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Genetically modified (GM) crops, particularly GM grain crops, have been controversial since their commercialization in 1996. However, only a few studies have investigated farmers’ attitudes toward adopting GM grain crops in China. The purpose of this paper is to explore farmers’ willingness to adopt GM insect-resistant rice prior to its commercial release in China and determines the factors that affect farmers’ prospective adoption decisions.

The data are collected using a questionnaire. Descriptive statistics are used to analyze the farmers’ potential willingness to adopt GM rice and level of awareness of GM rice and socioeconomic characteristics. Ordered and binary probit models are applied to identify the key factors that affect the farmers’ decision to adopt GM insect-resistant rice.

Descriptive statistics show that most farmers have little knowledge of GM rice, approximate 35.5 percent of farmers could plant GM rice, and over half of the respondents are uncertain whether or not they will adopt the new crops. The results of econometric analyses show that increasing output and income, and simplicity in crop management, have positive effects on prospective adoption, whereas the high-seed price of GM rice has a significantly negative effect. Health implications also have a significantly positive effect on the farmers’ decision to adopt GM grain crops. A comparative analysis of ordered and binary probit models demonstrates that farmers are more deliberate in their decisions when they have fewer choices. Aside from the above-mentioned variables, the following factors are also statistically significant in the probit model: government technicians’ recommendations, neighbors’ attitudes, level of environmental risks, and the farmer’s age.

Information on the major risks and benefits of GM rice was provided to the farmers in the questionnaire. The farmers were then asked to choose from the three ordered alternative answers, namely, “accept,” “uncertain,” and “reject”. Both ordered and binary probit models were applied to comparatively analyze the collected data. This study is one of a handful of studies that employ these econometric models to identify and explain the underlying factors that affect farmers’ decisions. The relevant findings have important implications for future agricultural policy in China.

Considering the relevance of understanding what influences environmentally sustainable consumer choices, the present study aims to examine and synthesize the key determinants factors from literature and outline a new conceptual framework for explaining green purchasing behaviors (GPBs).

A bibliometric analysis was conducted on 161 articles extracted from Web of Science and Scopus databases, which were systematically evaluated and reviewed, and represent the current GPB knowledge base. Content analysis, science mapping and bibliometric analysis techniques were applied to uncover the major theories and constructs from the state-of-the-art.

The evolving debate between altruistic and self-interest consumer motivations reveals challenges for rational-based theories, as most empirical applications are not focused on buying behaviors, but instead either on pro-environmental (non-buying) activities or on buying intentions. From the subset of leading contributions and emerging topics, nine thematic clusters are unveiled in this investigation, which were combined to create the new PSICHE framework with the purpose of predicting GPB: (P)roduct-related factors, (S)ocial influences, (I)ndividual factors, (C)oncerns about the environment, (H)abits and (E)motions.

By uncovering the multiple intervening factors in GPB decision processes, this study will assist practitioners and academics to move forward on how to foster more sustainable consumer behaviors.

The present study provides readers a summary of an unprecedentedly broad collection of papers, from which the key themes are categorized, the domain's intellectual structure is captured and an actionable framework for enhancing the understanding GPB is proposed. Four new thrust areas and a set of future research questions are included.

The purpose of this paper is to explore the potential causes of the reduction of cotton cultivation in Shandong Province of China from the perspective of smallholders and notably examine the role of off-farm employment.

This paper extends an integrated behavioral model to analyze the relationship between off-farm employment and cotton cultivation by taking into account farmers’ risk attitudes. A household survey data of 144 Bt cotton farmers in six villages in Linqing County, Shandong Province conducted in 2012 and 2013 is used. A simultaneous equations model is established and further estimated by using three-stage least squares method.

Although the introduction of Bt cotton has promoted the increase in cotton acreage in China from 1999 to 2007, the planting area of cotton has been decreasing since 2007. The results show the significant correlations among risk attitude, off-farm employment, and cotton cultivation. The planting area of cotton is positively correlated with farmers’ willingness to take risk but negatively associated with off-farm employment of family members. The findings imply that the rapid emergence of off-farm labor markets is a major reason for the reduction of cotton acreage in Shandong Province. In the context of the more opportunities of off-farm employment in China, cotton acreage is expected to decrease further.

The findings provide a reasonable explanation for the reduction of cotton cultivation in Shandong. This analysis contributes to a better understanding of the relationships among individual risk attitude, off-farm employment, and agricultural behavior, thereby adding to the literature about the application of the integrated behavioral model.

