Search results

The purpose of this paper is to propose sentiment annotation at sentence level to reduce information overloading while reading product/service reviews in the internet.

The keyword-based sentiment analysis is applied for highlighting review sentences. An experiment is conducted for demonstrating its effectiveness.

A prototype is built for highlighting tourism review sentences in Chinese with positive or negative sentiment polarity. An experiment results indicates that sentiment annotation can increase information quality and user’s intention to read tourism reviews.

This study has made two major contributions: proposing the approach of adding sentiment annotation at sentence level of review texts for assisting decision-making; validating the relationships among the information quality constructs. However, in this study, sentiment analysis was conducted on a limited corpus; future research may try a larger corpus. Besides, the annotation system was built on the tourism data. Future studies might try to apply to other areas.

If the proposed annotation systems become popular, both tourists and attraction providers would obtain benefits. In this era of smart tourism, tourists could browse through the huge amount of internet information more quickly. Attraction providers could understand what are the strengths and weaknesses of their facilities more easily. The application of this sentiment analysis is possible for other languages, especially for non-spaced languages.

Facing large amounts of data, past researchers were engaged in automatically constructing a compact yet meaningful abstraction of the texts. However, users have different positions and purposes. This study proposes an alternative approach to add sentiment annotation at sentence level for assisting users.

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.

This chapter presents systematic evidence on the persistent power of guanxi, the Chinese phrase for informal social relations and networks, in transitional China. I draw heavily on my previous publications reporting findings from a series of probability sample surveys of the Job-Search Network (thereafter JSNET) project in Chinese cities, and job histories of the survey respondents combined cover a span of 37 years from 1978, the beginning year of China's market-oriented reforms, to 2014, the year of last JSNET survey completed.

The basic assumption is that there is a symmetric relationship between review valence and rating, but what if review valence and rating were linked asymmetrically? There are few studies which have investigated the situations in which positive and negative online reviews exert different influences on ratings. This study considers brand strength as having an important moderating role because the average rating of existing reviews for a particular product is a heuristic cue for decision makers. Thus, the purpose of this paper is to argue that an asymmetric relationship between review content valence and numerical rating will depend on brand strength.

The authors have conducted a sentiment analysis via text mining, using self-developed computer programs to retrieve a data set from the TripAdvisor website.

This study finds there is an asymmetric relationship between review valence (verbal) and numerical rating. The authors further find brand strength to have an important moderating role. For a stronger brand, negative review content will have a greater impact on numerical ratings than positive review content, while for a weaker brand, positive review content will have a greater impact on numerical ratings than negative review content.

Marketers could adopt sentiment analysis via text mining of online reviews as a valid measure or predictor of consumer satisfaction or numerical ratings. Strong brands should direct more attention to negative reviews, because in such reviews the negative impact transcends the positive. In contrast, weak brands should aim to exploit as many positive reviews as possible to minimize the impact of any negative reviews.

This study finds there is an asymmetric relationship between review valence (verbal) and numerical rating and considers brand strength to play an important moderating role. The authors have used real data from the TripAdvisor website, which allow people to express themselves in an unsolicited manner, and linked these with the results from the sentiment analysis.

With the fierce competition in a knowledge economy, knowledge-intensive enterprises (KIEs) make technological progress in their catching-up processes through implementing product innovation and process innovation. In this study, the aim is to understand the determinants of enterprise innovation type in China's catch-up environment. Further, this paper intends to deal with two related questions. First, what effect does the internal knowledge base have on KIEs' technology innovation activities? Second, considering the technology gap and technology development speed, what are the different impacts of the knowledge base on the type of technology innovation activities?

This paper collected data from 212 KIEs in China through a two-stage questionnaire survey, combined with statistical data for research. The hypothesis was tested by regression analysis. Specifically, descriptive statistics and regression analysis are introduced to test the hypothetical relationship between the knowledge base and technology innovation. Meanwhile, multiple regression is used to test whether there is any difference in the influence of technology gap and technology development speed on enterprise knowledge base and technology innovation. Finally, the corresponding robustness tests are done.

This study finds that in a sample of Yangtze River Delta KIEs, firms' knowledge base influences innovation types. Specifically, the knowledge base width (KBW) and knowledge base depth (KBD) positively influence process innovation, and KBD positively affects product innovation. Regarding the effects of catch-up context factors on KIEs’ innovation choice, a wide technology gap tends to positively influence product innovation in industries with high levels of KBW. Moreover, when technology development speed is high, its potential positive influence on process innovation will be more significant for industries with deeper knowledge bases.

This paper fills the research gap that existing studies ignore the relationship between types of technology innovation and knowledge base dimensions, especially for KIEs. First, this paper deepens the understanding of the impact mechanism of KIEs' existing knowledge base on innovation activities; the unique use of resources by enterprises is the basis of enterprises' competitive advantage and will become enterprises' competitive advantage. Second, this study indicates that against different backdrops of technology gap and technology development speed, enterprises with different knowledge bases will adopt different types of technology innovation activities. Third, this paper shows that a wider technology gap provides broader innovation space, so the technology gap plays a pulling role in KBW and product innovation, thus pushing forward enterprises' technological catch-up.

In this paper, the authors aim to examine some characteristics of the innovation system and policy in France and China. For comparison, they also highlight some high technology features of Silicon Valley and California.

The authors study the characteristics of innovation in France and in China. The authors examine the technology systems and policies in both countries and compare their features with those in Silicon Valley.

As far as France is concerned, it can be stated that the innovation system and policy are under transformation, going from a strong state involvement to a more decentralized framework. This evolution leads to a multi-level governance of the innovation system and to the emergence of new actors. For China, the most interesting development in China is the evolution of its internet-related sector. The authors argue here that the internet-driven economy is a radical, systemic technological change and it is rapidly growing in China.

