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The purpose of this paper is to explore the factors that influence migrant workers' household registration transfer willingness at both individual and urban levels and to provide empirical evidence on adjusting the household registration system to accommodate economic development and migrant workers' imbalances.

This paper adopts a hierarchical nonlinear model and examines individual and urban influencing factors of migrant workers' household registration transfer willingness, based on the data from China Migrants Dynamic Survey (CMDS) and the Urban Statistical Yearbooks.

This paper shows that: (1) multi-factors, such as age, education, marital status, household demographics, industry and migrant workers' contract coverage, have significant effects on migrant workers' household registration transfer willingness; (2) The urban public service equalization indicators, such as regional economic, educational resources, medical care and ecological quality, have significant effects on migrant workers' willingness to transfer household registration; (3) The heterogeneity of migrant workers' willingness to transfer household registration is significant in central, eastern and western China.

The authors provide a fresh perspective on population migration research in China and other countries worldwide based on the pull–push migration theory, which incorporates both individual and macro (urban) factors, enabling a comprehensive examination of the factors influencing household registration transfer willingness. This hierarchical ideology and approach (hierarchical nonlinear model) could be extended to investigate the influencing factors of various other human intentions and behaviors.

Micro approaches (individual perspective) have dominated existing studies examining the factors influencing migrant workers' household registration transfer willingness. The authors combine individual and urban perspectives and adopt a more comprehensive hierarchical nonlinear model to extend the empirical evidence and provide theoretical explanations for the above issues.

Organisations using advanced technology, like ChatGPT, for executing their marketing practices are proliferating, but such fast growth also comes with different adverse impacts of ChatGPT. This interaction of ChatGPT with the humanly implemented marketing 5.0 approach complements the marketing effectiveness. However, while considering the brighter aspects of this techno-marketing integration, marketers should also keep its dark side in mind. Therefore, this chapter investigates the integration of AI-enabled ChatGPT into marketing 5.0 practices. However, both the concepts under study are growing in terms of literature, and the research gap is even more extended when considering their associated views. Furthermore, significantly less literature is available emphasising the negative aspects of this advanced technology. This chapter bridges these gaps by reviewing the literature and presenting the gold-plating effect of ChatGPT usage while implementing marketing 5.0 practices. It also proposes a framework for showing the relationship between ChatGPT utilisation and practicing marketing 5.0, depicting the dark side of this techno-marketing integration. It also emphasised the need for conscious and learned associations between the concepts under study.

Industrial Internet Platform (IIP) integrates various new information technologies and forms an ecosystem around the platform. It promotes the optimization of resource elements and the collaboration of industrial chains, driving traditional enterprises towards comprehensive Digital Transformation (DT). This research explores the mechanisms through which the Industrial Internet Platform enables the digital development of enterprises.

This study constructs an Industrial Internet Platform Ecosystem (IIPE) from an ecosystem perspective. Later, a systematic literature review was used to design a specific path for IIPE to enable enterprises' DT from the perspective of basic activities and organizational structure.

The results indicate that in IIPE there is a hierarchical structure in the enabling mechanism of IIP. Firstly, the IIPE enhances the digital capabilities of enterprises through the foundational activities of DT. Secondly, the IIPE promotes the adjustment in enterprise structure and strategic orientation for adapting to the DT.

More and more enterprises enter the IIPE and grow together in the ecosystem. As a result, the overall level of digitalization of the industry can be enhanced and all enterprises realize the expected benefits of DT.

Existing research recognized the role of IIP in enterprise management or production processes, but the DT of enterprises is not a single aspect. This research elaborates the mechanism of comprehensive DT of enterprises from the perspective of ecosystems and discovers specific paths for DT.

This study examines the role of crowd wisdom in misinformation correction. Going beyond fact-checking, we investigate the mechanisms underlying laypeople’s participation in misinformation correction. Drawing upon the Norm Activation Model (NAM), this study conceptualizes misinformation correction as a prosocial behavior and examines the impact of various media and social psychological factors on laypeople’s motivations to engage misinformation correction behavior.

