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Social media allow for observing different aspects of human behaviour, in particular, those that can be evaluated from explicit user expressions. Based on a data set of posts with user opinions collected from social media, this paper aims to show an insight into how the readers of different news portals react to online content. The focus is on users’ emotions about the content, so the findings of the analysis provide a further understanding of how marketers should structure and deliver communication content such that it promotes positive engagement behaviour.

More than 5.5 million user comments to posted messages from 15 worldwide popular news portals were collected and analysed, where each post was evaluated based on a set of variables that represent either structural (e.g. embedded in intra- or inter-message structure) or behavioural (e.g. exhibiting a certain behavioural pattern that appeared in response to a posted message) component of expressions. The conclusions are based on a set of regression models and exploratory factor analysis.

The findings show and theorise the influence of social media content on emotional user engagement. This provides a more comprehensive understanding of the engagement attributed to social media content and, consequently, could be a better predictor of future behaviour.

This paper provides original data analysis of user comments and emotional reactions that appeared on social media news websites in 2018.

Due to the conflicts between left turn traffic and opposite straight-going traffic in urban traffic network, some of the traffic lanes cannot be used to discharge vehicles during its green phases and the intersection capacity can be greatly reduced. This study/paper aims to reduce the effect of conflicts and increase its capacity through the reasonable pre-signal phase time with the exchangeable lanes.

This paper took into consideration various influence factors to intersection capacity and formulated the capacity optimization model based on 0-1 mixed-integer programming model. This model is efficiently solved by standard branch-and-bound algorithms.

The authors took an intersection as an example and solved the optimal signal timing and entrance lane capacity via this model. Then, simulations were carried out to verify the effect of the exchangeable lanes strategy of this intersection through the simulation software VISSIM and take the traffic volume and delay as outputs, which indicated that this model has better performance.

The front-end control strategy can not only exploit the full potential of the intersection but also significantly improve the operational efficiency of the intersection. It plays a positive role in improving urban intersection congestion.

Aiming at the lack of explanatory power of traditional industrial organization theory in cross-border competition, by introducing the idea of ecological niche, the authors aim to explore the competitive situation of platform-based enterprises when they operate in multiple fields.

With the help of ecological niche theory, construct the niche width and niche overlap index of typical enterprises in the platform economy, and find out the advantages and the intensity of competition through comparative analysis.

In an environment of cross-border competition, large enterprises have significant competitive advantages, and the fierce competition is concentrated among medium-sized enterprises.

The conclusions of this paper not only provide new insights for explaining the phenomenon of cross-border competition in the platform economy, but also provide theoretical reference for the anti-trust enforcement practice in the platform economy.

The main purpose of this study is to examine the impact of agricultural internet information (AII) acquisition on climate-resilient variety adoption among rice farmers in the Jianghan Plain region of China. Additionally, it explores the influencing channels involved in this process.

Based on survey data for 877 rice farmers from 10 counties in the Jianghan Plain, China, this paper used an econometric approach to estimate the impact of AII acquisition on farmers’ adoption of climate-resilient varieties. A recursive bivariate Probit model was used to address endogeneity issues and obtain accurate estimates. Furthermore, three main influencing mechanisms were proposed and tested, which are broadening information channels, enhancing social interactions and improving agricultural skills.

The results show that acquiring AII can overall enhance the likelihood of farmers adopting climate-resilient varieties by 36.8%. The three influencing channels are empirically confirmed. Besides, educational attainment, income and peer effects can facilitate farmers’ acquisition of AII, while climate conditions and age significantly influence the adoption of climate-resilient varieties.

Practical recommendations are put forward to help farmers build climate resilience, including investing in rural internet infrastructures, enhancing farmers’ digital literacy and promoting the dissemination of climate-resilient information through diverse internet platforms.

Strengthening climate resilience is essential for sustaining the livelihoods of farmers and ensuring national food security; however, the role of internet information has received limited attention. To the best of the authors’ knowledge, this study is the first to examine the casual relationship between internet information and climate resilience, which fills the research gap.

The purpose of this paper is to study how to effectively allocate water, energy and food (WEF) resources in urban development.

An agent-based model combined with NetLogo simulation model has been used in this paper.

This paper proposes a framework for agent analysis in urban WEF consumption.

Further discussions using empirical data are of great importance.

Apply to form the development model of the city in the future.

A new method of WEF management has been used at the city level.

Most of current studies have explored the impact of entrepreneurial culture on entrepreneurial intentions in specific region rather than cross-cultural regions; in addition, these studies have looked more at entrepreneurial role models as part of the environmental factors that influence individuals’ entrepreneurial intentions (Lafuente et al., 2007), rather than viewing environmental factors as independent variables. Furthermore, less research exists to hypothesize and validate the mechanism of this process, even if some studies have already shown the similar ideas. To fill the aforementioned research gap in this area, based on new institutional theory and social cognitive career theory, this paper aims to explore the influence of entrepreneurial role models on entrepreneurial intentions in different cultural contexts by introducing two independent national-level factors, collectivism and media publicity, and subsequently examines the mediating role of self-efficacy.

