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Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

This paper aims to analyze relative contribution of intensive margin (IM) and extensive margin (EM) to growth in India's agricultural exports for the period 2001 to 2020. It also analyses the determinants of IM and EMs through a standard gravity model.

The study uses export data from United Nations Comtrade, which is accessed through World Integrated Trade Solution (WITS) software. Data for the period 2001 to 2020 were compiled for analysis using the Harmonized System (HS) of commodity classification system at the six-digit level. This study decomposed the contribution of IM and EM in the growth of Indian agricultural trade by using Hummels and Klenow's approach. After performing the export decomposition analysis, the authors analyze the factors influencing IM and EM by using the Tobit regression model and Poisson pseudo-maximum-likelihood (PPML) method of estimation.

The EM grew at 1.24% per annum, while the intensive margin (IM) increased by 0.23%. The contribution of growth at the EM increased from 58.8% in 2001 to 70.2% in 2020. Export growth along the IM was relatively high for animal products and agricultural raw materials, while growth at the EM was an important contributor to the export growth of horticultural and processed agricultural products. There was a positive and significant effect of the free trade agreement (FTA) on export margins.

More disaggregated commodity-specific studies on value chain analysis would provide valuable insights into the issues hindering exports and realizing the untapped export potential.

There is a scarcity of holistic and recent studies illustrating the role of IM and EMs in agricultural trade growth, covering a large number of commodities and geographies associated with Indian agricultural trade. The study would be helpful to the stakeholders in facilitating informed policy decisions.

The demand for the cold chain logistics of agricultural products was investigated through demand forecasting; targeted suggestions and countermeasures are provided. This paper aims to discuss the aforementioned statement.

A Markov-optimised mean GM (1, 1) model is proposed to forecast the demand for the cold chain logistics of agricultural products. The mean GM (1, 1) model was used to forecast the demand trend, and the Markov chain model was used for optimisation. Considering Guangxi province as an example, the feasibility and effectiveness of the proposed method were verified, and relevant suggestions are made.

Compared with other models, the Markov-optimised mean GM (1, 1) model can more effectively forecast the demand for the cold chain logistics of agricultural products, is closer to the actual value and has better accuracy and minor error. It shows that the demand forecast can provide specific suggestions and theoretical support for the development of cold chain logistics.

This study evaluated the development trend of the cold chain logistics of agricultural products based on the research horizon of demand forecasting for cold chain logistics. A Markov-optimised mean GM (1, 1) model is proposed to overcome the problem of poor prediction for series with considerable fluctuation in the modelling process, and improve the prediction accuracy. It finds a breakthrough to promote the development of cold chain logistics through empirical analysis, and give relevant suggestions based on the obtained results.

Due to consumption changes in the post-pandemic era, the production safety of agricultural products is affecting global consumers. This paper constructs an evaluation index of the agricultural Internet of things (IOT) traceability system and evaluates it using the dynamic hesitant-fuzzy linguistic term sets (HFLTS)-based DEMATEL method to improve agricultural supply-chain links and improve production quality.

The agricultural IOT traceability index system is constructed using the literature and expert interviews; it comprises 6 first-level indices and 20 second-level indices. The agricultural IOT traceability system is evaluated using the dynamic HFLTS-DEMATEL method.

Producers' awareness of agricultural-production safety (A11) has the most significant impact on production and processing links, while warehouse location and storage capacity (A31) have the largest impact on the circulation link. Inspection authenticity and transparency and quarantine information (A41) have the largest impact on the detection-consumption link. The extent to which the traceability-platform construction is complete (A62) has the largest impact on technical support.

The present paper may be limited to the era of post-pandemic, and it is hard to consider all the indices. Further research can broaden the research context and establish a more comprehensive index system.

The index system constructed in this study will surely help relevant regulatory authorities in China to promote the construction of agricultural IOT traceability system and establish a unified standard, so as to provide a basis for future developers to enter the field. Accordingly, it also can help every subject to identify the key indices of each process in the agricultural-product supply chain and guide relevant departments to conduct targeted information tracking and management. The consumers could also understand the standards of traceable agricultural products and effectively protect their own rights and interests.

