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This paper aims to identify the factors that are constraining technological innovation to support the development of coalbed methane in China.

The analysis applies ideas relating to national and sector systems of innovation to explain why China’s strategies to support research and technological innovation have failed to stimulate the desired progress in coalbed methane production. It also provides a counter-example of the USA that implemented a number of measures in the 1970s that proved very effective.

The deficiencies of China’s research and development strategies in support of coalbed methane development reflect the national and sectoral systems of innovation. They are exacerbated by the structure of the national oil and gas industry. Key constraints include the excessively top-down management of the national R&D agenda, insufficient support for basic research, limited collaboration networks between companies, research institutes and universities and weak mechanisms for diffusion of knowledge. The success of the USA was based on entirely different systems for innovation and in quite a different industrial setting.

The originality of this analysis lies in placing the challenges facing research and innovation for China’s coalbed methane development in the context of the national and sectoral systems for innovation and comparing with the approach and success of the USA.

The aim of this paper is to analyze the interrelationship between film-induced tourism and visits to theme parks by tourists and examine the most viewed movies worldwide (2010–2022) which are related with theme parks and their attractions.

The methodology used in this study is a set of qualitative and quantitative indicators for measuring the most visited theme parks worldwide and the most viewed movies that have allowed to answer the research questions.

This research provides a new contribution to tourism and entertainment industries. Results have shown that film-induced tourism can be the perfect marketing tool to attract more tourists to theme parks through movies and their real or fictional characters represented in films such as Marvel, Minions, Avatar, Harry Potter and Disney, amongst many others. These famous characters are part of theme park’s rides to attract tourists to visit film theme parks These rides allow users to travel in a fantasy experience and interact with film characters of cartoons or fictions. There is a high correlation between film-induced tourism and theme parks’ attractions. Film-induced tourism provides great benefits to the society, theme parks, cinemas and tourist destinations. Indeed, movies help to increase the number of visitors to theme parks. In 2019, 215 million people visited the top 20 theme parks worldwide analyzed in this study, this figure is quite lucrative to entertainment and tourism sectors, local and regional economies where these theme parks are localized.

This study presents the importance of theme parks at tourist destinations because theme parks are an extension of movies, thus is, the end of the physical perfect experience at theme parks which began in a movie seat or on your TV/videogame/PC screens.

本文的主要目的是分析电影引起的旅游和游客参观主题公园之间的相互关系, 并研究与主题公园及其景点有关的全球最受欢迎的电影（2010-2022年）。

本研究使用的方法是一套定性和定量的指标来衡量全球访问量最大的主题公园和观看次数最多的电影, 使我们能够回答本研究中提出的问题。

这项研究为旅游和娱乐业提供了新的贡献, 结果表明, 电影引起的旅游可以成为完美的营销工具, 通过电影及其影片吸引更多的游客到主题公园。通过电影和他们在电影中所代表的真实或虚构的人物, 如漫威、小人、阿凡达、哈利波特、迪斯尼等, 主题公园。这些著名人物是主题公园景点的一部分, 以吸引游客参观与电影有关的景点。这些景点让游客有一个幻想的体验, 并与卡通人物互动。电影引起的旅游和主题公园景点之间存在着高度的相关性。我们必须认识到, 电影引发的旅游为社会、主题公园、电影院和旅游目的地提供了巨大的利益。事实上, 电影有助于增加主题公园的游客数量。2019年, 有2.15亿人参观了本研究中分析的世界前20大主题公园, 这个数字对于娱乐和旅游部门、这些主题公园所在的地方和区域经济来说是相当有利可图的。

本研究揭示了主题公园在旅游目的地的重要性, 因为这些旅游景点是电影的延伸, 也就是说, 主题公园及其基于电影和动画的景点是游客在主题公园生活体验的最后一部分, 而这种体验是从电影院的座位上、电视、视频游戏或电脑屏幕前开始的。

El principal desafío de este artículo es analizar la interrelación entre el turismo inducido por las películas y las visitas a los parques temáticos por parte de los visitantes, y examinar las películas más vistas en todo el mundo (2010-2022) relacionadas con los parques temáticos y sus atracciones.

La metodología utilizada en este estudio es un conjunto de indicadores cualitativos y cuantitativos para medir los parques temáticos más visitados a nivel mundial y las películas más vistas que nos han permitido responder a las preguntas planteadas en esta investigación.

