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This paper aims to systematically investigate the direct and indirect effects of four types of support – peer instrumental support, peer emotional support, platform business support and platform communication support – on seller trade volume in social commerce. It also aims to uncover the path of support-to-sales of the seller from a platform perspective and provides a more complete picture of the social commerce phenomenon.

This paper uses multi-source data including primary survey data and secondary data on trade volume to test the hypotheses. PROCESS mediation model is used to analyze the multi-source data set.

This study finds that the positive effects of peer instrumental support, platform business support and platform communication support on seller trade volume are fully mediated by seller collaborative information exchange. Also, peer emotional support has a significant negative effect on seller trade volume and collaborative information exchange can serve as a buffer to mitigate the negative effect.

The authors provide new insights into what types of support are or are not conducive to improving transaction volume of individual sellers and highlight the mediating role of seller information exchange in this value generation process in social commerce. These findings advance current knowledge of how seller interactions increase value in social commerce. The chosen research setting may limit the generalizability of the findings of this study.

This paper offers valuable implications for social commerce platforms on how to better serve their sellers to achieve high growth. Specifically, the findings suggest that platforms should encourage instrumental support and information exchange among peer sellers. In addition, platforms should expand seller support from a single-focus on sellers’ business to a dual-focus on both sellers’ business and socialization in social commerce.

This paper fulfills an identified need to study how sellers can better derive value from the social interactions and how social commerce platforms can effectively influence transactions, support sales and serve as a selling platform.

In this study, specific measures adopted by the social media platforms in China supporting personal information management are investigated via surveys targeting such platforms. The purpose of this paper is to find out how social media platforms understand information management, and from which aspects and through what specific methods they provide support for information management, which contributes to understanding the issues and strategies associated with personal information management on social media.

The dimensions and specific contents of the current platform support provided for information management are clearly defined by performing qualitative text analysis based on the content obtained from 11 platform policies published by five representative Chinese social media platforms.

How social media platforms support personal information management on creation, collection, utilisation, sharing, storage, protection, removal and modification is identified. By analysing the status quo of support provided by the Chinese social media platform, some issues are proposed for discussion. Improved normative management is required to address the coexistence of multivalued information and management risks. However, the user rights are limited because the platform policies tend to be more focused on the perspective of the social media platform. Furthermore, the platform policy contents regarding information management are incomplete, and the applicability of these policies should be improved.

This study seeks to contribute to personal information management on social media from the perspective of platform support. The perspective from the platforms as the service providers supporting information management also helps identify information management challenges and potential strategies. Furthermore, combining with the personal information management perspective, this study provides a background understanding of information management under a social collaborative framework for platforms, authorities, users and memory institutions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2020-0249

Digital technologies have become indispensable in businesses and are gaining attention in academic institutions context too. Digital technological ecosystems provide a platform to communicate and share their products and services to existing and potential customers. Entrepreneurial startups and companies face internal and external challenges utilizing social media technologies to commercialize their business ideas. The purpose of this paper is to identify opportunities and challenges faced by academic entrepreneurs' startups.

This research has adopted a qualitative approach comprising of semi-structured in-depth interviews with academic entrepreneurs’ startups to find the main challenge they face using social media platforms. The purpose was associated with an exploratory type of study and also included a prominent unified theory of acceptance and use of technology (UTAUT) and technological opportunism (TO) model. The research respondents were 23 academic entrepreneurs startups who were chosen applying purposive sampling. Respondents were given a set of a questionnaire consisting of close-ended questions that are five-point Likert scale. The questionnaire included various parameters to measure the social media challenges the academic entrepreneurs’ startups undergo in the initial phase of their businesses.

The study identified that business-to-customer relations, brand, reputation, competition and cultural and language influence digital technologies entrepreneurship. While, the findings discovered the extended research model has a positive influence on academic entrepreneurs' intentions to use digital technologies media platforms. The outcome of this paper has thrown more light on which issues are there in digital technologies entrepreneurship, the determinants and actual usage advantages from UTAUT model and TO model that could be properly employed to solve issues of digital technologies media platforms and the potential concerning the adoption and use of digital technologies.

