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The purpose of this paper is to investigate factors influencing knowledge sharing on enterprise social network (ESN) use behaviour among academic staff in universities, using the unified theory of acceptance and use of technology (UTAUT) as the underlying research framework

A conceptual framework was created by extending the UTAUT by incorporating three additional factors, namely, feature value (FV), relationship expectancy (RE) and professional benefits. A quantitative approach based on the survey was used to collect data from 254 academic staff. Data were analysed using structural equation modelling.

The result indicated significant differences around factors influencing both consumptive and contributive usage patterns within ESNs. These factors suggest more contributive than consumptive use.

Future research should consider a longitudinal study focusing on the change in ESN use behaviour among academic staff and the fundamental aspects influencing this change.

This study extends the UTAUT model by incorporating three additional factors: FV, RE and professional benefits, to study ESN use behaviour in a higher education context. This study has significantly modified UTAUT to include the dynamic nature of ESN usage.

The paper aims to explore “content” factors influencing consumptive and contributive use of enterprise social networking within UK higher education during the COVID-19 pandemic.

The methodology uses genre analysis and grounded theory to analyse empirical data from posts obtained through Microsoft Yammer and a focus group.

The findings reveal the motivators-outcomes-strategies and the barriers-outcomes-strategies of users. Motivators (M) include feature value, Information value, organizational requirement and adequate organizational and technical support. Barriers (B) include six factors, including resisting engagement on the online platform, emotional anxiety, loss of knowledge, the lack of organizational pressure, lack of content quality and lack of time. An Outcomes (O) framework reveals benefits and dis-benefits and strategies (S) relating to improving user engagement.

The research method and resultant model may serve as guidelines to higher educational establishments interested in motivating their staff and scholars around the use of enterprise social network (ESN) systems, especially during face-to-face restrictions.

This research study was conducted during the COVID-19 pandemic which provides a unique setting to examine consumptive and contributive user behaviour of ESN’s. Furthermore, the study develops a greater understanding of “content” factors leading to the benefits or dis-benefits of ESN use, drawing on user motivators, barriers and strategies during the COVID-19 pandemic in UK education.

Feature selection is crucial for machine learning to recognize lane-change (LC) maneuver as there exist a large number of feature candidates. Blindly using feature could take up large storage and excessive computation time, while insufficient feature selection would cause poor performance. Selecting high contributive features to classify LC and lane-keep behavior is effective for maneuver recognition. This paper aims to propose a feature selection method from a statistical view based on an analysis from naturalistic driving data.

In total, 1,375 LC cases are analyzed. To comprehensively select features, the authors extract the feature candidates from both time and frequency domains with various LC scenarios segmented by an occupancy schedule grid. Then the effect size (Cohen’s d) and p-value of every feature are computed to assess their contribution for each scenario.

It has been found that the common lateral features, e.g. yaw rate, lateral acceleration and time-to-lane crossing, are not strong features for recognition of LC maneuver as empirical knowledge. Finally, cross-validation tests are conducted to evaluate model performance using metrics of receiver operating characteristic. Experimental results show that the selected features can achieve better recognition performance than using all the features without purification.

In this paper, the authors investigate the contributions of each feature from the perspective of statistics based on big naturalistic driving data. The aim is to comprehensively figure out different types of features in LC maneuvers and select the most contributive features over various LC scenarios.

To measure the success of corporate social software (CSS), interviews, surveys, content and usage data analysis have been commonly used in practice. While interviews and surveys are only capable of making perceived use and benefits transparent, usage data analysis reveals many objective facts but does not allow insights into potential user-benefits. Hence, the purpose of this paper is to link both perspectives to advance CSS success measuring.

The research case is References+, a Corporate Social Software developed at Siemens to facilitate worldwide sharing of knowledge, experiences, and best practices since 2005. References+ currently has around 15,000 registered members located in more than 80 countries. This paper evaluates results from a user survey with nearly 1,500 responding employees and links all survey results to the corresponding participant’s data on platform use to generate additional insights.

