This research aims to develop a framework to capture the interplay of network strategic decisions, and to understand how firms operating within a supply network interact with each other. The research involves an in-depth longitudinal case study in one supply network consisting of 20 firms. Data was systematically collected through the use of a Supply Network Analysis Process (SNAP) methodology. Interviews and secondary data were collected for further data validation and triangulation. This paper describes the above case study in detail, explains the SNAP methodology and framework development, and discusses the implications of the research both in academia and industry.

In the age of digitalization, travel applications (or travel apps) are indispensable tools for modern travel activities. During an app's selection and adoption phases, privacy concerns remain a sensitive issue that may demotivate users’ from continuing to use it. This study integrated both the stimulus-organism-response model (S-O-R) and psychological reaction theory (PRT) to explore the factors that influence users’ app usage experiences and behavioral responses. A self-administered questionnaire was designed and distributed to Gen Y users in mainland China. The findings of PLS-SEM analysis showed that usage intentions are predicted by the ability of travel apps to engage with users and generate favorable values. Additionally, users with low privacy concerns were shown to have a stronger intention to recommend travel apps to others. All in all, the findings from this study offer valuable insights to tourism providers and app developers.

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