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Spirituality serves as an ethical benchmark for shaping human and brand identity. Only a few studies have recently attempted to examine the impact of spiritual attributes on customer behavior. This study extends the current literature and aims to develop a research model to investigate spiritual brand attributes toward customers’ behavior. The study employs the stimulus–organism–response (SOR) model as a theoretical signpost to construct the research model. Driven by this chapter, future research opportunities are presented, and the opportunity for empirical research is also illustrated.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.

This paper aims to further the understanding of the motivation to learn (ML) among an organisation’s older cohort of employees. It is proposed that age diversity climate (ADC) will positively impact ML by improving employees’ subjective age (SA) perception. Such a climate will indicate that the organisational climate is fair and inclusive regardless of the employee’s age.

Salaried Indian workers were administered a questionnaire on SA, ML and ADC.

ADC was positively related to ML, with SA acting as a mediator. The relationship is stronger for employees with higher chronological age (C.Age).

Policymakers and managers can draw from the findings and develop HR programs aimed at managing an age-diverse workforce and can incorporate measures that enhance the employability of the chronologically ageing but subjectively younger cohort to prevent premature departure from the labour market.

The present article contributes to the literature on work and ageing by investigating the subjective relationship of workers to their age. The findings also focus on successful ageing, thus contributing to the life span developmental theories.

This study empirically tests the influence of key elements on intent to use electronic (E)-ticket through the “Stimulus–Organism–Response (SOR)” framework and structural equation model. Results highlight factors such as E-trust Technology, Ease of Use, E-satisfaction, Intention to Purchase E-ticket, Price Perception, and Usefulness; the study comprehensively analyzes the factors influencing the decision-making process of consumers when it comes to purchasing E-tickets. The research employs a hypothesis-driven approach and gathers survey results from 408 observants to find out the intention of consumers to use E-tickets for using transportation services, which help transportation providers understand the importance of its platform to benefit customers who are willing to change their perceptions from paper tickets to E-tickets, the reason customers buying E-ticket rather than paper ticket while using digitalization to help firms control their cost and building internal legitimacy by better managing their internal stakeholder.

This study aims to investigate the “digitalization paradox” in manufacturing digital transformation, where significant investments in digital technology may not necessarily lead to increased returns. Specifically, it explores the intricate relationship between digital technology convergence, financial performance, productivity and technological innovation in listed Chinese manufacturing firms, drawing upon theories of digital innovation and knowledge networks.

Using a large panel data from 747 listed firms in China’s manufacturing sector and their 428,927 patents spanning from 2013 to 2022, this research first quantifies manufacturing firm-level digital technology convergence through patent network analysis. Furthermore, this study employs hierarchical regression analysis and the instrumental variable method to investigate the curvilinear relationship between digital technology convergence and financial performance. Furthermore, the moderating role of firms’ productivity and technological innovation is tested.

Three types of firm-level digital technology convergence (DTC) are delineated and quantified: local authority in digital convergence (DegreeDTC), convergence with heterogeneous digital knowledge (BetweenessDTC) and shortest-path convergence with digital technologies (ClosenessDTC, where a higher value signifies a more conservative and shorter path in adopting digital technologies). Network visualization shows that manufacturing firms' DTC has consistently increased over time. Contrary to traditional assumptions, our research reveals a U-shaped relationship between DTC (specifically, DegreeDTC and BetweenessDTC) and financial performance. This relationship is characterized by a negative correlation at lower levels and a positive one at higher levels. The joint effect of firms’ productivity and technological innovation significantly strengthens this relationship. These findings are robust across a series of robustness checks.

Our findings offer practical insights for both managers and policymakers. We recommend a balanced approach to digital innovation management within the technology convergence paradigm. Manufacturing firms can generate economic value by strategically choosing to either shrink or expand their digital technology application areas, thereby reducing uncertainties related to emerging convergent businesses. Additionally, the study underscores the synergistic strategy of combining innovation with productivity. Within the DTC business context, integrating productivity with technological innovation not only enhances cost flexibility but also improves problem-solution matching, ultimately amplifying synergistic benefits.

To the best of our knowledge, this is the first study to apply a digital technology co-occurrence network to unveil nuanced relationships in “DTC – finance performance” within the manufacturing sector. It challenges conventional thinking regarding the common positive effect of digital innovation and technological convergence. This study provides a comprehensive analysis of DTC, financial performance, productivity and technological innovation dynamics, as well as offers managerial implications for managers and policymakers.

