Search results

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

In international business (IB), the discussion of COVID-19-related global value chain (GVC) models driving resilience has taken momentum since May 2020. The purpose of this study is to uncover insights that the pandemic provided as a unique research opportunity, holistically, revealing the significant role of non-lead firms in GVC outcomes and resilience. This allows to extend theory as the authors critically identify impact criteria and assess interdependence and valence, thus progressing the traditional (pre-pandemic) IB view of GVC governance and orchestration.

This study opts for an integrative review to help create a much-needed extension of IB theory by means of a critical perspective on GVC theory. The authors examine the extant body of IB literature as the relevant stock of collective IB knowledge prompted by the COVID-19 pandemic, uncovering contributions – with a focus on the role of non-lead firms in orchestration and resilience – that allows to clarify what was not evident pre-pandemic. With this, the authors move the theory from its efficiency focus to a better recognition of the interdependencies of power and profit outcomes stemming from asymmetries of interrelationships. By design, the authors focus on the unique research period of the pandemic and orchestration complexities along the development of configurational arguments beyond simple correlations (Fiss, 2011), revealing key dependencies as key themes. The authors highlight further research avenues following Snyder (2019) that are called upon to strengthen that understanding and that helps extend theory.

This research provides a critical perspective on the application of the traditional IB views for GVC governance (designed for efficiency, cost and proximity to markets with pre-dominance for just in time), which has shifted during the pandemic to accommodate for adaptation and adjustment to resilience and just in case considerations. The holistic review reveals not only the key country- and multinational enterprise (MNE)-dependencies with residual impact determining the balance between just-in-time and just-in-case. Also, the authors advance the understanding of the (un)balance of the traditional GVC – focused on just-in-case rather than just-in-time through a lead and non-lead GVC participation and power lens yet rarely observed. The authors find that governance should not be construed as “management” such that it resolves into decisions undertaken in lead firms for execution in subordinate GVC participants. Autonomy allows to subsidiary units by MNE lead firms and/or exercised by (mainly, innovative) non-subsidiary GVC participant firms, is uncovered as a key driver in this. Greater delegation capacity appears to help provide resilience to loss in profit, with a recognition that there may be a dynamic trade-off between power and profit. In addition, the authors are able to identify correlations with innovation, demand elasticity, digital uptake, investment and other, that the authors trust will set the scene for additional research deepening and extending the findings.

Integrative literature reviews include a problem formulation (i.e. that is limited to published topics around an emerging theme) and are hence very focused in nature and approach. This applies to this paper. Data analysis in this method is not typically using statistical methods in contrast to meta-analyses. Also, the authors limit the sample to a relatively short time period with 33 publications analysed, purposefully focusing on the most prompt and “acute” insights into GVCs during the pandemic.

The traditional GVC governance model is designed for efficiency, cost and proximity to markets with pre-dominance for just in time. The authors reveal dependencies that are instrumental to better understand lead and non-lead interaction and relative autonomy, with a focus on residual impact determining the balance between just-in-time and just-in-case that, if in the sought equilibrium and agile, can allow alignment with context and this resilience. This paper specifically provides practical insights and visualization that highlights stages/“ripple” effects and their impact and the questions to ask as stakeholders look for GVC resilience. This includes, int.al., firms and their role as strategic agents, prompting participants through the learnings from exogenous shock to realign their strategies, redistributed manufacturing of production across subsidiary and non-subsidiary non-lead firms, greater competition and hence power for suppliers leveraging resilience and innovation, greater understanding of localization and regionalization of production of essential supplies, interaction with governments, and of investment impacts abroad especially to secure GVC participation.

