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 cross-organizational identity management system: Utilizing SSI for the certification of retailer attributes

2023 | Electronic Markets | Citations: 0

Authors: Guggenberger, Tobias; Kühne, Daniela; Schlatt, Vincent; Urbach, Nils

Abstract: The introduction of blockchain offers new opportunities to rethink enterprise id ... Expand

Abstract: The introduction of blockchain offers new opportunities to rethink enterprise identity management. Recently, a new concept has emerged in the blockchain community called self-sovereign identity. Self-sovereign identity combines several existing decentralized identity management approaches, promising new ways to promote more convenient, connected, and secure identity services for the private and public sector. Nevertheless, research in this area is still in its infancy. Most of the very few articles focus either on the opportunities self-sovereign identity might offer or on very specific technical features. Studies on real-world applications of organizations using modern self-sovereign identity implementations and design theory are very rare. To fill this gap, we follow the design science research approach to design, implement, and evaluate a self-sovereign identity system to present tax attributes of online retailers. We present four design principles and conclude that the use of self-sovereign identity and blockchain offers opportunities to improve verification processes. Collapse

Topics: blockchain Hyperledger electronic commerce government system privacy

Methods: design principle design artifact qualitative interview design theory literature study

Evaluating user acceptance of an open-source mobile app for hospital price transparency rule

2023 | European Conference On Information Systems | Citations: 0

Authors: Purkayastha, Saptarshi; Merine, Regina; Dsouza, Vyona; Singh, Pallavi; Gichoya, Judy

Abstract: ... Expand

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Topics: mobile application behavioral intention information system use open source price management

Methods: survey partial least squares path modeling cognitive walkthrough design science personal interview

Theories: unified theory of acceptance and use of technology

Detection of Malicious Bots on Twitter through BERT Embeddings-based Technique

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Vyas, Piyush; Vyas, Gitika; Chennamaneni, Anitha

Abstract: Cutting-edge Conversational Artificial Intelligence (CAI) technologies bring ea ... Expand

Abstract: Cutting-edge Conversational Artificial Intelligence (CAI) technologies bring ease to human life and the invention of social Artificial Intelligence (AI) bots is one of the ultimate devices in the social media sphere. However, malicious social AI bots lead to societal challenges such as data breaches, information loss, and the proliferation of misinformation. Thus, in this work, significant research has been conducted to address the problem of detecting malicious social AI bots on a microblogging platform such as Twitter. We perform classification through Bidirectional Encoder Representations from Transformer (BERT) embedding-based approach. Utilizing tagging-text features, our preliminary results show the potential of the proposed model to classify tweets as malicious AI bot-generated or human-generated. Collapse

Topics: Twitter artificial intelligence microblog social media web service

Methods: BERT machine learning language model word embedding transformer model

A Functional Taxonomy of Data Quality Tools: Insights from Science and Practice

2022 | International Conference on Business Informatics | Citations: 0

Authors: Altendeitering, Marcel; Tomczyk, Martin

Abstract: For organizations data quality is a prerequisite for automated decision making a ... Expand

Abstract: For organizations data quality is a prerequisite for automated decision making and agility. To provide high quality data, numerous tools have emerged that support the different steps of data quality management. Yet, these tools vary in their functional composition and support for current trends, such as AI. There is no common and up-to-date perception of the capabilities a data quality tool should fulfill. In this paper, we develop a functional taxonomy of data quality tools to address this shortcoming and provide a holistic overview of data quality functionalities. We derived the taxonomy through an iterative approach of deductive reasoning by conducting a systematic literature review and inductive reasoning by reviewing existing data quality tools and gaining insights from experts. By applying our taxonomy to 18 commercial data quality tools we aim to provide the reader with a review of data quality tools and reach a functional consensus in the field. Collapse

Topics: data quality analytical information system database system open source Google+

Methods: literature sample structured literature research group interview literature study survey

An Information Systems Design Theory for Digital Broker Platforms

2022 | DESRIST | Citations: 0

Authors: Bley, Katja; Hentschel, Raoul; Pappas, Ilias

Abstract: Service platforms are becoming dominant drivers of daily business operations in ... Expand

Abstract: Service platforms are becoming dominant drivers of daily business operations in a digitalized environment. Research focuses on technological and network effects of such platforms, while socio-technical opportunities remain limited. Guidance support in selecting appropriate digital services on a multisided market platform may help companies with low domain knowledge as it increases their benefits by reducing existing barriers in adopting emerging technologies. We adapt the concept of a broker to a digital platform, which instantiates guidance support on multisided markets as core platform element. Further, we abstract the concept of a digital broker platform as an Information Systems (IS) design theory. By providing the necessary components of an IS design theory, we offer the possibility to derive digital broker platform artifacts, which are theoretically and conceptually grounded. We provide design principles for the method artifact and describe their applicability in an exemplary instantiation of the design theory in the domain of cloud computing. Lastly, we present the artifact’s mutability as well as its testable propositions. Collapse

Topics: digital platform cloud computing software as a service user interface cloud storage

