Empirical research on the evolution trend of heat and sentiment for emergencies

Applying the model of evolutionary theory based on bound rationality, this paper indicates the strategy adjusting and evolutionary trend in Industry-University cooperation through analyzing the firms' mode choice and universities' supply preference of technology type. Some revelatory conclusions are obtained.

What do evolutionary psychologists study, which are their most highly cited articles, and which variables predict high citation counts? These are important questions for any emerging science. To help answer these questions, we present new empirical research on publication trends in evolutionary psychology's flagship journal, Evolution and Human Behavior (and its predecessor, Ethology and Sociobiology), from its inception in 1979 to 2008. First, analyses of 8,631 title words published in these journals between 1979 and 2008 (808 articles) show an increasing interest in researching sex, sex differences, faces, and attractiveness. For example, during the Ethology and Sociobiology era (1979–1996), the most frequent title words were “evolutionary,” “human,” “behavior,” “reproductive,” “evolution,” “selection,” and “altruism,” whereas during the Evolution and Human Behavior era (1997–2008), they were “sex,” “attractiveness,” “differences,” “sexual,” “human,” “male,” and “facial.” Second, we reveal the 20 most-cited articles in these journals, which show the importance of research teams. Third, citation analyses for these journals between 1979 and 2002 (562 articles) suggest articles that cite more references are in turn cited more themselves ( r = .44, R2 = .19). Lastly, we summarize recent research that suggests evolutionary psychology is not only surviving, but also thriving, as a new interdisciplinary science.

By quantitatively describing and analyzing the changing laws of opinions in knowledge collaboration, in order to design more scientific and reasonable knowledge collaboration rules. Considering the differences of individuals and the complexity of collaboration, the uncertainty of individual opinion selection is difficult to represent by a completely deterministic function or set of functions. The individual opinion selection probabilities are considered as a time series, and a suitable ARIMA model is built to fit and short-term expectation of individual opinion selection probabilities. By organizing an experiment to simulate the knowledge collaboration process, an eye tracker is introduced to collect information on individual eye movements in order to obtain real-time changes in the opinions held by individuals, and twelve sets of individual opinion selection probability sequences were obtained and modeled separately. The empirical results show that the ARIMA model can well simulate and predict the evolutionary trend of individual opinions. This method can effectively overcome the difficulties that the influencing factors of individual opinion changes are difficult to fully grasp and data are not easily obtained in the process of knowledge collaboration.

Predicting the number of coauthors for researchers: A learning model

Publication productivity affects nearly every aspect of researchers’ scientific career, whereas it is difficult to be predicted due to diversity in researchers’ productivity patterns. This study proposed a model for the publication dynamics of researchers. The model is based on Lotka’s law as well as the relationship between the annual number of publications and time given a historical number of publications. The law and the statistical significance of the relationship are validated by applying them to the high-quality dblp data set. The model allows to predict the number of publications for research groups, and its effectiveness is tested on the data set by fine fittings on the distribution of the number of publications for researchers, the evolutionary trend of their publication productivity, and the probability of producing publications. Due to its nature of regression, the model has the potential to be extended to assess the confidence level of the prediction results and thus would be useful for other empirical research.

Regional ecological efficiency and future sustainable development of marine ranch in China: An empirical research using DEA and system dynamics

Market characteristics of new energy supply in China

This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years were analyzed using the bibliometric package. The results indicate an increase in the volume of publications following the 2008 financial crisis, focusing on analyzing the factors influencing bank profitability and economic growth. The Journal of Banking and Finance is the preeminent publication in this field. The literature reviewed shows that bank profitability depends on internal factors (size, credit risk, liquidity, efficiency, and management) and external factors (such as GDP, inflation, interest rates, and unemployment). In addition to the traditional determinants, the recent literature highlights the importance of innovation and technological factors such as digitalization, mobile banking, and electronic payments as relevant to bank profitability. ESG (environmental, social, and governance) and governance indicators, which are still emerging but have been extensively researched in companies, indicate a need for evidence in this area. This paper also provides relevant insights for the formulation of monetary policy and the strategic formulation of banks, helping managers and owners to improve bank performance. It also provides directions for future empirical studies and research collaborations in this field.

