023 | International Conference on Information Systems | Citations: 0

Authors: HU, Wei; CHAN, Yuk Yee; HUANG, Jianming; Zhou, Wanyue; Li, Xin

Abstract: Innovation is widely acknowledged as a key driver of firm performance, with pat ... Expand

Abstract: Innovation is widely acknowledged as a key driver of firm performance, with patents serving as unique indicators of a company's technological advancements. This study aims to investigate the impact of textual novelty within patents on firm performance, focusing specifically on biotechnology startups listed on the Nasdaq. Utilizing deep learning-based approaches, we construct measures for semantic originality in patent texts. Through panel vector autoregressive (VAR) analysis, our empirical findings demonstrate a positive correlation between textual novelty and abnormal stock returns. Further, impulse response function analysis indicates that the impact of textual novelty peaks approximately one week after patent issuance and gradually diminishes within a month. These insights offer valuable contributions to both the theoretical understanding and practical application of innovation management and strategic planning. Collapse

Topics: innovation management organizational value organizational productivity missing data strategic management

Methods: BERT descriptive statistic deep learning Granger causality data transformation

FINFLUENCERS: OPINION MAKERS OR OPINION FOLLOWERS?

2023 | European Conference On Information Systems | Citations: 0

Authors: Haase, Frederic; Rath, Oliver; Kurka, Marco; Schoder, Detlef

Abstract: This paper explores the concept of Finfluencers: financial social network actor ... Expand

Abstract: This paper explores the concept of Finfluencers: financial social network actors with high potential social influence. Our research aims to clarify whether Finfluencers drive or are influenced by the broader social network sentiment, thereby establishing their role as either opinion makers or opinion followers. Using a dataset of 71 million tweets focusing on stocks and cryptocurrencies, we grouped actors by their social networking potential (SNP). Next, we derived sentiment time series using state-ofthe-art sentiment models and applied the technique of Granger causality. Our findings suggest that the sentiment of Finfluencer actors on Twitter has short-term predictive power for the sentiment of the larger group of actors. We found stronger support for cryptocurrencies in comparison to stocks. From the perspective of financial market regulation, this study emphasizes the relevance of understanding sentiment on social networks and high social influence actors to anticipate scams and fraud. Collapse

Topics: Twitter social network social influence cryptocurrency social media

Methods: longitudinal research time series analysis Granger causality descriptive statistic sentiment analysis

Derivative Work in Open-license Platforms

2023 | International Conference on Information Systems | Citations: 0

Authors: Joo, Heejin; Maruping, Likoebe

Abstract: The emergence of derivative works in open-license platforms has sparked inquiri ... Expand

Abstract: The emergence of derivative works in open-license platforms has sparked inquiries regarding their impact on original works and the platform as a whole. While it is widely recognized that derivative works may compete with the original content, there are also arguments that they can augment traffic and engagement. This remains an open empirical question. We extend the conceptualization of derivative works to open-license platform environments and then explore the implications of such works. Our empirical analysis of original music videos and corresponding reaction videos on YouTube shows that derivative works are complementary to original works and to the platform ecosystem. The findings shed new light on both the complex impact of derivative videos in open-license environments -as well as its broader strategic significance for platform operators seeking sustainable long-term growth opportunities. Collapse

Topics: digital ecosystem YouTube application programming interface intellectual property business model

Methods: Granger causality longitudinal research theory development field study vector autoregression

Improved healthcare disaster decision-making utilizing information extraction from complementary social media data during the COVID-19 pandemic

2023 | Decision Support Systems | Citations: 0

Authors: Kellner, Domenic; Lowin, Maximilian; Hinz, Oliver

Abstract: Managing an extreme event like a healthcare disaster requires accurate informati ... Expand

Abstract: Managing an extreme event like a healthcare disaster requires accurate information about the event's circum­ stances to comprehend the full consequences of acting. However, information quality is rarely optimal since it takes time to determine the information of relevance. The COVID-19 pandemic showed that even official data sources are far from optimal since they suffer from reporting delays that slow decision-making. To support decision-makers with timely information, we utilize data from online social networks to propose an adaptable information extraction solution to create indices helping to forecast COVID-19 case numbers and hospitalization rates. We show that combining heterogeneous data sources like Twitter and Reddit can leverage these sources' inherent complementarity and yield better predictions than those using a single data source alone. We further show that the predictions run ahead of the official COVID-19 incidences by up to 14 days. Additionally, we highlight the importance of model adjustments whenever new information becomes available or the underlying data changes by observing distinct changes in the presence of specific symptoms on Reddit. Collapse

Topics: Twitter Reddit social media pandemic website

Methods: BERT information extraction computational algorithm autoregressive integrated moving average time series analysis

Cryptocurrency Market: The Interplay Between Microblog Dynamic Opinion Leader Sentiments and Bitcoin Pricing

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Treku, Daniel; Wang, Bin; Escobari, Diego; Oraby, Tamer

Abstract: The relationship between tweet sentiment and cryptocurrency pricing has drawn a ... Expand

Abstract: The relationship between tweet sentiment and cryptocurrency pricing has drawn academic researchers' attention in recent years. However, empirical results have been inconsistent, and no research has examined the bidirectional relationship between cryptocurrency pricing and tweet sentiment nor the impacts of opinion leaders. In this research, we test the presence of bidirectional relationships between Bitcoin opinion leader tweet sentiments and Bitcoin price behaviors. By analyzing a big data set of 78 million Bitcoin-related tweets from 2014 to 2021 through vector autoregression modeling with exogenous variables, we reveal the influences of Bitcoin opinion leaders' tweet subjectivity and polarity on Bitcoin price return and volatility, as well as the reverse effects. Our research contributes to academic literature and business practice on cryptocurrency pricing, social media, and opinion leadership. KeywordsBitcoin cryptocurrency returns, social media sentiment analysis, opinion leader sentiment analysis, twitter microblogs. Collapse

