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The government has included social media technology applications in the public sector as part of the fifth wave of information and communications technology adoption. Academic interest in social media in the government sector has been increasing. But there has been little empirical research on the assimilation of social media in the local government. To fill this gap, based on technology–organization–environment (TOE) framework, this study aims to investigate the key technological, organizational and environmental factors that affect the assimilation of social media in local government agencies.

To empirically test the model, a survey study was conducted. Data were collected from 150 government employees in the government department of X municipal government in China. The collected data were analysed quantitatively to answer five hypotheses using structural equation model.

The findings suggest that technology competence, top management support, perceived benefits and citizen readiness significantly influence assimilation of social media in local government agencies. Top management support is the strongest predictor of social media assimilation in a government agency.

This study is one of the first attempts that adopted the TOE framework to understand assimilation of social media in the local government. In addition, the effect of the four factors that include one technological factor, two organizational factors and one environmental factor, namely, technology competence, top management support, perceived benefits and citizen readiness, on intention to assimilate social media was investigated.

With the arrival of the big data era, governments have appointed a chief data officer (CDO) to meet the opportunities and challenges brought by big data. The existing research on the CDOs is very limited, and what does exist focuses primarily on what are CDOs do. Little research has explored how CDOs do. To fill this gap, this study employed ambidexterity theory to investigate the ambidexterity of CDOs’ impact on data-driven innovation.

To empirically test the model, a survey study was conducted to empirically test the model. Data were collected from 261 CDOs in government and government employees in big data management centers or bureaus. The collected data were analyzed quantitatively to answer hypotheses using a structural equation model.

The findings suggest that data exploitation and data exploration significantly influence data-driven leadership, culture and value propositions. Data-driven leadership and value propositions significantly impact government performance.

This study is one of the first attempts to investigate how CDOs work, especially when promoting data-driven innovation. In addition, this study extends ambidexterity theory into the issue of the CDO in government.

To gain an in-depth understanding and provide direction to governments on their quality measurement practices related to open government data (OGD), this paper aims to develop a common frame of reference for quality assessment of OGD.

Qualitative meta-synthesis was used to synthesize previous studies on the quality measurement of OGD. This paper applies a meta-synthesis approach to integrate 10 qualitative studies into a common frame of reference for quality assessment of OGD.

Based on a seven-step meta-synthesis, the paper proposes a common frame of reference for quality assessment of OGD, which includes six indicators, namely, accuracy, accessibility, completeness, timeliness, consistency and understandability.

A common frame of reference for quality assessment of OGD will help researchers better understand the quality assessment of OGD and government agencies to improve the quality of OGD that they publish.

This study aims to investigate whether and how earnings guidance affects corporate innovation.

Exploiting the setting of China, where the Shenzhen Stock Exchange has required all public firms listed on its ChiNext board to issue earnings guidance since 2012, this study uses a difference-in-differences (DID) methodology to examine the effect of earnings guidance on corporate innovation and further conducts cross-sectional analyzes from the information risk and monitoring demand perspectives. Moreover, the authors conduct path analysis to verify the possible channels through which corporate innovation is impeded by market pressure or improved through increased corporate transparency.

This study documents a positive relationship between earnings guidance and corporate innovation, as measured by the number of invention patents, indicating that the “corporate governance” hypothesis dominates in China. Cross-sectional analyzes show that this positive effect is more pronounced for firms subject to greater information risk and monitoring demand. Finally, the path analysis further confirms that earnings guidance improves innovation by increasing corporate transparency.

First, this study captures the bright side of mandatory earnings guidance and suggests that increasing the disclosure frequency can yield benefits for firms. Second, the findings imply that regulations, regardless of what they refer to, should be based on a country’s specific context.

First, this study provides evidence supporting the “corporate governance” argument based on the context of China and, thus contributes to the debate on earnings guidance. Second, this study enriches the literature on the economic consequences of earnings guidance. Third, the study extends research on the determinants of corporate innovation.

The purpose of this paper is to investigate masculinity in Chinese social media marketing for global luxury fashion brands through two studies.

Study 1 compares physical characteristics of males in visually oriented US (Instagram) and Chinese (Weibo) social media posts promoting global luxury fashion magazine brands (e.g. Vogue, Cosmopolitan, GQ and Esquire). Study 2 examines the prevalence of and Chinese consumers’ responses (reposts, comments and likes) to different masculinities depicted in luxury fashion brand-sponsored Weibo posts.

Male portrayals for Chinese audiences feature more characteristics associated with emerging East Asian hybrid masculinities – “Little Fresh Meat” (LFM) and “Old Grilled Meat” (OGM) – than associated with global or regional hegemonic masculinity (i.e. the scholarly Wén and action-oriented Wu). Wén remains common in social media posts for luxury fashion goods, but LFM and OGM engender more consumer responses.

Chinese luxury fashion marketing depicts masculinity more similarly to other East Asian marketing than to Western marketing. Some luxury fashion brands are struggling for acceptance among Chinese youth. Luxury fashion marketers should incorporate hybrid rather than hegemonic masculinities to prompt more favorable responses among Chinese consumers, especially younger female target markets.

Growing female occupational and consumer power and shifting male employment from blue-collar to white-collar jobs have influenced media portrayals of masculinity. Social media marketing for luxury fashion brands demonstrates the prevalence and appeal of hybrid masculinities in China.

The purpose of this paper is to clarify agricultural services into five categories, including agricultural materials supply service, financial service, technical service, machinery service and processing and sales service, and to examine the effect of agricultural services on cost saving of rice production in China.

Based on a three-year panel data set covering 3,421 rice farmers in 12 Chinese provinces collected from the state rice industry experiment stations’ fixed watch points of China Agriculture Research System, a stochastic frontier model which takes the price vectors of input variables into cost function is developed by stochastic frontier analysis method in the study.

