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The proliferation of non-fungible token (NFT)-based crypto-art platforms has transformed how creators manage, own and earn money through the creation, assets and identity of their digital works. Despite this, no studies have examined the drivers of continuous content contribution behavior (CCCB) toward NFTs. Hence, this study draws on the theory of relational bonds to examine how various relational bonds affect feelings of psychological ownership, which, in turn, affects CCCB on metaverse platforms.

Using structural equation modeling and importance-performance matrix analysis, an online survey of 434 content creators from prominent NFT platforms empirically validated the research hypotheses.

Financial, structural, and social bonds positively affect psychological ownership, which in turn encourages CCCBs. The results of the importance-performance matrix analysis reveal that male content creators prioritized virtual reputation and social enhancement, whereas female content creators prioritized personalization and monetary gains.

We examine Web 3.0 and the NFT creators’ network that characterizes the governance practices of the metaverse. Consequently, the findings facilitate a better understanding of creator economy and meta-verse commerce.

This study explores the key platform affordances that online social platform providers need to offer digital creators to strengthen the creator ecosystem, one of the leading accelerators for platform growth. Specifically, it aims to investigate how these affordances make the dynamic combinations for high platform quality across diverse platform types and demographic characteristics of digital creators.

This study adopts a multi-method approach. Drawing upon the affordance theory, Study 1 aims to identify the key affordances of online social platforms based on relevant literature and the qualitative interview data collected from 22 digital creators, thereby constructing a conceptual framework of key platform affordances for digital creators. Building on the findings of Study 1, Study 2 explores the dynamic combinations of these platform affordances that contribute to platform quality using a configurational approach. Data from online surveys of 185 digital creators were analyzed using fuzzy set qualitative comparative analysis (fsQCA).

The results of Study 1 identified key online social platform affordances for digital creators, including Storytelling, Socialization, Design, Development, Promotion, and Protection affordance. Study 2 showed that the combinations of these platform affordances for digital creators are diverse according to the types of platforms, creators’ gender, and their professionality.

Like many studies, this research also has several limitations. One limitation of the research is the potential constraint of the extent of how well the data samples represent the group of creators who are actively producing digital content. Despite the addition of screening questions and meticulous data filtering, it is possible that we did not secure sufficient data from creators who are actively engaged in creative activities. In future research, it is worth contemplating the acquisition of data from actual groups of creators, such as creator communities. Future researchers anticipate obtaining more in-depth and accurate data by directly involving and collaborating with creators.

This study highlights the need for online social platforms to enhance features for storytelling, socializing, design, development, promotion, and protection, fostering a robust digital creator ecosystem. It emphasizes clear communication of these affordances, ensuring creators can effectively utilize them. Importantly, platforms should adapt these features to accommodate diverse creator profiles, considering differences in gender and expertise levels, especially in emerging spaces like the Metaverse. This approach ensures an equitable and enriching experience for all users and creators, underlining the importance of dynamic interaction and inclusivity in platform development and creator support strategies.

This study underscores the social implications of evolving digital creator ecosystems on online platforms. Identifying six key affordances essential for digital creators highlights the need for platforms to enhance storytelling, socializing, design, development, promotion, and product protection. Crucially, it emphasizes inclusivity, urging platforms to consider diverse creator profiles, including gender and expertise differences, particularly in transitioning from traditional social media to the Metaverse. This approach nurtures a more robust creator ecosystem and fosters an equitable and enriching experience for all users. It signals a shift towards more dynamic, adaptive online environments catering to diverse creators and audiences.

For academics, this study builds the conceptual framework of online social platform affordances for digital creators. Using the configurational approach, this study identified various interdependent relationships among the affordances, which are nuanced by specific contexts, and suggested novel insights for future studies. For practices, the findings specified by creators and platform types are expected to guide platform providers in developing strategies to support digital creators and contribute to platform growth.

Taking the dialogic organizational development perspective, this study aims to investigate the framing processes when engaging in dialogue for strategy implementation and how these enable the evolution of implementation opportunities.