Methods: design artifact design theory design principle design science design methodology

Theories: lemon market theory

DSSAE: Deep Stacked Sparse Autoencoder Analytical Model for COVID-19 Diagnosis by Fractional Fourier Entropy

2022 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Wang, Shui-Hua; Zhang, Xin; Zhang, Yu-Dong

Abstract: (Aim) COVID-19 has caused more than 2.28 million deaths till 4/Feb/2021 while it ... Expand

Abstract: (Aim) COVID-19 has caused more than 2.28 million deaths till 4/Feb/2021 while it is still spreading across the world. This study proposed a novel artificial intelligence model to diagnose COVID-19 based on chest CT images. (Methods) First, the two-dimensional fractional Fourier entropy was used to extract features. Second, a custom deep stacked sparse autoencoder (DSSAE) model was created to serve as the classifier. Third, an improved multiple-way data augmentation was proposed to resist overfitting. (Results) Our DSSAE model obtains a micro-averaged F1 score of 92.32% in handling a four-class problem (COVID-19, community-acquired pneumonia, secondary pulmonary tuberculosis, and healthy control). (Conclusion) Our method outperforms 10 state-of-the-art approaches. Collapse

Topics: artificial intelligence web service

Methods: machine learning computational algorithm deep learning autoencoder data transformation

The Path of the Righteous: Using Trace Data to Understand Fraud Decisions in Real Time

2022 | Management Information Systems Quarterly | Citations: 12

Authors: Weinmann, Markus; Valacich, Joseph; Schneider, Christoph; Jenkins, Jeffrey; Hibbeln, Martin

Abstract: race data—users’ digital records when interacting with technology—can reveal the ... Expand

Abstract: race data—users’ digital records when interacting with technology—can reveal their cognitive dynamics when making decisions on websites in real time. Here, we present a trace­data method, analyzing movements captured via a computer mouse, to assess potential fraud when filling out an online form. In contrast to existing fraud­detection methods, which analyze information after submission, mouse­movement traces can capture the cognitive deliberations as possible indicators of fraud as it is happening. We report two controlled studies using different tasks, where participants could freely commit fraud to benefit themselves financially. As they performed the tasks, we captured mouse­cursor movement data and found that participants who entered fraudulent responses moved their mouse significantly more slowly and with greater deviation. We show that the extent of fraud matters such that more extensive fraud increases movement deviation and decreases movement speed. These results demonstrate the efficacy of analyzing mouse­movement traces to detect fraud during online transactions in real time, enabling organizations to confront fraud proactively as it is happening at internet scale. Our method of analyzing actual user behaviors in real time can complement other behavioral methods in the context of fraud and a variety of other contexts and settings. Collapse

Topics: decision making web service website user behavior JavaScript

Methods: machine learning digital trace data descriptive statistic robustness check statistical hypothesis test

Theories: cognitive dissonance theory cognitive load theory conflict theory

Profiling Online Social Network Platforms: Twitter vs. Instagram

2021 | HICSS | Citations: 0

Authors: Ayora, Veruska; Horita, Flávio; Kamienski, Carlos

Abstract: Online Social Networks (OSN) have been increasingly used as sources of informati ... Expand

Abstract: Online Social Networks (OSN) have been increasingly used as sources of information for different applications, ranging from business, politics, and public services. However, there is a lack of information on OSN platforms' behavior that may impact big data processing and real-time services. In this paper, two of the most widely used social networks, Instagram and Twitter, are investigated to broaden the understanding of how each platform's message characteristics influence data completeness and latency. We performed a series of experiments to emulate data posting and collection automatically. Our results increase the level of transparency of the platforms' internal behavior, showing that both can deliver data with reasonably low latencies and high completeness, but Twitter can be up to eight times faster when it comes to multimedia messages. Collapse

Topics: Twitter Instagram data completeness application programming interface mobile application

Methods: experiment computational algorithm literature study

Theories: set theory

Integrating Blockchain for Data Sharing and Collaboration Support in Scientific Ecosystem Platform

2021 | HICSS | Citations: 0

Authors: Coelho, Raiane; Braga, Regina; David, José Maria; Dantas, Mário; Stroele, Victor; Campos, Fernanda

Abstract: Nowadays, scientific experiments are conducted collaboratively. In collaborative ... Expand

Abstract: Nowadays, scientific experiments are conducted collaboratively. In collaborative scientific experiments, we must consider aspects such as interoperability, privacy, and trust in shared data to allow the reproducibility of the results. A critical aspect associated with a scientific process is its provenance information, which can be defined as the origin or lineage of the data that helps understand the scientific experiment results. Another concern when conducting collaborative experiments is confidentiality, considering that only authorized personnel can share or view results. In this paper, we propose BlockFlow, a blockchain-based architecture, to bring reliability to the collaborative research, considering the capture, storage, and analysis of provenance data related to a scientific ecosystem platform (E-SECO). Collapse

Topics: Hyperledger blockchain application programming interface cloud computing covid 19

Methods: experiment literature study