Two major international databases, Adult Population Survey Global Entrepreneurship Monitor (APS GEM) 2017 and Global Leadership and Organizational Behavior Effectiveness (GLOBE), were used as data sources for this paper. In total, the authors obtained data from 174,128 respondents in the APS GEM 2017 database. Because there is a national-level variable, collectivism, which was collected by the GLOBE, the authors excluded 50,046 participants because their countries did not score collectivism in this database. After screening, 124,082 valid observations from 35 countries were obtained. In this study, hierarchical linear modeling (HLM) was used as the method and HLM 6.08 was adopted for data analysis. According to the purpose of the study, the following four different models will be tested in turn using the HLM, which include the null model, random coefficients regression model, intercepts as outcomes model and slopes as outcomes model.

Some previous studies have shown that entrepreneurial role models have a positive impact on individuals' entrepreneurial intentions, however, the exploration of this effect and its mechanisms in different cultural contexts is lacking (Abbasianchavari and Moritz, 2021). In response, based on a cross-level and cross-national survey, this paper advances the original literature by introducing two cultural dimensions, collectivism and media publicity. The current results suggest that the positive influence of entrepreneurial role models on individuals’ entrepreneurial intentions is somewhat generalized and that self-efficacy plays a mediating role. Moreover, collectivism and media publicity can negatively and positively moderate the effects of entrepreneurial role models on self-efficacy and entrepreneurial intentions, respectively. The findings provide some theoretical support for the role of cultural context in the formation of entrepreneurial intentions, which can help countries with diverse cultures to develop differentiated entrepreneurial role model advocacy strategies to better facilitate the emergence of potential entrepreneurs and advance their subsequent entrepreneurial activities.

First, because this study assumes that entrepreneurial role models are templates that can inspire potential entrepreneurs and provide them with entrepreneurial approaches (Laviolette et al., 2012), which has a certain positive bias, it may mean that the findings of this paper are not applicable to all scenarios, as role models are usually classified by scholars into positive and negative ones. The effect of different types of role models on entrepreneurial intention in a cross-cultural context will be considered as one of the future research directions. Second, in the measurement of country-level variables, this paper assumes that the degree of media publicity and collectivism are homogeneous within a country and does not take into account the differences in these two variables across regions within the same country. Future research is expected to use more granular designs to explore, for example, the effect of entrepreneurial role models on entrepreneurial intentions based on regional differences in media publicity and collectivism, rather than national differences. Third, due to the cross-sectional research design used in this paper, the dynamic influence of entrepreneurial role models in the entrepreneurial process was not included in the analysis. In addition, the focus of this study is only on entrepreneurial intention, which is separated from the subsequent entrepreneurial behavior of entrepreneurs. Therefore, the longitudinal study design that explores the dynamic influence of role models in entrepreneurial process should receive more attention.

First, enhancing the exposure of entrepreneurial role models is necessary because the authors found that entrepreneurial role models can positively promote entrepreneurial intentions, whereas self-efficacy plays a mediating role. For example, it is advised for the society to publish entrepreneurs' autobiographies, open entrepreneurial forums, create entrepreneurial interview columns, etc. In these books and activities, detailed descriptions of successful entrepreneurs' methods and skills are highly needed, as these can help potential entrepreneurs to better understand the entrepreneurial process, thus improving their self-efficacy and facilitating their entrepreneurial activities (Zhao et al., 2005). It is necessary to note here that matching the characteristics of entrepreneurial role models and potential entrepreneurs cannot be ignored, as similar characteristics could facilitate the desire of potential entrepreneurs to become more like entrepreneurial role models (Hoffner and Buchanan, 2005).These similar characteristics encompass both demographic characteristics, such as gender, race and age (Garcia, 2017; Harwood, 1999; Jose, 1989), and personal characteristics, such as goal embodiment and educational background (Bosma et al., 2012; Morgenroth et al., 2015). Moreover, the authors believe that the media's promotion of entrepreneurial role models and entrepreneurial activities needs to be enhanced, for example, by incorporating entrepreneurship education in television programs, allowing youth to meet face-to-face with successful entrepreneurs, and developing entrepreneurship lectures or interview programs.

At the same time, role models should be presented differently in diverse cultural contexts. For example, in countries with a strong collectivist orientation, the media should include collectivist messages when promoting entrepreneurial role models, such as his cooperation with the government, family and friends, which is in line with collectivist values, so that potential entrepreneurs in a collectivist context may perceive more similarity to role models and thus increase their entrepreneurial intentions (Morris et al., 1994); On the contrary, in countries with low collectivist tendencies, the media can appropriately carry an element of individualism when promoting entrepreneurial role models, for example, by telling how entrepreneurs succeed on their own strength and superior abilities, which is in accordance with the values of individualism. Based on the same logic, potential entrepreneurs in the context of individualism may thus generate more entrepreneurial intentions (Morris et al., 1994).