Through a qualitative exploratory study conducted in a large multinational, the authors analyse the dialogue and interactions among 25 dyads when identifying opportunities to contribute to strategy implementation. The data analysis relies on a process-coding approach and linkography, a valuable protocol analysis for identifying recursive interaction schemas in conversations.

The authors identify four main framing processes – shaping, unveiling, scattering and shifting – and provide a framework of how these processes affect individuals’ mental models through increasing the tangibility of opportunities or elevating them to new value hierarchies.

From a theoretical perspective, this study contributes to the strategy implementation and organizational development literature, providing a micro-perspective of how dialogue allows early knowledge structures to emerge and shape the development of opportunities for strategy implementation.

From a managerial perspective, the authors offer insights to trigger action and change in individuals to contribute to strategy when moving from formulation to implementation.

Rather than focusing on the structural control view of strategy implementation and the role of the top management team, this study considers strategy implementation as a practice and what it takes for organizational actors who do not take part in strategy formulation to enact and shape opportunities for strategy implementation through constructive dialogue.

Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech initiatives is key to successful Industry 4.0 technology adoption, but few studies have examined the determinants of employee acceptance. This study, therefore, aims to explore how managers affect employees' acceptance of Industry 4.0 technology, and, in turn, Industry 4.0 technology adoption.

Rooted in the unified theory of acceptance and use of technology model and social exchange theory, this inductive research follows an in-depth comparative case study approach. The two studied Dutch manufacturing firms engaged in the adoption of Industry 4.0 technologies in their primary processes, including cyber-physical systems and augmented reality. A mix of qualitative methods was used, consisting of field visits and 14 semi-structured interviews with managers and frontline employees engaged in Industry 4.0 technology adoption.

The cross-case comparison introduces the manager's need to adopt a transformational leadership style for employees to accept Industry 4.0 technology adoption as an organisational-level factor that extends existing Industry 4.0 technology user acceptance theorising. Secondly, manager's and employee's recognition and serving of their own and others' emotions through emotional intelligence are proposed as an additional individual-level factor impacting employees' acceptance and use of Industry 4.0 technologies.

Synthesising these insights with those from the domain of Organisational Behaviour, propositions were derived from theorising the social aspects of effective Industry 4.0 technology adoption.

This paper aims to explore whether crowdfunding creators can learn from previous experiences to have a better financing performance of future crowdfunding projects.

This paper uses Python to capture the data of 6,267 crowdfunding projects from one of the largest crowdfunding platforms in China (JingDong Crowdfunding) and the author use the negative binomial regression model and the OLS model in this empirical study.

The empirical results show that both the early-stage experience of creating a crowdfunding project and the early-stage experience of supporting projects of other crowdfunding creators can improve the financing performance of their newly launched projects. The social network of the previous projects and the “Blockbuster” projects initiated before can also make the newly initiated projects obtain better financing performance.

Current research on entrepreneurial experience shows that serial entrepreneurs have significantly different success rates than novice or inexperienced entrepreneurs but there is limited literature on the learning effect of crowdfunding creators. This study adds to the literature on entrepreneurial learning and provides suggestions to crowdfunding creators.

This study aims to determine the impact of attitude toward content creators, subjective norm and perceived content quality in affecting people’s intention and behavior to watch videos posted on YouTube in Indonesia.

Using questionnaire, data from the total of 112 individuals living in Indonesia were gathered in this study, and these respondents are individuals who have been watching YouTube contents at least 3 h a day for the past eight months. Moreover, all of these data were processed and analyzed using PLS method to determine the impact given by one variable toward the other.

Based on the results of the analysis, the authors concluded that both factors, namely, content credibility and perceived content quality, play significant and positive roles in determining people’s intention to watch – and ultimately behavior to watch – contents or videos published on YouTube, with the former turned out to be the stronger predictor.

The current study attempts to modify and merge both the concept of theory of reasoned action and product quality theory to explain Indonesians’ behavior toward watching contents published on YouTube, and to the best of the authors’ knowledge, this type of studies is still in rarity.

