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The goal of this paper is to use the stimulus-organism-response (S-O-R) paradigm to understand how ineffective marketplace stimuli affect perceptions related to online travel package booking, which in turn cultivate various types of confusion, and how these confusions are channelled into behavioural dispositions of consumers, such as negative electronic word-of-mouth (eWOM). It also aims to investigate the moderating effects of gender and technology self-efficacy for the suggested framework.

A sample of 437 participants who had recently booked an online travel package, underwent an analysis using a survey study design. Structural equation modelling with multigroup analysis was used to evaluate the hypotheses and the moderation effect.

The findings suggest that inefficient market stimulus results in various forms of confusion, further contributing to negative eWOM. The results also imply that technology self-efficacy lessens the effect of various confusions on adverse eWOM, and gender is found to have a moderating effect on the relationships between ineffective marketplace stimuli, confusion and negative eWOM.

The research offers tourism and hospitality management advice on how to deal with inefficient marketplace stimulation to lessen confusion, which then reduces unfavourable eWOM. Additionally, the moderate impact of technology self-efficacy and gender established through the current study has important ramifications from a tourism managers' perspective.

This study develops and validates an empirical model, which will be utilised as a framework to fully understand consumer confusion brought on by ineffective marketplace stimulation, which causes adverse eWOM. The study also gives new perspectives on the moderating roles of gender and technology self-efficacy, which have received little attention in earlier studies.

Drawing on appraisal theories, this paper aims to attempt to demonstrate how augmented reality (AR) strengthens relationships in the cognitive-affective-conative mechanism to shape visitors' recommendation of awe-inspiring heritage experiences.

A mixed-method approach was undertaken. First, an exploratory pre-study (n = 98) analyzed the multidimensionality of awe appraisals, eliciting the most salient dimensions in tourism experiences for informing the main study. Subsequently, an on-site survey was used to examine the relationships in the cognitive-affective-conative sequence, based on 316 questionnaires collected at a highly acclaimed religious heritage equipped with a multisensory AR activity.

Two distinct appraisals underlined in the awe concept were elicited during the exploratory phase: altered emotions (aggregating positive self-transformative dimensions) and the need for accommodation. The survey results demonstrated that the influence of authenticity on recommendation is shaped by emotions. Altered emotions hold a central mediating role and are differentiated from other discrete emotions. AR and the need for accommodation are revealed as contingencies that regulate the mediated mechanism.

This paper provides the hospitality and tourism stakeholders with a better understanding of how immersive technologies can be used for boosting recommendations, by enhancing the emotional responses toward authenticity perceptions.

This study introduces a novel conceptual framework to broaden our understanding of how cognitive and affective mental processes are linked to visitors’ recommendations, and how AR amplifies the outcomes. To the best of the authors’ knowledge, it is the first research to distinguish and document the specific effects of two different types of awe appraisal.

Although photographs in sustainability reports are useful in conveying complex messages, they may also be used to manipulate the presentation of disclosures to exploit the limited cognitive processing capacity of humans. Therefore, this paper aims to examine the features of photographs aimed at capturing individuals’ attention through visual structures and evoking specific emotions through carefully chosen content. Furthermore, it examines whether such framing practice is explained by incentives for legitimizing behaviours and influencing reputation.

The authors conduct a content analysis of photographs in 154 sustainability reports published by US companies. The authors captured the nature of photographs, the context in which they are being used, their themes and emotional content and layout and interaction features to understand how photographs are used for attribute framing to influence information processing. Furthermore, the authors statistically examine the framing practice between companies with different characteristics to identify any patterns for the impression management use of photographs in sustainability reports.

Photographs are often large with a horizontal orientation to capture attention and show content viewed at eye level and in either medium or close-up shots to engage viewers. Furthermore, photographs are emotionally loaded with different themes such as depictions of people, technology and nature. These themes are used to predominately evoke positive emotions of awe, nurturance, pride, amusement and attachment. This practice is often used by companies in environmentally sensitive areas that have close consumer relationships or are covered controversially in the media.

