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The development of digital inclusive finance appears to be able to solve the difficulty of traditional finance, which cannot completely cover agriculture and farmers and provides better financial services and products to Chinese farmers. Thus, it improves the farmers' enthusiasm for agricultural production. The purpose of this paper is to clarify whether this goal is indeed being achieved.

This paper theoretically analyzes the mechanism that influences the effect of digital inclusive finance on rural households' agricultural production decisions and conducts an empirical study based on a sample from the Chinese family database (CFD).

First, the development of digital financial inclusion in general can encourage rural households to reduce agricultural production. Second, the negative effect of digital inclusive finance on households' agricultural output is realized by widening the gap between the efficiency of non-agricultural economic activities and the efficiency of agricultural production. The wider the gap is, the lower the enthusiasm of households for agricultural production. Third, the mediating effect of “digital financial inclusion – difference in efficiency – agricultural output” has a significant negative effect on households with low agricultural production efficiency, but not households with high agricultural production efficiency. Digital inclusive finance has no significant effect on the difference in efficiency between the two economic activities of high-efficiency households, but a greater difference in efficiency between the two economic activities corresponds to higher enthusiasm of households for agricultural production.

To the best of our knowledge, this paper is the first to analyze the impact of digital financial inclusion on Chinese farmers' agricultural production. The findings of this study can provide policy-related insights to help local governments promote the development of digital finance in China's agricultural economy.

Both the SEC (Securities and Exchange Commission) and the popular press have routinely criticized firms for the complexity of their financial disclosures. This study aims to investigate how financial analysts respond to the tone complexity of firm disclosures.

Using approximately 20,000 earnings conference call transcripts of S&P 1,500 firms between 2005 and 2015, the authors first calculate the abnormal negative tone, the measure of tone complexity; then use such tone measure in econometric models to examine analyst forecast behavior. The authors also test the robustness of the results under different model specifications, tone word lists and alternative tone measure calculations.

Consistent with the notion that analysts respond to the information demand from investors and incur more costs and effort to analyze firm disclosure when the tone is more complex, the authors find that higher tone complexity is positively and significantly associated with more analyst following, longer report duration, more forecast revisions, larger forecast error and larger forecast dispersion. In addition, the authors find that tone complexity has a long-term impact on analyst following but has a limited long-term impact on analyst report duration, analyst revision, forecast error and dispersion.

This study complements existing literature by highlighting the information role of financial analysts and by providing evidence that analysts incorporate the management tone disclosed during conference calls to adjust their forecasting behaviors. The results can be used by policymakers as evidence and support for further improving firm communication from a new dimension of disclosure tone.

The purpose of this paper is automatic classification of TV series reviews based on generic categories.

What the authors mainly applied is using surrogate instead of specific roles or actors’ name in reviews to make reviews more generic. Besides, feature selection techniques and different kinds of classifiers are incorporated.

With roles’ and actors’ names replaced by generic tags, the experimental result showed that it can generalize well to agnostic TV series as compared with reviews keeping the original names.

The model presented in this paper must be built on top of an already existed knowledge base like Baidu Encyclopedia. Such database takes lots of work.

Like in digital information supply chain, if reviews are part of the information to be transported or exchanged, then the model presented in this paper can help automatically identify individual review according to different requirements and help the information sharing.

One originality is that the authors proposed the surrogate-based approach to make reviews more generic. Besides, they also built a review data set of hot Chinese TV series, which includes eight generic category labels for each review.

This study examines the relationship between brand digitalization and brand market performance, mediated by brand competence and brand warmth and moderated by brand familiarity, from a consumer perspective.

This study conducted a 2 (brand digitalization: yes vs no) × 2 (brand familiarity: high vs low) between-subject experiment and administered a survey with 693 valid responses. Two-way analysis of variance, Hayes' PROCESS macro and a linear regression model were used to analyze the data.

Brand digitalization positively affects brand market performance, which is mediated by brand competence and brand warmth. In addition, brand familiarity has a moderating effect on the relationship between brand digitalization and brand market performance, as well as on the mediating effect of brand competence and brand warmth.

Brand managers should enhance the integration of digital technologies into brand building and management and develop brand communication strategies that emphasize brand digitalization based on consumers' brand familiarity.

This study advances current knowledge of the drivers of brand performance by constructing the concept of brand digitalization and examining its role in improving brand market performance. Additionally, this study deepens our understanding of the relationship between digital technology usage and consumer brand response by examining the mediating effect of brand competence and brand warmth and the moderating effect of brand familiarity.

The digital economy is expected to revive the countryside and reduce the current level of urban–rural inequality. Nevertheless, whether rural e-commerce can narrow the urban–rural income gap still requires further analysis. The purpose of this paper is to clarify whether this goal is, in fact, being achieved.

Taobao villages have become the epitome of rural e-commerce development in China. Therefore, this paper matches the data of Taobao villages and the data of prefecture-level cities from 2014 to 2019, and employs a two-way fixed effect model, nonlinear model, instrumental variable model and interactive fixed effects model to explore the impact of rural e-commerce on the urban–rural income gap.

Firstly, the ability of urban residents to share rural e-commerce development is higher than that of rural residents, which actually widens the urban–rural income gap. Secondly, the migration to cities of rural families that have profited from e-commerce, and the return of working-class people to the countryside, are two factors that are contributing to the widening of the urban–rural income gap. Thirdly, the farther the distance from the urban area and the higher the spatial agglomeration of the rural e-commerce cluster is, the weaker the impact on widening the urban–rural income gap will be. Finally, while industrial-led rural e-commerce is responsible for widening the urban–rural income gap, agricultural-led rural e-commerce has no significant impact on the urban–rural income gap.

