Investigating the Determinants of Compliance Intention in Behavior Change Support Systems

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ekpezu, Akon; Oinas-Kukkonen, Harri; Wiafe, Isaac

Abstract: The effectiveness of behavior change support systems (BCSS) in promoting health ... Expand

Abstract: The effectiveness of behavior change support systems (BCSS) in promoting health and well-being is unflinching. However, its long-term effectiveness is hindered by non-compliance. Research in BCSS that focuses on compliance is scarce, particularly the determinants of compliance intention are not well established. To address this gap, this study investigated the determinants of compliance intention in BCSS by extending the persuasive system design model to include competence, effectiveness, enjoyment, and persuasiveness. By surveying a sample of prospective BCSS users (N=234), partial least squares structural equation modeling was used to evaluate the proposed model. The findings suggest that the prospective users' perceptions of primary task support and dialogue support, as well as social support and credibility support significantly influenced their perceptions of self-competence and system effectiveness respectively. These perceptions influenced enjoyment, then persuasiveness, and finally compliance intention. Future studies will validate these findings on the compliance behavior of BCSS. Collapse

Topics: mobile application persuasive information system IS effectiveness systems design social network

Methods: survey partial least squares path modeling design principle PLS tool path analysis

Factors that Affect Consumer-to-Consumer Sales: An Inductive Predictive Analytics Approach

2023 | Americas Conference on Information Systems | Citations: 0

Authors: El Arabaty, Ashraf; Okoli, Chitu

Abstract: This study investigates factors affecting consumer-to-consumer (C2C) sales perf ... Expand

Abstract: This study investigates factors affecting consumer-to-consumer (C2C) sales performance, specifically in the context of second-hand luxury goods. Using a large dataset of users from a French C2C luxury fashion website, the research identifies factors influencing C2C sales beyond current knowledge. Findings show that the number of followers a seller has, as well as the number of products a seller wishes for and likes, are associated with increased sales. Additionally, the study uncovers unexpected results: sellers listing many products also buy many products, and the number of users a seller follows is associated with increased sales. These findings contribute to a better understanding of the unique characteristics of C2C e-commerce. The article provides practical implications for sellers and C2C platforms to improve their sales performance, catering to the dual-role nature of users in C2C transactions. Collapse

Topics: electronic commerce website explainable artificial intelligence social capital

Methods: machine learning linear regression analysis literature study random forest classification decision tree classification

An Action Design Research Study on Responsible Innovation Teaching and Training for Information Systems Students

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

Authors: El Idrissi, Sarah Cherki; Corbett, Jacqueline; Mellouli, Sehl

Abstract: While information systems organizations recognize the importance of incorporati ... Expand

Abstract: While information systems organizations recognize the importance of incorporating responsible innovation into their activities, they often face difficulty implementing this practice because employees lack the required knowledge and skills, particularly the capacity for reflexivity and reflection. This paper aims to accelerate responsible innovation teaching and training for information systems students to expedite the process of positive change for sustainability. Using the action design research methodology and the responsible innovation lens, we developed a workshop enabling information systems students to form measurable reflection skills. The workshop evaluation suggests that learning took place and that students are willing to adopt responsible innovation in their future workplaces. A set of design guidelines is proposed to guide further training programs to enhance students' ability to address complex challenges responsibly. This paper answers the call for more impactful information systems research to address societal and environmental challenges and enriches the literature on sustainable social development and business practices. Collapse

Topics: innovation management task complexity personality responsible artificial intelligence digital innovation

Methods: design guideline qualitative interview action design research design science qualitative coding

Criteria Based Evaluation of Cross-Platform Development Frameworks

2023 | HICSS | Citations: 0

Authors: El Tom, Ali; Bogdan, Cristian; Majchrzak, Tim A.; Grønli, Tor-Morten

Abstract: Cross-platform development frameworks continue to play an important role in deve ... Expand

Abstract: Cross-platform development frameworks continue to play an important role in developing of mobile applications. There are a plethora of possible frameworks to choose between, and all claim to give developers an advantage in one or more aspects of the development cycle. To further shed light on this area, our research investigates the selection of mobile cross-platform frameworks by investigating criteria and methods for choosing the best suitable framework for the development context. Our study confirm previous research findings and with that anchor the categorisation for a cross-platform comparison taxonomy. Our research further contribute with a criteria check-list to apply for cross-platform framework selection and showcase its use through a comparative study of a cross-platform application implemented in two frameworks. Although showcasing novelty in the criteria checklist, further research is needed to make the checklist robust and streamlined for public use. Collapse

Topics: mobile application Android iOS JavaScript programming language

Methods: cross sectional research literature study

Is There a Place for Responsible Artificial Intelligence in Pandemics? A Tale of Two Countries

2023 | Information Systems Frontiers | Citations: 0

Authors: El-Haddadeh, Ramzi; Fadlalla, Adam; Hindi, Nitham M.