The authors reveal reporting practices and identify photographic features that attract attention and convey emotions that go beyond aesthetic qualities. This is important because emotions conveyed through photographs can be potentially misleading and influence judgements subconsciously.

This study aims to investigate the potential of an empathetic mindset aimed at empowering undergraduate students to work toward sustainable development (SD), addressing both theoretical and practical dimensions.

A mixed quantitative and qualitative research method was used in this study. Cross-sectional quantitative survey data on students’ mindsets and actions toward SD was collected to examine the theoretical relationship between belief and behavior. Qualitative inquiry using focus-group interviews explored students’ on-site learning experiences.

This study provides evidence for the impact of an empathetic mindset on education for sustainable development (ESD). Results showed that students with a more empathetic mindset showed better attitudes and behaviors toward SD actions. Findings suggest that developing an empathetic mindset improves students’ attitudes toward taking substantial action to protect the environment.

This study introduces a novel perspective extending the application of empathetic mindset in ESD.

This research examines the drivers of electric vehicle (EV) acceptance in the Kingdom of Saudi Arabia (KSA) by applying the unified theory of acceptance and use of technology (UTAUT) model, contextualized for the EV setting. The study aims to provide insights supporting the transition to sustainable transportation and identifying consumer perceptions and behavioral intentions toward EV adoption.

Based on survey data from a convenience sample collected from undergraduate and MBA students in a major university of KSA, the authors use seemingly unrelated regressions to provide novel insights on electric vehicle acceptance.

The study shows UTAUT constructs influence purchase intentions and attitudinal outcomes. Results indicate that perceived EV sustainability plays an important role in the relationship between UTAUT constructs and purchase intention alongside attitudes toward EV technology. Technological innovativeness enhances the impact of EV attitude and weakens the effect of perceived EV sustainability on purchase intention.

The study benefits researchers on sustainable technology acceptance and stakeholders facilitating sustainable transportation shifts. The insights guide the promotion of eco-friendly transportation solutions.

The research contextualizes and extends the UTAUT model constructs to understand drivers of EV acceptance. The study contributes to understanding sustainable innovation acceptance, considering the mediating role of perceptions of EV sustainability and the moderating role of technological innovativeness in driving purchase intentions.

This study aims to contribute to the International Business literature by investigating the marketing stimuli that drive impulsiveness and perceived value in mobile shopping (MS) platforms and their impact on consumer response.

This study uses a sample of 891 MS platform users and applies structural equation modeling based on the stimulus–organism–response and the consumption value theory.

The empirical finding revealed that rewards, recognition, reviews and ratings are the most influential factors driving perceived value. In addition, the results indicated that customized offerings and visually appealing experiences were the most critical factors affecting the state of impulsiveness. This study also highlights the negative impact of the ubiquitous nature of MS on impulse buying behavior, emphasizing the importance of providing consumers with tools to make informed decisions. This study demonstrates a significant positive relationship between perceived value and impulsiveness, influencing MS.

This study reveals generational differences in the impact of reviews and ratings on perceived value, which can inform businesses’ MS strategies. The results have implications for managers of international firms seeking to optimize their business strategies.

To the best of the authors’ knowledge, using structural equation modeling, this study is the first to conduct a comprehensive examination of marketing stimuli, impulsiveness and perceived value in MS platforms. It offers businesses strategic insights by identifying rewards, recognition and customized offerings as the key determinants of consumer behavior.

Message stream advertising (MSA) has become an increasingly popular option for advertising on mobile social media. However, MSA is often avoided by consumers, and this avoidance deserves more research attention. The purpose of this study is therefore to identify the underlying mechanism and key variables that affect consumer avoidance of MSA in the context of mobile social media.

A face-to-face survey was administered to current mobile users of WeChat (N = 438). Structural equation modeling was conducted to test the relationships in the research model.

Results revealed that mobile consumers employ mechanical avoidance methods (i.e. zipping, muting and zapping) against MSA. The findings also demonstrated that advertising intrusiveness (stimulus) is directly linked to negative emotions, perceived entertainment and sense of control (organism), which, in turn, relate to MSA avoidance (response).

