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

THE IMPACT OF CEOS’ TECHNOLOGICAL FRAME ON ORGANIZATIONAL AGILITY AND THE MEDIATING EFFECT OF DIGITAL BUSINESS CAPABILITIES: AN EMPIRICAL ANALYSIS

2023 | European Conference On Information Systems | Citations: 0

Authors: Glanz, Alena; Greven, Andrea; Brettel, Malte

Abstract: The information systems (IS) literature elaborates on how firms develop organiz ... Expand

Abstract: The information systems (IS) literature elaborates on how firms develop organizational agility based on organizational capabilities to sense and respond to rapidly changing environments. However, the underlying mechanism of how companies and their chief executive officers (CEOs) understand and implement digital technologies to foster organizational agility is lacking. The technological frame concept provides an impetus to explain the process by which CEOs' sensemaking of digital technologies influences organizational agility. Our paper draws on the individual-level perspective of the technological frame concept and proposes a mediating role of digital business capabilities, composed of digital strategy, digital integration, and digital control. Our quantitative research design is based on findings derived from 386 German CEOs and confirms that CEOs' technological frame influences organizational agility through digital business capabilities. Thereby, we expand the concept of the technological frame on the individual level and contribute to the IS literature by revealing the mechanism of how CEOs' sensemaking influences organizational agility. Collapse

Topics: sensemaking information systems strategy information technology capability electronic business systems implementation

Methods: survey partial least squares path modeling descriptive statistic partial least squares regression mediation analysis

Theories: technological frames of reference theory of organizational sensemaking dynamic capabilities theory

ARTIFICIAL INTELLIGENCE-AUGMENTED DECISION MAKING IN SUPPLY CHAIN MONITORING: AN ACTION DESIGN RESEARCH STUDY

2023 | European Conference On Information Systems | Citations: 0

Authors: Herath Pathirannehelage, Savindu; Jóhannsson, Jóhann; Shrestha, Yash; Krogh, Georg von

Abstract: Organizations are progressively adopting hybrid human-artificial intelligence ( ... Expand

Abstract: Organizations are progressively adopting hybrid human-artificial intelligence (AI) systems in decisionmaking processes, with human decisions being augmented by AI insights. Among the promising AI applications in supply chain monitoring (SCMo) are predictive maintenance systems that predict potential device failures and augment maintenance decisions, allowing for timely and efficient interventions. Despite the growing proliferation of such systems, prescriptive knowledge encompassing technical, business, and organizational aspects on how to design, develop, and deploy them in actual operational environments remains limited. To address this shortcoming of evidence-based design principles in practice, our action design research developed a predictive maintenance system that predicts SCMo device failures and augments the maintenance decisions about those devices. By doing so, we outline generalizable design principles to guide prospective predictive maintenance systems in SCMo. Collapse

Topics: artificial intelligence predictive maintenance organizational context decision making systems evaluation

Methods: machine learning design principle design artifact artificial neural network random forest classification

Theories: evidence-based design

Robo-advisors and investment intention: A perspective of value-based adoption

2023 | Information & Management | Citations: 0

Authors: Hong, Xianpei; Pan, Liwei; Gong, Yeming; Chen, Qian

Abstract: Financial robo-advisors have been widely used to assist individuals in their inv ... Expand

Abstract: Financial robo-advisors have been widely used to assist individuals in their investment decisions, making it important to reduce uncertainties in the assistance process. Existing empirical studies rarely explore uncertainty reduction strategies and their implications on users’ investment intentions in the context of financial roboadvisors; our study attempts to address this gap. We construct a model to explain how uncertainty reduction strategies affect users’ investment intention in using financial robo-advisors. By collecting and analyzing a sample of 307 financial robo-advisor users, we find that algorithmic interpretability, structural assurance, and interactivity as uncertainty reduction strategies are positively related to users’ investment intention through the value-based adoption mechanism. Our research extends the value-based adoption model and uncertainty reduction theory in the financial robo-advisor context. We provide insights to financial robo-advisor service providers about focusing on improving algorithmic transparency, third-party assurance, and interactivity of financial robo-advisors to enhance perceived value and investment intention. Collapse