Through a national survey of 1,022 respondents, we explore the norm activation process triggered by the perceived prevalence of online misinformation, which directly and indirectly impacts online misinformation correction intentions via awareness, norms, and efficacy. This mechanism was tested using structural equation modeling.

This study found that perceived prevalence of misinformation, self-efficacy, and outcome efficacy play multilayered roles in shaping misinformation correction intentions. The effects were mediated by the activation of personal norms, which showed the strongest direct relationship with correction intentions. However, these factors also demonstrated direct associations with correction intentions, indicating multiple paths in misinformation correction.

Differing from mainstream fact-checking approaches, this study provides a more comprehensive examination of the mechanisms underlying laypeople’s willingness to engage in social media misinformation correction behaviors. In addition, this study also extends NAM by incorporating media environment (perceived prevalence of online misinformation) into the model, identifying more paths affecting misinformation correction behaviors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0437

The aim of this paper is to explore the relationship between digital transformation and corporate fraud.

This paper uses panel data of Chinese listed corporations from 2010 to 2021 and captures digital transformation from the perspectives of awareness and investment by extracting related content from annual reports. Our work investigates whether and how digital transformation influences corporate fraud and examines the moderating effects of the legal environment, media environment and privacy concerns.

Our findings show that digital transformation, captured either from awareness or actual investment, can significantly alleviate corporate fraud. Our results are robust in a set of endogeneity tests and robustness checks. Additionally, we confirm that digital transformation alleviates corporate fraud through two mechanisms: improving internal monitoring and boosting information flow. Additionally, this alleviating effect is more pronounced for corporations with fewer privacy concerns and in worse legal and media environments.

Our findings provide insights for policymakers to motivate corporations to engage in digital transformation for fraud prevention. We also offer guidelines for corporations to improve their awareness and actual investments in digital transformation and take advantage of its governance effect in preventing corporate fraud.

Overall, we highlight the governance role of digital transformation in alleviating corporate fraud and provide policy implications for regulators in emerging economies to regard digital transformation as an effective tool for fraud prevention.

This study aims to assess the relationships between limit parametric settings of in-nozzle impregnation additive manufacturing, namely, nozzle temperature and layer height, on the micromorphology and induced mechanical properties of continuous flax yarns-reinforced biocomposites.

The additively manufactured biocomposites with different printing parameters were characterized by X-ray microcomputed tomography and tensile testing to link the process–structure–properties relationships regarding the internal morphologies of yarns, matrix and porosities and tensile properties.

Several types of morphology were defined regarding fiber, void, raster and interfaces. The results showed a competition between porosity development, coating effect and variation in fiber volume fraction on the biocomposite quality and mechanical performance when simultaneously varying the layer height and the temperature due to rheology-related phenomena and process-induced defects.

To the best of the authors’ knowledge, no previous study has been carried out on the relation between the internal micromorphologies in three directions of continuous biocomposites manufactured by in-nozzle impregnation additive manufacturing and the limit printing parameters. The findings are thought to help manufacturers master this technology for high-end applications.

The purpose of this study is to prepare thermal transfer ribbons with good alcohol resistance.

A variety of alcohol-resistant thermal transfer inks were prepared using different polyester resins. The printing temperature, printing effect, adhesion and alcohol resistance of the inks on the label were studied to determine the feasibility of using the ink for manufacturing thermal transfer ribbons. The ink formulations were prepared by a simple and stable grinding technology, and then use mature coating technology to make the ink into a thermal transfer ribbon.

The results show that the thermal transfer ink has good scratch resistance, good alcohol resistance and low printing temperature when the three resins coexist. Notably, the performance of the ribbon produced by 500 mesh anilox roller was better than that of other meshes. Specifically, the ink on the matte silver polyethylene terephthalate (PET) label surface was wiped with a cotton cloth soaked in isopropyl alcohol under 500 g of pressure. After 50 wiping cycles, the ink remained intact.

