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Drawing upon the third-person effect (TPE) theory, this study focuses on two types of misinformation countering intentions (i.e. simple correction and correction with justification). Accordingly, it aims to (1) assess the tenability of the third-person perception (TPP) in the face of misinformation on social media, (2) explore the antecedents of TPP and its relationship with individual-level misinformation countering intentions and (3) examine whether the mediating process is contingent on different social media usage conditions.

An online survey was conducted with 1,000 representative respondents recruited in Mainland China in January 2022 using quota sampling. Paired t-test, multiple linear regression and moderated mediation analysis were employed to examine the proposed hypotheses.

Results bolster the fundamental proposition of TPP that individuals perceive others as more susceptible to social media misinformation than they are. The self-other perceptual bias served as a mediator between the perceived consequence of misinformation and misinformation countering (i.e. simple correction and correction with justification) intentions. Furthermore, intensive social media users were likely to be motivated to counter social media misinformation derived from the indirect mechanism.

The findings provide further evidence for the role of TPE in explaining misinformation countering intention as prosocial and altruistic behavior rather than self-serving behavior. Practically, promising ways to combat rampant misinformation on social media include promoting the prosocial aspects and beneficial outcomes of misinformation countering efforts to others, as well as reconfiguring the strategies by impelling intensive social media users to participate in enacting countering actions

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2022-0507.

The purpose of this article is to identify how the organisations are able to improve their business value through acquisition of business analytics capabilities and by improving their performance.

With the help of literature survey, along with standard resource-based view framework, a conceptual model has been developed. These have been statistically tested by collecting the data using the survey questionnaire from 306 selected respondents from various service sector- and product-based organisations in India. To analyse the data we have used partial least square–based structural equation modelling.

The study highlights that by the help of data acquisition and tool acquisition as two vital components the acquisition of business analytics capabilities could improve the business value of the organisation by strengthening its organisational performance. The findings of this research also indicated that acquisition of business analytics capabilities has a significant influence on an organisation's business process performance and business decision, which in turn significantly influences organisational performance. And organisational performance eventually positively influences its business value. The model was found to provide an explanative power of 71%.

The proposed research model can provide effective recommendations to the management of the organisations to realise the importance of acquisition of effective business analytics capabilities to eventually improve the business value of the organisation.

No specific studies, as yet, have analysed the effects of acquisition of business analytics capabilities for improving organisational performance mediated through business process performance and business decision. Therefore, this research has explored the distinctive effort to empirically validate this understanding.

The study aims to provide insights in the sensemaking process and the use of business analytics (BA) for project selection and prioritisation in start-up settings. A major focus is on the various ways start-ups can understand their data through the analytical process of sensemaking.

This is a comparative case study of two start-ups that use BA in their projects. The authors follow an interpretive approach and draw from the constructivist grounded theory method (GTM) for the purpose of data analysis, whereby the theory of sensemaking functions as the sensitising device that supports the interpretation of the data.

The key findings lie within the scope of project selection and prioritisation, where the sensemaking process is implicitly influenced by each start-up's strategy and business model. BA helps start-ups notice changes within their internal and external environment and focus their attention on the more critical questions along the lines of their processes, operations and business model. However, BA alone cannot support decision-making around less structured problems such as project selection and prioritisation, where intuitive judgement and personal opinion are still heavily used.

This study extends the research on BA applied in organisations as tools for business development. Specifically, the authors draw on the literature of BA tools in support of project management from multiple perspectives. The perspectives include but are not limited to project assessment and prioritisation. The authors view the decision-making process and the path from insight to value, as a sensemaking process, where data become part of the sensemaking roadmap and BA helps start-ups navigate the decision-making process.

Large optical mirror processing systems (LOMPSs) consist of multiple subrobots, and correlated disturbance terms between these robots often lead to reduced processing accuracy. This abstract introduces a novel approach, the nonlinear subsystem adaptive dispersed fuzzy compensation control (ADFCC) method, aimed at enhancing the precision of LOMPSs.

The ADFCC model for LOMPS is developed through a nonlinear fuzzy adaptive algorithm. This model incorporates control parameters and disturbance terms (such as those arising from the external environment, friction and correlation) between subsystems to facilitate ADFCC. Error analysis is performed using the subsystem output parameters, and the resulting errors are used as feedback for compensation control.

Experimental analysis is conducted, specifically under the commonly used concentric circle processing trajectory in LOMPS. This analysis validates the effectiveness of the control model in enhancing processing accuracy.

The ADFCC strategy is demonstrated to significantly improve the accuracy of LOMPS output, offering a promising solution to the problem of correlated disturbances. This work holds the potential to benefit a wide range of practical applications.

This study aims to explore the determinants of viewers’ gifting and social sharing behaviours in online streaming from a dual-attachment perspective and to explain how live streaming fosters attachment through a social interaction aspect.

