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The purpose of this paper is to examine the potential economic impacts of China’s insect-resistant GM maize and provide new evidence for decision making concerning its commercialization.

This study uses data drawn from the production trials of insect-resistant GM maize and expert interviews to determine the impacts of commercializing GM maize at farm level under three scenarios with varying severity of insect pest attacks in maize production. Economic impacts are simulated using a modified Global Trade Analysis Project model.

In farm terms, insect-resistant GM maize increases crop yield and reduces both pesticide and labor inputs. In national terms, China can increase its GDP by USD8.6 billion and maize self-sufficiency by about 2 percent given normal insect pest attacks if China commercializes GM maize. Additional beneficiaries include consumers and the livestock industry. Non-maize crops can also benefit from land saving through GM maize commercialization. Chemical is a sector with the decrease in its output because demand for pesticides will fall.

Although China has announced a roadmap for commercializing GM crops for use as feed and in processing after nearly two decades of producing GM cotton, no clear timetable for producing GM maize as feed has been established due to several concerns, including the potential for economic gains from GM maize. This study is the first to assess the economic impacts of commercializing China’s GM maize. The findings should have significant policy implications for the development and commercialization of GM crops in general and GM maize in particular.

Public and private policy responses to the introduction of genetically modified (GM) crops have differed across countries and regions, resulting in market fragmentation that is in conflict with the entry mode strategy of standardisation that has dominated the food distribution system for a century. To deal with the new market reality, an alternative entry mode strategy must be established which is capable of segregation – or identity preservation (IP) – of the commodity supply system. A multi‐mode strategy is presented that combines the economic transaction cost perspective with the institutional theory perspective. A seemingly paradoxical result emerges: standardisation is the solution to market differentiation. That is, an IP entry mode strategy must first be built on a foundation of standardised norms and protocols, which then makes it easier to target specific entry mode strategies to meet the divergent export market access rules resulting from the differential public policy and private strategies in various countries and regions.

The purpose of this paper is to provide an overview of the current state of knowledge on the economic performance of genetically modified (GM) cotton worldwide based on a wide range of data and source from available literature, and second to assess yield gain and economic performance.

A systematic review was captured to provide the evidence of potential benefits of GM cotton. A country-specific analysis was conducted in order to compare economic indicators and employed meta-analysis to find out the significance of the different of GM cotton over its counterpart.

This paper depicts positive impact of commercialized GM cotton in terms of net revenue, and the benefits, especially in terms of increased yields, are greatest for the mostly farmers in developing countries who have benefitted from the spill over of technology targeted at farmers in industrialized countries.

Due to the variability of the data which came from different methodologies, it is difficult to determine the differences of the performances each individual study.

This, it is believed that results from this study can be useful for operations of all sizes as the authors think about what needs to be focussed on for long-term producers survival.

The paper clearly indicates that China is the highest cotton yield of GM cotton, the lowest cost of GM seed and the lowest cost of chemical spray compare to any other countries. Therefore, this is the fact that the adoption of GM cotton has been widely spread among the farmers across the regions in China.

This paper seeks to provide an in‐depth discussion on the impact of agricultural biotechnology in developing and least developed countries (LDCs) as well as the concomitant biosafety concerns that might have an impact on trade and the environment whilst highlighting the importance of choosing development pathways that are conducive to the specific needs of these nations without endangering the biodiversity and affecting people's health.

The paper adopts a socio‐legal approach by undertaking a content analysis of decided cases, relevant treaties and existing studies conducted in areas related to agricultural biotechnology within the framework of sustainable development imperatives.

The paper suggests that developing countries venturing into agricultural biotechnology need to enrich the technology according to their needs and capabilities in order to be able to weigh the benefits against the risks in the production and import of genetically modified organisms (GMOs) specifically via the implementation of the “precautionary principle” and viable “risk assessment” techniques which conform to their existing international law obligations in view of the findings that most of these nations have not formulated adequate legal and institutional frameworks supported with the necessary expertise to regulate, monitor, and ensure safety of agricultural GMOs produced and/or imported by them.

The issues and suggestions in this paper will enable the development process of developing and least developed economies to conform to the tenets of sustainable development and minimize the loss of Earth's biodiversity.

The paper is of practical use to stakeholders and policymakers alike venturing into agricultural biotechnology. It pools the findings of a cross‐section of studies to look at the implications therein and the arising biosafety and trade issues with special reference to developing and LDCs.

The purpose of this paper is to develop an analytical model to value traits at different developmental phases and to determine the value of drought tolerance (DT) in wheat using GM technology.

A stochastic binomial real-options model of GM traits was developed to estimate the value of a DT wheat trait.

The results indicate that the value of DT wheat using GM technology is in-the-money at each development phase. The greatest value would accrue for the Prairie Gateway and Northern Great Plains regions in the USA.

The approach is useful for valuing high-cost risky investments in technology and results provide guidance for development strategies.

The model is original and its applications to wheat are unique.

The purpose of this paper is to assess the impacts of GM crop adoption on the profitability of farms operated by young and/or beginning farmers and ranchers (YBFR).

This research uses weighted quantile regression analysis in conjunction with 2004‐2006 Agricultural Resource Management Survey to evaluate the impact of GM crop adoption on financial performance of farms operated by YBFR. The methodology employed in this study corrects for the simultaneity of technology adoption and farm financial performance.