Esta investigación proporciona una nueva contribución a las industrias del turismo y el entretenimiento. Los resultados han demostrado que el turismo inducido por el cine puede ser la herramienta de marketing perfecta para atraer más visitantes a los parques temáticos a través de películas y sus personajes reales o ficticios representados en películas como Marvel, Minions, Avatar, Harry Potter, Disney, entre muchos otros. Estos personajes famosos son parte de las atracciones de los parques temáticos para atraer a los visitantes a visitar las atracciones relacionadas con las películas. Estas atracciones permiten a los visitantes tener una experiencia de fantasía e interactuar con personajes de películas de dibujos animados o ficción. Existe una alta correlación entre el turismo inducido por el cine y las atracciones de los parques temáticos. Debemos reconocer que el turismo inducido por el cine ofrece grandes beneficios a la sociedad, parques temáticos, cines y destinos turísticos. De hecho, las películas ayudan a aumentar el número de visitantes a los parques temáticos. En 2019, 215 millones de personas visitaron los 20 parques temáticos más importantes del mundo analizados en este estudio, esta cifra es bastante lucrativa para los sectores de entretenimiento y turismo, y la economía local y regional donde se encuentran estos parques temáticos.

Este estudio revela la importancia de los parques temáticos en los destinos turísticos, dado que estas atracciones turísticas son una extensión de las películas, es decir, los parques temáticos y sus atracciones basadas en películas y animaciones son la parte final de una experiencia vivida por los visitantes en dichos parques y que comenzó en un asiento de cine, frente a su TV, un videojuego, o pantalla de ordenador.

This study aims to investigate the response of green investments of emerging countries to own-market uncertainty, oil-market uncertainty and COVID-19 effect/geo-political risks (GPRs), using the tail risks of corresponding markets as measures of uncertainty.

This study employs Westerlund and Narayan (2015) (WN)-type distributed lag model that simultaneously accounts for persistence, endogeneity and conditional heteroscedasticity, within a single model framework. The tail risks are obtained using conditional standard deviation of the residuals from an asymmetric autoregressive moving average – ARMA(1,1) – generalized autoregressive conditional heteroscedasticity – GARCH(1,1) model framework with Gaussian innovation. For out-of-sample forecast evaluation, the study employs root mean square error (RMSE), and Clark and West (2007) (CW) test for pairwise comparison of nested models, under three forecast horizons; providing statistical justification for incorporating oil tail risks and COVID-19 effects or GPRs in the predictive model.

Green returns responds significantly to own-market uncertainty (mostly positively), oil-market uncertainty (mostly positively) as well as the COVID-19 effect (mostly negatively), with some evidence of hedging potential against uncertainties that are external to the green investments market. Also, incorporating external uncertainties improves the in-sample predictability and out-of-sample forecasts, and yields some economic gains.

This study contributes originally to the green market-uncertainty literature in four ways. First, it generates daily tail risks (a more realistic measure of uncertainty) for emerging countries’ green returns and global oil prices. Second, it employs WN-type distributed lag model that is well suited to account for conditional heteroscedasticity, endogeneity and persistence effects; which characterizes financial series. Third, it presents both in-sample predictability and out-of-sample forecast performances. Fourth, it provides the economic gains of incorporating own-market, oil-market and COVID-19 uncertainty.

The purposes of this paper are 1) to develop model of long term financial health for logistics companies in Thailand 2) to identify factors that determine long term financial stability. Many researchers currently provide factors affecting financial health. Most factors refer to financial ratios, not many non-financial ratios such as age and size have been mentioned. This paper considers both financial and non-financial ratios that affect financial performance of Logistics companies in Thailand. The study has covered some interesting non-financial ratios such as Nationality of Shareholders, type of network in Logistics Company, growth rate (consisted of sales growth rate/profit growth rate/asset growth rate / Liability growth rate) and variable of growth rates. The target group is 110 logistics companies in Thailand enlisted from Department of International Trade Promotion Ministry of Commerce, Royal Thai Government. The group is divided into three categories according to financial health of company; Healthy financial, Unhealthy (Distress) and normal situation. The Multidiscriminant Analysis (MDA) is applied to analyze the differentiations among the three categories. Significant variables from MDA will be used as the independent variables for Multimonial Logistic Regression Analysis (MLRA) to identify factors that determine long terms financial stability. This paper find CF/D, RE/TA, BE/TL, Size, Age, Type of network, Nationality of Shareholders and Number of Shareholders are significant factors determine long term financial stability of Logistics company in Thailand.

This study aims to analyze a backchannel account on news of the coronavirus at the beginning of the pandemic, with information not disseminated in official media due to the social alarm it might cause and the negative image of government management. Specifically, it examines acceptance and dissemination of this type of content in a period of lack of information, while reflecting on what would constitute proper management of this type of channel.

First, based on a literature review, this study classifies possible explanatory variables of online content dissemination into content richness and psychological content. Second, this study performs sentiment analysis of the Twitter backchannel account @COVID_19NEWS and use Qualitative Comparative Analysis to find causal configurations of variables that obtained a high rate of retweets.

The results reveal predominance of one combination of three factors in backchannel information diffusion: emotional, identifying and video content. Other interesting combinations of factors were shown to be attractive enough to contribute to success of the tweets.

