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This research explores the differential effects of pixel-level and object-level visual complexity in firm-generated content (FGC) on consumer engagement in terms of the number of likes and shares, and further investigates the moderating role of image brightness.

Drawing on a deep learning analysis of 85,975 images on a social media platform in China, this study investigates visual complexity in FGC.

The results indicate that pixel-level complexity increases both the number of likes and shares. Object-level complexity has a U-shaped relationship with the number of likes, while it has an inverted U-shaped relationship with the number of shares. Moreover, image brightness mitigates the effect of pixel-level complexity on likes but amplifies the effect on shares; contrarily, it amplifies the effect of object-level complexity on likes, while mitigating its effect on shares.

Although images play a critical role in FGC, visual data analytics has rarely been used in social media research. This study identified two types of visual complexity and investigated their differential effects. We discuss how the processing of information embedded in visual content influences consumer engagement. The findings enrich the literature on social media and visual marketing.

This study examined how people assess health information from AI and improve their diagnostic ability to identify health misinformation. The proposed model was designed to test a cognitive heuristic theory in misinformation discernment.

We proposed the heuristic-systematic model to assess health misinformation processing in the algorithmic context. Using the Analysis of Moment Structure (AMOS) 26 software, we tested fairness/transparency/accountability (FAccT) as constructs that influence the heuristic evaluation and systematic discernment of misinformation by users. To test moderating and mediating effects, PROCESS Macro Model 4 was used.

The effect of AI-generated misinformation on people’s perceptions of the veracity of health information may differ according to whether they process misinformation heuristically or systematically. Heuristic processing is significantly associated with the diagnosticity of misinformation. There is a greater chance that misinformation will be correctly diagnosed and checked, if misinformation aligns with users’ heuristics or is validated by the diagnosticity they perceive.

When exposed to misinformation through algorithmic recommendations, users’ perceived diagnosticity of misinformation can be predicted accurately from their understanding of normative values. This perceived diagnosticity would then positively influence the accuracy and credibility of the misinformation.

Perceived diagnosticity exerts a key role in fostering misinformation literacy, implying that improving people’s perceptions of misinformation and AI features is an efficient way to change their misinformation behavior.

Although there is broad agreement on the need to control and combat health misinformation, the magnitude of this problem remains unknown. It is essential to understand both users’ cognitive processes when it comes to identifying health misinformation and the diffusion mechanism from which such misinformation is framed and subsequently spread.

The mechanisms through which users process and spread misinformation have remained open-ended questions. This study provides theoretical insights and relevant recommendations that can make users and firms/institutions alike more resilient in protecting themselves from the detrimental impact of misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0167

This study examines the non-linear impact of financial development on income inequality and analyses the mediators through which financial development affects income inequality.

The study uses a dynamic panel threshold method with an endogeneous threshold variable on a comprehensive sample of 85 countries over the period of 1996-2015.

The author finds that financial development activities increase income inequality in developed countries. However, financial development promotes income equality in developing countries. Further, the study finds that education and institutional quality are the channels through which financial development has non-linear impacts on income inequality.

The study explores relatively new method to examine the nonlinear impact of financial development and also considers new dataset for the main explanatory variable.

The study investigates the influence of perceived security (PS) on behavioral intention (BI) via the trust attitude process and explores the moderating effects of gender. PS in mobile wallets enhances user trust (TR), attitude (ATT) and intention (INT). Using a multiple and serial mediation model, both TR and ATT were found to mediate the relationship between PS and BI.

Drawing on the stimulus-organism-response (S-O-R) theory, the proposed conceptual model comprises PS, TR, ATT and BI. An online survey was conducted with a cross-sectional sample of 744 mobile wallet users in India. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the hypothesized relationships and test the mediation effects.

Results show that the stimulus, PS, has a positive and significant influence on TR and ATT, which eventually has a positive influence on BI. The research model explains 64.4 percent of the variance in BI. Further, both TR and ATT independently and parallelly mediate the relationship PS and BI. Lastly, gender is found to moderate the relationship between TR and BI and ATT and BI.

