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The purpose of this paper is to analyse whether publicly shared images on Instagram are representative of tourist behaviour in a destination. This aspect is crucial for destination image management, as it can influence the way tourists perceive the destination.

The research compares three different factors: the route followed by a group of tourists, the whole set of photographs taken by them and the images that they made publicly available on Instagram. It relies on a field work done by a group of 122 tourists in Turin (Italy). At a qualitative level, the answers given by tourists to the motivations that led them to share some of the image are analysed.

The results showed how the spatial distribution of the images shared publicly on Instagram only partially coincides with the whole set of images taken by tourists.

It is important to avoid basing marketing and management policies on just the places featured in publicly shared images. If not, there is a risk of taking decisions based on the behaviour of some, rather than all, tourists.

Many papers claim to be based on the Instagram image as elements to study tourism. However, most of these papers only analyse public images. This fact can affect the results as there may be, for example, areas visited by tourists where photos are not taken. This paper therefore contributes to a better understanding of Instagram as a tool for the study of urban tourism.

This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g. Xiaohongshu and Weibo).

Media attention on nonconsensual intimate image dissemination has led to the relatively recent proliferation of academic research on the topic. This literature has focused on many areas including victimization and perpetration prevalence rates, coerced sexting, legal and/or criminal contexts, sexual violence in digital spaces, gendered constructions of blame and risk, and legal analysis of high-profile cases and legislation. Despite this research, several gaps exist, including a lack of empirical research with service providers. Informed by in-depth interviews with 10 sexual violence frontline professionals in Southern Ontario (Canada), this chapter focuses on their perspectives of the additive role of technology. With respect to nonconsensual intimate image dissemination, technology acts as a digital “layer” that operates in addition to the commission of physical acts of sexual violence, and compounds the harms experienced by the victim by adding a virtual – and indelible – “permanent remembering” of the violence. Nuancing the contours of consent in a digital age, this chapter concludes by considering what consent means in a technological context.

The nonconsensual taking or sharing of nude or sexual images, also known as “image-based sexual abuse,” is a major social and legal problem in the digital age. In this chapter, we examine the problem of image-based sexual abuse in the context of digital platform governance. Specifically, we focus on two key governance issues: first, the governance of platforms, including the regulatory frameworks that apply to technology companies; and second, the governance by platforms, focusing on their policies, tools, and practices for responding to image-based sexual abuse. After analyzing the policies and practices of a range of digital platforms, we identify four overarching shortcomings: (1) inconsistent, reductionist, and ambiguous language; (2) a stark gap between the policy and practice of content regulation, including transparency deficits; (3) imperfect technology for detecting abuse; and (4) the responsibilization of users to report and prevent abuse. Drawing on a model of corporate social responsibility (CSR), we argue that until platforms better address these problems, they risk failing victim-survivors of image-based sexual abuse and are implicated in the perpetration of such abuse. We conclude by calling for reasonable and proportionate state-based regulation that can help to better align governance by platforms with CSR-initiatives.

Canada criminalized the nonconsensual distribution of intimate images in 2014. Lawmakers and commentators noted that this new offense would fill a legislative gap in relation to “revenge pornography,” which entails individuals (typically men) sharing intimate images of their ex-partners (typically women) online in an attempt to seek revenge or cause them harm. Feminist writers and activists categorize revenge pornography as a symptom and consequence of “rape culture,” in which sexual violence is routinely trivialized and viewed as acceptable or entertaining, and women are blamed for their sexual victimization. In this chapter, I analyze Canada's burgeoning revenge pornography case law and find that these cases support an understanding of revenge pornography as a serious form of communal, gendered, intimate partner violence, which is extremely effective at harming victims because of broader rape culture. While Canadian judges are taking revenge pornography seriously, there is some indication from the case law that they are at risk of relying on gendered reasoning and assumptions previously observed by feminists in sexual assault jurisprudence, which may have the result of bolstering rape culture, rather than contesting it.

Against the background of the popularity of social media and heritage tourism, this study aims to focus on world heritage sites, proposing a method to examine and compare the digital spatial footprints left by tourists using geographic information systems.

By analyzing user-generated content from social media, this research explores how digital data shapes the destination image of WHS and the spatial relationships between the components of this destination image. Drawing on the cognitive-affective model (CAM), it investigates through an analysis of integrated data with more than 20,000 reviews and 2,000 photos.

