• Title/Summary/Keyword: Star-Rated Hotel

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The Impact of Manager's Leadership on Organizational Innovation Behavior in China's Star-Rated Hotel Industry: Focused on the mediating effect of Empowerment (중국 호텔 관리자의 리더십이 조직 혁신 행동에 미치는 영향: 심리적 임파워먼트의 매개효과를 중심으로)

  • Li, Meng;Lee, Yoon-koo
    • Journal of Digital Convergence
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    • v.19 no.1
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    • pp.151-165
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    • 2021
  • The purpose of this research is to explore the impact of managers' leadership on organizational innovation behavior in Star-Rated hotels. 244 valid Chongqing hotels' questionnaires were obtained. Through SPSS 23.0, the model structure was verified between the four variables. The results as below. First, transformational, transactional leadership has a positive impact on organizational innovation behavior. Second, transformational, transactional leadership has a significant effect on empowerment. Third, empowerment has a positive impact on organizational innovation behavior. Lastly, empowerment plays a mediation effect between transformational, transactional leadership, and organizational innovation behavior. In conclusion, managers can contribute to organizational innovation behavior by improving the abilities of leadership.

Menu Analysis Using Menu Engineering and Cost/Margin Analysis - French Restaurant of the Tourism Hotel in Seoul - (메뉴엔지니어링기법과 CMA 기법을 이용한 메뉴 분석에 관한 연구 - 서울지역 특1급 호텔의 프렌치레스토랑을 중심으로 -)

  • Lee, Eun-Jung;Lee, Young-Sook
    • Journal of the Korean Society of Food Culture
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    • v.21 no.3
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    • pp.270-279
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    • 2006
  • This study was designed to : (a) analyze the menus of the French restaurant in tourism hotel using the menu analysis techniques of Kasavana & Smith and Pavesic, (b) compare the characteristics of the two analysis techniques. The calculations for the menu analysis were done using the MS 2000 Excel spreadsheet program. The menu mix % and unit contribution margin were used as variables by Kasavana & Smith and weighted contribution margins (WCM) and potential food cost % (PFC%) by Pavesic. In two cases, a four-cell matrix was created and menu items were located in each according they achieved high or low scores with respect to two variables. The items that scored favorably on both variables were rated in the top category (e.g., star, prime) and those that scored below average on both were rated in the lowest category (e.g., dog, problem). While Kasavana & Smith's method focused on customer's viewpoints, Pavesic's method considered the manager's viewpoints. Therefore, it is more likely to be desirable for decision-making on menus if the menu analysis techniques chosen is suited to its purpose.

Influence of Big Data Analytics Capability on Innovation and Performance in the Hotel Industry in Malaysia

  • Muhamad Luqman, KHALIL;Norzalita Abd, AZIZ
    • The Journal of Asian Finance, Economics and Business
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    • v.10 no.2
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    • pp.109-121
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    • 2023
  • This study aims to address the literature gap by examining the direct relationship between big data analytics capability, marketing innovation, and organizational innovations. Additionally, this study would examine big data analytics capability as the antecedent for both innovation types and how these relationships influence firm performance. The research model is developed based on the integration of resource-based view and knowledge-based view theories. The quantitative method is used as the research methodology for this study. Based on a purposive sampling method, a total of 115 questionnaires were obtained from managers in star-rated hotels located in Malaysia. Partial least square structural equation modeling (PLS-SEM) is utilized for the data analysis. The result shows that big data analytics capability positively affects marketing and organizational innovations. The findings show that big data analytics capability and organizational innovation positively influence firm performance. Nonetheless, the result revealed that marketing innovation is not positively related to firm performance. The findings also indicate to hotel managers the importance of big data analytic capability and the resources required to build and develop this capability. The contributions from this study enrich the literature on big data and innovation, which is particularly limited in the hospitality and tourism context.