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This paper aims to systematically visualize the structure and trends from 2005 to 2021, which will help scholars gain a deeper appreciation for existing studies and grasp future research possibilities and directions.

The approach is bibliometric, using VOSviewer and CiteSpace to analyze 765 journal articles and reviews from the Web of Science (WoS) and Scopus databases over the past 16 years.

There is considerable interest in urban tourism destination image (U-TDI), partly because of the role of image in promoting the economic development of urban tourism and the associated benefits to stakeholders. Most research output concerns China, the USA, Spain and the United Kingdom (UK); research in the USA context has had a particularly wide range of influence. Highly cited journals play a crucial role, while subject structure, key articles and high-frequency keywords indicate popular topics, sub-themes and development trends. Drawing on these findings, the authors identify four topics that deserve further study.

This systematic review will enhance understanding of U-TDI research and inform future research directions as well as highlighting the need to explore destination image in greater depth, it guides policymakers in the tourism industry seeking to develop city image.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Understanding the multifaceted images of tourism destinations is critical for effective destination marketing and management strategies. Traditional approaches, including conceptualization of destination images or analysis of their antecedents and consequences, are commonly used. This study aims to advocate the inclusion of visitors’ latent profiles based on cognitive images to enrich the evaluation and formulation of destination marketing and management strategies.

The analysis focuses on Serbia, an emerging destination, that attracts an increasing number of first-time, repeat and prospective visitors. Exploratory factor analysis and confirmatory factor analysis were used to test the potential dimensions (tangible and intangible cultural destination; infrastructural and accessible destination; active, nature and family destination; sensory and hospitable destination; and welcoming, value for money (VFM) and safe destination) of the cognitive destination image factors scale while subtypes (profiles) were obtained using latent profile analysis (LPA).

The cognitive image component encompasses the perceived attributes of a destination, whether derived from direct experience or acquired through other means. The study identified the following profiles: conventional destination; sensory and hospitable destination; welcoming, VFM and safe destination; secure and active family destination and accessible cultural destination, which are presented individually with their sociodemographic assets.

The main contribution of the paper is the application of a novel method (LPA) for profiling visitor segments based on cognitive destination image. From a theoretical perspective, this research contributes to the extant body of literature pertaining to the destination image, thereby facilitating the identification of discrete latent visitor segments and elucidating noteworthy differences among them concerning a cognitive image.

This study aims to examine how veganism is “seen” by young adult non-vegan consumers and how prevailing attitudes reinforce or challenge stigmas around veganism.

Photovoice methodology was used to explore young non-vegan consumers’ attitudes and beliefs towards veganism. Data was collected from students studying advertising at a major university in Australia, who produced images and narratives reflective of their own attitudes towards veganism. Polytextual thematic analysis of the resulting visual data was then undertaken to reveal the dominant themes underpinning participants’ attitudes. Participant narratives were then reviewed to confirm whether the ascribed meaning aligned with participants’ intended meaning.

Participant images were reflective of first, how they saw their world and their place within it, which showed the interplay and interconnectedness between humans, animals and nature, and second, how they saw vegans within this world, with both positive and negative attitudes expressed. Interestingly, vegans were simultaneously admired and condemned. By situating these attitudes along a spectrum of moral evaluation, bounded by stigmatisation and moral legitimacy, participants saw vegans as being either Radicals, Pretenders, Virtuous or Pragmatists. For veganism to become more widely accepted by non-vegans, there is an important role to be played by each vegan type.

This study offers a more nuanced understanding of how and why dissociative groups, such as vegans, become stigmatised, which has implications for messaging and marketing practices around veganism and associated products/services. Future research could use a similar methodology to understand why other minority groups in society are stereotyped and stigmatised, which has broader social implications.

The present study aims to examine and explain cultural heritage destination by applying multiple dimension image model (cognitive–affective–conative aspects).

A total of 233 international heritage-based tourists were surveyed on-site at some of the most prominent historical attractions in Malacca, one of the first cities in Malaysia declared as a UNESCO World Heritage Site. The covariance-based structural equation modelling was applied to examine the hypotheses.

The structural equation modelling validated that cognitive image aspects such as living culture, intangible and tangible are affected positively. The effects are statistically significant for conative and affective images. On the other hand, cognitive tangible image is an aspect that impacted affective image to a lesser degree than conative image. Whereas affective image attributes were found to have significant and positive influence on conative image.

This study enriches the limited empirical research study on heritage image conceptualisation by expanding into tri-component model. The destination image has garnered a great deal of attention, particularly due to its significant and impactful influence on the decision-making and the sustainable behaviour of tourists, and it has since become the subject of many studies in the tourism and hospitality literatures. But most research concerning heritage image for destinations has considered the construct uni-dimensionally.

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.

Drawing from the Personal Construct Theory, this study aims to analyze the impact of using gamified apps on user behavior by investigating the service-related images and individual preferences of Generation Z (GenZ) consumers, as these emerge from gamified applications in a tourism context.

The repertory grid analysis (RGA) elicited the top elements that reflect GenZer perceptions in tourism from empirical studies in the UK and Greece. Generalized procrustes analysis was used to investigate the structure of the data for the creation of representative consensus biplots of the most important conceptual constructs to advance consumer decision-making modeling via gamification.