This study conducted an online survey with 316 valid responses to test the research model. The structural equation modelling approach was applied to assess both the measurement and structural models.

The results show that both bond-based and identity-based attachments promote gifting and social sharing behaviours. Participation and cognitive communion motivate viewers to establish bond-based attachment, while group interaction among viewer crowds encourages viewers to create identity-based attachment. In addition, group interaction can moderate the relationship between participation and bond-based attachment.

This study is one of the earliest attempts to highlight the significance of viewer crowd and viewer-viewer interaction in promoting viewers’ behaviours in live streaming context. This study also indicates that viewer-viewer interaction can moderate the impact of viewer–streamer interaction, which is among the first to investigate the interaction effects of viewer-viewer interaction and viewer–streamer interaction.

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.

Drawing on information foraging theory and the SERVQUAL model, this study built a research model to investigate the roles of middle-aged and elderly short-video creators' online attributes in attracting short-video viewers to be their followers.

Taking Douyin (a famous short-video platform in China) as an example, this study used a sequential triangulation mixed-methods approach (quantitative → qualitative) to examine the proposed model by investigating both creators and viewers.

Viewers who clicked the “like” button for the middle-aged and elderly creators' videos are more likely to follow the creators. Viewers will believe that middle-aged and elderly creators who received more likes are more popular. Thus, middle-aged and elderly creators with more likes usually have more followers. Viewers usually believe that middle-aged and elderly creators who more frequently publish professional and high-quality videos have invested more effort and who have official verification also have a high level of authority and are recognized by the platform. Thus, middle-aged and elderly creators with more professional videos and verification usually have more followers. Moreover, verification, the number of videos and the professionalism of videos can enhance the transformation of viewers who liked middle-aged and elderly creators' videos into their followers, and thus strengthen the positive relationship between the number of likes and the number of followers; however, the number of bio words will have an opposite effect.

These findings have implications for platform managers, middle-aged and elderly creators and the brands aiming to develop a “silver economy” by attracting more followers.

This study researches short-video platforms by using a mixed-methods approach to develop an understanding of viewers' decision-making when following middle-aged and elderly creators based on information foraging theory and the SERVQUAL model from the perspectives of both short-video creators and viewers.

This paper aims to disentangle the mechanism linking digital servitization and manufacturing firm performance. The contributions of the service networks and slack resources are analyzed.

Drawing on a survey of manufacturing firms that have implemented or are implementing digital service projects in China, this paper examines the mediation effect of service networks and the moderated mediation effect of slack resources to capture the role of service networks and slack resources in the relationship between digital servitization and manufacturing firm performance.

Both basic and advanced digital services can equally contribute to manufacturing firm performance. Service networks mediate the relationship between basic digital servitization and manufacturing firm performance. No moderated mediation effect of slack resources is found, but slack resources negatively moderate the effects of basic digital services on service networks and positively impact service networks.

The mediating mechanism of service networks in the relationship between digital servitization and manufacturing firm performance is theorized, and it is clarified that service networks mediate the association between basic digital services and manufacturing firm performance but not advanced digital services. Additionally, there is no significant difference in performance implications when manufacturing firms provide basic versus advanced digital services, answering the call for research on the various types of digital servitization. This paper also identifies firms’ slack resources as the boundary conditions under which basic digital services influence service networks and the positive impacts of slack resources on service networks, bridging the network literature, organizational slack literature and digitalization literature under the framework of service ecosystem research.

The final properties of ductile iron are decided by the inoculant processing while pouring the melt. The shape and size of nodules generated during solidification are of paramount importance in solidification of ductile cast iron. The purpose of this study is to examine the effect of different inoculant addition on the solidification of ductile cast iron melt through thermal analysis.

Thermal analysis has recently grown as a tool for modeling the solidification behavior of ductile cast irons. Iron properties will be predicted by analyzing the cooling curve patterns of the melts and predicting the related effectiveness of inoculant processing. In this study, thermal analysis is used to evaluate the need for inoculation.

The amount and type of inoculation will affect the amount of undercooling during the solidification of ductile cast iron. It is found that the addition of 0.1 to 0.4 Wt.% inoculant lowers the austenite dendrite formation starting temperature while increasing the eutectic freezing temperature. Microstructure analysis revealed that the addition of inoculation increases the nodule count from 103 to 242 nodules. The beneficial effects of inoculation are sustained by an improved graphitization factor, which shows the formation of graphite nodules in the second phase of the eutectic reaction.

The inoculation treatment has improved metallurgical occurrences such as carbide to graphite conversion, graphite microstructure control, graphite nodule count at the start of solidification and the last stage of solidification, which determines the soundness of casting. The foundry industry can follow these steps for monitoring the solidification of ductile iron castings.

The purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.

This paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.

Despite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.

The proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.