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The purpose of this paper is to examine Chinese consumers’ level of perception of genetically modified (GM) foods and the determinants of their willingness to pay (WTP) for Fad-3 GM lamb, a newly developed GM product.

Based on a randomized choice experiment involving 576 consumers in Beijing, the authors adopt a double-bounded contingent valuation method to estimate consumers’ WTP for Fad-3 GM lamb, as well as the causal impact of (randomized) product-information disclosure on it.

The econometric result indicates that the randomly disclosed product information describing details about Fad-3 GM lamb, the potential risks associated with the consumption of it, and the related governmental regulation policies raised consumers’ WTP by 6.2 yuan per Jin (or US$2/kilogram).

This paper provides new experimental evidence of the effect of product-information disclosure on consumers’ WTP for a newly developed GM food product.

The purpose of this paper is to examine how households’ engagement in concurrent business (CB), which is measured by the contribution of off-farm income to household income, affects the farm size–technical efficiency (TE) relationship in Northern China.

This paper applies a stochastic frontier analysis method to analyze data on 1,006 rural households collected from four major wheat-producing provinces in Northern China, adopting a translog specification for the underlying production function.

The analysis yields three findings. First, the farm size–TE relationship is inverted U-shaped for all CB engagement levels higher than 5 percent, and the most technically efficient farm size increases with the level of household CB engagement. Second, how TE varies with the level of CB engagement depends on farm size: an inverted-U relationship for relatively small farms (<10μ), a positive relationship for middle-size farms (10–20μ), and a negative relationship for large farms (>20μ). Finally, the overall TE score, 0.88, suggests that wheat output can be increased by 12 percent in Northern China if technical inefficiency were eliminated.

Unlike most previous studies that examine the impacts of farm size and households’ off-farm business involvement separately, this paper examines how these two factors interact with each other.

Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in predicting consumers' food choices combined with conventional socio-demographic data.

A discrete choice experiment was conducted to elicit the underlying preferences of 484 participants from seven provinces in China. By linking three types of data (—data from the choice experiment, socio-demographic information and individual genotyping data) of the participants, the authors employed four machine learning-based classification (MLC) models to assess the performance of genetic information in predicting individuals' food choices.

The authors found that the XGBoost algorithm incorporating both genetic and socio-demographic data achieves the highest prediction accuracy (77.36%), significantly outperforming those using only socio-demographic data (permutation test p-value = 0.033). Polygenic scores of several behavioral traits (e.g. depression and height) and genetic variants associated with bitter taste perceptions (e.g. TAS2R5 rs2227264 and TAS2R38 rs713598) offer contributions comparable to that of standard socio-demographic factors (e.g. gender, age and income).

This study is among the first in the economic literature to empirically demonstrate genetic factors' important role in predicting consumer behavior. The findings contribute fresh insights to the realm of random utility theory and warrant further consumer behavior studies integrating genetic data to facilitate developments in precision nutrition and precision marketing.

The purpose of this paper is to estimate the returns to rural schooling in China, addressing both endogeneity in rural individuals’ schooling and self-selection into off-farm work.

This paper exploits geographical proximity to rural secondary schools to create instrumental variables (IV) for individuals’ years of schooling. It addresses both endogenous schooling and self-selection using the two-step procedure developed in Wooldridge (2002, p. 586).

The preferred IV estimate of schooling returns, 7.6 percent, is considerably higher than most previous estimates found in rural China.

This paper is among the few papers that examine returns to rural schooling in China while simultaneously addressing both endogeneity in individuals’ schooling and self-selection into off-farm work. Its findings suggest that rural education in China is potentially able to generate a respectable level of economic returns if policies are designed to provide greater school accessibility to rural individuals.

The purpose of this paper is to examine the roles social networks play in households’ contribution to the provision of small hydraulic facilities (SHFs) in rural China.

This paper adopts a sample-selection ordered probit model (Greene and Hensher, 2010) to estimate the impacts of overall social-network intensity, of the number of strong ties (relatives), and of the number of weak ties (friends), using data on 1,064 representative households collected from three provinces (Inner Mongolia, Ningxia, and Shandong).

The numbers of strong ties and weak ties both have significant impacts on households’ willingness to contribute to SHFs provision, but only the latter has a significant impact on their level of contribution. More specifically, a one standard deviation increase in the number of weak ties (i.e. friends) is associated with a 6.6 percent increase in households’ propensity of contributing more than 550 yuan and a 8.2 percent decrease in their propensity of contributing less than 100 yuan.