To the best of the authors' knowledge, this paper is the first to analyze the impact of rural e-commerce on the urban–rural income gap from the perspective of the coverage of Taobao villages. This empirical study will enrich existing theoretical perspectives on urban–rural integration under the backdrop of the digital economy.

The current study aims to investigate the factors that impact the feedback received on answers to questions in social Q&A communities and whether the expertise-required question influences the role of these factors on the feedback.

To understand the antecedents and consequences that influence the feedback received on answers to online community questions, the elaboration likelihood model (ELM) is applied in this study. The authors use web data crawling methods and a combination of quantitative analyses. The data for this study came from Zhihu; in total, 353,775 responses were obtained to 1,531 questions, ranging from 49 to 23,681 responses per question. Each answer received 0 to 113,892 likes and 0 to 6,250 comments.

The answers' cognitive and emotional components and the answerer's influence positively affect user feedback behavior. In addition, the expertise-required question moderates the effects of the answer's cognitive component and emotional component on the user feedback, moderating the effects of the answerer's influence on the user approval feedback.

This study builds upon a limited yet growing body of literature on a theme of great relevance to scholars, practitioners and social media users concerning the effects of the connotation of answers (i.e. their cognitive and emotional components) and the answerer's influence on user feedback (i.e. approval and collaborative feedback) in social Q&A communities. The authors further consider the moderating role of the domain expertise required by the question (expertise-required question). The ELM model is applied to explore the relationships between questions, answers and feedback. The findings of this study add a new perspective to the research on user feedback and have implications for the management of social Q&A communities.

Whether training contributes to stabilizing employment among rural migrant workers in cities remains unclear. Based on this gap in the research, the purpose of this paper is to examine how on-the-job training affects rural migrant workers’ job mobility in China.

By using randomly sampled survey data on migrant workers in Liaoning province in 2014, the authors applied a logistic model and survival analysis to explore the effect of on-the-job training on migrant workers’ job turnover and understand workers’ job change behaviour after receiving on-the-job training.

The results showed that job training provided by employers can significantly reduce migrant workers’ turnover by increasing specific human capital. By contrast, training provided by the government or migrant workers themselves focuses on increasing general human capital and thus fails to reduce job turnover. Moreover, further discussion revealed that, in the trained group, those people with a short tenure and low wage in the first job, people without any skills before migration, male migrant workers, and people that work in medium-sized and large cities have a higher probability of changing jobs. These findings suggest that to tackle the high rate of job mobility among rural migrant workers, firms should entice this labour to train by adjusting their internal training mechanisms, and local governments should subsidize firms that provide on-the-job training for rural migrant workers to help share the costs and risks of training. Moreover, for sake of reducing job changing among those trained workers, firms even should take actions to protect their labour rights of migrant workers and to ensure that they receive equal treatment to their urban counterparts.

This paper makes three contributions to the field of job mobility in China. First, it explores the mechanism between on-the-job training and rural migrant workers’ job mobility. Second, it empirically analyses the effect of on-the-job training on migrant workers’ job mobility as well as the different effects of general and specific training. Lastly, its results have important policy implications for the employment stability of rural migrant workers.

This chapter is concerned with the social pillar of sustainability and how management education can assist in ensuring the equity among people that is necessary to achieve sustainability. The chapter considers how a sense of responsibility towards ensuring equity and fairness is derived and the sources of this. It argues that early education teaches aspects of fairness, but at a higher education level, further education is a working context continues to be necessary but is very often absent. It is at this stage that the educators in management have a role and responsibility. Unfortunately in a work context, people tend to be considered merely as operands within a production process and not as real people, and thus considerations of fairness and concern tend to be eliminated, with a tendency towards exploitation. This of course is not sustainable, and the chapter argues that at the higher education level this can be addressed with noticeable effect.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

The role of marketing as a business function is rapidly changing in China. Consequently, their views on marketing orientation – whether it is accepted, rejected, modified or reframed – have been seriously impacted. This paper aims to report on the results of a survey among Chinese small- and medium-sized enterprise (SME) managers and their perceptions of the market-orientation philosophy. In particular, emphasis was placed on three dimensions of market orientation: intelligence generation, intelligence dissemination and responsiveness. The effect of market orientation on business performance was also examined.

The authors collected data from 214 managers from SMEs. These businesses were located in the cities of Beijing, Shanghai and Shenzhen. The commonly used market orientation (MARKOR) measure was used to test the hypotheses.

Consistent with the extant literature, the findings provided empirical support for the three dimensions of market orientation among Chinese SME. The authors also found that a positive relationship existed between Chinese SME market orientation and firm performance.

This study provides major insights into the market orientation measurement and practices of SME in China. From a measurement perspective, the empirical support for MARKOR across a non-Western context is noteworthy. From a practitioner perspective, the implications relating to understanding Chinese SME and how these companies can best market their products and services to their respective markets are critical. Some of the limitations of our study relates to the sample size, convenience sampling and geographic concentration of the respondents.

This study addresses the gaps in the literature by exploring market orientation in non-large scale businesses as well as the adaptation of the concept in a non-Western cultural setting. The findings extend the conceptualization and application of market orientation to Chinese SME.