Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities

2023 | Information Systems Frontiers | Citations: 0

Authors: Alahakoon, Damminda; Nawaratne, Rashmika; Xu, Yan; De Silva, Daswin; Sivarajah, Uthayasankar; Gupta, Bhumika

Abstract: The emerging information revolution makes it necessary to manage vast amounts of ... Expand

Abstract: The emerging information revolution makes it necessary to manage vast amounts of unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors that can sense their surroundings and communicate with each other, a digital environment has been created with vast volumes of volatile and diverse data. Traditional AI and machine learning techniques designed for deterministic situations are not suitable for such environments. With a large number of parameters required by each device in this digital environment, it is desirable that the AI is able to be adaptive and self-build (i.e. self-structure, self-configure, self-learn), rather than be structurally and parameter-wise pre-defined. This study explores the benefits of self-building AI and machine learning with unsupervised learning for empowering big data analytics for smart city environments. By using the growing self-organizing map, a new suite of self-building AI is proposed. The self-building AI overcomes the limitations of traditional AI and enables data processing in dynamic smart city environments. With cloud computing platforms, the self-building AI can integrate the data analytics applications that currently work in silos. The new paradigm of the self-building AI and its value are demonstrated using the IoT, video surveillance, and action recognition applications. Collapse

Topics: artificial intelligence smart city big data cloud computing distributed system

Methods: computational algorithm experiment unsupervised learning machine learning longitudinal research

Measuring Workers’ Perceptions of Algorithmic Control: Item Development and Content Validity Assessment

2023 | HICSS | Citations: 0

Authors: Alizadeh, Armin; Hirsch, Felix; Benlian, Alexander; Wiener, Martin; Cram, W. Alec

Abstract: Algorithmic control (AC) refers to organizations’ use of increasingly intelligen ... Expand

Abstract: Algorithmic control (AC) refers to organizations’ use of increasingly intelligent algorithms and related digital technology to steer worker behavior. While previous studies have identified and conceptualized various forms of AC in both platform and traditional work contexts, the presented conceptualizations lack measurability. This key shortcoming hampers further empirical research on the current use of AC and its manifold consequences. In this study, we report on the item development process for a scale for measuring perceived AC from a workers’ perspective. Following well-established approaches, an initial item pool was developed. The items were discussed and refined with the support of five academic experts and three AC workers. A subsequent rating study with 98 workers was conducted to ensure the content validity of all items. On this basis, the study at hand presents a comprehensive set of items for both AC in general and its seven sub-dimensions. Collapse

Topics: platform worker organizational context technostress database system ride sharing platform

Methods: qualitative interview survey design card sorting computational algorithm survey

Perceived Algorithmic Control: Conceptualization and Scale Development

2023 | European Conference On Information Systems | Citations: 1

Authors: Alizadeh, Armin; Hirsch, Felix; Benlian, Alexander; Wiener, Martin; Cram, W.

Abstract: Organizations today leverage big data analytics combined with modern informatio ... Expand

Abstract: Organizations today leverage big data analytics combined with modern information and communication technology (ICT) to control workers in a largely automated manner. This phenomenon is commonly referred to as algorithmic control (AC). Research has shown that worker perceptions of AC applications can impact critical outcomes such as worker resistance, continuance intention, and well-being. Despite recent efforts to better understand these worker-level effects of AC, no systematic measures of workers' perceptions of AC exist to date. In this study, we develop and present a scale to empirically measure AC at the worker level. In particular, following established scale development guidelines, we conceptualize AC in terms of seven distinct forms, and derive, evaluate, and validate a final set of 33 measurement items. In doing so, our study paves the way for a much-needed, more systematic investigation of AC and its worker-level implications. Collapse

Topics: database system video conference social media

Methods: qualitative interview survey design psychometrics card sorting descriptive statistic

Symbolic Shareholder Democracy: Toward a Behavioral Understanding of the Role of Shareholder Voting in CEO Dismissals

2023 | Organization Science | Citations: 0

Authors: Andrei, Alina G.; van Oosterhout, J. (Hans); Sauerwald, Steve

Abstract: We investigate the effect of expressive shareholder dissent voting, in which sha ... Expand

