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The purpose of this paper is to present a novel image sensor technology for raised characters based on line structured‐light. It can convert raised character's three‐dimensional (3D) features into image's grayscale levels.

The measurement principle and mathematical model are described. An experimental device is established and system parameters are calibrated. A grayscale conversion algorithm is proposed to convert the distortion of laser stripe to the grayscale intensity of image. The article also introduces a four‐factor method to assess the image quality of characters.

Experimental results show that the method can get high‐contrast images of raised characters that are conventionally low‐contrast with the background. Besides, the method does not need complicated calibration and mass computation, which makes the system structure simple and increases the speed of image acquisition.

The paper presents a novel image acquisition method for raised characters.

This study investigated how Generation Z adopted brand messages through trending topics and analysed the central and peripheral routes of information adoption. It explored the roles of informational and emotional supports in influencing information adoption through perceived information usefulness and considered the adoption of brand messages within trending topic discussions.

Drawing on the extension information adoption model, this study employed a quantitative approach by utilising covariance-based structural equation modelling to analyse 400 valid web-based questionnaire responses from Sina Microblog users among Generation Z in China.

Adopting brand messages via trending topics, with cues emphasising information quality as the central route and information credibility as the peripheral route, enhances perceived information usefulness. Notably, Generation Z can derive informational and emotional support from trending topic discussions, influencing their perceived information usefulness. This process operates independently of the dual routes of information adoption.

Marketers can leverage influencers and users’ comments to motivate Generation Z to adopt brand messages through trending topics, but this study was limited by the demographic diversity of its sample and the specific types of brands analysed. Incorporating cross-cultural comparisons, group analyses, potential moderating factors and control variables could improve the model’s generalisability.

Compared to information adoption models rooted in the organisational information exchange, the originality of this study lies in confirming that, within the context of trending topics, which blend social connections with an anonymous environment, informational and emotional supports can serve as additional cues influencing brand information adoption via perceived information usefulness.

This study employs bibliometric analysis to map the research landscape of social media trending topics during the COVID-19 pandemic. The authors aim to offer a comprehensive review of the predominant research organisations and countries, key themes and favoured research methodologies pertinent to this subject.

The authors extracted data on social media trending topics from the Web of Science Core Collection database, spanning from 2009 to 2022. A total of 1,504 publications were subjected to bibliometric analysis, utilising the VOSviewer tool. The study analytical process encompassed co-occurrence, co-authorship, citation analysis, field mapping, bibliographic coupling and co-citation analysis.

Interest in social media research, particularly on trending topics during the COVID-19 pandemic, remains high despite signs of the pandemic stabilising globally. The study predominantly addresses misinformation and public health communication, with notable focus on interactions between governments and the public. Recent studies have concentrated on analysing Twitter user data through text mining, sentiment analysis and topic modelling. The authors also identify key leading organisations, countries and journals that are central to this research area.

Diverging from the narrow focus of previous literature reviews on social media, which are often confined to particular fields or sectors, this study offers a broad view of social media's role, emphasising trending topics. The authors demonstrate a significant link between social media trends and public events, such as the COVID-19 pandemic. The paper discusses research priorities that emerged during the pandemic and outlines potential methodologies for future studies, advocating for a greater emphasis on qualitative approaches.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2023-0194.

The purpose of this study is to empirically investigates the influence of geopolitical risk acts (GPR) on world crude oil production. GPRs are a proxy for waging wars and military actions, thus it is expected to have a clear impact on world crude oil production (WCOP).

The current study formulates a theoretical model, and its parameters are estimated using three methodologies – traditional autoregressive distributed lag (ARDL) model, Dynamic ARDL model, and Frequency domain causality test – across the period 1973–2023 to ensure robust findings.

The results illustrate that GPRs constrain the global crude oil supply. The final impact relies on the positive interaction term between GPRs and international economic activity from one side and the negative interaction term with crude oil prices from the other. Likewise, the findings show that geopolitical threats reduce producing crude oil. Furthermore, this research deliberates on policy implications stemming from these findings.

Examining existing literature reveals a gap in understanding the relationship between geopolitical risk and crude oil production. Most of the studies in this research strand focus on investigating the impact on oil price volatility.