The proposed method not only ensures good alcohol resistance but also has lower printing temperature and wider label applicability. Therefore, it can effectively reduce the loss of printhead and reduce production costs, because of the low printing temperature.

This paper aims to investigate the effects of process parameters on parts produced through the material extrusion process to create a piping spacer suitable for oil and gas applications.

The two primary materials examined were Acrylonitrile Styrene Acrylate (ASA) and High-Impact Polystyrene (HIPS). Taguchi’s design of experiment methodology was used for the design of experiments. The effect of processing parameters fill density, layer thickness and printing orientation) on the output factors (maximum compressive strength and specific energy) was analyzed through analysis of variance. According to the application of the piping spacer, compression testing is deemed to be as per ASTM-D695 requirements. In addition to this, the optimum processing factors were identified through gray relational analysis (GRA) and response surface methodology (RSM).

ANOVA results indicate that fill density had the highest percentage contribution for ASA, with a percentage of 29.84%, followed by layer thickness (27.54%) and printing orientation (22.08%). However, for the HIPS material, density was the most influential element, with a contribution of 77.80%, followed by layer thickness at 16.77% and printing orientation at 4.39%. Optimization of the process parameters through GRA and RSM suggested the optimum parameters combination for ASA was 90° printing orientation, 0.09 mm layer thickness and 100% fill density, whereas HIPS had the same response except for the printing orientation, which was 0°, 0.09 mm layer thickness and 100% fill density.

This paper can serve as an aid in understanding the effect of printing orientation, layer thickness and fill density on the plyometric material extrusion process.

The online healthcare platform (OHP) has become an essential element of the healthcare system, representing a technological shift in the job responsibilities of medical professionals. Drawing on a technology-based job demands–resources (JD-R) model, this study aims to examine how the technological characteristics of OHP affect doctors’ OHP use psychology and behavior.

This empirical study was based on a survey conducted among 423 doctors with OHP use experience. The proposed model underwent assessment through partial least squares structural equation modeling (PLS-SEM) to reveal the effects of technology-based job demands (i.e. technology-based work overload and technology-based work monitoring) and resources (i.e. perceived usefulness, facilitating conditions and IT mindfulness) on doctors’ OHP fatigue and continuance use intention.

Results suggest that technology-based work monitoring, perceived usefulness and facilitation conditions have significant impacts on doctors’ psychological and behavioral responses to using OHP, whereas technology-based work overload and IT mindfulness have a single impact on continuance use intention and fatigue of OHP.

It assists doctors, healthcare administrators, policymakers and technology developers in understanding OHPs’ technological characteristics, enabling them to harness its benefits and mitigate potential challenges. Additionally, given the self-reported cross-sectional data from China, future studies can improve generalizability and adopt experimental methods or longitudinal designs with objective data.

It extends the research on OHP by employing a technology-based JD-R model to explore work attributes and dual effects associated with OHP’s technological characteristics. It also enriches existing research by examining the role of OHP’s technological characteristics in doctors’ psychological and behavioral responses.

Carbon emissions trading is an effective instrument in reducing greenhouse gas emissions. There is a notable scarcity of comprehensive reviews on the modelling techniques within carbon trading research in construction.

This paper reviews 68 relevant articles published in 19 peer-reviewed journals using systematic search. Scientometric analysis and content analysis are undertaken.

Generally, China was the largest contributor to carbon trading research using quantitative models (representing 36% of the total articles). From the results, the modelling techniques identified were multi-objective grasshopper optimisation algorithm; system dynamics; interpretive structural modelling; multi-agent-based model; decision-support model; multi-objective chaotic sine cosine algorithm; optimised backpropagation neural network; sequential panel selection method; Granger causality test; and impulse response analysis. Moreover, the advantages and disadvantages of these techniques were identified. System dynamics was recommended as the most suitable modelling technique for carbon trading in construction.

This study is significant, and through this review paper, practitioners can easily be more familiar with the significant modelling techniques, and this will motivate them to better understand their uses.