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

The Effects of Machine-powered Content Modereation: An Empirical Study on Reddit

2022 | HICSS | Citations: 0

Authors: He, Qinglai; Raghu, T S; Santanam, Raghu

Abstract: With increasing participation in social media and online communities, content mo ... Expand

Abstract: With increasing participation in social media and online communities, content moderation has become an important part of the online experience. Volunteer moderators have been the essential workforce for content moderation. Recently, platforms move toward the technical and automated mode of moderation. There is a growing concern over de-humanization and whether machines would lead volunteer moderators to reduce their contributions. We conduct an empirical study to examine the impact of machine-powered regulations on volunteer moderators’ behaviors. With data collected from 156 subreddits on Reddit, we found that delegating moderation to machines augments volunteer moderators’ role as community managers. Human moderators engage in more moderation-related activities, including 20.2% more corrective and 14.9% supportive activities with their community members. Importantly, the effect manifests primarily among communities with large user bases and detailed guidelines, suggesting that community needs for moderation are the key factors driving more voluntary contributions in the presence of bot moderators. Collapse

Topics: Reddit Google+ Wikipedia Google Cloud Platform ride sharing platform

Methods: BERT machine learning natural language processing computational algorithm longitudinal research

Classification of COVID-19 Cases: The Customized Deep Convolutional Neural Network and Transfer Learning Approach

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Vyas, Piyush; Ragothaman, Kaushik Nagarajan Muthusamy; Chauhan, Akhilesh; Rimal, Bhaskar P.

Abstract: The recent advancements under the umbrella of artificial intelligence (AI) open ... Expand

Abstract: The recent advancements under the umbrella of artificial intelligence (AI) open opportunities to tackle complex problems related to image analysis. Recently, the proliferation of COVID-19 brought multiple challenges to medical practitioners, such as precise analysis and classification of COVID-19 cases. Deep learning (DL) and transfer learning (TL) techniques appear to be attractive solutions. To provide the precise classification of COVID-19 cases, this article presents a customized Deep Convolutional Neural Network (DCNN) and pre-trained TL model approach. Our pipeline accommodated several popular pre-trained TL models, namely DenseNet121, ResNet50, InceptionV3, EfficientNetB0, and VGG16, to classify COVID-19 positive and negative cases. We evaluated and compared the performance of these models with a wide range of measures, including accuracy, precision, recall, and F1 score for classifying COVID-19 cases based on chest X-rays. The results demonstrate that our customized DCNN model performed well with randomly assigned weights, achieving 98.5% recall and 97.0% accuracy. KeywordsCovid19, transfer learning, deep convolutional neural network, medical imaging. Collapse

Topics: Google Cloud Platform Google+ covid 19

Methods: machine learning ImageNet deep learning convolutional neural network literature study

A Latent Space Modeling Approach to Interfirm Relationship Analysis

2021 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Ng, Ka Chung; So, Mike K. P.; Tam, Kar Yan

Abstract: Interfirm relationships are crucial to our understanding of firms’ collective an ... Expand

Abstract: Interfirm relationships are crucial to our understanding of firms’ collective and interactive behavior. Many information systems-related phenomena, including the diffusion of innovations, standard alliances, technology collaboration, and outsourcing, involve a multitude of relationships between firms. This study proposes a latent space approach to model temporal change in a dual-view interfirm network. We assume that interfirm relationships depend on an underlying latent space; firms that are close to each other in the latent space are more likely to develop a relationship. We construct the latent space by embedding two dynamic networks of firms in an integrated manner, resulting in a more comprehensive view of an interfirm relationship. We validate our approach by introducing three business measures derived from the latent space model to study alliance formation and stock comovement. We illustrate how the trajectories of firms provide insights into alliance activities. We also show that our proposed measures have strong predictive power on stock comovement. We believe the proposed approach enriches the methodology toolbox of IS researchers in studying interfirm relationships. Collapse

Topics: database system mobile system Python internet of things decision making

Methods: descriptive statistic machine learning computational algorithm regression analysis method statistical hypothesis test

Theories: resource based view of the firm

Insight from a Containerized Kubernetes Workload Introspection

2021 | HICSS | Citations: 0

Authors: Watts, Thomas; Benton, Ryan; Shropshire, Jordan; Bourrie, David

Abstract: Developments in virtual containers, especially in the cloud infrastructure, have ... Expand

Abstract: Developments in virtual containers, especially in the cloud infrastructure, have led to diversification of jobs that containers are used to support, particularly in the big data and machine learning spaces. The diversification has been powered by the adoption of orchestration systems that marshal fleets of containers to accomplish complex programming tasks. The additional components in the vertical technology stack, plus the continued horizontal scaling have led to questions regarding how to forensically analyze complicated technology stacks. This paper proposed a solution through the use of introspection. Collapse

Topics: Kubernetes cloud computing Docker ease of use database system

Methods: experiment random forest classification singular value decomposition data transformation machine learning

Representing the Twittersphere: Archiving a representative sample of Twitter data under resource constraints

2019 | International Journal of Information Management | Citations: 0

Authors: Hino, Airo; Fahey, Robert A.