Evolution characteristics, drivers and trends of rural residential land in mountainous economic circle: A case study of Chengdu-Chongqing area, China

This article takes social network services as the research object and mainly conducts two aspects of research: first, based on previous research, combining the behavior characteristics of users in the social network environment related to digital information privacy, the digital information privacy of users pays attention to the influential factors of users’ digital information privacy information disclosure behavior, summarize and refine them, establish theoretical research models, and then use structural equation modelling to empirically analyze the significance of each influence path; then, based on the first part of the empirical research, the evolutionary game theory was used to analyze the interests of digital information privacy between social network users and service providers. This paper also studies the evolution of the willingness of each parameter to provide digital information to users under variable expected return conditions and uses MATLAB to analyze its evolutionary trends. It is found that the regulatory intensity coefficient, information leakage loss, and information sensitivity are both for users and websites. It has an important impact, and the loss of information leakage and information sensitivity can affect the evolution direction of users’ willingness to provide digital information and change the speed of website evolution, and the regulatory intensity coefficient is the opposite.

Based on the urban resident population statistics from 2005 to 2018, this paper analyzes the distribution and evolution of city scale in China by screening city samples according to the threshold criteria and using empirical research methods such as the City Primacy Index, the Rank-Scale Rule, the Gini coefficient of city scale, Kernel Density Estimation and Markov transfer matrix. The results show that: the most populous city in China has obvious advantages. The population distribution is concentrated in high order cities and in accordance with the law of order-scale; the economic scale of cities is in a concentrated state, the gap between the economic development levels of different types of cities is large, and the megacities are more attractive, which to a certain extent limit the development of the scale of the rest of the cities; the number of China’s city population is increasing, however, the gap between the population scale of other cities and the most populous city continues to be large, and the structure of city population scale is not reasonable enough; megacities and megalopolises keep their original scale levels unchanged to a large extent, and the scale transition between the two types of cities is rather difficult. Finally, based on the explanatory framework of the dynamics of city scale evolution, policy recommendations are proposed to promote a more balanced distribution of city scale.

Innovation of new generation entrepreneurs is crucial to the development of a country. Empirical research method can analyze the history and current situation, but it is difficult to reflect the dynamic process and evolution trend under different scenarios. In this paper, we adopt computational experiment method to model the decision-making process of new generation entrepreneurs. Multi-agent evolution model is constructed to simulate individual behavior of different types of new generation entrepreneurs under different scenarios. By the comparison of different results, it analyses the evolutionary rules of innovation behaviors and explores guidance policies to promote entrepreneurs’ innovation behavior and achieve better innovation performance. The experimental results show that although internal elements such as individual’s innovative spirit, innovative ability and cognition of social capital determine the innovation intention, the capital, technology and talent conditions are also very important for innovation implementation. New generation entrepreneurs with different risk preferences should objectively evaluate and treat innovation risks according to their own characteristics. This helps to reduce the negative impact of innovation risk on continuous innovation. Meanwhile, government should pay attention to establishing risk guarantee mechanism such as innovation insurance fund to promote the innovation of new generation entrepreneurs.

A synergistic study of policy and literature on rumor governance

Neuromarketing (NM) uses neuroscience tools, for example, but not limited to functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) to study, explore, analyze, and explain the neural correlates of consumer’s behavior (i.e., decision-making processes), the cognitive processes (i.e., attention and memory) and emotional processes (i.e., emotion) of interest for marketing research (e.g., advertising, brand, product, price). In the last decades, NM studies appear more often because the researchers are looking for understanding the mechanisms of decision-making in the consumer's brain toward marketing stimuli. This document aims to conduct a systematic review in order to identify evolution and research trends in the area of NM. Besides, on the basis of collating and reviewing the relevant literatures on ERP empirical research in the past 20 years, this paper sorts out and summarizes the neural mechanism of consumer purchase decision and the commonly used ERP components, providing a reference for corresponding brain activity areas for marketing scholars to study consumer purchase decision applying ERP neural technology, which helps marketing scholars better use ERP technology to guide and develop existing marketing management theories and practices. It became evident that NM is still an immature and incipient area with a low degree of theoretical consensus. Additionally, we established corresponding analysis between NM perspective and traditional marketing perspectives.

PurposeThis paper reviews the evolution, current state and ongoing trends of the empirical literature on employee-owned firms (EOFs).Design/methodology/approachUsing a structured literature review methodology, I analyze 280 empirical publications on EOFs published in English peer-reviewed academic journals over the 1970–2019 period.FindingsTwo generations (before and after 2001) of the EOF empirical literature are identified and characterized in terms of authors, journals, topics, methods, targets, relations to theoretical modeling and countries studied. Two research trends are structuring the current generation: one investigating diverse research questions engaging EOFs as emblematic forms of social economy, and the other comparing EOFs to conventional firms to offer insights mainly into the seminal question of the EOF relative rarity.Research limitations/implicationsThe sample studied does not take into account articles written in languages other than English and does not include books.Originality/valueThis article displays the first structured literature review of the EOF empirical literature.