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Due to the worldwide growth of digital image sharing and the maturity of the tourism industry, the vast and growing collections of digital images have become a challenge for those who use and/or manage these image data across tourism settings. To overcome the image indexing task with less labour cost and improve the image retrieval task with less human errors, the content-based image retrieval (CBIR) technique has been investigated for the tourism domain particularly. This paper aims to review the relevant literature in the field to understand these previous works and identify research gaps for future directions.

A systematic and comprehensive review of CBIR studies in tourism from the year 2010 to 2019, focussing on journal articles and conference proceedings in reputable online databases, is conducted by taking a comparative approach to critically analyse and address the trends of each fundamental element in these research experiments.

Based on the review of the literature, the trends of CBIR studies in tourism is to improve image representation and retrieval by advancing existing feature extraction techniques, contributing novel techniques in the feature extraction process through fine-tuning fusion features and improving image query of CBIR systems. Co-authorship, tourist attraction sector and fusion image features have been in focus. Nonetheless, the number of studies in other tourism sectors and available image databases could be further explored.

The fact that no existing academic review of CBIR studies in tourism makes this paper a novel contribution.

Because of the fast-growing digital image collections on online platforms and the transfer learning ability of deep learning technology, image classification could be improved and implemented for the hostel domain, which has complex clusters of image contents. This paper aims to test the potential of 11 pretrained convolutional neural network (CNN) with transfer learning for hostel image classification on the first hostel image database to advance the knowledge and fill the gap academically, as well as to suggest an alternative solution in optimal image classification with less labour cost and human errors to those who manage hostel image collections.

The hostel image database is first created with data pre-processing steps, data selection and data augmentation. Then, the systematic and comprehensive investigation is divided into seven experiments to test 11 pretrained CNNs which transfer learning was applied and parameters were fine-tuned to match this newly created hostel image dataset. All experiments were conducted in Google Colaboratory environment using PyTorch.

The 7,350 hostel image database is created and labelled into seven classes. Furthermore, its experiment results highlight that DenseNet 121 and DenseNet 201 have the greatest potential for hostel image classification as they outperform other CNNs in terms of accuracy and training time.

The fact that there is no existing academic work dedicating to test pretrained CNNs with transfer learning for hostel image classification and no existing hostel image-only database have made this paper a novel contribution.

One reason for the severe short age of nurses is the un will ing ness of males to pursue the profession in great numbers. This article explores people’s negative stereotypic beliefs about males in the nursing profession. Participants were asked to provide evaluations and trait descriptions of both male and female nurses. The results revealed that both male and female participants harbored favorable impressions of female nurses but unfavorable impressions of male nurses. Male participants were especially likely to form negative evaluations of men who pursue the nursing profession. Exploratory multivariate analyses of trait descriptions revealed that male nurses are viewed as feminine, non traditional, intelligent, and caring. Additional results suggest that unfavorable stereo types of male nurses can be moderated by highlighting the masculine qualities of nurses’ job duties. Implications for the recruitment of males into nursing are discussed.

Recent years have witnessed an unexpected and astonishing rise of AI-generated (AIGC), thanks to the rapid advancement of technology and the omnipresence of social media. AIGCs created to mislead are more commonly known as DeepFakes, which erode our trust in online information and have already caused real damage. Thus, countermeasures must be developed to limit the negative impacts of AIGC. This position paper aims to provide a conceptual analysis of the impact of DeepFakes considering the production cost and overview counter technologies to fight DeepFakes. We will also discuss future perspectives of AIGC and their counter technology.

We summarize recent developments in generative AI and AIGC, as well as technical developments to mitigate the harmful impacts of DeepFakes. We also provide an analysis of the cost-effect tradeoff of DeepFakes.

The mitigation of DeepFakes call for multi-disciplinary research across the traditional disciplinary boundaries.

Government and business sectors need to work together to provide sustainable solutions to the DeepFake problem.

The research and development in counter-technologies and other mitigation measures of DeepFakes are important components for the health of future information ecosystem and democracy.

Unlike existing reviews in this topic, our position paper focuses on the insights and perspective of this vexing sociotechnical problem of our time, providing a more global picture of the solutions landscape.