Abstract: This research examines the considerations of responsible Artificial Intelligence ... Expand

Abstract: This research examines the considerations of responsible Artificial Intelligence in the deployment of AI-based COVID-19 digital proximity tracking and tracing applications in two countries; the State of Qatar and the United Kingdom. Based on the alignment level analysis with the Good AI Society’s framework and sentiment analysis of official tweets, the diagnostic analysis resulted in contrastive findings for the two applications. While the application EHTERAZ (Arabic for precaution) in Qatar has fallen short in adhering to the responsible AI requirements, it has contributed significantly to controlling the pandemic. On the other hand, the UK’s NHS COVID-19 application has exhibited limited success in fighting the virus despite relatively abiding by these requirements. This underlines the need for obtaining a practical and contextual view for a comprehensive discourse on responsible AI in healthcare. Thereby offering necessary guidance for striking a balance between responsible AI requirements and managing pressures towards fighting the pandemic. Collapse

Topics: Twitter responsible artificial intelligence mobile application artificial intelligence pandemic

Methods: sentiment analysis qualitative content analysis synthesis

Blockchain Transformation for Banking and Financial Services: Examining the Opportunities and Risks

2023 | Americas Conference on Information Systems | Citations: 0

Authors: El-Haddadeh, Ramzi; Weerakkody, Vishanth; Hindi, Nitham; Sivarajah, Uthayasankar

Abstract: The advancement of blockchain technologies has created new opportunities for bu ... Expand

Abstract: The advancement of blockchain technologies has created new opportunities for businesses to deliver new innovative offerings while improving their existing efficiencies to stay relevant and maintain the required competitive advantage. As such, blockchain technology has emerged as an opportunity to radically revolutionize and transform the banking and financial industry. This paper aims to bridge the existing gap in the literature by identifying empirically relevant opportunities and anticipated risks of blockchain transformation in the sector. This study collated and empirically analyzed the conceptualized model using a qualitative case study approach, culminating with specific recommendations. The findings highlight how the realization of blockchain technology value, competitive advantage, innovation and impact is required to develop successful implementation strategies. Similarly, acknowledging associated risks from scalability, Interoperability, security, and regulatory perspectives is equally vital to developing the necessary measures to guide its successful implementation. Collapse

Topics: blockchain systems implementation innovation management IS value competitive advantage

Methods: qualitative interview case study personal interview synthesis

A Task-Technology-Identity Fit Model of Smartwatch Utilisation and User Satisfaction: A Hybrid SEM-Neural Network Approach

2023 | Information Systems Frontiers | Citations: 0

Authors: El-Masri, Mazen; Al-Yafi, Karim; Kamal, Muhammad Mustafa

Abstract: Smartwatches are wearable devices intended to be smartphone companions that capt ... Expand

Abstract: Smartwatches are wearable devices intended to be smartphone companions that capture health data and ease access to notifications. They have also become personalisable standing as a fashion statement. This combination resulted in staggering adoption rates recently leading to question whether smartwatch users’ choice and use satisfaction emerge from utility features or from its fashion characteristics. This paper proposes and validates a fit theory to investigate the antecedents of adopters’ satisfaction. Besides evaluating fit with identity, the model assesses both perceived and actual task-technology fit of smartwatches. A questionnaire-based quantitative approach is used to collect data from about 300 smartwatch users in Qatar. To test the proposed model, data is analysed using structural equation modeling (SEM) and artificial neural networks (ANN). Furthermore, ANN sensitivity analysis ranks the importance of the fit factors affecting users’ choice during pre- and post-adoption stages. Both task-technology and technology-identity fit factors are quasi-equally important in explaining 62% of satisfaction variance. ANN analysis revealed that post-adoption satisfaction is primarily attributed to smartwatches’ ability to fit with users’ identity and secondarily to its perceived fit with tasks. Nevertheless, pre-adoption choice of smartwatches is mainly guided by their functionality. This paper is the first to propose and validate an integrated task-technology-identity fit model to explain smartwatch utilization and users’ satisfaction. The originality also lies in assessing actual task-technology fit and as perceived by users. Employing two modes of analysis revealed extra insights too. Collapse

