Data Science for Social Good

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Abbasi, Ahmed; Chiang, Roger; Xu, Jennifer

Abstract: Data science has been described as the fourth paradigm of scientific discovery. ... Expand

Abstract: Data science has been described as the fourth paradigm of scientific discovery. The latest wave of data science research, pertaining to machine learning and artificial intelligence (AI), is growing exponentially and garnering millions of annual citations. However, this growth has been accompanied by a diminishing emphasis on social good challenges-our analysis reveals that the proportion of data science research focusing on social good is less than it has ever been. At the same time, the proliferation of machine learning and generative AI has sparked debates about the sociotechnical prospects and challenges associated with data science for human flourishing, organizations, and society. Against this backdrop, we present a framework for "data science for social good" (DSSG) research that considers the interplay between relevant data science research genres, social good challenges, and different levels of sociotechnical abstraction. We perform an analysis of the literature to empirically demonstrate the paucity of work on DSSG in information systems (and other related disciplines) and highlight current impediments. We then use our proposed framework to introduce the articles appearing in the JAIS special issue on data science for social good. We hope that this editorial and the special issue will spur future DSSG research and help reverse the alarming trend across data science research over the past 30-plus years in which social good challenges are attracting proportionately less attention with each passing day. Collapse

Topics: societal evaluation criteria digital dashboard productivity social media pandemic

Methods: word embedding literature study literature sample longitudinal research design science

THE IMPACT OF ONLINE ADVERTISMENT PERSONALIZATION AND TRANSPARENCY ON INDIVIDUAL DEFENSIVE RESPONSES AND ENGAGMENT

2023 | European Conference On Information Systems | Citations: 0

Authors: Al Helaly, Yasser; Dhillon, Gurpreet; Oliviera, Tiago

Abstract: This study identifies the different individual defensive responses that are tri ... Expand

Abstract: This study identifies the different individual defensive responses that are triggered by ad personalization. We investigate how these responses impact user engagement behavior on social media. The study also examines the role of transparency in advertising and the perceived benefits of personalization on user engagement in Europe. To conduct our study, we are theoretically grounded in the defensive response model. A multi-step quantitative approach constituting two experiments and a survey is used. With 154 and 199 participants each, the experiments allowed us to define the theoretical model. The experiment identified paradoxical findings. We indent surveying online ads-users to examine the impact of personalization on individual defensive responses and the role transparency plays in predicting user engagement. Our research contributes to the theory by identifying defensive responses that explain the engagement behavior, and the impact of transparency on personalized advertising. Collapse

Topics: personalization usability Facebook social media privacy

Methods: experiment survey Student's t-test statistical hypothesis test parametric test

Designing a Digital Marketing Analytics Operations Platform using Action Design Research

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Babu, Xavier; Motiwalla, Luvai

Abstract: Digital environment has transformed the work environment of marketing firms. Tr ... Expand

Abstract: Digital environment has transformed the work environment of marketing firms. Traditional marketing processes are repetitive, lack coordination, and are not dynamic or data-driven. To compete effectively in the digital world, marketing firms need a digital marketing analytics operations platform (DMAOP) optimized for data analytics, workflow, team coordination, and quick decision-making. We developed a DMAOP using a design science research model known as ADR. DMAOP uses data analytics leading to marketing decisions that create value with intelligent robotic processes assisting marketing practitioners in executing marketing actions. DMAOP is customized to a user's skill level, supporting marketing functions, advanced analytics, preserving privacy, and episodic reporting for users without technical skills. This study contributes to descriptive knowledge problem space by identifying the key aspects of DMAO. It also contributes to the "elaborated ADR" model with a new cycle, "personalization". Finally, it contributes to prescriptive knowledge and DMAOP instantiation with design science for digital platforms. Collapse

Topics: marketing management usability personalization marketing intelligence distributed computing

Methods: design science case study action design research design artifact design principle

The Type to Listen to the Machine? The Effect of Personality on the Use of AI Advice

2023 | International Conference on Business Informatics | Citations: 0

Authors: Asbach, Simon; Graf-Vlachy, Lorenz; Fügener, Andreas

Abstract: ... Expand

Abstract: Collapse

Topics: artificial intelligence personality personalization usability

Methods: regression analysis method survey moderation analysis general multivariate regression model

Theories: big five model personality theory

Towards a thematic dimensional framework of online fraud: An exploration of fraudulent email attack tactics and intentions

2023 | Decision Support Systems | Citations: 1

Authors: Bera, Debalina; Ogbanufe, Obi; Kim, Dan J.