This information will be useful in the selection of materials and technology for the detection and removal of mercury ions at a low cost and with high sensitivity and selectivity. The purpose of this study is to provide the useful information for selection of materials and technology to detect and remove the mercury ions from water with high sensitivity and selectivity. The purpose of this study is to provide the useful information for selection of materials and technology to detect and remove the mercury ions from water with high sensitivity and selectivity.

Different nano- and bio-materials allowed for the development of a variety of biosensors – colorimetric, chemiluminescent, electrochemical, whole-cell and aptasensors – are described. The materials used for their development also make it possible to use them in removing heavy metals, which are toxic contaminants, from environmental water samples.

This review focuses on different technologies, tools and materials for mercury (heavy metals) detection and remediation to environmental samples.

This review gives up-to-date and systemic information on modern nanotechnology methods for heavy metal detection. Different recognition molecules and nanomaterials have been discussed for remediation to water samples. The present review may provide valuable information to researchers regarding novel mercury ions detection sensors and encourage them for further research/development.

This study explores the factors that promote university teachers' switching intention from a traditional classroom to a smart classroom based on the push–pull–mooring (PPM) framework to enrich the theoretical research on the smart classroom and provide a reference for smart classroom promotion.

The proposed conceptual framework was developed from a comprehensive review of the related literature. This study tested and validated the proposed framework using a partial least square structural equation model based on 269 valid questionnaires.

(1) Perceived inefficiency, inquiry-based learning, future expectation and technical self-efficacy had significant effects on switching intention, while low participation, perceived usefulness and habit had no significant effects on university teachers’ switching intention in the smart classroom. (2) In the process of decision-making, the course category significantly moderates the impact of perceived inefficiency and technical self-efficacy on switching intention, while the user experience of smart classrooms significantly moderates the impact of perceived inefficiency on switching intention.

This study explains university teachers' switching intention from a traditional classroom to the smart classroom, which enriches the application area of the PPM framework.

In today’s Taiwan, sha-cha sauce is an indispensable ingredient for beef hot pot and stir-fried dishes. The purpose of this paper contextualizes the history of sha-cha sauce in Tainan, the oldest city in Taiwan, and argues that sha-cha sauce, introduced by Chaoshan immigrants, has contributed to new styles and habits of beef consumption tastes and habits in the post-1949 Tainan and beyond.

This paper uses documentary materials, oral interviews and diaries to explore the relationship between beef consumption and sha-cha sauce. It begins with an historical overview of Taiwan’s beef consumption during the Japanese colonial era (1895-1945). Then, it focuses on two Chaoshan business enterprises: the Bull-Head, which makes the world’s largest “canned sha-cha sauce,” and the Xiao Haozhou, a Tainan restaurant specializing in sha-cha beef hot pot. Finally, this study analyzes Xinrong Wu, a Tainan gentry whose diary entries from 1933 to 1967 documented the changing dietary habits of beef consumption among Taiwanese.

The Chaoshan migrants played an important role in introducing the sha-cha sauce to postcolonial Tainan, and this input bolstered the beef consumption among Taiwanese. The production of sha-cha provided a reliable source of income for these migrants in Tainan, and major businesses like the Bull-Head became the international brands of Taiwanese food products.

The study, though limited to Tainan, reveals the symbiosis between popularization of sha-cha sauce and widespread beef consumption in Taiwan.

This study helps researchers examine the connection between Chinese migrations and food culture.

This paper is an original scholarly investigation of the relationship between food diet and Chaoshan migration in postcolonial Tainan.

This paper aims to overcome the limitations of low efficiency, low power density and strong electromagnetic interference (EMI) of the existing pulsed melt inert gas (MIG) welding power supply. So a novel and simplified implementation of digital high-power pulsed MIG welding power supply with LLC resonant converter is proposed in this work.

A simple parallel full-bridge LLC resonant converter structure is used to design the digital power supply with high welding current, low arc voltage, high open-circuit voltage and a wide range of arc loads, by effectively exploiting the variable load and high-power applications of LLC resonant converter.

The efficiency of each converter can reach up to 92.3%, under the rated operating condition. Notably, with proposed scheme, a short-circuit current mutation of 300 A can stabilize at 60 A within 8 ms. Furthermore, the pulsed MIG welding test shows that a stable welding process with 280 A peak current can be realized and a well-formed weld bead can be obtained, thereby verifying the feasibility of LLC resonant converter for pulsed MIG welding power supply.

The high efficiency, high power density and weak EMI of LLC resonant converter are conducive to the further optimization of pulsed MIG welding power supply. Consequently, a high performance welding power supply is implemented by taking adequate advantages of LLC resonant converter, which can provide equipment support for exploring better pulsed MIG welding processes.