We conducted a pilot study to compare the emotions experienced by Dutch and Chinese students during a face‐to‐face negotiation role play. Emotions play an important role in negotiations because they influence the behaviour and judgments of negotiators. The Data Printer case developed by Greenhalgh was used to examine the patterns of feelings that emerge during negotiations. One hundred and four participants (62 Chinese and 42 Dutch post graduate students) role‐played two different characters who were confronted with a payment dispute regarding the servicing of a defective printer. The results of the MANOVA and of the Factorial Analysis demonstrates that culture as a carrier of social values and norms did influence the emotional reactions of the people socialised in different cultural contexts. The paper concludes that in order to facilitate conflict resolution and interpersonal communication amongst protagonists in mono as well as in inter‐cultural negotiation context individuals should learn to manage their emotions constructively.

The power vacuum in Europe after World War II induced the United States and the Soviet Union to seek European allies against one another (an action that neorealists would describe as “external balancing”). The disparate geopolitical circumstances facing the two super powers were bound to have some effect on the types of alliances they sought. In the United States, many officials and legislators initially were reluctant to maintain a permanent military presence in Europe. They planned instead to help the West European states themselves acquire the wherewithal to sustain a viable balance against the Soviet Union. Not until after the outbreak of the Korean War in June 1950 did U.S. perceptions of the Soviet threat change enough to generate wide spread support for a huge increase in the U.S. military commitment to Western Europe. By that point, U.S. officials already sensed, from the Berlin crisis of 1948‐49, that the United States would need an extensive network of military bases in Western Europe if it wished to deter or rebuff Soviet probes on the continent. The increased deployment of U.S. troops and weapons in Europe from late 1950 on was geared toward that end, and was also intended to reassure the West Europeans of the strength of the U.S. commitment to their defense. That commitment had been nominally codified in April 1949 ‐ primarily at the West Europeans’ initiative ‐ with the establishment of the North Atlantic Treaty Organization (NATO), but it was not until the early 1950s, after the shock of Korea, that the United States began putting up the resources needed to fulfill its military obligations to NATO.

The purpose of the study is to evaluate the severity of public events in real time from the perspective of social media and to construct the early warning mechanism of public events.

This study constructed the severity assessment system of public events from the dimensions of the netizens' role, the Internet media's role, the spread of public events and the attitudes and feelings of netizens. The method of analyzing the influence tendency of the public event severity indicators was proposed. A total of 1,107,308 microblogging entries regarding four public events were investigated. The severity of public events was divided into four levels.

It is found that serious public events have higher indicator values than medium level events on the microblogging platform. A quantitative severity classification standard for public events was established and the early warning mechanism of public events was built.

Microblogging and other social media platforms provide rich clues for the real-time study and judgment of public events. This study only investigated the Weibo platform as the data source. Other social media platforms can also be considered in future.

Different from the ex-post evaluation method of judging the severity of public events based on their physical loss, this study constructed a quantitative method to dynamically determine the severity of public events according to the clues reflected by social media. The results can help the emergency management departments judge the severity of public events objectively and reduce the subjective negligence and misjudgment.

This paper aims to review and discuss customer satisfaction and its application to the hospitality and tourism industries. This paper defines the concept and analyzes its importance to services in general and to hospitality/tourism services in particular. This paper is a revision and update of an article previously published by Pizam and Ellis (1999) on customer satisfaction measurements.

The most recent research on customer satisfaction measurements and scales is summarized and presented in the paper.

Following a discussion on the dimensions and attributes of satisfaction, the main methods of measuring satisfaction are listed, and cross-cultural issues that affect satisfaction are reviewed. Finally, the paper concludes with a comprehensive review of the current online tools and techniques available for measuring customer satisfaction.

This summary gives a good overview to researchers who require a comprehensive review of the available research measurements and scales for customer satisfaction.

For the past decade, a considerable amount of research has been conducted in customer satisfaction. Finding the appropriate measurements and scales for customer satisfaction can be time-consuming and confusing. This paper provides a comprehensive overview of the best-known measurements and scales in customer satisfaction research. The paper also provides innovative online tools and techniques available for research.

Presents over sixty abstracts summarising the 1999 Employment Research Unit annual conference held at the University of Cardiff. Explores the multiple impacts of globalization on work and employment in contemporary organizations. Covers the human resource management implications of organizational responses to globalization. Examines the theoretical, methodological, empirical and comparative issues pertaining to competitiveness and the management of human resources, the impact of organisational strategies and international production on the workplace, the organization of labour markets, human resource development, cultural change in organisations, trade union responses, and trans‐national corporations. Cites many case studies showing how globalization has brought a lot of opportunities together with much change both to the employee and the employer. Considers the threats to existing cultures, structures and systems.