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This study aims to explore how youth express empathy as an aspect of social action. Social empathy was investigated among adolescents participating in a youth organizing initiative.

This study used elements of critical discourse analysis to examine participant expression of social empathy through examination of participant journal entries. The social empathy model was used as a conceptual framework to guide the analysis and interpretation of themes.

Two core themes emerged from the analysis: characterization of empathy and empathy as a desired trait. Overall, results indicate that social empathy may be expressed differentially according to one’s development of empathy and critical consciousness. Thus, this study classifies dimensions of empathetic expression as existing across a continuum.

Before youth can engage in meaningful social action, they must first understand an issue from differing social and affective perspectives, defined as social empathy. While existing research highlights the role of social empathy in social action initiatives, there are no known studies that investigate the performative expressions of social empathy among youth organizing participants. Building from these results, this study offers a continuum that elucidates the multidimensionality of empathy expression among youth engaged in a social action initiative.

The purpose of this article was to investigate the employee perceptions of diversity management and employee performance. To achieve this, employee respondents’ perceptions and perspectives have been tested, and findings are discussed.

To address this study's purpose, survey data were collected from 250 employees of two organizations in the United Arab Emirates (UAE). Data were analyzed by age, gender and nationality for two variables: diversity management and employee performance.

Results showed that respondents perceived an improvement in employee performance when diversity was managed for employees of different age groups, females/males working together and a workplace composed of employees from various nationalities.

The implication of this limited study is that further studies on the perception of diversity management for employee performance in the Middle East region needs to be conducted. The social implication is that organizational leaders can initiate diversity management to improve employee performance. The research is limited by the geographical context and access to the collection of data during the COVID-19 pandemic.

The implication of this limited study is that further studies on the perception of diversity management for employee performance in the Middle East region needs to be conducted. The social implication is that organizational leaders can initiate diversity management to improve employee performance.

The contribution to academic knowledge from this research is two-fold: findings from a novel study conducted in the Middle East evidenced diversity management improved perceptions of employee performance. The value of the study for praxis is to incorporate employees' belief in diversity management for its potential to improve employee performance.

Purpose: The purpose of this paper is to consolidate knowledge and benchmark the progress being made across the 32 International Federations (IFs) in the Summer Olympic Programme.

Design/methodology/approach: A website content analysis, analytical hierarchy of information, and social media research was conducted to triangulate the barriers and drivers of environmental sustainability (ES) progress. This data was then analysed to empirically substantiate the findings of previous methods by exploring potential drivers of IF ES progress and communication and refining the ranking of IF ES progress.

Results and findings: World Sailing is by far the most advanced IF in terms of ES progress, followed by World Athletics. Only 4 out of 32 have any sort of strategic ES plans. Only golf, surfing, football, sailing, and hockey have received any academic attention. There is a significant lack of understanding of environmental practices across sport, and their drivers/barriers. There is limited accountability with regards to ES progress and activities throughout the Olympic Movement. This has resulted in uneven diffusion of environmental activities.

Originality: This paper is a new contribution to sport management and ES literature. It provides a benchmark of understanding for ES in the Summer Olympic Programme for the first time using a hierarchy of information to ground results. The exploration and comparison of the perspectives of separate sports adds to the paper's originality.

Social media marketers are keen to understand how viewers perceive their brands on a platform and how the learning experiences from content can impact their attitudes toward a brand. This study aims to focus on examining the effect of firm-generated content (FGC) on X (formerly known as Twitter), using Kolb’s experiential learning theory to analyze the viewers’ learning process. In addition, the study investigates how the length of time a viewer follows a brand and the type of brand can influence their attitudes toward it.

This study involved three qualitative studies on X to investigate how content learning affects consumer attitudes toward two brands, namely, Nike and Subway. The study also examined the impact of the duration of following the brands, with participants following the brands for 4, 8 and 12 weeks, respectively, to assess changes in their attitudes.

The results demonstrate that content learning significantly impacts consumer attitudes. By following brands and engaging with their FGC over time, viewers can transition from being occasional or intermittent followers to becoming devoted brand enthusiasts. Through the four-stage experiential learning process, followers undergo cognitive, emotional and behavioral transformations that collectively shape their brand attitudes. The impact of content learning varies according to the brand type, and the duration of following has a positive effect on brand attitudes.

The study’s findings have significant marketing implications for social media marketers, suggesting that they should restructure their social media platforms as learning platforms to effectively engage followers. Companies should adjust their content marketing strategies from a learner’s perspective, providing followers with content that resonates with them, enhances their learning outcomes and helps shift their beliefs and brand attitudes, ultimately converting them into loyal consumers.

To the best of the author’s knowledge, this qualitative research is the first of its kind to apply experiential learning theories to investigate how users learn from FGC by following brands on social media and how this learning ultimately changes their brand attitude. The study provides a unique perspective on social media marketing, enriching the understanding of content marketing and consumer experiences on social media platforms.

Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lightning prediction.

The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

The research is limited to the data collected in support of weather prediction work through the 45th Weather Squadron of the United States Air Force.

These methods are important due to the increasing reliance on sensor systems. These systems often provide incomplete and chaotic data, which must be used despite collection limitations. This work establishes a viable data imputation methodology.

Improved lightning prediction, as with any improved prediction methods for natural weather events, can save lives and resources due to timely, cautious behaviors as a result of the predictions.

Based on the authors’ knowledge, this is a novel application of these imputation methods and the forecasting methods.

All hypothesized relationships were significant. Specifically, H1 was supported as disconfirmation and surprising consumption were significantly correlated. Moreover, arousal (H2) and outrage (H4a) were functions of surprising consumption and negative affect (H3) and outrage (H4b) were functions of arousal. H4c was also supported as negative affect had a significant direct effect on consumer outrage. In addition, disconfirmation had negative direct effects on both negative affect (H5) and dissatisfaction (H6a) and dissatisfaction was a function of negative affect. Finally, both outrage (H7a) and dissatisfaction (H7b) had significant negative effects on behavioral intentions.

