IT Enabled Collaboration for Development
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ItemInvestigating Antecedents and Development of Trust in Ridesharing Platform: A Case from China( 2019-01-08)Trust is playing an important role in the sharing economy-driven business. However, little research has been conducted measuring trust as a dynamic process in the sharing economy era. This research is a preliminary exploration investigating trust antecedents and the dynamic development of clients’ trust in ridesharing platforms. We used 102 two-stage interviews collected from clients of a major Chinese ridesharing platform. Then we conducted a qualitative content analysis and proposed a theoretical model based on literature and data analysis. We found that antecedents of trust in two stages are different. Personality-based beliefs and cognition-based beliefs are the main antecedents of initial trust, while knowledge-based beliefs, institution-based beliefs, and calculus-based beliefs are the main antecedents of ongoing trust. These findings could help us understand how trust evolves over time and enable us to explore several viewpoints on ridesharing platforms.
ItemEnabling the Identification of Industrial Symbiosis through ICT( 2019-01-08)Industrial Symbiosis (IS) is an emerging business tool with a systemic and collaborative approach to optimize and close cycles of materials and energy by identifying synergies and fostering cross-sectoral cooperation among economic actors. The major facilitator of revealing IS opportunities for organizations is both analyzing the status quo with quantitative methods and connecting the supply and demand of the entities involved through an adequate Information Communication Technology (ICT) solution. This study analyzed the extant body of literature and the corresponding ICT tools of IS in order to design a preliminary concept of an Information Technology (IT) supported IS tool that supports the identification and assessment of IS potentials, providing more transparency among market players and proposing potential cooperation partners according to selectable criteria (e.g. geographical radius, material properties, material quality, purchase quantity, delivery period), bringing synergy partners together.
ItemUnderstanding Patients’ WOM of IT-Enabled Healthcare Service: A Case Study of Online Health Consultation( 2019-01-08)In healthcare context, the service delivery and information management are facilitated via varieties of IT-Enabled collaborative platforms. The effect of IT-Enabled collaboration health service has been extensively explored in recent decades. However, few studies have investigated the IT-Enabled health service from the perspective of patients or health consumers. Our research fills this research gap through a case study of an online health consultation website. The review systems on the website enable patients to write their word of mouth about services and physicians, thus providing us with a material to understand the interests, motivations and expectations of patients. In this work, we utilize text-analysis techniques: term frequency analysis, sentiment analysis, feature words clustering and topic modelling to process textual WOM of patients about their experience. The results of our research have both theoretical and practical implications for optimizing the IT-Enabled health service, maintaining a harmonious physician-patients’ relationship and increasing patient satisfaction.
ItemHow Text Mining Algorithms for Crowdsourcing Can Help Us to Identify Today's Pressing Societal Issues( 2019-01-08)Crowdsourcing is increasingly applied in the area of open development with the goal to find solutions for today’s pressing societal issues. To solve such wicked problems, manifold solutions need to be found and applied. In contrast to this, most recent research in crowdsourcing focuses on the few winning ideas, ignoring the sheer amount of content created by the community. In this study we address this issue by applying an automated text mining technique to analyze the ideas contributed by the crowd in an initiative tackling plastic pollution. We show that automated text mining approaches reveal numerous possibilities to make use of the so far unused content of IT enabled collaboration projects. We further add insights into how our findings can help researchers and practitioners to accelerate the solution process for today’s pressing societal issues.