Search results

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.

Social networking services (SNSs) have become deeply ingrained into our daily life. However, it has often been reported that users experience negative feelings regarding SNS usage. This phenomenon presents challenges for SNS providers in retaining or increasing their customer base. This study focuses on SNS fatigue, a negative psychological state that can lead to discontinuance intention among SNS users. This study proposes two distinctive SNS-specific contexts and investigates how they alleviate the negative effect of SNS fatigue on user behavior.

Drawing upon the context-specific theorization perspective, a model involving moderation effects of the SNS-specific contexts on the relationship between user's SNS fatigue and discontinuance intention was proposed. The model was tested using survey data of active SNS users.

The results indicate that SNS fatigue leads to user discontinuance intention. However, the SNS-specific contexts, such as social interaction context and platform service context, negatively moderate the relationship between SNS fatigue and user discontinuance intention.

The findings of this study are expected to help SNS providers develop strategies to improve their services for effective user retention.

The purpose of this study is to understand how IT capabilities for knowledge management and process integration can build a firm's agile process capabilities for sensing, strategic decision and responding. The study also investigates how the three agile capabilities affect firm performance in different competitive environments.

This study conducted a large-scale field survey with firms in the United States. Survey invitations were sent to business executives of the target firms. A total of 254 complete samples were collected for our hypotheses test.

The results confirm the overall significant roles of IT capabilities in the three agile capabilities. The results further reveal that the IT capability for knowledge management has a higher influence on sensing capability, while the IT capability for process integration has a higher influence on responding capability. Moreover, strategic decision and responding capabilities are more important in the high market competition. However, in the low market competition, sensing capability becomes more important while responding capability demonstrates a negative impact on firm performance.

This study helps both academics and practitioners better understand a firm's IT-agility-performance mechanism. Particularly, our findings guide how to achieve agile capabilities and what to focus on under the different levels of market competition.

The rapid growth of artificial intelligence (AI)-based voice-assistant systems (VASs) has created many opportunities for individuals to use VASs for various purposes in their daily lives. However, traditional quality success factors, such as information quality and system quality, may not be sufficient in explaining the adoption and use of AI-based VASs. This study aims to propose interaction quality as an additional, yet more important quality measure that leads to trust in an AI-based VAS and its adoption.

The authors propose a research model that highlights the importance of interaction quality and trust as underlying mechanisms in the adoption of AI-based VASs. Based on survey methodology and data from 221 respondents, the proposed research model is tested with a partial least squares approach.

The results suggest that interaction quality and trust are critical factors influencing the adoption of AI-based VASs. The findings also indicate that the impacts of traditional quality factors (i.e. information quality and system quality) occur through interaction quality in the context of AI-based VASs.

This research adds interaction quality as a new quality factor to the traditional quality factors in the information systems success model. Further, given the interactive nature of VASs, the authors use social response theory to explain the importance of the trust mechanism when individuals interact with AI-based VASs.

As social networking is becoming more popular, social software has achieved an important position in the internet business industry. For social software to be successful, it is crucial to understand how users form their continuous usage intentions toward social software. This paper aims to discuss these issues.

Drawing upon socio-technical and social cognitive perspectives, this study proposes a theory-based model that investigates the interaction effects between social (i.e. perceived user base and relationship commitment) and technical (i.e. perceived system quality) factors of social software, in addition to their direct effects on continuous usage intentions. To empirically validate the proposed research model, a structural equation modelling technique was used.

The results of our model test indicate that all relevant social and technical factors are significant determinants of continuous usage intention. Moreover relationship commitment exhibits a positive interaction effect with perceived system quality on continuous usage intention, while perceived user base does not.

Service designers or providers of social software should make an effort to nurture social relationships among users, expand users' social networks, and reinforce users' relationship commitment to their friends.