The research showed the importance of PS, TR and ATT towards mobile wallet adoption INTs. Further, the findings support the idea that developing TR and ATT is essential for shaping INTs. This suggests that mobile wallet service providers should invest in methods that not just enhance user TR but also reinforce a positive ATT towards the platform. To demonstrate TR, mobile wallet providers must ensure the confidentiality and privacy of user data, keep customer interests in mind and fulfill commitments. Lastly, for strengthening customer TR, excellent customer support is extremely important.

While prior researchers have majorly used technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) models to explain adoption INTs, this study examines the relationship between PS, TR, ATT and BI through the lens of the SOR framework.

Service failures usually occur in front of third-party customers. Third-party customers react emotionally and behaviorally to service failure and recovery efforts aimed at focal customers. However, there is a gap in the literature on how third-party customers react to a service failures incident and a recovery over another customer, depending on how socially close or distant they are from. This study investigates the effect of third-party customers' emotions on consumer forgiveness, negative word-of-mouth (WoM) and repatronage intentions in the service recovery process by comparing close and distant third-party customers.

This study utilizes a 2 (social distance to the focal customer: close, distant) × 2 (service recovery: yes, no) between-subjects design. The authors used a scenario-based experiment to test the proposed hypotheses. A total of 576 respondents were involved in the study.

The results from the authors' scenario-based experimental study show that positive and negative emotions felt by distant third-party customers are higher than those of close third-party customers. In addition, the effect of positive emotions on customer forgiveness is more substantial for distant third-party customers. Third, moderated-mediation analysis indicates that social distance has a moderator effect only on the relationship between positive emotions and customer forgiveness.

This study contributes to the service literature by comparing socially close and socially distant third-party customers' reactions to service failure and recovery attempts.

The importance of multidimensional and engaging instruction for sustainable development goals (SDGs) in higher education cannot be overstated. Such instructions should motivate students not only to memorize and contemplate these goals but also to actively participate in addressing SDG-related challenges. Consequently, this study aims to develop practical and appropriate instructional approaches to education for sustainable development (ESD) in higher education to enhance students’ knowledge, attitudes and behaviors concerning sustainability.

By using a quasi-experimental design, this ESD study was conducted at a university in central Taiwan. A total of 121 students from diverse academic backgrounds participated in the 16-week experiment, which was divided into three groups. Lecturing, thematic teaching and design-thinking strategies were applied to these respective groups.

The thematic-teaching and design-thinking groups displaying improved cognitive performance. However, the quantity results revealed that the design-thinking group surpassed the other two groups in sustainability knowledge, attitudes, behaviors and mind map tasks. The qualitative findings further indicated that design thinking – through multiple practical problem-solving activities – guided college students to think independently and sustainably, as well as enabled them to internalize the value of sustainable development. By implementing these effective approaches, the core goals of ESD-related personal and societal transformations may be realized.

This study proposed a goal-oriented ESD instructional model for educators, demonstrating the efficacy of design thinking in cultivating higher-order thinking and affection for ESD in students. Additionally, this study introduced an innovative evaluation approach – mind mapping – to the ESD domain, which may compensate for the limitations of the survey method.

This study provides empirical evidence for the effectiveness of design thinking and thematic-based pedagogies in sustainable development higher education. Additionally, it also offers a practical ESD instructional model with reference value for scholars and multi-domain instructors. Moreover, the study highlights that by examining organizational governance from the perspectives of design thinking and higher-order affection, sustainable and economic development need not be mutually exclusive concepts. Instead, pursuing SDGs can be viewed as investment opportunities for organizations rather than mere costs.

The purpose of this study is to compare the competition and productivity of the US freight rail transportation industry for the past 41 years (1980 ∼ 2020), which consists of the two periods, before and after the abolishment of the Interstate Commerce Commission (ICC) in 1995.

This study investigates any relationships between the market concentration index values and labor productivity values in the separate two periods, and how the existence of a regulatory body in the freight transportation market impacted the productivity of the freight rail transportation industry by using a Cobb–Douglas production function on annual financial statement data from the US stock exchange market.