As per different gamified app best-practices considered, the authors extract not only common perceptual elements (e.g. place informative aspects, exploration, lodgings, food/catering) but also different image components (e.g. virtual/interactive, business vs commercial traveling, entertainment, heritage/cultural informative aspects) from comparing UK with Greek GenZers’ responses. These extracted attributes are then presented in two dimensional charts, respectively, toward creating tourist perception scales.

Notwithstanding the wide availability of gamified apps, research on gamification design in tourism and hospitality is still in the early phase. This study demonstrates the need to identify and optimize the formation of different images among GenZers. It also highlights the advantageous nature of the proposed combination of procrustes analysis with the RGA.

To the best of the authors’ knowledge, this research is among the first empirical ones toward creating scales for measuring tourist perceptions of GenZers coming from different consumer markets. It responds to scholars’ recent calls for better informing gamification design and improving contemporary consumer experience.

This study aims to explore image-based visual price determinants (image features and visual aesthetic perception) and how image features affect Airbnb listing price on a sharing accommodation platform.

The study uses an SOR model and a hedonic price model to examine the connections between the characteristics of image features, visual aesthetic perception and Airbnb listing prices. The model is then examined by an econometric model using data from Insideairbnb.com.

Empirical results revealed that image features have a significant positive effect on visual aesthetic perception, visual aesthetic perception has a significant positive effect on Airbnb listing price and visual aesthetic perception has a significant mediating effect between image features and Airbnb listing price.

This study contributes to the relationship and effect mechanism among image features, visual aesthetic perception and Airbnb listing price and has some implications for both property operators and the sharing accommodation platform.

本研究探讨了基于图像的视觉价格决定因素（图像特征和视觉美学感知）以及图像特征如何影响共享住宿平台Airbnb价格。

本研究采用SOR模型和hedonic价格模型来检验图像特征特征、视觉美感与Airbnb房源价格之间的关系。然后使用Insideairbnb.com上的数据, 通过计量经济学模型对该模型进行检验。

实证结果显示：1）图像特征对视觉美学感知有显著的正向影响; 2）视觉美学感知对Airbnb价格有显著的正向影响; 3）视觉美学感知在图像特征和Airbnb价格之间有显著的中介效应。

本研究有助于探讨图像特征、视觉美学感知和Airbnb价格之间的关系和影响机制, 对房源经营者和共享住宿平台都有一定的借鉴意义。

Este estudio explora los determinantes visuales del precio basados en las imágenes (características de las imágenes y percepción estética visual) y cómo afectan las características de las imágenes al precio de los anuncios de Airbnb en una plataforma de alojamiento compartido.

El estudio emplea un modelo SOR y un modelo de precios hedónicos para examinar las conexiones entre las características de los rasgos de la imagen, la percepción estética visual y los precios de Airbnb. A continuación, se examina el modelo mediante un modelo econométrico utilizando datos de Insideairbnb.com.

Los resultados empíricos revelan que 1) las características de la imagen tienen un efecto positivo significativo sobre la percepción estética visual, 2) la percepción estética visual tiene un efecto positivo significativo sobre el precio de los anuncios de Airbnb, y 3) la percepción estética visual tiene un efecto mediador significativo entre las características de la imagen y el precio de los anuncios de Airbnb.

Este estudio contribuye al mecanismo de relación y efecto entre las características de la imagen, la percepción estética visual y el precio del anuncio de Airbnb, y tiene algunas implicaciones tanto para los operadores inmobiliarios como para la plataforma de alojamiento compartido.

This article approaches the possibilities of photo elicitation as a technique for social research in the landscape of technology-mediated instantaneous interpersonal communication.

This case study, which involved persons with prison experience in the process of returning to the community, demonstrates how participant-generated photographs made with mobile handheld electronic devices and the meanings participants have attached to them allowed the research to take a co-creative turn.

The data analyzed show the potential of photo elicitation to build a link between researcher and researched that empowers the latter with agency in designing the results and also throughout the research process as a whole, thus allowing the former to reach a deeper level of understanding of the research participants' social reality.

The research conducted showcases the possibilities of this technique to approach the field of emotions from the ethnography and how they can build knowledge – especially in the work with vulnerable populations in vulnerable contexts – and generate new categories of analysis.

The proliferation of digital communication on social media provides new opportunities for businesses to take advantage of Internet memes to boost customer engagement. Academic literature on digital communications mostly focuses on popular forms such as selfies, branded posts, and branded emoticons. Less attention has been paid to brand memes and their implications for brand management. Based on the cue utilization theory, this research aims to investigate the informational cues of brand memes foster brand partnerships.

The structural equation modeling and importance-performance matrix analysis were used to empirically validate the research hypotheses with 595 respondents to an online survey.

Three informational cues of brand memes (i.e. comprehensibility, novelty, and meme-brand congruity) stimulated consumers' attitudes, which in turn impacted consumer-brand relationships. Another brand meme informational cue, sarcasm, negatively moderated the relationships between the three informational cues and consumer-brand relationships.

Our findings indicate that a brand can engage consumers in conversations on social media and foster long-term consumer-brand relationships through brand memes.