First, building on previous studies that explored the relationship between entrepreneurial role models and individuals’ entrepreneurial intentions (Stupacher et al., 2017), the authors further validated the moderating role of two national-level situational factors, collectivism and media advocacy, in this process, which echoes Abbasianchavari and Moritz (2021) that exploring the effects of entrepreneurial role models on entrepreneurial intentions in different cultural context is an essential topic for the future research. Second, the authors demonstrated that self-efficacy can mediate the relationship between entrepreneurial role models and entrepreneurial intentions and that this finding is generalizable. This responds to the hypothesis presented by Morgenroth et al. (2015) that role models, who are served as behavioral templates, can facilitate the generation of goals and behavioral intentions by increasing role aspirates’ self-efficacy, as it enhances their perceived accessibility to goals. Another contribution is that the authors found a possible explanation that the interaction of collectivism and media publicity with entrepreneurial role models may influence individuals' entrepreneurial intentions by affecting their self-efficacy, which unifies the new institutional theory and social cognition career theory.

This research aims to provide a comprehensive understanding of the evolution and trends in psychological capital (PsyCap) research and related issues.

This research uses bibliometric analysis. A total of 2,244 journal articles were extracted from the Scopus database using relevant keywords, covering the period from 1997 to 2023. The data analysis was conducted utilizing VOSviewer software, Microsoft Excel, and an online text analysis tool.

There is a rapid rise in the quantity of PsyCap publications, especially from 2017, with significant contribution of research from Chinese scholars with 577 articles in the period 2019–2023. The antecedents of PsyCap have a stagnation of leadership-related topics and increased focus on social support and perceived organizational support. The attention has been specifically directed toward well-being and mental health, with special emphasis on work engagement, job satisfaction, and job performance.

The exclusion of certain publications in this research may overlook emerging trends. Thus, future research endeavors should adopt a multifaceted approach that combines bibliometric analysis with qualitative and quantitative methods to glean comprehensive insights into PsyCap research.

PsyCap research is growing rapidly, with more publications in the last three years than in all the previous years combined. This study, updating data until the end of 2023, provides the most up-to-date insights on research trends in PsyCap to aid scholars in discerning suitable avenues for their research endeavors.

The purpose of this paper is to investigate the impacts of investor attention on stock market activity.

The authors employed the Google Search Volume (GSV) Index, a direct and non-traditional proxy for investor attention.

The results indicate a strong correlation between GSV and trading volume – a traditional measure of attention – proving the new measure’s reliability. In addition, market-wide attention increases both stock illiquidity and volatility, whereas company-level attention shows mixed results, driving illiquidity and volatility in both directions.

To the best of the authors’ knowledge, Nguyen and Pham’s (2018) study has been the only previous study identifying investor attention in Vietnam by using GSV as a proxy and examining the impacts of broad search terms about the macroeconomy on the stock market as a whole – on stock indices’ movements. The paper will contribute to this by quantifying GSV impacts on each stock individually.

Stock price prediction is a hot topic and traditional prediction methods are usually based on statistical and econometric models. However, these models are difficult to deal with nonstationary time series data. With the rapid development of the internet and the increasing popularity of social media, online news and comments often reflect investors’ emotions and attitudes toward stocks, which contains a lot of important information for predicting stock price. This paper aims to develop a stock price prediction method by taking full advantage of social media data.

This study proposes a new prediction method based on deep learning technology, which integrates traditional stock financial index variables and social media text features as inputs of the prediction model. This study uses Doc2Vec to build long text feature vectors from social media and then reduce the dimensions of the text feature vectors by stacked auto-encoder to balance the dimensions between text feature variables and stock financial index variables. Meanwhile, based on wavelet transform, the time series data of stock price is decomposed to eliminate the random noise caused by stock market fluctuation. Finally, this study uses long short-term memory model to predict the stock price.

The experiment results show that the method performs better than all three benchmark models in all kinds of evaluation indicators and can effectively predict stock price.

In this paper, this study proposes a new stock price prediction model that incorporates traditional financial features and social media text features which are derived from social media based on deep learning technology.

Mobile location-based service (m-LBS) seems like a new class of personalized service due to location positioning technologies. This work aims to investigate consumer readiness (RED) toward m-LBS based on integrating pull effect- and push effect-related factors into the technology acceptance model (TAM).

An online survey collected data from 423 participants, and the research framework was analyzed using structural equation modeling (SEM).

The results divulge that consumer RED is determined by TAM antecedents, including usefulness (USE) and ease of use (EOU). EOU motivates USE in m-LBS. Regarding pull effect-related factors, absorptive capacity (ABC) is the strongest positive factor influencing consumer RED to use m-LBS, followed by technology willingness (TWI) and innovativeness (INN). Moreover, INN, trust (TRU) and perceived risk (RIS) significantly influence USE and EOU.

This work endeavors to explicate customer RED toward m-LBS by incorporating some meaningful pull effect-related dimensions (i.e. ABC, TWI and INN) and pushing effect-related dimensions (i.e. RIS) into crucial antecedents rooted in TAM. Thus, the findings assist practitioners in developing marketing strategies by boosting pull effects and controlling push effects on customer engagement in m-LBS.