The paper generates findings on how CSS is used in practice and how it is perceived by employees of a large-scale enterprise. Furthermore, it explores how a combination of subjective and objective evaluation methods can be applied to advance the state-of-the-art in measuring use and benefits. By linking CSS usage data to corresponding survey data, the paper provides results on what type of use of CSS may create what type of benefit.

This study encourages practitioners to take advantage of a variety of instruments for measuring the benefits of CSS. It generates numerous arguments for practitioners on how to make the benefit of CSS more transparent to financial-oriented decision-makers to successfully defend knowledge management projects against shrinking IT budgets.

This paper is one of the first attempts to explore the relationship between “perceived use” and “perceived benefits” measured by surveys and “factual use” measured by CSS usage statistics for knowledge management research. The findings of this paper may empower the role of user surveys in generating additional insights on use and benefits.

The purpose of this paper is to dismantle the complex issue of “use of accounting information (AI)” by pointing to different groups of information users, diverging interests and needs of these user groups and various influential factors on the usability and the actual use of AI.

This paper includes a literature review and conceptual reflections.

The review of recently published articles on the issue of “use of accounting information” presents an actual picture of the academic debate on purposes of use, user types, needs of various user groups and factors influencing the usability and the actual use of AI. The subsequent conceptual reflections deal with so far less regarded user groups, with options to strengthen the user perspective in budgeting and financial reporting, with approaches for engaging users in the content of accounting documents, with interrelations between user needs, usability and use intensity, including various antecedents of the different variables of the information-use issue.

This paper presents promising routes for future research.

The paper emphasizes the importance of paying more attention to the specific information needs and the motivations of various stakeholder groups generally interested in using financial information.

The paper presents results of reviewing recent literature on the issue of “use of accounting information” and provides some insight into specific aspects of this issue.

While the sizable body of research focusses on various psychological effects of enterprise social media (ESM), research connecting the link between ESM and cyberslacking is still very sparse. Drawing inspiration from the social bonding theory, the authors have proposed a moderated mediation model to explain how ESM affordances reduce cyberslacking, mediated significantly by workplace social bonding when the perceived co-worker involvement is high.

Utilising a sample of 384 respondents, the study tested the model fit and hypothesised relationships with AMOS and PROCESS MACRO.

The findings show that workplace social bonding mediates the relationship between ESM affordances and cyberslacking. The results are also consistent with the moderated mediation model as the mediation is significant when the perceived co-worker involvement is high, and the mediation is insignificant when the moderator is low/moderate.

Considering the potential behavioural dynamics of ESM artefacts, the authors have introduced self-expression (via microblogging), recognition (from paralinguistic digital affordances) and network externality as ESM affordances. Alongside the existing measures to reduce employee deviance, the proposed model with the above-mentioned affordances can be investigated in detail by the future research community.

In light of the findings, the study demonstrates that ESM can be treated as a mechanism to keep cyberslacking at bay. The results offer significant implications for managers, who lookout for innovative and soft strategies to reduce cyberslacking in the workplace.

Instead of implementing strict policies to kerb cyberslacking, this study proposes an alternative and an interesting model by introducing ESM as a strategic tool in reducing cyberslacking. The paper argues that ESM, being a potential tool for employee engagement and bonding, may offset the employees' tendency to involve in cyberslacking.

Enterprise social media (ESM) applications offer new opportunities for organizations to mobilize employees for open innovation, by promoting innovation beyond traditional R&D functions. Despite the popularity and success of these applications, current research has yet to fully explore the potential of ESM applications as a driver of employee-driven innovation, specifically through advancements in innovation culture. To fill this gap, this study proposes a theoretical framework that explains the role of ESM applications in facilitating employee innovation.

The authors administered a cross-sectional survey to collect data from professionals who use ESM applications regularly at work. Following a pilot study and instrument refinement, the authors conducted a field study to test measurement and the structural model by using the partial least square-structural equation modeling (PLS-SEM) method.