The existing literature does not provide an objective, unified standard for measuring a decentralized traceability system or identifying key processes. This study therefore proposes a new evaluation index system and uses a dynamic evaluation method to determine the importance of key indices. This study identifies the most important indices in each process, making it possible to discover, improve, and enhance the quality of agricultural products at a practical level.

This paper seeks to apply a framework of collaborative planning, forecasting and replenishment (CPFR) to develop a procurement model for agricultural products.

Considering the biological nature, seasonality and perishable characteristics of agricultural raw materials and products, the paper revises the CPFR reference model. Then, the paper constructs a n‐tier CPFR procurement model by extending a two‐echelon supply chain to a multi‐echelon supply chain and incorporating upstream suppliers in the supply chain. Moreover, the concept of collaborative transportation management (CTM) is integrated into the n‐tier CPFR procurement model. Finally, a case study is analysed and the efficacy of the proposed model is also validated.

The finding suggests that CPFR approach is applied in the procurement of agricultural products. The case results show that the service level is increased and inventory variance is reduced. The proposed model can thus improve the accuracy of forecasting and reduce inventory losses.

The paper offers a useful insight into procurement of agricultural products. The proposed model is a useful development for the agricultural industry in implementing CPFR in the future.

The purpose of this paper is to analyze the impact of reference effects on online purchase intention (OPI) of agricultural products in B2C context and to examine how consumers’ food safety consciousness (FSC) moderates that impact.

An empirical survey was used to test the hypotheses. Data were collected from a total of 297 online consumers in China. A structural equation modeling is utilized to assess the relationships proposed in the research model.

The findings of this study show that reference effects have a significant impact on OPI of agricultural products. Both perceived value (PV) and perceived risk (PR) play a mediating role in the relations between reference effects and OPI, but the mediating effect of the PV is found to be significantly greater than that of the PR. Consumers’ FSC significantly and positively moderates the impact of reference effects on OPI, meaning that the more attention consumers pay to food safety, the greater the impact of reference effects on OPI will become.

First, this study mainly analyzes the positive impact of reference effects on OPI. Future research could discuss the negative impact of reference effects and compare the differences between them. Second, this study only takes the PV and PR as mediators into the research model. Future research could consider adding trust, attitude, and other variables and further explore and clarify the influencing mechanism between reference effects and OPI. Third, this study examines the moderating role of consumers’ FSC but does not fully discuss the moderating role of product categories. Further research could compare the influence of reference effects among multiple product categories.

This study provides valuable insights for agricultural enterprises and online vendors that reference effects are one of the most important factors to influence OPI. It suggests to agricultural enterprises and online vendors that reference effects can be used as a new instrument to influence consumers’ online purchase decisions.

This study for the first time defines reference effects in an online setting and introduces the perspective of reference effects to establish a theoretical model to explain consumers’ OPI of agricultural products. The study reveals the influencing mechanism of reference effects on OPI and thus enriches the theory of online purchase behavior.

This paper therefore aims at systematically estimating the agricultural trade induced farm employment effects in China.

Using detailed agricultural trade and production data during 1994‐2009, the authors estimate the “labor contents” of agricultural trade flows and use these estimates to compute the farm employment effects.

The authors find that China's agricultural trade has indeed generally developed along its widely believed comparative advantages and disadvantages; however, the farm employment “creation” effect due to labor‐intensive exports has actually been dominated by the employment “substitution” effect due to increased land‐intensive imports, thereby mostly resulting in negative net farm employment in the post‐WTO accession era.

Findings from this first systematic attempt to estimate the trade‐induced farm employment effects do not lend support to the popular notion that increased agricultural trade would help increase farm employment and have important implications for evaluating current and future trade policy in China and elsewhere.

This study aims to investigate the effects of interaction in agricultural product live rooms, including personalization, responsiveness, and entertainment, on consumers’ purchase intention.

The SOR model has been applied to formulate hypotheses. This study is based on an online survey conducted with a sample of 433 valid questionnaires from Chinese consumers on the TikTok agricultural products live platform. A partial least squares structural equation modeling (PLS-SEM) is used to test the hypotheses.

The findings indicate that (1) interactions (personalization, responsiveness, and entertainment) in the agricultural products live room have a positive effect on perceived values (utilitarian value, symbolic value, and entertainment value); (2) utilitarian value positively affects purchase intention and mediates the effects of personalization and entertainment interactions on purchase intention, respectively; (3) entertainment value positively influences purchase intention and mediates the influence of entertainment interaction on purchase intention.