The insights provided through this extension of theory with its literature review reveal the importance of aligning IB research into GVCs to factors that became visible through alternative or unusual settings, as they have the power to reveal the limitations of traditional views. In this case, a mainly efficiency-led, just-in-time focused GVC governance model is reviewed through the literature that emanated during the pandemic, with a critical perspective, which helped uncover and underline the complexities and evolution of GVC governance, providing fundamental support to solutioning the continuing global supply chain challenges that started as a result of the pandemic and are yet again accelerated by the Ukraine and Middle Eastern wars and its impact with, int.al., concerns over possible severe global food, labour/migration and resources crises. IB holds a social responsibility to help identify critical challenges from the disciplinary perspective and help advance resilience for social benefit.

This paper supports the original IB theory development by extending GVC theory into the lead – non-lead dynamics that may, under certain conditions, provide a “Resilience wall” for GVCs. The value created through insights stemming from a unique period of time for GVC is significant. It allows us thus also to pave the way to an emerging and critical research adaption looking into equilibrium, nuancing demand elasticity, better understanding trade and investment impacts along GVCs and more. By examining views on the sources of pandemic risks in a possibly unique setting, the authors offer added value from extant IB research insights by combining them, revealing the importance for GVCs to investigate not only key dependencies between the exogenous shock, i.e. context, and the impacts assessed through this literature but to further use their inherent value to create a framework for further conceptualization and extension of the traditional IB view on GVC governance. This work illustrates the urgency and importance for IB to take a timely and possibly more critical approach to the investigation of governance models that have, to date, shown some significant limitations.

The main objective of this work is to design a statistical multiple regression model that helps to empirically explain the impact of economic incentives, management style, emotional health and research activities on university professors in northern Mexico and their perception of happiness.

In this research, the authors analysed the correlation between happiness perception and four independent variables divided into two dimensions: 1. individual dimensions: emotional health and research activities and 2. organisational dimensions: economic incentives and management styles. A questionnaire was developed, tested and analysed for this matter. The authors applied this instrument to 384 university professors of both genders among 1301 in the region.

Using correlational analysis, the authors confirm a strong and statically significant relationship between all variables. It is also no evidence of multicollinearity. Finally, by applying multiple regression analysis, it was accepted that all independent variables have significance in explaining the emergence of personal happiness (R2 = 42%). Finally, the predictive equation presents possible results with values that confirm the effectiveness of the theoretical model. Results indicate that happiness perception is related to independent variables, with economic incentives being the most vital relationship.

This study's limitations are that the novel perspective of the explanatory variables of economic incentives, emotional health, management style and research activities needs additional confirmatory studies. Therefore, the authors need to perform studies with new explanatory perspectives. Another limitation of the study may be considering a cross-sectional and not a longitudinal model. This study considered it more appropriate to analyse the explanatory variables that influence and are the outcome of happiness perception for the data collected. Finally, it is essential to highlight that this research has been conducted in an underdeveloped country. Thus, it should consider conducting subsequent confirmatory studies in similar settings and other types of economies, such as in a developed country.

This paper explains the relevance of two-dimensional activities in the happiness perception of professors. As other studies mention, productivity is correlated to happiness, and production outcomes could be improved if the schools implement policies to promote this perception. Happiness could be a solid strategy to improve academic outcomes, and the results propose several actions to achieve this goal.

This paper addresses an important activity of professors from a perspective of happiness perception. Thus, putting the professor as the leading relevant agent in schools, the authors propose a multivariate analysis of the outcomes of professors' jobs. Both the schools and the professors have their own goals at their own levels. If policies are created based on persons, in this case, professors, to improve organizational goals, then it might profoundly impact social actions inside the schools.

This paper increases the literature on happiness perception studies and proposes the examination of the relationship between perceived personal happiness and dimensions that influence this perception; these are from two kinds: 1. individual dimensions: emotional health and research activities and 2. organisational dimensions: economic incentives and management styles, which is an original approach and open discussion to further new approaches to this study.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

This study aims to examine the association between parental financial socialization and life satisfaction and the mediating roles of desirable financial behavior in the association between parental financial socialization and life satisfaction of college students in India. Furthermore, this research also explores the moderating effects of parents’ socioeconomic characteristics (education, income and professions) in the association between parental financial socialization and desirable financial behavior.