Knowledge of the main configurations that attract information dissemination in backchannel accounts is useful for public management of a health crisis such as the Covid-19 outbreak. Rather than suppressing these channels, the authors discuss different solutions.

This study advances scholarship on backchannel communications in emergency situations, providing insights to understand and manage such channels.

Este estudio analiza una cuenta extraoficial sobre noticias del coronavirus al inicio de la pandemia, con información no difundida en los medios oficiales por su posible repercusión en la alarma social y la imagen negativa de la gestión gubernamental. Concretamente examina la aceptación y difusión de este contenido en un periodo de desinformación, así como reflexiona sobre la gestión de este tipo de canales.

En primer lugar, en base a la revisión de la literatura, clasificamos las variables explicativas según la riqueza de contenido y el contenido psicológico. En segundo lugar, sobre la cuenta extraoficial de @COVID_19NEWS en Twitter, realizamos análisis de sentimiento y utilizamos Análisis Comparativo Cualitativo (QCA) para encontrar configuraciones causales de variables que obtuvieron una alta tasa de retweets.

Los resultados revelan la importancia de una combinación de tres factores en la difusión de información del canal secundario: contenido emocional, identificativo y video. Otras combinaciones de factores también contribuyeron al éxito del tweet.

Estas configuraciones podrían ser útiles para la gestión pública ante una crisis sanitaria como la Covid-19, prestando atención a los factores cuya configuración atrae la difusión de información en las RRSS. En lugar de suprimir estos canales, se presentan soluciones para garantizar una colaboración eficaz.

Este estudio realiza una contribución académica a las comunicaciones extraoficiales en situaciones de emergencia, proporcionando información para comprender y gestionar este tipo de canales.

Covid-19, Coronavirus, Canal extraoficial, Twitter, Análisis cualitativo comparado

Trabajo de investigación

在新冠疫情初期, 由于可能引起社会恐慌和政府管理部门的负面形象, 官方媒体缺少相关的新闻报道。本文研究了在这种官方信息匮乏的危机时期, 非正式渠道（backchannel）对于新冠病毒内容的接受和传播情况, 本文同时反思了如何对这类非正式渠道进行正确的管理。

基于文献综述, 我们先将在线内容传播的可能解释变量分为内容丰富度和心理内容这两个方面。其次, 我们对推特上的非正式渠道账户@COVID_19NEWS发布的内容进行情感分析, 并使用定性比较分析法来寻找内容获得高转发率的原因。

结果显示, 对于非正式渠道信息的成功传播, 情绪化、具有辩认度和包含视频内容这三个要素的组合占主导地位。此外, 其他要素的组合也有来助于推文的成功传播和扩散。

了解非正式渠道吸引信息传播的主要原因, 将有利于应对健康危机（例如Covid-19爆发）和进行公共管理。文本讨论了不同的解决方案, 而不是简单地压制这些非正式渠道。

这项研究推进了危机背景下非正式渠道传播的学术研究, 为理解和管理这类非正式渠道提供了见解。

关键词 - Covid-19, 新冠病毒, 非正式渠道, 推特, 定性比较分析

This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based growth model drove China's high-speed economic growth between 2000 and 2007, which came into existence around 2000 when China plugged into the global production network.

This paper also finds that China slowed down to the New Normal because of the disruption to the socio-economic underpinnings of this growth model. As China adapts to and steers the New Normal, supply-side structural reforms can channel excess capacity to the construction of underground pipe networks in rural areas of central China and fix capital while advance rural revitalization.

At the same time, enterprises must strive to build a key component development platform for key component innovation and the standard-setting power in global manufacturing.

The establishment of a domestic production network integrating the integrated innovation-driven core enterprises and modular producers at different levels can satisfy the dynamic demand structure of China in which standardized demands and personalized demands coexist.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

The purpose of this study is to sort out the potential dark sides of shared leadership so as to promote a more comprehensive and balanced views of the impact of shared leadership and provide directions for future research.

Through extensive database and manual searches, 766 literature records were obtained. After three rounds of literature screening, 17 studies were retained. On this basis, the 17 studies were coded and analyzed.

From the perspectives of individual motivation, hierarchical functionalism and leadership role configuration, the existing studies have explored the negative impacts of shared leadership on team members, formal team leaders and the overall work teams. Specifically, for team members, shared leadership may cause negative consequences like power struggle, role stress and knowledge hiding. For formal team leaders, shared leadership may cause negative consequences like psychological territorial loss, leadership motivation declines and the dualistic paradox of self and group. For the overall work teams, shared leadership may cause negative consequences like team performance inhibition, low decision-making efficiency, team responsibility dispersion and team creativity decline. Meanwhile, contextual factors play a key role in determining the effects of shared leadership.

Through a systematic review of the negative impact of shared leadership, this study responds to the research calls for exploring the dark sides of shared leadership, provides the academic community with a more comprehensive and balanced view of the impact of shared leadership and identifies several directions for future research.

The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).