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still resu ... Expand

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still result in billions of dollars lost annually, significant personal identity theft, loss of corporate secrets, and espionage. We review the phishing literature on psychological attacks and design tactics employed for deception by attackers. The result reveals the need to continuously identify tactics embedded in fraudulent email content to understand why users still fall prey to phishing attacks. Using the literature as a backdrop, we identify and conceptualize a thematic dimensional framework of fraudulent phishing attacks. This study uses benchmark datasets of fraudulent email to empirically validate the proposed dimensional framework. Specifically, a combination of machine learning-based content analysis and topic modeling found a majority of the discovered topics were labeled against the proposed di­ mensions. Statistical analysis was employed to provide empirical evidence of the thematic dimensions of fraudulent email attacks. This study thus, not only extends the cybersecurity literature by identifying and vali­ dating eight dimensions that enrich our understanding of phishing and attack identification but stimulates cu­ mulative research endeavors to develop yet more comprehensive dimensional frameworks of phishing email attacks. Collapse

Topics: phishing email phishing electronic mail email spam personalization

Methods: term frequency–inverse document frequency natural language processing topic model discriminant analysis literature study

Designing a conversational AI agent: Framework combining customer experience management, personalization, and AI in service techniques

2023 | HICSS | Citations: 0

Authors: Blümel, J.; Jha, G.

Abstract: Conversational AI agents are fundamentally changing how firms are delivering se ... Expand

Abstract: Conversational AI agents are fundamentally changing how firms are delivering service to their customers. The rapid advancement of technology and ready tools means that deploying a conversational AI agent has become far simpler than ever imagined. However, customers remain unsatisfied with their experience and firms are unable to demonstrate value of conversational AI agents. Drawing on the theoretical notions of customer experience (CX) management, personalization, and AI in service, we develop a framework to design conversational AI agents. We propose a six-stage iterative design for conversational AI agents that begins with sensing customer intent, adapting to journey context, assigning tone to the conversation, delegating to humans, orchestrating processes to service requests and training of AI agents to adaptively improve and loopback into prior design stages. Additionally, we recognize that firms need to holistically qualify and allocate service requests to such conversational AI agents based on the firm's purpose and CX strategy. Collapse

Topics: artificial intelligence usability personalization conversational agent Amazon Alexa

Methods: chatbot natural language processing literature study

The Evaluation of Founder Failure and Success by Hiring Firms: A Field Experiment

2023 | Organization Science | Citations: 0

Authors: Botelho, Tristan L.; Chang, Melody

Abstract: Organizations tout the importance of innovation and entrepreneurship. Yet, when ... Expand

Abstract: Organizations tout the importance of innovation and entrepreneurship. Yet, when hiring it remains unclear how they evaluate entrepreneurial human capital—namely, job candidates with founder experience. How hiring firms evaluate this experience—and especially how this evaluation varies by entrepreneurial success and failure—reveals insights into the structures and processes within organizations. Organizations research points to two perspectives related to the evaluation of founder experience: Former founders may be advantaged, due to founder experience signaling high-quality capabilities and human capital, or disadvantaged, due to concerns related to fit and commitment. To identify the dominant class of mechanisms driving the evaluation of founder experience, it is important to consider how these evaluations differ, depending on whether the founder’s venture failed or succeeded. To isolate demand-side mechanisms and hold supply-side factors constant, we conducted a field experiment. We sent applications varying the candidate’s founder experience to 2,400 software engineering positions in the United States at random. We find that former founders received 43% fewer callbacks than nonfounders and that this difference is driven by older hiring firms. Further, this founder penalty is greatest for former successful founders, who received 33% fewer callbacks than former failed founders. Our results highlight that mechanisms related to concerns about fit and commitment, rather than information asymmetry about quality, are most influential when hiring firms evaluate former founders in our context. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1592. Collapse