A sample of 1,161 college students was collected in India. Parental financial socialization is measured by direct parental teaching in this study. The first stage moderated mediation model is performed to examine the direct and indirect effects through financial behavior of parental financial on life satisfaction as well as the moderating role of parents’ socioeconomic characteristics.

The mediation analysis shows that parental direct teaching is positively associated with young adults’ financial behavior, which in turn contributes to their life satisfaction. Furthermore, this study also finds negative moderation effects of parental education on the association between parental direct teaching and children's financial behavior.

This study extends the knowledge of family financial socialization in the context of India. Moreover, it examines the mediation roles of desirable financial behavior in the association between parental direct teaching and children’s life satisfaction. Furthermore, this paper explores the potential influence of parents’ education, income and professions on children’s financial behavior and life satisfaction.

Taking attribution theory as an overarching framework, the study aims to examine how employees attribute and respond to a colleague's approach crafting.

Two complementary studies, including a scenario experiment (Study 1; N = 114) and an online survey (Study 2; N = 220), were conducted to test the hypothesized model.

Study 1 found support for the attribution of a prosocial motive to approach crafting, which in turn led to more social support and less social undermining among observers. This mediation was stronger when the job crafter was perceived as less other-oriented. Study 2 replicated the findings of Study 1 and further showed that when observers attributed both high impression management and prosocial motives to approach crafting, the positive relationship between their prosocial motive attribution and social support for the job crafter got weakened, while the negative relationship between their prosocial motive attribution and social undermining of the job crafter was strengthened.

The findings demonstrate that approach crafting gives rise to specific attributions and reactions toward the job crafter, which enrich the understanding of the social consequences of job crafting in the workplace.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

This study aims to discuss the main points in the dimensions of the quality of the electronic services to be considered in the future to adapt to future transactions and how to benefit from them.

This study relies on the developments and to cope with them so that the banks and customers shift from dealing in the traditional way to the electronic method, which has become a cause of the gap in understanding customers for electronic banking use of the descriptive-analytical approach. A questionnaire was used as a source for collecting data and information about the study variables. It was distributed to three Jordanian banks, and the number of participants was 170. This study uses two primary sources for collecting data and information: secondary sources that relate to the theoretical aspect and preliminary sources related to the analytical aspect of the study subject.

The results showed that the impact of e-banking quality dimensions of the study (ease of use, time, confidentiality and security) was high, which required the bank to maintain its high levels and monitor them from time to time.

The value of this study comes from the following points: the relationship between the quality of electronic banking services and customer satisfaction; this study is one of the few field attempts in Jordan to assess the impact of the quality of electronic banking services on the satisfaction of customers in banks; this study provides new scientific results on the impact of the quality of electronic banking services on the satisfaction of customers in the Jordanian banks.

The purpose of this paper is to simulate the tension process of tension-type anchor cable and to explore the mechanical characteristics and tension-torsion coupling effect of anchor cable subjected to tension.

ABAQUS numerical software is applied to construct the numerical models of tension-type anchor cables with different diameters. Through explicit contact, the characteristics of contact between grouting body-anchor cable and grouting body-rock mass are determined. Confining pressure is applied to the model through surface pressure, and drawing force is applied to the model by displacement loading so as to simulate the tension process of the anchor cable.

The results show that the stress is transmitted in both axial and radial directions in the anchorage section and distributed in a cone. The shear stress in the grouting body is unevenly distributed, and its peak value increases with the rise in confining pressure and anchor cable diameter. The stress characteristics of torque and axial force are basically consistent and evenly distributed in the free section; they gradually decrease in the anchorage section. Due to the tension-torsion coupling effect, the internal stress characteristics of the anchor cable structure vary. On average, the anchorage performance of each anchor cable model is improved by 6.19%.

The proposed method of numerical modelling is effective in addressing the interface contact between the anchor cable and the grouting body and in solving the problem with convergence of calculation. Compared with the indoor test, this method is more suited to collecting the internal mechanical data of the anchor body.

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.