This paper is the first to examine the impacts of social networks on households’ contribution to SHFs provision in rural China. Its finding is of great policy relevance-fostering and maintaining social networks (e.g. through rural cooperatives) can significantly increase households’ contribution to public-good provision.

This study aims to estimate the synergy effect of agricultural dual-scale management (ADM) on farmers' total household income, its heterogeneous effects and its mechanisms.

This study constructs a theoretical analysis framework based on the division of labor and synergy theory, empirically assesses the impact of ADM on farmers' income, and further discusses the heterogeneity and mechanisms using the propensity score matching (PSM) and quantile treatment effect (QTE) models. Data is collected from 1,076 households across 4 cities in Liaoning Province of China in 2021.

ADM can improve the total household income of farmers, and the impact force is greater than that of the single-scale management mode. ADM is more conducive to improving the income of farmers with low income and low labor endowment. Moreover, ADM can improve agriculture production efficiency, increase net grain production income. Nevertheless, it has no significant effect on farmers' off-farm employment income.

Previous studies have mainly focused on the income effect of land scale management or service scale management. To the best of our knowledge, this study is the first to identify the synergy effect of ADM on farmers' income in China. It provides new insights into the process of agricultural production and management mode transitions in rural China.

The purpose of this paper is to analyze changes in consumers’ knowledge and acceptance of genetically modified (GM) foods over the past decade and identifies the determinants in the consumer attitudes toward GM foods in urban China.

The data used in this study were collected from 952 urban consumers in 2013 in 15 provinces. The ordinal logit model was chosen to identify the determinants in the consumers’ subjective knowledge and acceptance of GM foods.

Results show that the consumers’ awareness of GM foods, biotech knowledge, and subjective knowledge improved significantly, while the acceptance rate toward GM foods declined considerably from 2002 to 2013. Moreover, the consumers’ subjective knowledge of GM foods had a significantly negative impact on their acceptance rate of GM foods. Finally, the media coverage with the “event of Golden rice in 2012” as a proxy helped consumers in shaping their negative perceptions toward GM foods, suggesting that the media coverage was one of major factors in leading to the low acceptance rate of GM foods in urban China.

The findings of previous studies conducted in the early 2000s might not reflect current Chinese consumer attitudes because the public opinion toward GM foods in modern China has considerably changed. This study thus filled in the void by updating estimates on consumer attitudes toward GM foods and by underlining the factors that have led to the changes in consumer attitudes, using a mass survey covering Chinese urban consumers in 15 provinces in 2013.

Based on the technology affordance theory, this study aims to explore the relationship among artificial intelligence (AI) orientation, global value chain collaboration (collaboration breadth and collaboration depth) and the international performance of entrepreneurial firms while considering the contingency of board international experience.

This study’s sample was selected using the Sci-Tech Innovation Board (STAR Market) of the Shanghai Stock Exchange in China from 2019 to 2023, from which 1,928 final usable observations from 570 entrepreneurial firms over five years were obtained.

The empirical results indicate that AI orientation positively affects both collaboration breadth and collaboration depth of the global value chain. In addition, both collaboration breadth and collaboration depth mediate the relationship between AI orientation and the international performance of entrepreneurial firms, and board international experience enhances the positive effect of AI orientation on collaboration breadth.

This study contributes to the literature on AI orientation, global value chain and board international experience by introducing the technology affordance theory into the international performance of entrepreneurial firms, and it provides managerial implications for entrepreneurial firms and government policymaking.

The purpose of this paper is to investigate the process optimization of a precast concrete component production line by using value stream mapping.

This paper is an empirical focused on of lean production theory and value stream mapping. The data in the case study were collected in real time on-site for each process during the production process of a prefabricated exterior wall.

The results of the current value stream map indicate that the main problems of the current production process are related to equipment, technology and organization. The equipment problems include simple demolding and cleaning tools and the lack of professional transfer channels. The technology problems include the lack of a marking mechanism and pipeline exit mechanism. There is a lack of standard operating procedures and incomplete process convergence. A comparison and analysis of the current value stream and the future value flow indicate that optimizations of the process flow, the production line layout, and the standard operating procedures have shortened the delivery cycle, reduced the number of workers, improved the operator’s operating level and balanced the production line.

The results of this study provide practitioners with a clear understanding of the optimization of the precast concrete component production and represent a method and basis for the process optimization of a factory production line; the approach is suitable for process optimization in other areas.

This research represents an innovative application of lean production theory and value stream mapping in a complex production line of precast concrete components and thereby fills the gap between the theory and practice of the optimization of a precast concrete component production line.