Topics: robo advisor privacy artificial intelligence usage intention organizational productivity

Methods: survey computational algorithm factor analysis statistical hypothesis test structural equation modeling

Theories: uncertainty reduction theory

Software in the Manufacturing Industry: A Review of Security Challenges and Implications

2023 | International Conference on Business Informatics | Citations: 0

Authors: Landeck, Yannick; Balta, Dian; Wimmer, Martin; Knierim, Christian

Abstract: Software defines digital infrastructures in the manufacturing industry, connect ... Expand

Abstract: Software defines digital infrastructures in the manufacturing industry, connecting services and computation resources to machines and devices. These infrastructures aim at increased flexibility, scalability, and a wider application portfolio for automated manufacturing processes. At the same time, the complexity of securing software increases dramatically. Threats to confidentiality, integrity, and availability of software can result in critical losses for automated industrial production and impact manufacturing companies. In order to map existing and emerging security challenges, we present the results of a hermeneutic literature review structured along abstraction levels and vertical integration of software. Based on this structure, we derive implications for academia and practice focused on system integrators, developers, and security auditors of digital infrastructures. Thereby, we discuss courses of action mapped to software security black boxes, infrastructure heterogeneity, and the adaptation of security for operational usage. Collapse

Topics: IT security enterprise application integration system integration cloud computing supply chain management

Methods: literature study interpretative method structured literature research

Information System Articulation Development - Managing Veracity Attributes and Quantifying Relationship with Readability of Textual Data

2023 | International Conference on Information Systems | Citations: 0

Authors: Naik, Neelam; Nimmagadda, Shastri; Purohit, Seema; Reiners, Torsten; Mani, Dr Neel

Abstract: Often the textual data are either disorganized or misinterpreted because of uns ... Expand

Abstract: Often the textual data are either disorganized or misinterpreted because of unstructured Big Data in multiple dimensions. Managing readable textual alphanumeric data and its analytics is challenging. In spatial dimensions, the facts can be ambiguous and inconsistent, posing interpretation and new knowledge discovery challenges. The information can be wordy, erratic, and noisy. The research aims to assimilate the data characteristics through Information System (IS) artefacts that are appropriate to data analytics, especially in application domains that involve big data sources. Data heterogeneity and multidimensionality can make and preclude IS-guided veracity models in the data integration process, including customer analytics services. The veracity of big data thus can impact visualization and value, including knowledge enhancement in the vast amount of textual data qualitatively. The manner the veracity features construed in each schematic, semantic and syntactic attribute dimension in several IS artefacts and relevant documents can enhance the readability of textual data robustly. 2Modelling Veracity Attributes of Textual Data concepts and contexts (Lacasta et al. 2010). We have proposed a holistic methodology to build relationships between veracity attributes and instances and ease the readability of textual data. We can ontologically structure textual facts to explore connections between wordy readable, erratic, and noisy data. For example, ontologically structured alphanumeric data can logically and physically be integrated into unified textual metadata in a repository system. The metadata can be cost-effective for explicitly exploring new knowledge in a textual form (Vasarhelyi et al. 2015).The rest of the research paper is structured in various sections. The research objectives are highlighted, along with the motivation and significance of the research. The literature review identifies the research gaps in textual data mining. Various issues and challenges of Big textual Data mining are discussed in the next section. IS guided data mapping and modelling methods are described, including how the veracity attribute instances are mappable qualitatively with textual data mining artefacts that are construed with readability attributes and their occurrences, which are the highlights of the framework development. The value of information systems in various business contexts is highlighted in Rainer and Prince (2022). Several IS artefacts are articulated in the framework development. The integrated methodological framework adapts the ontology-based alphanumeric metadata with various mining artefacts, all accommodated in a repository. Results and discussions are analyzed, along with contributions and the intended research audience. The research is concluded with future scopes and limitations. Collapse

Topics: Python big data website Twitter decision making

Methods: experiment machine learning data modeling design artifact product review