Given the lack of investigations into socio-technical interactions in prior social software studies, the theoretical perspectives and empirical findings of this study are useful to both academics and practitioners. The findings also raise new implications regarding the various types of interactions (e.g. enhancing or suppressing) between the social and technical factors around social software.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Agile firms are better equipped to navigate challenges in today’s unpredictable business environment. Developing specific IT capabilities can help strengthen the different agility aspects and increase competitiveness. 10; 10;

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Facial recognition payment is an emerging mobile payment method that uses human biometrics for personal identification. The purpose of this study is to examine how users' salient beliefs regarding the technology–organization–environment–individual (TOE–I) dimensions affect their attitudes and how attitudes subsequently influence the intention to use facial recognition payment in offline contactless services.

This study comprehensively investigates customers' decision-making psychological mechanism of using facial recognition payment by integrating the belief–attitude–intention (B–A–I) model and the extended TOE–I framework. Data from 420 valid samples were collected through an online survey and analyzed using partial least squares structural equation modeling.

Research results indicate that convenience and perceived herd exert positive effects on trust and satisfaction. Meanwhile, familiarity has a significantly positive effect only on trust but not on satisfaction. In contrast, perceived privacy risk exhibits a negative effect on both trust and satisfaction. Trust and satisfaction positively influence the intention to use facial recognition payment. Unexpectedly, self-awareness negatively moderates the effect of satisfaction on intention to use, but its effect on the relationship between trust and intention to use is non-significant.

To the best of the authors’ knowledge, this study is one of the early studies that explicate customers' psychological mechanism in facial recognition payment in offline contactless services through an understanding of the B–A–I causal linkages with the identification of users' perceptions from a comprehensive context-specific perspective. This study enriches the literature on facial recognition payment and explores the moderating role of self-awareness in the relationship between users' attitudes and intention to use, thereby revealing a complex psychological process in the usage of offline facial recognition payment systems.

This study aims to propose and validate a model for e-Learning success based on students’ experiences in the “new normal.” To achieve this goal, this study focused on answering three research questions: (1) What are the students’ experiential factors that impact e-Learning? (2) How do these experiential factors affect e-Learning success? (3) In what ways does a multimethod provide a comprehensive perspective and an in-depth understanding of students’ e-Learning experiences in the new normal?

This study applied a mixed-methods sequential approach using exploratory, confirmatory and complementary studies. First, this study undertook a text-mining exploratory analysis of the review data to extract e-Learning topics. Then, based on the Information Systems (IS) success model, this study identified an integrated framework drawn from the results of the text-mining analysis. Second, this study proposed an e-Learning, experience-based success model and corresponding hypotheses and conducted a confirmatory study with surveys to validate the model. Third, this study conducted in-depth interviews to better identify the phenomenon of interest.

The five factors extracted from the first stage are system quality, lecture content, teaching quality, online interaction and achievement. This study subsequently confirmed the significant relationships between the e-Learning success factors in the second stage based on the IS success model. Finally, a complementary study identified the importance of interactivity for e-Learning success in the new normal.

To the best of the authors’ knowledge, this paper is the first to develop an e-Learning success model using a comprehensive mixed-methods approach.

This study aims to apply the information system success model (ISSM) to examine the relationships among actual use, use continuance intention, user satisfaction and net benefits in the context of quick-service restaurant (QSR) patrons using two contactless technologies (CT): self-service kiosks (SSK) and mobile applications (MA) for food ordering. The study also investigates the moderating roles of social interaction anxiety (SIA) and language proficiency (LP) in the abovementioned relationships.

Survey data from 421 QSR patrons with experience using McDonald's SSK and MA were collected and analyzed through a seemingly unrelated regressions (SUR) technique.

Research findings reveal positive associations among actual use, use continuance intention and satisfaction with CT (i.e. SSK and MA). The actual use and satisfaction with CT are positively associated with individual benefits, leading to improved patron satisfaction with QSR. Findings also reveal that, in the case of MA, SIA positively moderates relationships between actual use/satisfaction and individual benefits and between satisfaction and organizational benefit, while LP shows negative moderating effects on those relationships.

This study is one of the first attempts to present empirical evidence of constructs in the ISSM (actual use, use continuance intention, satisfaction and individual/organizational benefits) in the context of QSR patrons using SSK and MA. It also shows that using MA can address some patrons' psychological problems interacting with others in their food-ordering processes.