Topics: IT career human resource management entrepreneurship systems development innovation management

Methods: qualitative interview field experiment theory development experiment experimental design

Theories: lemon market theory

Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success

2023 | Information Systems Frontiers | Citations: 1

Authors: Chen, Yu; Jensen, Scott; Albert, Leslie J.; Gupta, Sambhav; Lee, Terri

Abstract: In higher education, low teacher-student ratios can make it difficult for studen ... Expand

Abstract: In higher education, low teacher-student ratios can make it difficult for students to receive immediate and interactive help. Chatbots, increasingly used in various scenarios such as customer service, work productivity, and healthcare, might be one way of helping instructors better meet student needs. However, few empirical studies in the field of Information Systems (IS) have investigated pedagogical chatbot efficacy in higher education and fewer still discuss their potential challenges and drawbacks. In this research we address this gap in the IS literature by exploring the opportunities, challenges, efficacy, and ethical concerns of using chatbots as pedagogical tools in business education. In this two study project, we conducted a chatbot-guided interview with 215 undergraduate students to understand student attitudes regarding the potential benefits and challenges of using chatbots as intelligent student assistants. Our findings revealed the potential for chatbots to help students learn basic content in a responsive, interactive, and confidential way. Findings also provided insights into student learning needs which we then used to design and develop a new, experimental chatbot assistant to teach basic AI concepts to 195 students. Results of this second study suggest chatbots can be engaging and responsive conversational learning tools for teaching basic concepts and for providing educational resources. Herein, we provide the results of both studies and discuss possible promising opportunities and ethical implications of using chatbots to support inclusive learning. Collapse

Topics: artificial intelligence IT career anonymity user experience accounting

Methods: chatbot survey qualitative interview personal interview machine learning

Affect between Humans and Conversational Agents: A Review and Future Research Directions

2023 | International Conference on Information Systems | Citations: 0

Authors: Cui, Wei; Baskaran, Krutheeka; Kankanhalli, Atreyi

Abstract: Conversational agents (CAs) are digital artifacts which communicate with humans ... Expand

Abstract: Conversational agents (CAs) are digital artifacts which communicate with humans through natural language for performing a variety of tasks. When humans interact with CAs, affective responses e.g., emotions, are seen to influence both CA adoption and performance. Despite the vital role of affect in human-CA interaction, understanding of its antecedents, affective outcomes, and their relationships from prior research is nascent and segregated. Motivated thus, we review empirical studies on affect in human-CA interactions, classify them in terms of affective outcomes, and identify corresponding antecedents. We further analyze the relationships between antecedents and outcomes and highlight significant relationships as well as inconsistent findings. Drawing on the review, we propose future research directions for this area. We contribute by developing a deeper understanding of research on affect between human and CAs, identifying gaps in prior knowledge, and outlining future research directions. Additionally, we lay out our plans for extending this work. Collapse

Topics: usability human computer interaction task characteristic user satisfaction personalization

Methods: literature study synthesis literature sample

Avoiding the Diffusion of Responsibility in Social Networking Groups: A Field Experiment on Responses to Online Help-Request Referrals

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Feng, Nan; Hu, Zhongtao; Wu, Yi; Choi, Ben

Abstract: Help-request referral (HRR) campaigns are being increasingly adopted by online s ... Expand

Abstract: Help-request referral (HRR) campaigns are being increasingly adopted by online service providers to attract online traffic and engage new users. In these campaigns, participants are required to collect a specific amount of help from their social network in exchange for attractive rewards. Participants often face challenges in obtaining positive feedback from their social networking groups due to the diffusion of responsibility. Based on the triangle model of responsibility, this study proposes and empirically tests a research model that examines two key determinants (i.e., request personalization and relational closeness) of recipients’ perceived responsibility that further shape their responses to HRR. Our field experiment empirically supports the research hypotheses. Overall, this study enriches the literature on online social referrals by focusing on HRR, where social referrals are broadcasted and senders reap referral benefits. The study also provides practical insights for HRR designers and social networking service providers. Collapse

Topics: personalization usability WeChat marketing management online word of mouth

Methods: survey experiment field experiment logistic regression analysis of covariance