Abstract: We investigate the effect of expressive shareholder dissent voting, in which shareholders use their votes symbolically to express their discontent with management, on subsequent chief executive officer (CEO) dismissals. Using the routine but highly symbolic executive board discharge proposal voted on at the annual shareholder meetings of German firms, we argue that the board of directors understands these votes as a “vote of confidence in management” that challenges the CEO’s mandate to lead the firm. Arguing that board chairs are uniquely positioned to take up the stance of a steward of the firm and its leadership, we examine how independent and family board chairs moderate the board’s response to expressive voting dissent. Using a sample of German public firms over the period 2008–2015, we find that expressive voting dissent increases the chance of CEO dismissal increasingly with the level of dissent expressed. Contrary to prevailing agency theoretical expectations, we do not find that independent chairs are more responsive to expressive voting dissent, nor that this relationship is strengthened by the degree of minority institutional investor ownership of the firm. Consistent with the symbolic perspective on shareholder voting that we seek to develop, however, we find that family chairs are more likely to lead the board to dismiss the CEO due to the intrinsic disvalue they incur from symbolic leadership legitimacy challenges in their firms, and that the positive effect of having a family chair on the dissent induced chance of CEO dismissal is strengthened by the level of family ownership in the firm. Funding: A University of Illinois at Chicago Summer Research Grant is gratefully acknowledged for S. Sauerwald. Collapse

Topics: corporate governance financial performance accounting organizational productivity

Methods: theory development statistical hypothesis test post-hoc analysis longitudinal research survival analysis

Theories: stewardship theory behavioral theory

What Makes Digital Technology? A Categorization Based on Purpose

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

Authors: Baier, Marie-Sophie; Berger, Stephan; Kreuzer, Thomas; Oberländer, Anna; Röglinger, Maximilian

Abstract: Digital technology (DT) is creating and shaping today's world. Building on its ... Expand

Abstract: Digital technology (DT) is creating and shaping today's world. Building on its identity and history of technology research, the Information Systems discipline is at the forefront of understanding the nature of DT and related phenomena. Understanding the nature of DT requires understanding its purposes. Because of the growing number of DTs, these purposes are diversifying, and further examination is needed. To that end, we followed an organizational systematics paradigm and present a taxonomic theory for DT that enables its classification through its diverse purposes. The taxonomic theory comprises a multi-layer taxonomy of DT and purpose-related archetypes, which we inferred from a sample of 92 real-world DTs. In our empirical evaluation, we assessed the reliability, validity, and usefulness of the taxonomy and archetypes. The taxonomic theory exceeds existing technology classifications by being the first that (1) has been rigorously developed, (2) considers the nature of DT, (3) is sufficiently concrete to reflect the diverse purposes of DT, and (4) is sufficiently abstract to be persistent. Our findings add to the descriptive knowledge on DT, advance our understanding of the diverse purposes of DT, and lay the ground for further theorizing. Our work also supports practitioners in managing and designing DTs. Collapse

Topics: knowledge base perceived usefulness competitive advantage decision making technology adoption

Methods: cluster analysis theory development longitudinal data analysis focus group computational algorithm

Theories: information systems theory sociomaterialism theory

The Paradoxical Role of Humanness in Aggression Toward Conversational Agents

2023 | Journal of Management Information Systems | Citations: 0

Authors: Brendel, Alfred Benedikt; Hildebrandt, Fabian; Dennis, Alan R.; Riquel, Johannes

Abstract: Conversational Agents (CAs) are becoming part of our everyday lives. About 10 pe ... Expand

Abstract: Conversational Agents (CAs) are becoming part of our everyday lives. About 10 percent of users display aggressive behavior toward CAs, such as swearing at them when they produce errors. We conducted two online experiments to understand user aggression toward CAs better. In the first experiment, 175 participants used either a humanlike CA or a non-humanlike CA. Both CAs worked without errors, and we observed no increased frustration or user aggression. The second experiment (with 201 participants) was the focus of this study; in it, both CAs produce a series of errors. The results show that frustration with errors drives aggression, and users with higher impulsivity are more likely to become aggressive when frustrated. The results also suggest that there are three pathways by which perceived humanness influences users' aggression to CAs. First, perceived humanness directly increases the frustration with the CA when it produces errors. Second, perceived humanness increases service satisfaction which in turn reduces frustration. Third, perceived humanness influences the nature of aggression when users become frustrated (i.e., users are less likely to use highly offensive words with a more humanlike CA). Our research contributes to our theoretical understanding of the role of anthropomorphism in the interaction with machines, showing that designing a CA to be more humanlike is a double-edged sword—both increasing and decreasing the frustration that leads to aggression—and also a means to reduce the most severe aggression. Collapse

Topics: Wikipedia user behavior ease of use electronic mail personality

Methods: experiment theory development statistical hypothesis test chatbot SEM tool

Theories: social response theory

Doing good by going digital: A taxonomy of digital social innovation in the context of incumbents

2023 | Journal of Strategic Information Systems | Citations: 0

Authors: Buck, Christoph; Krombacher, Anna; Röglinger, Maximilian; Körner-Wyrtki, Katrin

Abstract: Digital social innovation (DSI) offers incumbents a strategic field of action to ... Expand