As expected, the impact of GM crop adoption on profitability is positively affected by the scale of operation and leverage. On the other hand, off‐farm employment by “beginning” farmers has a negative impact on farm's profitability if they choose to adopt GM crops. Finally, quantile regression results from a farm household study shows that the model performs better at the higher quantile of the distribution.

This study helps to determine whether the adoption of GM crops increases the profitability of farms operated by “beginning” farmers. In addition, it explores the impact of other factors (such as farm, operator, demographic, and financial characteristics) on the profitability of farms operated by “beginning” farmers.

Computing the profitability of adoption decisions for YBFR will provide significant information to YBFR that they can use in constructing their farm operations strategic business plan and future decisions regarding farming operations.

Existing research does not examine the impact of GM crops adoption on farm profitability of YBFR. Furthermore, YBFR operators face significant challenges in making their operations financially viable, owing to lack of access to capital and land.

This paper aims to study the antecedents of Internet of Things (IoT) adoption among farmers and determine how trust in the technology influences its adoption when mediated by perceived value and risk. Through the conceptualization of trust and perceived risk, the authors factor in farmers’ perceptions of agricultural technology providers and discuss different forms of perceived value, spanning economic, green and epistemic value.

This paper develops a distinctive research design, drawing on elements of the value-based adoption and technology acceptance models. By linking different elements of perceived value with IoT technology, the authors also apply the service-dominant logic to this study. They study how trust affects perceived value and risk and then determine how perceived value and risk, in turn, affect IoT adoption. The authors test the hypotheses by developing a structural equation model to analyze the results of a survey, wherein 492 farmers from Iowa, the USA, participated.

The results show a positive relationship between trust and perceived value and a negative relationship between trust and perceived risk. Perceived value had a positive impact on IoT adoption, whereas perceived risk had a negative impact on IoT adoption.

The research findings on trust and perceived value and risk are timely and relevant for business-to-business (B2B) marketing practitioners and agricultural stakeholders, especially in an era where farmers are expressing growing concerns about data handling risk posed by IoT technology adoption.

The research findings signal a transition in focus from the goods-dominant logic to the service-dominant logic in agriculture, whereby farmers are drawn to IoT technology because of perceived economic, green and epistemic value and as a result, can differentiate themselves on how well they deploy operant resources. This paper not only provides a unique conceptualization of perceived value but also pave the way for a richer conceptualization of IoT core functions that enable farmers to fulfill green and epistemic goals. This is the first B2B marketing paper discussing the antecedents of IoT adoption in agriculture, such as farmers’ perceptions of both monetary and non-monetary forms of value and perceived data handling risk.

The paper aims to examine impact of adopted maize seed technology on farm profitability. It assesses both the revenue and cost implication of the adopted technology on farmers' welfare. The study aims to expand the domain of farm investment assessment analysis by including a broader range of production outcome indicators than is normally found in the adoption impact on farm profitability literature.

The paper opted for an empirical study using field survey data. A structured questionnaire was used to interview 400 maize farmers across four regions of Ghana. The survey was complemented with focus group discussions in each region with participants representing male and female farmers cultivating maize on a commercial basis. The data captured detail household level (i.e. demographic and socioeconomic characteristics) as well as farm-level information on maize production (i.e. input use and farm output).

The paper provides empirical insights about maize farmers' perception on the adopted maize seed technology and the factors influencing adoption. It also shed light on the fact that maize farmers do not base their adoption decisions solely on farm output and revenue indicators alone, but mainly on the return on their investment and the cost associated with the maize seed technology adopted.

Because of data limitation, the influence of some important actors (market power) could not be directly captured in the analysis; this may lead to over simplification of a very complex situation in the maize sector. Therefore, researchers are encouraged to future investigate the influence of such important phenomenon on farm profitability.

Improving maize productivity and farm profitability across the sectors is important in order to improve farmer income. This study, therefore, highlights the effect of adopted seed technology and its impact on farm profitability.

This paper fulfils an identified need to study how investment cost in maize seed technology affect farm profitability.

This paper aims to identify the future trends in the agro‐food sector over the next two decades. Ten national technology foresight studies have been reviewed with the purpose of (i) envisaging the future socio‐economic and technology framework of the sector and (ii) highlighting major agro‐food technology clusters and their future application.

The purpose of this paper is to test the impact of the soybean rejuvenation plan and the subsidy on farmers' land allocation decisions, which may reference policy adjustment from a micro perspective.

The paper develops a multi-objective optimized programming model on farm-level, which simulated the land-use changes, as well as the resulting changes in benefits of the rational “typical farm”. The simulation scenarios include changes in subsidy policy and production efficiency, and the baseline scenario was the production status in 2018.

The results show that an increase in soybean producer subsidy will encourage farmers to allocate more land for soybean planting, which can be considered as a policy tool in promoting soybean production in China. Besides, the effect of subsidy in adjusting soybean acreage for farms is further affected by external conditions such as production technology (such as breeding technology, pesticide and fertilizer application efficiency). Meanwhile, large-scale farms show more significant land adjustments when facing changes in policies and external conditions.

The value of this paper is to simulate the effects of soybean policy and subsidy change on farmers' land-allocation decisions through a multi-objective farmer decision-making model, which provides a micro perspective to understand the implementation effect of the soybean revitalization plan.