There is a deviation between the actual cost and the minimum cost on rice production in China due to the loss of cost efficiency, whose score is 0.7983 at the mean. Agricultural services can help improve cost efficiency, thus contributing to cost saving. Specifically, the effect of technical service on cost saving is the highest, followed by processing and sales service, machinery service, financial service and agricultural materials supply service.

The results of this paper are of great significance to the effectiveness and efficiency of the targeted agricultural services and indicate implications for policy improvement under the context of clear upward trend of agricultural production costs.

This study examines the relationship between internal control and corporate environmental responsibility.

Unlike US studies that concentrate solely on internal control over financial reporting, this study uses a comprehensive index that encompasses internal control over financial reporting, operations, and compliance. Corporate environmental responsibility is measured by environmental investments. Our research sample comprises Chinese listed firms from 2010 to 2018.

The results demonstrate a positive correlation between internal control and corporate environmental investments. Furthermore, we find that firms with high-quality internal control can improve their financial and environmental performance through environmental investments. After decomposing internal control into its five components, we show that the control environment, control activities, and information and communication components exhibit stronger effects on environmental investments than the risk assessment and monitoring components. Finally, the cross-sectional analyses reveal that the positive effect of internal control is more pronounced in private firms and in firms that are subject to weaker environmental regulation.

By focusing on the effect of a comprehensive internal mechanism on corporate environmental responsibility in China, this study contributes to the literature in developed-country settings that overwhelmingly focuses on the impact of external stakeholders and regulations.

The purpose of this paper is to develop a common remaining shelf life prediction model that is generally applicable for postharvest table grape using an optimized radial basis function (RBF) neural network to achieve more accurate prediction than the current shelf life (SL) prediction methods.

First, the final indicators (storage temperature, relative humidity, sensory average score, peel hardness, soluble solids content, weight loss rate, rotting rate, fragmentation rate and color difference) affecting SL were determined by the correlation and significance analysis. Then using the analytic hierarchy process (AHP) to calculate the weight of each indicator and determine the end of SL under different storage conditions. Subsequently, the structure of the RBF network redesigned was 9-11-1. Ultimately, the membership degree of Fuzzy clustering (fuzzy c-means) was adopted to optimize the center and width of the RBF network by using the training data.

The results show that this method has the highest prediction accuracy compared to the current the kinetic–Arrhenius model, back propagation (BP) network and RBF network. The maximum absolute error is 1.877, the maximum relative error (RE) is 0.184, and the adjusted R² is 0.911. The prediction accuracy of the kinetic–Arrhenius model is the worst. The RBF network has a better prediction accuracy than the BP network. For robustness, the adjusted R² are 0.853 and 0.886 of Italian grape and Red Globe grape, respectively, and the fitting degree are the highest among all methods, which proves that the optimized method is applicable for accurate SL prediction of different table grape varieties.

This study not only provides a new way for the prediction of SL of different grape varieties, but also provides a reference for the quality and safety management of table grape during storage. Maybe it has a further research significance for the application of RBF neural network in the SL prediction of other fresh foods.

The purpose of this study is to propose a new consumer value segmentation method for low-dimensional dense market datasets to quickly detect and cluster the most profitable customers for the enterprises.

In this study, the comprehensive segmentation bases (CSB) with richer meanings were obtained by introducing the weighted recency-frequency-monetary (RFM) model into the common segmentation bases (SB). Further, a new market segmentation method, the CSB-MBK algorithm was proposed by integrating the CSB model and the mini-batch k-means (MBK) clustering algorithm.

The results show that our proposed CSB model can reflect consumers' contributions to a market, as well as improve the clustering performance. Moreover, the proposed CSB-MBK algorithm is demonstrably superior to the SB-MBK, CSB-KMA and CSB-Chameleon algorithms with respect to the Silhouette Coefficient (SC), the Calinski-Harabasz (CH) Index , the average running time and superior to the SB-MBK, RFM-MBK and WRFM-MBK algorithms in terms of the inter-market value and characteristic differentiation.

This paper provides a tool for decision-makers and marketers to segment a market quickly, which can help them grasp consumers' activity, loyalty, purchasing power and other characteristics in a target market timely and achieve the precision marketing.

This study is the first to introduce the CSB-MBK algorithm for identifying valuable customers through the comprehensive consideration of the clustering quality, consumer value and segmentation speed. Moreover, the CSB-MBK algorithm can be considered for applications in other markets.

Before the turn of the century, taking overseas students was more about a diplomatic issue dominated by the state in China, for which reason this section is relatively independent within the higher education system. However, evidence from a series of new policy documents and their impacts suggests that international student mobility (ISM) has been intensively shaped by the central government in the desire to promote its national strategy, namely the belt and road initiative. ISM policy, although with a significant proportion marketized, was introduced for a clear purpose of cultural diplomacy. The paper aims to discuss these issues.

Looking beyond the debate of market-driven vs state-dominated, this paper attempts to provide a thorough understanding of this changing pattern based on examination of key changes of policy statements along with official data analysis.

This paper argues that the new pattern must be understood against a context of a hierarchy of higher education institutes in contemporary China: a sector led by a small number of prestigious universities generously funded by the central government with a large number of ordinary universities underfunded and eager to generate income. Prestigious institutes enroll international students to satisfy performance indicators listed by policies like “Double First-rate”; other universities, benefiting from the reputation and momentum generated by the top ones, take self-funded students for profit.

By making good use of both performance indicators and market motives, the country managed to move a state-dominated ISM policy in the twentieth century into the existing state-steering marketization model and made China a major destination for overseas study.