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This study seeks to investigate issues transpiring in green hotels from a human resource perspective which is unlike most green-hotel studies centering on consumer behavioral subjects. It hypothesizes that the employees’ green ability consisting of environmental awareness, environmental knowledge, and environmental skill creates a positive impact on hotels’ green ability and ultimately on the overall performance of hotels. Using alumni from a tourism and hospitality program, this study collects 233 responses from a structured questionnaire survey. The findings indicate that hotel employees approximately contribute toward a fifth of the hotels’ ability to implement greener practices.

Using the Analytical Hierarchy Process, this study aims to identify organizational and market factors that prevent hoteliers from adopting greener management systems. This study first constructs a list of critical factors based on expert judgments reported in the literature and the responses from a select group of experienced managers. Then, the list is further refined by six hotel managers who consolidate the factors, which results in four categories explained by 20 items. Subsequently, this study draws from surveys on an expert panel consisting of 20 study subjects who are familiar with hotel operations. The survey results show that hoteliers’ abilities to create a greener image are the most important factor influencing the managers’ decisions to adopt environmentally friendly management schemes. Nevertheless, their motivation of adopting a green strategy seems to be associated with a marketing strategy, instead of generic environmental stewardship.

This chapter derives sentiment indicators (implied volatility and implied skewness) from the option pricing models of Corrado and Su (1996), Bakshi, Kapadia, and Madan (2003), and Zhang, Zhen, Sun, and Zhao (2017), and then integrates these sentiment indicators with artificial intelligence deep neural network (AIDNN) for developing the behavioral finance AIDNN (BFAIDNN) algorithms. We apply the BFAIDNN algorithms to daily derivatives data of Taiwan Futures and Options markets from 2015 to 2017. Our results demonstrate that the trading strategies established by the BFAIDNN algorithms can generate positive rewards.

The authors focus on a non-Western setting that has hardly featured in debates around political authenticity, Taiwan. The authors also adopt a novel inter-generational perspective to look at varying attitudes towards two ‘unconventional’, high-profile politicians, Ko Wen-je and Han Kuo-yu. Drawing on focus group data, the authors note the similarities and differences in the way that the different generations engage with, and assess, the two politicians with a particular focus on the extent to which their personalities, appearance, and everyday activities are perceived as authentic.

Nearly a century ago, Max Weber studied Chinese lineage system and argued that the power of the patriarchal sib impeded the emergence of industrial capitalism in China. Recently, Martin Whyte re-evaluated Weber's thesis on the basis of development studies and argued that, rather than an obstacle, Chinese family pattern and lineage ties may have facilitated the economic growth in China since the 1980s. This paper empirically tests the competing hypotheses by focusing on the relationship between lineage networks and the development of rural enterprises. Analyses of village-level data show that lineage networks, measured by proportion of most common surnames, have large positive effects on the count of entrepreneurs and total workforce size of private enterprises in rural China.