The study of academic entrepreneurs' startups can be considered original in nature. There is dearth of standard literature in the upcoming area of academic entrepreneurship. Governments are taking initiatives to promote academic entrepreneurs' startups, and the findings will be able to give them a right direction.

This research study aims to investigate consumer usage motivations for three of the top social media platforms today: Facebook, Twitter and Instagram. Additionally, through understanding various platform distinctions, firms can understand which social media platforms consumers prefer to use to co-create with brands online.

An exploratory qualitative study is first conducted to understand consumer motivations for using different social media platforms. The main study tests five hypotheses related to consumer usage intentions and social media co-creation behavior across three social media platforms. A survey is conducted with 1,050 social media users with a comparison of mean responses using multivariate analysis of covariance.

Results support significant differences between platforms in terms of use and co-creation behaviors. For informational purposes, consumers gravitate toward Twitter. For social purposes, Twitter and Instagram are preferred. Instagram is the primary platform for entertainment motivation as well as co-creating with brands via social media. Surprisingly, Facebook shows the lowest usage intentions and co-creation despite being the largest platform and network most widely used by marketers.

To the best of the authors’ knowledge, this is one of the first studies to take a multi-platform approach to understanding consumer social media use and co-creation with brands. The results highlight that marketing academics and practitioners must segment the various social media platforms as each offers unique value propositions to consumers.

The main purpose of this study is to explore and validate the question “whether altmetric mentions can predict citations to scholarly articles”. The paper attempts to explore the nature and degree of correlation between altmetrics (from ResearchGate and three social media platforms) and citations.

A large size data sample of scholarly articles published from India for the year 2016 is obtained from the Web of Science database and the corresponding altmetric data are obtained from ResearchGate and three social media platforms (Twitter, Facebook and blog through Altmetric.com aggregator). Correlations are computed between early altmetric mentions and later citation counts, for data grouped in different disciplinary groups.

Results show that the correlation between altmetric mentions and citation counts are positive, but weak. Correlations are relatively higher in the case of data from ResearchGate as compared to the data from the three social media platforms. Further, significant disciplinary differences are observed in the degree of correlations between altmetrics and citations.

The results support the idea that altmetrics do not necessarily reflect the same kind of impact as citations. However, articles that get higher altmetric attention early may actually have a slight citation advantage. Further, altmetrics from academic social networks like ResearchGate are more correlated with citations, as compared to social media platforms.

The paper has novelty in two respects. First, it takes altmetric data for a window of about 1–1.5 years after the article publication and citation counts for a longer citation window of about 3–4 years after the publication of article. Second, it is one of the first studies to analyze data from the ResearchGate platform, a popular academic social network, to understand the type and degree of correlations.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2019-0364

Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

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.

Social interaction in comment sections has become a key factor for backers' decision making in crowdfunding platforms. However, current research on the two-way social interaction in crowdfunding is insufficient, and there exist inconsistent conclusions. This study focuses on the social interaction between creators and backers and explores its influence on the successful exit of crowdfunding projects.

The extended Cox model is used for the empirical analysis of 1,988 crowdfunding projects on the Modian (www.modian.com) platform, a crowdfunding platform for cultural and creative projects in China. The two-way social interaction is reflected in comment quantity and sentiment, as well as reply rate.

Results reveal an inverted U-shaped relationship between comment quantity/sentiment and the successful exit of crowdfunding projects. This relationship is strengthened by high reply rate.

This study focuses on comment quantity and sentiment. The inverted U-shaped results reconcile previous conclusions. Replies from creators are regarded as a separate factor, and their moderating role is explained. The study research proves the importance of social interaction in crowdfunding platforms and provides suggestions for backers, creators and platform managers.