In indoor localization applications, many different methods have been proposed to increase positioning accuracy. Among these methods, fingerprint-based techniques are generally preferred because they use existing resources such as Wi-Fi, Bluetooth, FM signals, etc., and can be implemented on commonly used devices such as mobile phones. In this paper, we evaluate different Wi-Fi fingerprint-based methods on two datasets (with and without room-to-room transition features) created from the same environment, and we investigate the impact of room-to-room transition features on classification performance. To the best of our knowledge, transition time between rooms has not been used in past studies on fingerprint-based indoor localization. This information is of significant importance, due to the physical distance between rooms. Therefore, in this study source room and transition time to a target room have been included as features in addition to signal sources and signal strength values in the target room. From preliminary experimental results we observed that the transition time between rooms increases the performance of all tested positioning algorithms, with the Back-propagation classifier showing the best performance increase (13%).
The aim of this study is to investigate the factors that determine employee’s knowledge sharing intention through the perspectives of social capital, emotion and motivation. The impacts of individual factors, namely social capital, enjoyment in and fear for knowledge sharing, sense of belonging and knowledge sharing self-efficacy on employee’s intention to share knowledge with colleagues are examined.
In order to test the hypotheses regarding the relationships among aforementioned variables, data were gathered through question forms from 267 employees working at two shopping malls in a province of Turkey. First, confirmatory factor analysis was applied to data on LISREL 8.7 software. Second, the validity of the measurement model was examined and last, anticipated relationships among variables were investigated through path analysis in structural equation modelling. The results stated that fear for sharing knowledge affected intention negatively while enjoyment in sharing knowledge and knowledge sharing self-efficacy affected intention positively. Also, relational capital was not found to impact intention to share knowledge via fear and enjoyment. On the other hand, sense of belonging impacted intention merely through enjoyment in sharing knowledge.
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