This study found that, after the abolishment of the ICC: (1) the rail industry became less competitive, (2) even if the rail industry had an increasing labor productivity trend, there was a strong negative correlation between the market concentration index and labor productivity and (3) the rail industry’s total factor productivity was decreased.

This study is to find empirical evidence of the effect of the ICC abolishment on the competition and productivity levels in the US freight rail transportation industry using a continuous data set of 41-year financial statements, which is unique compared to previous studies.

This paper aims to examine the impact of metaverse experiences on customers’ offline behavioral intentions: How do customers’ visits to a hospitality business’s virtual property in the metaverse affect their intentions to visit the physical property in the real world?

Based on the general learning model and social cognitive theory, this research hypothesizes the positive impact of metaverse experiences on customers’ visit intentions and explores two boundary conditions for positive impact: user–avatar resemblance and servicescape similarity. Two experimental studies were conducted.

Metaverse experience has a significant impact on customers’ visit intentions, and this impact is moderated by user–avatar resemblance and servicescape similarity.

This research addresses the call for empirical studies regarding the effects of metaverse experience on people’s behavioral intentions.

As one of the earliest empirical studies on the marketing effects of the metaverse, this research provides a basis for future metaverse studies in the hospitality field.

This study aims to explore the spillover effects of data breaches from a consumer perspective in the e-commerce context. Specifically, we investigate how an online retailer’s data breach affects consumers’ privacy risk perceptions of competing firms, and further how it affects shopping intention for the competitors. We also examine how the privacy risk contagion effect varies depending on the characteristics of competitors and their competitive responses.

We conducted two scenario-based experiments with surveys. To assess the spillover effects and the moderating effects, we employed an analysis of covariance. We also performed bootstrapping-based mediation analyses using the PROCESS macro.

We find evidence for the privacy risk contagion effect and demonstrate that it negatively influences consumers’ shopping intention for a competing firm. We also find that a competitor’s cybersecurity message is effective in avoiding the privacy risk contagion effect and the competitor even benefits from it.

While previous studies have examined the impacts of data breaches on customer perceptions of the breached firm, our study focuses on customer perceptions of the non-breached firms. To the best of the authors’ knowledge, this study is one of the first to provide empirical evidence for the negative spillover effects of a data breach from a consumer perspective. More importantly, this study empirically demonstrates that the non-breached competitor’s competitive response is effective in preventing unintended negative spillover in the context of the data breach.

Gender diversity is known to trigger creative and relationship conflicts alike, the former a boon for innovation and the latter a bane. This study aims to explore the possibility of a gender mix that is “just right” for balancing the intensities of varied forms of conflict to boost innovation in firms in India. Specifically, this paper investigated the presence of an optimal level of women as a percentage of the firm’s full-time permanent employees (Percent-Women) that maximized the firm’s likelihood of product innovation (Product–Innovation–Likelihood).

Logistic regression analyses of firm-level data of Indian establishments of varied sizes and industries from World Bank Enterprise Surveys 2014 was performed. Instrumental variable addressed the potential endogeneity of Percent-Women.

The analysis demonstrated an inverted U-shaped relationship between Product–Innovation–Likelihood and Percent-Women. Product–Innovation–Likelihood peaked when Percent-Women lay between 35% and 58%, i.e. when the firm was gender-balanced or close to it.

The finding of an optimal level of female inclusion presents to firms a defined target of gender mix to be achieved, failing to which they may be limiting their innovation potential. It compels firms to view gender diversity as a business imperative with definite implications for their long-term performance.

For India, the demonstrated relationship between workplace gender diversity and innovation brings additional reason and urgency to public initiatives, such as female literacy, for boosting female economic engagement. Innovation can power the next stage of the Indian growth story by engaging the heretofore insufficiently tapped female worker.

By demonstrating an optimal degree of female inclusion at which innovation potential peaks, the study reconciled opposing theories of diversity-driven conflicts and went beyond the commonly observed simple linear relationship between female inclusion and innovation. Further, the paper focused on India, a major developing economy with a vast female populace and growing innovation ambitions but scarcely researched for gender diversity’s role in innovation.