Abstract: Digital social innovation (DSI) offers incumbents a strategic field of action to leverage the op­ portunities of digital technologies to address pressing societal challenges. By proposing a tax­ onomy and 12 clusters of incumbents’ DSI initiatives based on a sample of 296 real-world objects, we develop a unified understanding of DSI and its characteristics. This lays the foundation for further theorising on DSI from an incumbent perspective and for researchers to shape the DSI field. The taxonomy provides incumbents with an orientation to realise DSI’s rich strategic po­ tentials throughout the DSI ideation process and in assessing DSI types. Collapse

Topics: innovation management societal challenge database system value creation digital innovation

Methods: literature sample cluster analysis agglomerative hierarchical clustering structured literature research theory development

Theories: information systems theory

Understanding active participation of online dating services: A mixed methods study

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Qi; Yun, Guobiao; Lu, Jiandong; Wang, Xiaolei

Abstract: Online dating has transformed the way people meet and start relationships. Howev ... Expand

Abstract: Online dating has transformed the way people meet and start relationships. However, online dating platforms typically have many lurkers without active participation. Using a self-regulation framework, this paper aims to study users’ active participation in online dating through a mixed methods study. We first conducted qualitative and quantitative investigations with a machine learning method to explore user active participation and its antecedents. We then developed a theoretical model and conducted a statistical analysis of the model. The empirical findings showed that service quality and trust significantly affected individual active participation in a dating site through attachments to the daters and services. The findings of the study contribute to the extant literature by analyzing user participation in online dating from an attachment perspective. Collapse

Topics: service quality online dating participatory design online dating service Python

Methods: design methodology mixed method qualitative coding machine learning machine learning method

Theories: attachment theory marketing theory

A Bitter Pill to Swallow? The Consequences of Patient Evaluation in Online Health Question-and-Answer Platforms

2023 | Information Systems Research | Citations: 0

Authors: Chen, Chen; Walker, Dylan

Abstract: Online health question-and-answer (Q&A) platforms (OHQPs), where patients post h ... Expand

Abstract: Online health question-and-answer (Q&A) platforms (OHQPs), where patients post health-related questions, evaluate advice from multiple doctors, and direct a bounty (monetary reward) to their most preferred answer, have become a prominent channel for patients to receive medical advice in China. To explore the quality of medical advice on these platforms, we analyzed data on patients’ evaluation of ∼497,000 answers to ∼114,000 questions on one of the most popular OHQPs, 120ask.com, over a three-month period. We assembled a panel of independent physicians and instructed them to evaluate the quality of ∼13,000 answers. We found that the quality of medical advice offered on the platform was high on average, and that low-quality answers were rare (6%). However, our results also indicate that patients lacked the ability to discriminate advice quality. They were as likely to choose the best answer as the worst. The medical accuracy of patient evaluation was worse in critical categories (cancer, internal medicine) and for vulnerable subpopulations (pediatrics). Given that millions of patients seek medical advice from OHQPs in China annually, the social and economic implications of this finding are troubling. To understand how patients evaluate advice, we trained deep neural networks to think like patients, allowing us to identify patients’ positive and negative responses to different heurist cues. Although our results indicate that OHQPs perform well, we identified several concerns that should be addressed through platform design and policy changes. Because the Q&A process lacks peer review mechanisms, signals of advice quality are not conveyed to patients, forcing them to rely on heuristic cues, which cannot effectively guide them toward the best advice. We also found that the platform reputation metric was not correlated with the quality of the advice giver’s advice, may effectively encourage patients to select lesser quality medical advice, and increased the risk of moral hazard for malicious players to intentionally provide less accurate but more agreeable advice for personal gain. Our analysis revealed bad actors on the platform, including drug promoters and spammers. Finally, we found that OHQPs exacerbated care avoidance. We discuss several potential policy changes to address these shortcomings. History: Param Singh, Senior Editor; Idris Adjerid, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1158. Collapse

Topics: decision making local interpretable model agnostic explanation digital platform health information system pandemic

Methods: artificial neural network psychometrics survey deep learning natural language processing

Theories: lemon market theory

How Cover Images Represent Video Content: A Case Study of Bilibili

2023 | HICSS | Citations: 0

Authors: Dedema, M.; Herring, S.

Abstract: User generated videos are the most prevalent online products on social media pl ... Expand

Abstract: User generated videos are the most prevalent online products on social media platforms nowadays. In this context, thumbnails (or cover images) serve the important role of representing the video content and attracting viewers' attention. In this study, we conducted a content analysis of cover images on the Bilibili video-sharing platform, the Chinese counterpart to YouTube, where content creators can upload videos and design their own cover images rather than using automatically generated thumbnails. We extracted four components -snapshot, background, text overlay, and face -that content creators use most often in cover images. We found that the use of different components and their combinations varies in cover images for videos of different duration. The study sheds light on human input into video representation and addresses a gap in the literature, as video thumbnails have previously been studied mainly as the output of automatic generation by algorithms. Collapse

Topics: YouTube TikTok social media sharing platform

Methods: qualitative content analysis grounded theory chi squared test