The creativity of this research lies in the creation of a comprehensive method that combines text and image analytics with machine learning and GIS to examine spatial relationships within the CAM framework in a visual manner.

The results reveal tourists' perceptions, emotions, and attitudes towards George Town and Malacca in Malaysia, highlighting several key cognitive impressions, such as history, museums, churches, sea, and food, as well as the primary emotions expressed. Their distributions and relationships are also illustrated on maps.

Tourism practitioners, government officials, and residents can gain valuable insights from this study. The proposed methodology provides a valuable reference for future tourism studies and help to achieve a sustainable competitive advantage for other heritage destinations.

This study aims to predict the effect of cultural distance, perceived risk and electronic word of mouth (eWOM) on higher education institutes' students' destination image. In addition, it examines the mediating role of destination image in relation to students' travel intentions.

An online survey was employed to collect data from 200 graduate and postgraduate students. The partial least squares was employed to analyse the hypothesised relationships.

The results of this study found support for the positive effect of cultural distance and eWOM on destination image. Additionally, the mediating effect of destination image was also supported.

This research confirms the vital role of destination image as an antecedent of students' future intention to visit the destination. Moreover, this study contributes to marketing theory by predicting the critical drivers of higher education students' destination image and discussing their applications in the education sector.

Due to the intense rivalry in the smartphone market, manufacturers of mobile phones are becoming increasingly interested in knowing the factors that influence consumers' purchase intention. This paper aims to examine the effect of country-of-origin image, brand image and attitude towards the brand on the purchase intention of smartphone users.

An empirical study was performed based on the information gathered from smartphone users. The structural equation modeling (SEM) technique was applied to examine the hypotheses.

The authors found that brand image and attitude towards the brand significantly influence consumer purchase intention. Additionally, there is an indirect effect even when the nation of origin image does not directly influence the consumer's purchase intention. Indeed, brand image and attitude towards the brand act as a mediator between the country-of-origin image and purchase intention.

This study presents a conceptual model on the impact of country-of-origin image on the propensity of consumers to buy smartphones in a field where little research has been done. The investigation offers a consumer-focused analysis regarding the country-of-origin image. This suggests a significant shift from the current strategy, which is frequently centered on the viewpoint of the companies.

This paper aims to discuss the development of a defect classification system that can be used to detect and classify powder bed surface defects from captured layer images without the need for specialised computational hardware. The idea is to develop this system by making use of more traditional machine learning (ML) models instead of using computationally intensive deep learning (DL) models.

The approach that is used by this study is to use traditional image processing and classification techniques that can be applied to captured layer images to detect and classify defects without the need for DL algorithms.

The study proved that a defect classification algorithm could be developed by making use of traditional ML models with a high degree of accuracy and the images could be processed at higher speeds than typically reported in literature when making use of DL models.

This paper addresses a need that has been identified for a high-speed defect classification algorithm that can detect and classify defects without the need for specialised hardware that is typically used when making use of DL technologies. This is because when developing closed-loop feedback systems for these additive manufacturing machines, it is important to detect and classify defects without inducing additional delays to the control system.

This study aims to draw on cue utilization and irradiation theories to: determine the extent to which country-of-origin image and its sub-dimensions exert an aggregate and relative influence on consumer brand evaluations; and identify the contextual and methodological factors that account for between-study variance in the focal relationship.

A random-effects model was used to examine 166 empirical articles encompassing 499,563 observations, and 282 effect sizes from 1984 to 2020 using Comprehensive Meta-Analysis software.

Results show that country-of-origin image has a positive, moderate effect on consumer brand evaluations. Moreover, findings reveal that each dimension of country-of-origin image – general country image, general product country image, specific product country image and partitioned country image – significantly influences consumer brand evaluation, but the effect of general product country image is the largest. What’s more, the aggregate impacts of country-of-origin image on consumer brand evaluation – brand commitment, brand-specific associations and general brand impressions – show that the effect on brand commitment is the largest. Finally, findings show that contextual factors (brand source, product sector, culture [individualism vs collectivism], brand origin continents and respondents’ continent) and methodological factors (cues, sampling unit, publication year and sample size) significantly account for between-study variance.

This study provides the first meta-analytic review of the relationship between country-of-origin image and consumer brand evaluation to help clarify mixed findings and balance out the literature, which has only seen quantitative reviews on product evaluation and purchase decisions.