The findings of this study support the validity of the proposed theoretical model. First, the results confirmed the three antecedents of ESM use for innovation: perceived innovation possibilities enabled by ESM technology, the expected value of ESM use for innovation and organizational support for using ESM applications for innovation. Next, the results confirmed the importance of ESM use in encouraging individual innovation productivity in terms of product/service innovation, process innovation and social innovation. Finally, the results corroborated the mediating role of risk-taking and knowledge-sharing culture in the use of ESM to increase innovation productivity.

The findings presented here have implications for theory and practices that would concern fostering a supportive environment and building an organizational culture that promotes employees' innovation behavior (internal open innovation) by using social technologies.

This study aims to understand how organizations in the service industry can encourage the use of enterprise social networks (ESNs) for knowledge sharing, focusing on the concepts of intra-organizational trust and governance.

The authors gathered data through an online survey of 104 participants from the financial services industry. Data were analyzed using structural equation modelling to test the proposed model and evaluate the constructs’ reliability and validity.

The findings of the survey data indicate that intra-organizational trust and governance are related to the use of ESN for knowledge sharing to enhance service innovation. Further, the findings suggest that, although trust directly affects service innovation, using ESN for knowledge sharing partially mediates the relationship between trust and service innovation. The findings also reveal that governance significantly moderates the relationship between ESN for knowledge sharing and innovation.

This paper provides insights into the relationship between trust, knowledge sharing and innovation. The novelty of this study demonstrates that governance strengthens the relationship between ESN for knowledge sharing and innovation. Further, the study suggests that firms using or intending to use ESNs could keep track of the evolving nature of ESNs, develop an open culture and create a trusted environment in their organizations.

The purpose of the research is to analyze the factors that determine the intention of small- and medium-sized enterprises (SMEs) to adopt the Metaverse. For this purpose, the analysis of the effort expectancy and performance expectancy of the constructs in relation to business satisfaction is proposed.

The analysis was performed on a sample of 182 Spanish SMEs in the technology sector, using a PLS-SEM approach for development. For the confirmation of the model and its results, an analysis with PLSpredict was performed, obtaining a high predictive capacity of the model.

After the analysis of the model proposed in this research, it is recorded that the valuation of the effort to be made and the possible performance expected by the companies does not directly determine the intention to use immersive technology in their strategic behavior. Instead, the results obtained indicate that business satisfaction will involve obtaining information, reducing uncertainty and analyzing the competition necessary for approaching this new virtual environment.

The study represents one of the first approaches to the intention of business behavior in the development of performance strategies within Metaverse systems. So far, the literature has approached immersive systems from perspectives close to consumer behavior, but the study of strategic business behavior has been left aside due to the high degree of experimentalism of this field of study and its scientific approach. The present study aims to contribute to the knowledge of the factors involved in the intention to use the Metaverse by SMEs interested in this field.

Enterprise social media (ESM) usage has gained considerable momentum within organizations. The purpose of this paper is to seek a better understanding of ESM usage based on the task environments and the technology affordances of ESM.

This study is based on a survey consisting of 556 usable responses. Regression methods are applied to analyze the data.

This study finds strong support for the positive impact of task-technology fit on ESM usage. Considering separately, task equivocality had no impact; task interdependence had a negative effect on ESM usage; bridging social capital had a positive effect; and bonding social capital had a marginal impact on ESM usage.

This research incorporated social capital into discussions of task-technology fit. A 2×2 matrix based on task equivocality and task interdependence was developed, which may be extended to other contexts or technologies.

ESM implementation should account for both task environments and the appropriate technology affordances. Individuals access bridging social capital to a greater extent than bonding social capital using ESM, and they do not use ESM when the task environments alone are considered.

This is an original study that considers task environments and technology affordances in the context of ESM usage. The findings offer valuable and timely contributions to both scholars and practitioners.