The study contributes to the MSA avoidance literature by using the stimulus-organism-response model to deepen the understanding of consumers' MSA avoidance on mobile social media, and it suggests important managerial implications for advertising practitioners and platform operators.

This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether tourists’ travel intention is affected by travel content consumption in social networks, and more importantly, whether social comparison and envy play a mediating role in this process.

Data was collected through intercept in four popular tourist spots in Guangzhou and Zhuhai in South China. A self-administered questionnaire was used. A total of 400 participants were recruited, and 291 valid questionnaires were obtained. Bias-corrected nonparametric percentile bootstrap mediation variable test method was used to test hypotheses.

The study yielded three results. First, travel content consumption in the social networks positively influences travel intention. Second, travel content consumption in social networks indirectly affects travel intention through social comparison and envy. Third, the control variables, such as gender, age, education and income, mainly affect envy.

This study constructs a theoretical framework of stimulus–cognitive appraisal–emotion–behavioral responses. To the best of the authors’ knowledge, it is the first study to reveal that the internal psychological mechanism of travel content consumption affects travel intention. It also discloses that envy of seemingly negative emotions can encourage positive behaviors in certain situations.

This study aims to develop a methodology for predicting the resilience of individual firms to economic crisis, using historical government data to optimize one of the most important and costly interventions that governments undertake, the huge economic stimulus programs that governments implement for mitigating the consequences of economic crises, by making them more focused on the less resilient and more vulnerable firms to the crisis, which have the highest need for government assistance and support.

The authors are leveraging existing firm-level data for economic crisis periods from government agencies having competencies/responsibilities in the domain of economy, such as Ministries of Finance and Statistical Authorities, to construct prediction models of the resilience of individual firms to the economic crisis based on firms’ characteristics (such as human resources, technology, strategies, processes and structure), using artificial intelligence (AI) techniques from the area of machine learning (ML).

The methodology has been applied using data from the Greek Ministry of Finance and Statistical Authority about 363 firms for the Greek economic crisis period 2009–2014 and has provided a satisfactory prediction of a measure of the resilience of individual firms to an economic crisis.

The authors’ study opens up new research directions concerning the exploitation of AI/ML in government for a critical government activity/intervention of high importance that mobilizes/spends huge financial resources. The main limitation is that the abovementioned first application of the proposed methodology has been based on a rather small data set from a single national context (Greece), so it is necessary to proceed to further application of this methodology using larger data sets and different national contexts.

The proposed methodology enables government agencies responsible for the implementation of such economic stimulus programs to proceed to radical transformations of them by predicting the resilience to economic crisis of the firms applying for government assistance and then directing/focusing the scarce available financial resources to/on the ones predicted to be more vulnerable, increasing substantially the effectiveness of these programs and the economic/social value they generate.

To the best of the authors’ knowledge, this study is the first application of AI/ML in government that leverages existing data for economic crisis periods to optimize and increase the effectiveness of the largest and most important and costly economic intervention that governments repeatedly have to make: the economic stimulus programs for mitigating the consequences of economic crises.

Eco-innovations (EIs) are intended to benefit not only the environment but society and firms, but how the relationship is reconciled is unclear, particularly in emerging economies. The advancement of EI has resulted in both positive and negative relationships with sustainability, indicating that the association is more complex than a simple linear one.

Thus, the authors hypothesize that EI has a curvilinear relationship with sustainable business performance (SPB) and that market turbulence (MT) exerts stimulus that reinforces EIs. Accordingly, using the Stata software, the authors apply a moderated regression to a sample size data of 511 manufacturing firms to test the hypothesized assumptions.

Although the results attest to a positive relationship between EI and SBP, the results are synonymous with an inverted “U” shape that renders EIs unprofitable beyond a certain threshold (rebound effect). Additionally, the authors observe that the moderation stimulus of technology turbulence flattens the inverted U-shaped curve.

Built on the foundations of natural-resource-based view (NRBV) and contingency theory, the authors identify the rebound effect point of EI and SBP and the reinforcing stimulus of MT.