This study offers theoretical insights into live marketing of agricultural products and practical implications for practitioners of agricultural products in live streaming commerce.

Pesticide residue is a stubborn problem affecting the quality and safety of agricultural products in China, and has not yet been fundamentally resolved. The purpose of this paper is to study farmers' perception of pesticide residues, as well as the main factors affecting their perception from the viewpoint of farmers. Additionally, this research attempts to explore the basic characteristics of pesticide residues arising in the process of producing agricultural products under the prevailing policy background, so as to provide decision‐making references for the Chinese government to deepen the security management system of agricultural products.

The structural equation model (SEM) is an analytical tool for the observation and treatment of latent variables that are difficult to observe directly, and for the consideration of inevitable errors. This paper investigates the main factors affecting farmers' perception of pesticide residues in the investigated regions based on the SEM and samples of 241 farmers in six counties (cities and regions) of three districts in the Jiangsu Province of China.

According to the research, regional difference, farmers' gender, age, years of education, pesticide training and their own demand for safe agricultural products had different influences on their perception of pesticide residues. Additionally, it was difficult to measure the influence of family characteristics on farmers' perception of pesticide residues. Although the present paper only shows a preliminary study, its conclusion provides a reference value for the Chinese government to deepen the reform of the quality and safety regulatory system of agricultural products.

There are many similar studies in overseas countries, but the application of SEM in the study of the main factors affecting farmers' perception of pesticide residues has not been completely reported previously in domestic literatures. The research assumption of this paper has practically verified that corresponding research conclusions of foreign scholars in this field have universality in China.

The purpose of this study is to explore the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports.

Based on the theoretical analysis of the mechanism of the digital economy’s influence on the binary margin of agricultural exports, this study empirically examines the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports based on China’s customs export data from 2011 to 2016.

The relevant findings are threefold. (1) The digital economy significantly improves the binary margin of agricultural exports, and its effect on the intensive margin is stronger than that on the expansive margin. After the expansive margin is subdivided, the effects on the three sub-variables of the expansive margin are in the following order: old products exported to new markets > new products exported to old markets > new products exported to new markets. (2) The heterogeneity analysis reveals that the digital economy has a stronger role in promoting the binary margin of exports for enterprises in the eastern region, high-income countries as the destination of exports and state-owned enterprises. (3) Mechanism analysis shows that the digital economy promotes the binary margin of agricultural exports by reducing trade costs and intensifying market competition.

First, in terms of research perspective, although there are some studies on the impact of the digital economy on export trade in existing literature, the research objects mainly focus on manufacturing enterprises. In fact, agricultural trade is susceptible to natural conditions and seasonal factors, and countries may impose more SPS measures and TBT measures on agricultural trade due to risk considerations. The relationship between the digital economy and agricultural trade also has its own characteristics, but there are few research studies in this area. At present, only Liu and Gao (2022), based on the data of total imports and exports of different agricultural products from 2004 to 2018, have established a vector auto-regressive model to empirically analyse the heterogeneous dynamic impact of the digital economy on the trade volume of agricultural products. In addition, Ma and Guo (2023) conducted an empirical test on the total effect, regional heterogeneity and threshold effect of the digital economy on agricultural export trade based on China’s provincial panel data from 2011 to 2020. Therefore, under the new circumstances of continuous integration of digital technology and agriculture, this study interprets the impact effect and mechanism of the digital economy on the binary margin of agricultural exports from the perspective of the digital economy, providing new research perspectives and approaches for promoting the growth of agricultural exports. Second, in terms of theoretical analysis, the above studies have not been fully analysed in terms of the specific mechanism of the impact of the digital economy on agricultural exports. Based on the positive and negative characteristics of agricultural trade, this study introduces two kinds of roles into the theoretical analysis framework to comprehensively determine the trade impact effect of the digital economy. Third, in terms of research design, this study empirically examines the impact of the digital economy on the binary margin of agricultural products, passing a series of robustness tests and investigating the mediating roles of trade cost and market competition effects, producing an empirical basis for China to leverage the digital economy to promote the binary margin of agricultural exports.