Student welfare and wellbeing is crucial to successful postgraduate study, regardless of the global location in which the study is taking place, making it an international issue. This study sought to add to the conversations occurring globally on this topic, focusing particularly on exploring academic faculty participation in higher education postgraduate taught (PGT) student mentoring initiatives.

By applying two theories, social exchange theory (SET) and equity theory (ET), faculty participation in postgraduate mentoring was explored and examined. A qualitative methodology, comprising 19 semi-structured interviews with faculty participating as mentors, was conducted. Data was analysed using template analysis, with SET and ET used to create thematic templates.

The application of SET and ET enabled faculty participation to be understood in terms of the perceived equity, costs and rewards of mentoring. Costs can be significant, sometimes outweighing the benefits, thus endangering the viability and sustainability of the PGT mentoring initiative. Analysis suggested two distinct types of “mentor mindsets” exist, which influence the perception of investments, equity, costs and rewards.

As higher education institutions face increasing pressure to support student welfare, it is imperative that personalised support is put under scrutiny so management practices can be established that support and encourage academic faculty participation in these support initiatives. This paper recommends how institutions can allay the costs of mentoring by considering mentor recruitment, selection, training and other supportive measures.

While social media data are used increasingly in studies of social movements, social media evolves far more rapidly than academic research and publication. This chapter argues that researchers should adopt historical and archival approaches to social media data. Treating social media data as an “instant archive” – one that is self-curated, is co-constituted, and changes rapidly – we caution researchers to pay attention to the features of this archive and their implications for working with the data therein. Applying insights from recent discussions of archival methods for social science research to the specific features of social media data, we explore how platform features, repressive effects, and user innovations affect the content of the instant archive. We then offer strategies for researchers' methodological approaches, including how best to select units of analysis and platforms, how to collect and interpret archival materials, and how to identify silences in the data.

The social media industry has entered a new stage with intensifying competition and heightened uncertainty about future directions. The purpose of this paper is to provide analyses of the current challenges and to identify industry-wide trends that may offer a roadmap for the future.

Drawing on publicly available key performance metrics, company reports and press reports, this paper offers critical analyses of the challenges facing the major social media platforms and new trends in the social media industry.

This study identified five major trends in the current social media industry: 1) content is king, and that content is moving to visual; 2) artificial intelligence is key to competitive advantage; 3) network effects still matter, but business model innovation can overcome that barrier; 4) the need to broaden revenue sources; and 5) the strive for the everything app. In this changing environment, social media companies need to adapt and innovate their business models proactively to stay ahead.

This paper not only sheds light on the current challenges of individual social media platforms but also identifies industry-wide trends that may apply across all platforms. Taken together, these insights paint a comprehensive picture of the current industry landscape, as well as offer clues about its future directions.

This study aims to investigate the rising trend of virtual influencers – digitally created characters with human-like attributes. It aims to evaluate and compare their effectiveness with human influencers in terms of brand attitudes and purchase intentions. It uncovers the mechanisms underlying the differences in effectiveness observed between virtual influencers and their human counterparts.

The research uses a 2 (influencer type: human vs virtual) × 3 (product type: functional vs symbolic vs experiential) between-subjects design. Through a pilot study (n = 334) and a main study (n = 352), the research examines the interactive effects of influencer and product type on brand attitude and purchase intentions. Hypotheses were developed and tested using moderating mediation models centered on authenticity and product–endorser fit.

Virtual influencers are perceived as less authentic than human influencers across all product types, negatively influencing brand attitude and purchase intention. However, the extent to which influencer type affects brand attitudes and purchase intentions, mediated by product–endorser fit, varies based on the product type.

This research emphasizes two key mechanisms – authenticity and product–endorser fit – influencing the effectiveness of virtual influencers. It suggests that aligning virtual influencers with suitable product types can offset their perceived authenticity deficit, significantly affecting their endorsement effectiveness.