Topics: Bitcoin Twitter cryptocurrency price management social media

Methods: longitudinal research vector autoregression descriptive statistic computational algorithm Granger causality

Winner Takes All? The Blockbuster Effect on Crowdfunding Platforms

2023 | Information Systems Research | Citations: 0

Authors: Wang, Zhiyi; Yang, Lusi; Hahn, Jungpil

Abstract: Crowdfunding platforms are characterized by an uneven distribution of quality an ... Expand

Abstract: Crowdfunding platforms are characterized by an uneven distribution of quality and resources. Some projects achieve outstanding and exceptional performance. Those projects, which we call “blockbuster projects,” are believed to have a considerable impact on crowdfunding platforms, especially on other concurrent projects. There are two plausible yet opposing predictions: they may exhibit both a negative effect by monopolizing backer attention and resources and a positive effect by increasing the activeness of backer side. This tension could be further complicated, considering that blockbusters are inherently heterogeneous, which could result in different interrelations with other concurrent projects. To fully understand this tension, this study examines the effects of blockbuster projects on the overall performance of concurrent projects on the platform and the nuances of such effects for different interrelations between blockbusters and other projects. Drawing on the cross-side network effects literature and integrating insights from the unique features of crowdfunding, we develop a theoretical framework that highlights the multidimensional view of blockbuster effects: we propose that blockbuster projects have an overall positive effect on the performance of concurrent projects (overall effect), and such positive effect is stronger for related blockbusters (local effect) and blockbusters emerging before the focal project (temporal effect). Using data from a leading reward-based crowdfunding platform, the proposed hypotheses are tested and largely supported. Additional analyses, based on off-platform data and backer data, verify the mechanism driving the blockbuster effects: blockbusters increase the popularity of the platform, whereby backers participating in the blockbusters tend to develop positive impressions and heightened expectations, so that they are likely to participate in other concurrent projects. This study contributes to the crowdfunding literature on interactions among projects, the literature on distinctive agents in online markets, and the cross-side network effects literature. We also discuss practical implications for project creators and platform operators. History: Anandasivam Gopal, Senior Editor; Sunil Wattal, Associate Editor. Funding: This work was supported by the National University of Singapore and the Singapore Ministry of Education Academic Research [Grants R-253-000-119-112 and R-253-000-136-114]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1154. Collapse

Topics: crowdsourcing crowdfunding network effect Google+ consumer behavior

Methods: robustness check cluster analysis k-means clustering theory development econometric modeling

The influence of project initiators’ person-to-person followership on project popularity in open source communities: The role of reach and importance

2023 | Journal of Strategic Information Systems | Citations: 0

Authors: Weng, Qin; Soh, Franck

Abstract: Person-to-person (P2P) followership is an important aspect of major open source ... Expand

Abstract: Person-to-person (P2P) followership is an important aspect of major open source software (OSS) development platforms. In this age of social media platforms, P2P followership has significantly shaped the way users engage in OSS development by facilitating the establishment of connections among OSS users. Despite the prevalence of P2P followership, less is known about the impact of OSS project initiators’ P2P followership nodes on their project popularity. This is a particularly important gap considering the low rate of OSS project success. We posit that OSS project initiators derive information and influence benefits from the quantity and connectivity of their P2P followership nodes, explaining the popularity of the projects initiated. We determine the con­ nectivity of OSS project initiators’ P2P followership nodes based on the nodes’ reach and importance. To test the hypotheses, we use a large panel dataset collected over 24 months from GitHub. The findings indicate that the quantity of OSS project initiators’ P2P followership nodes including followers and followees has a positive effect on their project popularity. Moreover, such an effect is mostly dependent on the connectivity of the OSS project initiators’ P2P followership nodes in such a way that highly connected P2P followership nodes do not impact influence benefits but they increase information benefits. We discuss the theoretical and practical impli­ cations of our findings. Collapse

Topics: peer-to-peer model social network application programming interface social media Instagram

Methods: longitudinal research autocorrelation analysis theory development Granger causality descriptive statistic

Theories: social network theory

More than watching: An empirical and experimental examination on the impacts of live streaming user-generated video consumption

2023 | Information & Management | Citations: 0

Authors: Zhang, Yuan; Hua, Lei; Jiao, Yue; Zhang, Jie; Saini, Ritesh

Abstract: Live streaming user-generated video (UGV), a nascent format of crowdsourced cont ... Expand

Abstract: Live streaming user-generated video (UGV), a nascent format of crowdsourced content, has grown massive popularity among social media users and is believed to have substantial potential business influences. However, industry practitioners express concerns regarding this new form on social media platforms and the influences of live streaming UGV consumption lack research. Motivated such, through a uniquely merged dataset from the video game industry, we conduct a series of panel time-series empirical analyses to investigate the business value of live streaming UGV consumption. Further, we propose a conceptual framework based on the sense of com­ munity literature to understand the consequences of live streaming UGV consumption and verify it through several online experiments. This research contributes to the IS literature by shedding light on the influences of emergent crowdsourced content, providing a conceptual framework to existing literature, and offering rich managerial implications and guidelines to managers regarding utilizing live streaming UGVs. Collapse

Topics: video streaming service digital service marketing management organizational value crowdsourcing

Methods: experiment survey parametric test Student's t-test nonparametric test