• (1)

  We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

• (2)

  A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

• (3)

  The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

• (4)

  We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.

We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.

Immersion is a primary objective in video game gameplay, utilising tropes and techniques from cinema, music, art, literature and ludology. VR video games are capable of enhancing immersion, offering a life-like sense of scale, embodiment, agency and presence. As VR becomes more accessible, these immersive capabilities demand a new framework to understand the multifaceted nature of immersion in VR. The Player's Immersive Experience (PIE) model addresses this need by accounting for the multidimensional experience of immersion in VR video games. This model expands on previous frameworks like Ermi and Mäyrä’s sensory, challenge-based and imaginative immersion (SCI) model and Calleja's Player Involvement Model, introducing eight dimensions: sensory, bodily, game feel, affective and empathetic, world-building, narrative, ludological and social immersive strategies. These dimensions, experienced collectively but not necessarily equally, provide a comprehensive understanding of how VR games immerse players. The chapter illustrates these strategies with examples from Blade & Sorcery, Boneworks and Half-Life: Alyx, which each illustrate a range of unique possibilities and contributions of VR to the gaming experience. By framing the immersive experience through the PIE model, this chapter offers a foundational framework for future studies on immersion in VR video games.

This study aims to better understand the emotional challenges that inexperienced accounting researchers may face in conducting ethnographies. To do so, the authors use Arlie Russell Hochschild’s (1979, 1983) notions of “feeling rules” and “emotion work” to shed light on the possible nature and impact of these challenges, and how her ideas may also become fruitful for academic purposes.

The authors take a reflective approach in sharing the raw observation notes and research diaries as first-time ethnographers in the area of management accounting. The authors use these to analyze “unprocessed” experiences of emotional challenges from the fieldwork and how the authors learned to cope with them.

The authors illustrate how emotional challenges in conducting ethnographies can be rooted in a clash with prevalent feeling rules of certain study situations. The authors explore the conditions under which these clashes occur and how they may prompt researchers to respond through means of emotion work to (re-)stabilize those situations. Based on these insights, the authors also discuss how wider conventions of the accounting academy may contribute to emotional challenges as they stand in contrast to principles of ethnographic research.

There remains a tendency in the accounting domain to largely omit emotional challenges in the making of ethnographies, especially in writing up studies. In this paper, the authors are motivated to break this silence and openly embrace such challenges as an asset when the authors talk about the process of creating knowledge.

Disruptive technologies have changed the way that firms model their business approach. The aim of this study is to analyse the influence of novel digital technologies (artificial intelligence [AI] and machine learning [ML]) and big data analytics on the digital transformation of digital marketing firms. This research study is based on a review of the extant literature, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Gaps in the extant research literature were identified and emerged that are directly linked with the impact of AI, ML and big data analytics on digital transformation for digital marketing firms. Potential opportunities for digital transformation in digital firms were also unlocked, as well as related challenges. The research informs practice and policy for the current trends and provides future research directions. The study was limited to the application of the PRISMA methodology, which is incapable of fully providing testable results for a given study. Complementary cross-sectional research studies using the same methodology in different areas of study with the same topic can be applied to check for relevancy and applicability. This study contributes to digital marketing, information communication technologies, information systems practice and theory building. In addition, it provides researchers with an agenda for future digital transformation research directions.

This study aims to understand how product attributes (object stimuli), social influences (social-psychological stimuli) and internal factors (internal stimuli) contribute to Chinese Generation Z’s purchase intentions (responses) for new Chinese style apparel (NCSA) through NCSA attitudes (cognitive state) and cultural pride (affective state) based on the stimulus-organism-response (S-O-R) model.

Data were collected from 989 respondents aged between 18 and 29 years through self-administrated questionnaires via a professional survey panel, Credamo, in China. Data were analyzed using structural equation modeling.

Results showed that among the seven stimuli, NCSA’s design, online social networking communities, cultural identity and personal norms significantly influenced Generation Z’s purchase intentions through both NCSA attitudes and cultural pride. Further, NCSA’s cultural connotations and celebrity influences elicited purchase intentions merely through the affective state – cultural pride. In contrast, NCSA’s functionality did not have a significant influence on NCSA attitudes and adversely affected cultural pride.

This study fills the research gap and extends the application of the S-O-R model within the NCSA context. The findings of this study shed light on the practical implications for marketers, brands and policymakers with regard to a better understanding of Chinese Generation Z’s NCSA consumption.