Topics: smart watch mobile system user satisfaction personality smart wearable device

Methods: structural equation modeling data transformation survey factor analysis principal component analysis

Theories: theory of task technology fit unified theory of acceptance and use of technology technology acceptance model

Implementation as Regulation: Implementing Industrial Internet of Things in Manufacturing

2023 | International Conference on Information Systems | Citations: 0

Authors: Eley, TC; Lyytinen, Kalle

Abstract: There is an exponential increase in information systems with few or no organiza ... Expand

Abstract: There is an exponential increase in information systems with few or no organizational rules initially embedded in them, such as the Industrial Internet of Things (IIoT). Implementing these systems has been identified as an important challenge in practice and research. However, past information systems implementation research has mostly focused on systems with many organizational rules embedded in them. We present an initial case study of implementing IIoT using a regulation lens. This research demonstrates the embeddedness of rules within systems leads to different implementation processes and develops an initial process model of implementing systems with few rules embedded in them. These results show the usefulness of viewing implementation as regulation and suggest opportunities to improve implementation outcomes for IIoT. We plan on continuing this research by conducting a multiple case study. Collapse

Topics: systems implementation IS implementation success electronic mail

Methods: qualitative interview participant observation case study archival research theory development

Theories: theory of affordance socio technical theory

Toward the Sustainable Development of Machine Learning Applications in Industry 4.0

2023 | European Conference On Information Systems | Citations: 0

Authors: Ellenrieder, Sara; Jourdan, Nicolas; Biegel, Tobias; Cassoli, Beatriz; Metternich, Joachim; Buxmann, Peter

Abstract: As the level of digitization in industrial environments increases, companies ar ... Expand

Abstract: As the level of digitization in industrial environments increases, companies are striving to improve efficiency and resilience to unplanned disruptions through the development of Machine Learning (ML)based applications. Still, sustainable deployment and operation beyond proofs-of-concept is a challenging and resource-intensive task in dynamic enviroments such as industry 4.0, often impeding practical adoption in the long-term and thus sustainable ML product development. In this work, we systematically identify these challenges based on the CRISP-ML process model phases by applying a design science research approach. To this end, we conducted 15 interviews with data science practitioners in industry 4.0. Following a qualitative content analysis, design requirements and design principles for the development and sustainable long-term deployment of ML systems are derived to address identified challenges such as robustness to, and management of data drift caused by timedependencies and machine/product differences, missing metadata, interfaces to other IT systems, expectation management, and MLOps guidelines. Collapse

Topics: production management industry 4.0 systems design systems development new product development

Methods: qualitative interview business process modeling design requirement design principle Cross-Industry Standard Process for Data Mining

Promoting Learning Through Explainable Artificial Intelligence: An Experimental Study in Radiology

2023 | International Conference on Information Systems | Citations: 0

Authors: Ellenrieder, Sara; Kallina, Emma; Pumplun, Luisa; Gawlitza, Joshua Felix; Ziegelmayer, Sebastian; Buxmann, Peter

Abstract: The deployment of machine learning (ML)-based decision support systems (DSSs) i ... Expand

Abstract: The deployment of machine learning (ML)-based decision support systems (DSSs) in high-risk environments such as radiology is increasing. Despite having achieved high decision accuracy, they are prone to errors. Thus, they are primarily used to assist radiologists in their decision making. However, collaborative decision making poses risks to the decision maker, e.g. automation bias and long-term performance degradation. To address these issues, we propose combining findings of the research streams of explainable artificial intelligence and education to promote human learning through interaction with ML-based DSSs. We provided radiologists with explainable vs nonexplainable decision support that was high-vs low-performing in a between-subject experimental study to support manual segmentation of 690 brain tumor scans. Our results show that explainable ML-based DSSs improved human learning outcomes and prevented false learning triggered by incorrect decision support. In fact, radiologists were able to learn from errors made by the low-performing explainable ML-based DSS. Collapse

Topics: decision support system decision support explainable artificial intelligence decision making artificial intelligence

Methods: experiment qualitative interview magnetic resonance imaging parametric test ANOVA