Abstract: The rising popularity of social media posts, most notably Twitter posts, as a da ... Expand

Abstract: The rising popularity of social media posts, most notably Twitter posts, as a data source for social science research poses significant problems with regard to access to representative, high-quality data for analysis. Cheap, publicly available data such as that obtained from Twitter's public application programming interfaces is often of low quality, while high-quality data is expensive both financially and computationally. Moreover, data is often available only in real-time, making post-hoc analysis difficult or impossible. We propose and test a methodology for inexpensively creating an archive of Twitter data through population sampling, yielding a database that is highly representative of the targeted user population (in this test case, the entire population of Japanese-language Twitter users). Comparing the tweet volume, keywords, and topics found in our sample data set with the ground truth of Twitter's full data feed confirmed a very high degree of representativeness in the sample. We conclude that this approach yields a data set that is suitable for a wide range of post-hoc analyses, while remaining cost effective and accessible to a wide range of researchers. Collapse

Topics: Twitter application programming interface database system social media information management

Methods: topic model post-hoc analysis Gensim regression analysis method qualitative content analysis

Hands-on Exercises and Assignments on Google Cloud Platform

2018 | Americas Conference on Information Systems | Citations: 0

Authors: Chi, Tai-Yin

Abstract: It has been challenging for instructors in the MIS/IST discipline to engage stud ... Expand

Abstract: It has been challenging for instructors in the MIS/IST discipline to engage students by using a lectureonly teaching technique. This paper presents a set of nifty assignments that consist of the instructor-led hands-on exercises and the take-home individual assignments in an introductory MIS course. Students were instructed to use an online tool to exchange encrypted messages and use Google Cloud Platform (GCP) to deploy virtual machines running PrestaShop, an eCommerce application. The results of a student survey showed that the assignments were fun, relevant, useful, and helpful in improving the students’ engagement and learning. Collapse

Topics: cloud computing data encryption database system IT work electronic commerce

Methods: survey personal interview

IT INNOVATIONS AND ENTREPRENEURSHIP IN EMERGING ECONOMIES - IS CLOUD COMPUTING A MAGIC INGREDIENT FOR EGYPTIAN ENTREPRENEURS?

2017 | European Conference On Information Systems | Citations: 0

Authors: El-Gazzar, Rania; Henriksen, Helle; Wahid, Fathul

Abstract: Using the concept of affordances as an analytical lens, this study aims to under ... Expand

Abstract: Using the concept of affordances as an analytical lens, this study aims to understand the use of Cloud Computing (CC) by Egyptian entrepreneurs. The study analyses impact of CC on their businesses and its inhibiting and enabling factors. In general, Egyptian entrepreneurs have positive perceptions of CC and note its various actualized affordances: accessing information technology (IT) resources rapidly, broadening reach and transferring responsibility. The use of CC has yielded diverse effects: shortened time to market, reduced costs, a diversified audience and more useful feedback. We also identify what inhibits the use of CC, including transparency and corruption problems, limited support for online transactions, unsupportive government policies, low appreciation from the domestic market, cumbersome bureaucracy, account hacking and unreliable infrastructure. Finally, we also reveal some enabling factors, including institutional support, overseas market potential and CC uptake (i.e., growing use). Collapse

Topics: entrepreneurship affordance user experience database system usability

Methods: qualitative interview literature sample literature study

Theories: theory of affordance

Integrating Decision-Making Support in Geocollaboration Tools

2014 | Group Decision and Negotiation | Citations: 0

Authors: Antunes, Pedro; Zurita, Gustavo; Baloian, Nelson; Sapateiro, Claudio

Abstract: Collaborative spatial decision making (CSDM) involves multiple stakeholders maki ... Expand

Abstract: Collaborative spatial decision making (CSDM) involves multiple stakeholders making strategic decisions based on spatial data. Current CSDM tools have been exploring different ways to integrate spatial data with collaboration, distribution and mobility. Notably, decision-making support has not seen the same level of attention. This paper discusses the challenges raised by the integration of decision-making models in CSDM tools. We review a large collection of decision-making models using three different views: sequential, dynamic and continuous. From this review we derive a conceptual model and a set of functional requirements necessary to integrate decision-making support in CSDM tools. The conceptual model highlights the importance of several functions in decision-making processes: representing problems, finding alternatives and making choices (sequential view); classification and communication (dynamic view); and perception, comprehension and projection (continuous view). The paper also describes a prototype developed to validate the model. The paper provides two main research contributions: a unified view of decision-making support and an innovative CSDM tool blending spatial data with decision-making support. Collapse

Topics: decision making business process design situation awareness Google Cloud Platform tablet

Methods: conceptual modelling experiment computational algorithm design requirement synthesis

Exploring solutions for mobile companionship: A design research approach to context-aware management

2013 | International Journal of Information Management | Citations: 0

Authors: Grønli, Tor-Morten; Ghinea, Gheorghita; Bygstad, Bendik

Abstract: a b s t r a c tThe mobile phone is not just another device; it is with you day ... Expand

Abstract: a b s t r a c tThe mobile phone is not just another device; it is with you day and night, and you rely on its capabilities in work and in private. In short, the mobile phone is your companion. As your companion, it should understand your situational and informational needs. How do we increase the friendliness of your mobile phone, in order to fulfil this promise? In this paper, we explore how context awareness can be used for managing the user mobile experience. To this end, we employed a design research approach to integrate context-aware and cloud based services in an Android application. Through a user evaluation and proofof-concept implementation we show how new technologies can increase the friendliness of your mobile phone. In so doing, we provide evidence that adaptive applications based on user context offer a fertile ground for taking mobile companionship to the next level.Tor-Morten Grønli received a Masters degree in distributed information systems and computing in 2008 and was awarded a PhD in 2012 for research conducted on cloud computing and context-aware mobile computing -both from Brunel University, Uxbridge, UK. He is currently an associate professor at the Norwegian School of IT. His current research interests include mobile solutions, pervasive and ubiquitous computing, context-aware systems and software engineering. Collapse

Topics: cloud computing mobile system Google+ Android user experience

Methods: experiment design science wearables based research usability testing survey