KNOWLEDGE SHARING IN A SMOKING CESSATION ONLINE COMMUNITY: A PRIVACY CALCULUS PERSPECTIVE

The paper presents a study design intended to disentangle the various components of social support and privacy concerns related to knowledge-sharing in a smoking cessation online health community from a privacy calculus perspective. In the research model, social support confers benefits of informational support, emotional support, esteem support, and network support, all of which have a positive effect on knowledge-sharing behaviour therein. The privacy concerns, articulated in terms of risks, entail threat appraisals (perceived severity and perceived vulnerability) and coping appraisals (response efficacy and self-efficacy). Threat appraisals negatively affect knowledge-sharing in the smoking cessation OHC, whereas coping appraisals have a positive effect on the sharing. Under privacy calculus theory, the risk-benefit analysis determines individual users’ knowledge-sharing behaviour in a smoking cessation OHC. The individual user’s smoking cessation OHC usage experience and the stage of smoking cessation are set as moderators in the proposed research model to explore user differences in knowledge sharing behaviour in the smoking cessation OHC. This study may contribute to a comprehensive understanding of the core antecedents to knowledge-sharing in smoking cessation OHCs

KNOWLEDGE-SHARING MECHANISMS IN A SOCIO-TECHNICAL COLLABORATIVE PROJECT IN IT-RELATED FACULTIES: PRELIMINARY FINDINGS

The aim of this research is to explore how knowledge is shared from a participant’s perspective within a collaborative project in university-industry collaborations in Australian IT-related faculties. A case study using the three parts of Nonaka’s theory of knowledge creation was carried out. Semi-structured interviews, participant observation, and document analysis were conducted for data collection to study the ways in which researchers and industry representatives within these partnerships share information and knowledge. The findings showed that based on the continuum of tacit and explicit knowledge, there are five knowledge-sharing mechanisms including reactive, articulate, sequential, accumulate, and transfer in this socio-technical collaborative project. Researchers and industry representatives experienced a variety of challenges during these mechanisms such as language failure, different work routines, different organisational cultures, and difficulty in tele-communication, mutual understanding, working hours and research aims. Also, further drivers for these mechanisms are identified, such as interest in research, mutual benefit, and partner’s needs

OFFERING ACCOUNTS OF COMPLEX IS-PHENOMENA: TOWARDS A COMBINATION OF MECHANISTIC PREDICTIONS AND GENERATIVE EXPLANATIONS

Information Systems (IS) phenomena have become increasingly volatile, complex and fast changing. Capturing their essence is an increasingly daunting task. Data science have emerged in awe to predict future outcomes. Decision-making thus becomes faster while data become bigger. Yet, in the wake of this promising path, many of these predictions lack accuracy due to the unpredictability of complex phenomena. That is why researchers promote the importance of thick qualitative data analysis as a way of seeking explanations of the generativity underlying complex phenomena. This approach is (in comparison) slow, but can answer why events occurred. Thus, we argue that sound accounts of complex IS-phenomena must come from a combinatory approach of fast predictions with slower accounts. Predictions apply laws theorized as causal mechanisms. When these outcomes do not arise, we suggest applying explanatory accounts that apply a different form of causality - generative mechanisms. Generative mechanisms can explain unpredictable outcomes, but can only be inferred through longitudinal qualitative studies. This paper opens up a research agenda for combinatory approaches of fast mechanistic predictions from big data and slower generative explanations from thick data. This combination will help capturing the essence of complex socio-technical phenomena in our capricious digitalized world

INFORMATION FLOWS IN CIRCULAR ECONOMY PRACTICES

Recently, other disciplines and scientific communities discuss the Circular Economy paradigm as a key vehicle to establish more sustainable production and consumption patterns by decoupling eco-nomic output and emissions. Conversations about information system solutions for sustainable pro-duction and consumption, however, remain notably absent in the Information Systems research community. We develop a taxonomy of information flows relevant for the successful application of Circular Economy practices. Drawing on conceptual and empirical data, we categorized nine Circu-lar Economy practices based on their underlying material flow networks and identified four classes of information flows that enable the proper functioning of these practices. Our work (a) provides a conceptual foundation for Circular Economy-related conversations within the Information Systems research community, (b) stimulates future solution-oriented Information Systems research for envi-ronmentally sustainable production and consumption, and (c) strengthens inter-disciplinary re-search

BRINGING CARE QUALITY TO LIFE: TOWARDS QUALITY INDICATOR-DRIVEN PATHWAY MODELLING IN HEALTH CARE NETWORKS

Integrated care is a promising approach to create connectivity, alignment, and collaboration in a network of health care providers, especially for people with long-term and complex conditions. It aims at improving care quality, but a common, standardised quality management approach for such networks is still missing. In this context, care pathways are recognised as important quality management tools. They define key goals of care and organise actions to achieve them. However, their utilisation in terms of quality management is lacking methodological support. The article provides the conceptual foundations as part of a design-oriented research project that aims to develop a method for the utilisation of care pathways for quality management purposes in inte-grated care settings. Therefore, the realm of process quality in integrated care is analysed and structured by means of a classification framework. Moreover, relevant concepts for the integration of quality indicators in care pathways are analysed and represented with a semi-formal domain ontology. These conceptualisations prepare the next steps in the project’s research agenda. These comprise the development and evaluation of an indicator-driven care pathway modelling lan-guage and its application for quality management in integrated care. This approach could make quality of integrated care more transparent and manageable