One of the earliest papers comparing the innovation policies and activities in France, China and Silicon Valley.

The aim of this study was to investigate the impact of the transactive memory system (TMS) on green innovation and examine the mediation role of the social network at all hierarchical levels.

Three hypotheses were examined by performing regression analyses on survey data from manufacturing firms in China. Especially, the nested sets of data from 389 individual observations nested in 53 work teams, including individual level and collective level have been investigated.

The study results show that the TMS has a positive effect on green innovation. Furthermore, the results indicate that at the team level, structure holes' mediation in this relationship is stronger than degree centrality; at the individual level, weak ties mediation in the relationship of specialization and green innovation is stronger than strong ties, conversely, strong ties mediation in the relationship of credibility and green innovation is stronger than weak ties.

This study expands previous research by highlighting the significance of multilevel social network elements in the context of the TMS and sustainable development and enriches the present research on green innovation.

Wine tourism is gaining increasing popularity among Chinese tourists, making it necessary to thoroughly examine tourist behavior. While online reviews posted by wine tourists have been extensively studied from the perspectives of destinations and wineries, the perspective of the tourists themselves has been overlooked. To address this gap, this study aims to identify significant attributes intrinsic to the tourism experiences of Chinese wine tourists by adopting a text-mining approach from a tourist-centric perspective.

The authors use topic modeling to extract these attributes, calculate topic intensity to understand tourists’ attention distribution across these attributes and conduct topical sentiment analysis to evaluate tourists’ satisfaction levels with each attribute. The authors perform importance-performance analyses (IPAs) using topic intensity and sentiment scores. Furthermore, the authors conduct semistructured in-depth interviews with Chinese wine tourists to gain insights into the underlying reasons behind the key findings.

The study identifies eleven attributes for domestic wine tourists and seven attributes for outbound wine tourists. From the reviews of both domestic and outbound tourists, three common attributes have been identified: “scenic view”, “wine tasting and purchase” and “wine knowledge”.

According to the results of the IPAs, there is a pressing need for enhancements in the wine tasting and purchasing experience at domestic wine attractions. Additionally, managers of domestic wine attractions should continue to prioritize the positive aspects of the family trip experience and scenic views. On the other hand, for outbound wine attractions, it is crucial for managers to maintain their efforts in providing opportunities for wine knowledge acquisition, ensuring scenic views and upholding the reputation of wine regions.

First, this study breaks new ground by adopting a tourist-centric perspective to extract significant attributes from real wine tourism reviews. Second, the authors conduct a comparative analysis between Chinese wine tourists who travel domestically and those who travel abroad. The third novel aspect of this study is the application of IPA based on textual review data in the context of wine tourism. Fourth, by integrating topic modeling with qualitative interviews, the authors use a mixed-method approach to gain deeper insights into the experiences of Chinese wine tourists.

This study aims to analyze Chinese and Western visitors’ on‐line reviews of Shenzhen under five dimensions: catering, accommodation, transportation, travel and shopping.

This study used a multidimensional discourse analysis to assess visitors’ experience, perception and emotional evaluations of Shenzhen in reviews on TripAdvisor.com.

The findings suggest that both Chinese and Western visitors show positive perceptions of Shenzhen’s transportation convenience and options and show great interest in folk culture. Both groups focus on shopping, service and price but believe that the prices in Shenzhen are high.

The classification of reviews highlights tourism elements in Shenzhen, which can offer implications for destination image formation for similar destinations.

This study offers suggestions on how to build an appealing destination that meets both Chinese and Western tourists’ needs.

This study enriches the theory of tourism image perception of Shenzhen as it relates to language and culture.

This study offers implications on building an appealing destination that meets Chinese and Western tourists’ expectations.

深圳目的地形象感知：基于中西方游客在线评论的话语分析

摘要

本研究从餐饮、住宿、交通、旅游、购物五个维度分析中西方游客对深圳的评价。

本研究采用多维语篇分析来评估访问者对深圳的体验、感知和情感评价。

调查结果表明, 中国和西方游客对深圳的交通便利和选择都表现出积极的看法, 并对民俗文化表现出浓厚的兴趣。两组都关注购物、服务和价格, 但认为深圳的物价偏高。

评论的分类突出了深圳的旅游元素，可以为相似目的地形象的构建提供启示。

本研究丰富了深圳旅游形象感知与语言相关的理论。它为建设一个满足中国和西方游客期望的吸引人的目的地提供了启示。

旅游目的地形象, 话语分析, 深圳, 多维话语分析, 中西方游客

文章类型： 研究型论文

Tourists with different cultural backgrounds think and behave differently. Accurately capturing and correctly understanding cultural differences will help tourist destinations in product/service planning, marketing communication and attracting and retaining tourists. This research employs Hofstede's cultural dimensions theory to analyse the variations in destination image perceptions of Chinese-speaking and English-speaking tourists to Xiamen, a prominent tourist attraction in China.

The evaluation utilizes a two-stage approach, incorporating LDA and BERT-BILSTM models. By leveraging text mining, sentiment analysis and t-tests, this research investigates the variations in tourists' perceptions of Xiamen across different cultures.

The results reveal that cultural disparities significantly impact tourists' perceived image of Xiamen, particularly regarding their preferences for renowned tourist destinations and the factors influencing their travel experience.

This research pioneers applying natural language processing methods and machine learning techniques to affirm the substantial differences in the perceptions of tourist destinations among Chinese-speaking and English-speaking tourists based on Hofstede's cultural theory. The findings furnish theoretical insights for destination marketing organizations to target diverse cultural tourists through precise marketing strategies and illuminate the practical application of Hofstede's cultural theory in tourism and hospitality.