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Participative leadership's influence on employee task performance has garnered significant attention in a rapidly evolving organizational landscape. This study explores the multilevel dynamics of participative leadership congruence between unit managers and direct supervisors and its effects on employee task performance.

Drawing on two longitudinal studies based on the firms randomly selected from the Taiwan Economic Journal (TEJ) database, the research observes the mediating role of Person-Unit fit and the moderating influence of Unit-Member Exchange in the participative leadership-performance relationship.

The findings reveal how participative leadership congruence enhances person-unit fit, which in turn benefits employee task performance. Unit-member exchange plays a critical role in augmenting the participative leadership congruence? Person-unit fit? Employee task performance relationship.

The study extends leadership literature by highlighting the significance of leadership alignment across levels and the interplay between psychological and social factors in improving employee performance.

This paper aims to improve a sentiment analysis (SA) system to help users (i.e. customers or hotel managers) understand hotel evaluations. There are three main purposes in this paper: designing an unsupervised method for extracting online Chinese features and opinion pairs, distinguishing different intensities of polarity in opinion words and examining the changes in polarity in the time series.

In this paper, a review analysis system is proposed to automatically capture feature opinions experienced by other tourists presented in the review documents. In the system, a feature-level SA is designed to determine the polarity of these features. Moreover, an unsupervised method using a part-of-speech pattern clarification query and multi-lexicons SA to summarize all Chinese reviews is adopted.

The authors expect this method to help travellers search for what they want and make decisions more efficiently. The experimental results show the F-measure of the proposed method to be 0.628. It thus outperforms the methods used in previous studies.

The study is useful for travellers who want to quickly retrieve and summarize helpful information from the pool of messy hotel reviews. Meanwhile, the system will assist hotel managers to comprehensively understand service qualities with which guests are satisfied or dissatisfied.