AiLingo – A Design Science Approach to Advancing Non-Expert Adults’ AI Literacy

2023 | International Conference on Information Systems | Citations: 0

Authors: Pinski, Marc; Haas, Miguel; Franz, Anjuli

Abstract: Non-experts struggle in human-AI collaboration due to AI's differences from mor ... Expand

Abstract: Non-experts struggle in human-AI collaboration due to AI's differences from more traditional technologies, such as inscrutability. Meanwhile, information systems research on AI education primarily focuses on students in formal learning settings and neglects non-expert adults. Applying a design science research approach, we develop a learning application ("AiLingo") as an informal learning experience to advance nonexpert adults' AI literacy. Based on self-determination theory, we deduct design principles and features tailored to non-expert adults. Through experimental evaluation (n = 101), we find that a learning experience with our design features present (vs. absent) leads to greater AI literacy advancement. Additionally, we find downstream effects of AI literacy, as it increases AI usage continuance intention and leads to a more positive attitude toward AI. Our study contributes to AI literacy and educational literature with a perspective on non-expert adults, novel design knowledge for AI education, and the discovery of crucial AI literacy consequences. Collapse

Topics: artificial intelligence mobile application online learning system robotic user experience

Methods: design artifact design science experimental group experiment regression analysis method

Theories: self determination theory

Towards a multi-stakeholder framework for evaluating digital government success

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Tate, Mary; Lofgren, Karl; Pirini, Jesse

Abstract: In this paper, we develop an inclusive framework for identifying the direct and ... Expand

Abstract: In this paper, we develop an inclusive framework for identifying the direct and indirect stakeholders in digital government projects. Using a public value lens, we develop a systems view of digital government initiatives. We use an illustrative case study to show how stakeholders, especially indirect stakeholders, can exert influence on digital government projects, including what projects are perceived as legitimate, what factors are considered as important for success, and what stakeholders are involved in postimplementation evaluation. We also review several lenses commonly used for evaluation of digital government projects and illustrate how they fit into our framework Collapse

Topics: government system systems evaluation public good decision making outsourcing

Methods: case study

Human or AI? Using Digital Behavior to Verify Essay Authorship

2023 | International Conference on Information Systems | Citations: 0

Authors: Wilson, David; Burnett, Parker; Valacich, Joseph; Jenkins, Jeff

Abstract: ... Expand

Abstract: Collapse

Topics: systems design artificial intelligence JavaScript systems evaluation deception detection

Methods: design artifact chatGPT design science experiment design requirement

Digital transformation solutions of entrepreneurial SMEs based on an information error-driven T-spherical fuzzy cloud algorithm

2023 | International Journal of Information Management | Citations: 0

Authors: Yang, Zaoli; Chang, Jinping; Huang, Lucheng; Mardani, Abbas

Abstract: The digital transformation of enterprises has become an inevitable development t ... Expand

Abstract: The digital transformation of enterprises has become an inevitable development trend and one of the key driving forces that promotes the sustainable development of enterprises. However, due to the many obstacles of financial burdens, technical thresholds, and talent shortages, digital transformation has become a challenging task for entrepreneurial Small and Medium-Sized Enterprises (SMEs). Additionally, many competitive digital trans­ formation solutions on the market cause confusion when enterprises must choose one. This study drew a new information error-driven T-spherical fuzzy cloud algorithm to evaluate digital transformation solutions of entrepreneurial SMEs and support its selection. First, an evaluation index system for the digital transformation solution of entrepreneurial SMEs was established from four aspects. Then, a new concept of a T-spherical fuzzy cloud was defined to represent the evaluation information of the indicators. Additionally, a T-spherical Fuzzy Cloud Weighted Heronian Mean (T-SFCWHM) operator was used to aggregate the evaluation information. Af­ terward, an evaluation and selection decision framework for the digital transformation solution of entrepre­ neurial SMEs based on the T-SFCWHM operator was developed. Further, a practical example was given to illustrate the effectiveness of the proposed method. Finally, a discussion of the findings in our study was con­ ducted, and the conclusions were summarized. Collapse

Topics: digital transformation cloud computing IT strategic planning decision making smart manufacturing

Methods: computational algorithm expert evaluation design science theoretical contribution synthesis

Theories: fuzzy set theory