Respondents were recruited to participate in the data collection in a “college town” in the Southeastern United States. Respondents were provided a paper and pencil data collection instrument that include complete survey instructions and the balance of the research design. To adequately test all hypotheses, the researchers developed a unique scenario that described an extreme service failure that takes place during a hotel check-in. Each respondent was asked to read the scenario and then reflect upon it as they responded to items that assessed their feelings toward the hotel check-in experience.

The results provide additional evidence in support of the existence of the satisfaction-dissatisfaction continuum, as well as specifically identifying the affective nature of levels of satisfaction that fall surprisingly well-below the zone of tolerance. The authors feel that the present study is a necessary step to provide a more comprehensive view of the satisfaction-dissatisfaction continuum. Likewise, the authors posit initial evidence of the antecedents and consequences of consumer outrage. This research supports the prior assumptions of Westbrook (1987) about the vast detrimental effects of negative affective responses to service or product failures.

Future research needs to discover just how extremely deficient service has to be to elicit outrage. Is outrage a personal phenomenon with every consumer experiencing it to different degrees? As such, is outrage triggered at different points on the satisfaction-dissatisfaction continuum? The zone of tolerance seems to suggest this, but it would be interesting to discover if at some collective level of dissatisfaction consumers generally begin to show signs of outrage. Likewise, it would be interesting to understand how the level and pattern of outrage results in customers exiting the relationship but also results in loyal customers becoming enemies (e.g. Gregiore et al., 2009; Gregiore and Fisher, 2008).

The motivation for the current study is both pragmatic and theoretical. As alluded to above, it is evident that the level of service customers’ emotional responses to their service experiences are increasing in frequency and intensity. These negative emotions affect the efficacy of service workers and impede the financial performance of service providers. The popular mantra of “anti-woke” consumers, “Go Woke, Go Broke,” is indicative of the importance of negative emotion. Sometimes referred to as “brand activism” (Moorman, 2020; Sarkar and Kotlet, 2019), recent public stances on social and political issues have led to a boycott of Gillette razors, the burning of Nike shoes, and the canceling of Costco Memberships in what has been called “virtue signaling” (Vredenburg et al., 2020). While none of these actions are desirable, the importance of investigating the impact of strong negative emotions (i.e. outrage) is further demonstrated in reports that 65% of consumers expect companies to authentically support such issues (Barton et al., 2018; Edelman, 2018; Larcker and Tayan, 2018; Moorman, 2020).

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

This article aims to develop a new theory that can better explain and predict how and when humans interact with commercial robots. To this end, utility maximization theory (UMT) along with four principles and propositions that may guide how human-to-commercial robot interactions are developed.

This article conceptualizes UMT by drawing from social exchange, conservation of resources, and technology-driven theories.

This article proposes UMT, which consists of four guiding principles and propositions. First, it is proposed that the human must invest sufficient resources to initiate a human-to-commercial robot interaction. Second, the human forms an expectation of utility gain maximization once a human-to-commercial robot interaction is initiated. Third, the human severs a human-to-commercial robot interaction if the human is unable to witness maximum utility gain upon the interaction. Finally, once the human severs a human-to-commercial robot interaction, the human seeks to reinvest sufficient resources in another human-to-commercial robot interaction with the same expectation of utility maximization.

This article is one of the few studies that offers a theoretical foundation for understanding the interactions between humans and commercial robots. Additionally, this article provides several managerial implications for managing effective human-to-commercial robot interactions.

This paper aims to explore the perspectives of registered nurses towards communication with family members of older people with a tracheostomy.

A qualitative design was used. Ten participants were recruited through purposive sampling. Face-to-face, semi-structured interviews were used in collecting data. Data were analysed by thematic analysis.

The four themes identified were as follows: communication by considering time difference; considering factors related to effective communication, either family member–related factors or registered nurse–related factors; strategies of communicating to support family members, such as giving an opportunity to ask for accurate information, communicating to build self-confidence and communicating through cases; and using the art of communication by speaking slowly and clearly, using colloquialisms, being steady and calm, as well as using positive language.

Having strategies and using the art of communication are important to help family members in obtaining accurate information and in building self-confidence in the care of older people.

The paper indicates that registered nurses consider factors related to communication, and they gave more information to family members using effective strategies and the art of communication. Therefore, effective communication training to nursing teams should be performed to promote adherence to treatment and family members’ satisfaction.

This study aims to develop a comprehensive, theoretically grounded framework of customer-to-customer interaction (CCI) management, by revisiting three older services marketing models: the servuction model, the services marketing triangle and the services marketing pyramid.

Noting the lack of theoretical frameworks of CCI management, this study adopts a problematization approach to identify foundational services marketing models, question their underlying assumptions, develop an alternative conceptual framework and evaluate its adequacy for CCI management, on the basis of a systematic literature review and content analyses.

By revisiting the assumptions underlying three relevant models in the light of the present-day, technology-infused service environment, this study proposes a four-triangle CCI management framework encompassing four specific modes of CCI management: managerial decisions by the firm; frontline employees; the design of the physical environment; and technology. Furthermore, this study emphasizes the triadic relationships involving the focal customer, other customers and the four modes of CCI management. Building on these findings, this study concludes with an extensive research agenda.

To the best of the authors’ knowledge, this study represents the first scholarly effort in services marketing literature to provide a comprehensive, theoretically grounded framework of CCI management. With its basis in foundational models, the new framework is well-suited to address future challenges to service marketplaces too.