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The main purpose of this paper is to address the impact of product design changes on supply chain risk, and to identify the supply chain risk dimensions in the Chinese special‐purpose vehicle (SPV) industry in the context of product design change.

Case study methodology is adopted to describe the current situation of supply chain risk management in the Chinese SPV industry. Data are mainly collected from in‐depth semi‐structured interviews, and a cause‐effect diagram is used to identify and summarize the internal and external risk dimensions of supply chain risk.

This paper identifies both the internal and external supply chain risk from the perspective of the focal manufacturer in the SPV supply chain. At the level of the external supply chain, customer‐required design change normally leads to risk in supply, delivery, and policy. Internally for the manufacturer, the risk dimensions are R&D, production, planning, information, and organization. All of these risk dimensions have their respective causes.

The risk identification of product design change in this paper is only meant to lay a foundation; further case studies should focus on the best practices and approaches of risk management and extend them to other industries.

The current identification of the risk dimensions and their respective causes will help both practitioners and researchers to better understand supply chain risk in the context of product design change. The identified risk dimensions and cause‐effect diagram provide practitioners with a risk framework and useful tools to recognize and identify their potential supply chain risks.

This paper shows the “big picture” of supply chain risk from product design changes in the Chinese SPV industry.

This paper deals with estimation of risk and the risk preference function when producers face uncertainties in production (usually labeled as production risk) and output price. These uncertainties are modeled in the context of production theory where the objective of the producers is to maximize expected utility of normalized anticipated profit. Models are proposed to estimate risk preference of individual producers under (i) only production risk, (ii) only price risk, (iii) both production and price risks, (iv) production risk with technical inefficiency, (v) price risk with technical inefficiency, and (vi) both production and price risks with technical inefficiency. We discuss estimation of the production function, the output risk function, and the risk preference functions in some of these cases. Norwegian salmon farming data is used for an empirical application of some of the proposed models. We find that salmon farmers are, in general, risk averse. Labor is found to be risk decreasing while capital and feed are found to be risk increasing.

The quantitative understanding of the safe input management practices of vegetable producers is essential for both food safety and environmental protection. The purpose of this study is to investigate the current status of safe production in vegetable enterprises and examine the key risk factors affecting the safe production of vegetables from the perspective of agricultural inputs.

Based on the theory of risk analysis, a framework of safe vegetable production risk analysis is constructed from the perspective of production input behaviour. Based on 202 valid questionnaires in Beijing, China, this paper identifies direct risks in input management through statistical descriptive analysis; determines weights through an expert elicitation process and calculates weighted safety values accordingly; and finally uses a categorical regression model to explore the indirect risks affecting corporate safety production.

The results show that direct risk factors include seed treatment risk, pesticide and fertilizer use criteria risk, pesticide and fertilizer operation risk, and pesticide application object risk. The production safety value of Beijing's enterprises is found to be high in the north and south regions, and low in the central region. Finally, some indirect risk factors, namely the cognition of agricultural product safety laws, the cognition of pesticide safety intervals, the cognition of prohibited pesticides and the possession of brands, are found to have positive and significant impacts on the safe production behaviour of enterprises.

These findings provide entry points for interventions aimed at reducing dependence on pesticides and fertilizers and promoting input management for safe vegetable production in enterprises, thus avoiding vegetable safety incidents due to improper practices in the production chain.

To strengthen the correlation analysis on risk factors of drug production safety and reduce the influence due to fuzzy judgments, a safety risk assessment method based on Grey-Analytic Network Process (G-ANP) is proposed.

First, an index system evaluating drug production safety risk is constructed according to the “Good Manufacture Practice of Medical Products,” next the influence weight of each risk index is derived by using the Analytic Network Process, then the grey number of each risk index is determined by further utilizing the grey statistical theory, and finally the risk level of drug production is obtained.

An empirical study is conducted and the results support the feasibility and practicability to use G-ANP method for drug production safety risk evaluation. The results of the case show that it is feasible and practical to use G-ANP method for drug production safety risk evaluation.

The innovation lies in the use of G-ANP method to fully consider the interdependence and interaction between the risk factors of drug production safety, which improves the objectivity in judging the risk level of drug production and provides a scientific basis for pharmaceutical manufacturers to formulate further decisions and management in the case of insufficient quantification of risk factors. Based on the findings, more targeted suggestions are made to reduce the production risk of pharmaceutical enterprises.

The factory production stage constitutes the bridge in the supply chains of modular integrated construction (MiC) projects. It embodies the fundamental differences between MiC and site-based construction. However, there is a poverty of knowledge of the uncertainties and risk events at the production stage. This study aims to investigate the critical production risk factors (PRFs) for MiC projects.

Comprehensive literature research and expert review identified and validated 22 candidate PRFs for MiC projects. A structured questionnaire survey was then used to gather opinions of domain experts in 18 countries on the relative impact of the validated PRFs for MiC projects. The collected data were analysed using multiple statistical techniques.

Statistical analysis identified nine critical PRFs for MiC projects. The top five include dimensional conflicts between modules during production; delays in production materials procurement; defective design; design information gap between designer and manufacturer; and limited capacity of manufacturers.

The study addressed the gap associated with identifying critical risk factors peculiar to the factory production stage of MiC projects. Its novelty lies in providing an opposite assessment of severities and prioritization of critical PRFs for MiC projects. The prioritized critical PRFs for MiC projects may inform resource allocation. Thus, it provides valuable information to MiC production specialists and project managers in their production risk planning and management strategies. The identified PRFs contribute to the theoretical checklist of MiC supply chain risk factors and may assist practitioners in assessing the severity levels of the PRFs of their MiC projects.

The purpose of this paper is to evaluate the technical efficiency and production risk in China's rice production and examine the effect of factor market reform on these two agricultural performance metrics.

Using an unbalanced farm-level panel data with 2,193 observations on 329 rice farms from 2004 to 2016, the authors estimate a translog stochastic production frontier model that accounts for both technical inefficiency and production risk. A one-step procedure through the maximum likelihood method that combines the stochastic production frontier, technical inefficiency and production risk functions is used to circumvent the bias problem often found in the conventional two-step model.

Estimation results show that both land and labor market reforms significantly improved the level of technical efficiency over the years, although the effect of land market deregulation is of a much higher magnitude compared to the latter. The land market reform, however, has also increased the risk of production. The authors further find that a higher proportion of hired labor in total labor cost helps lower production risk, while also acting to decrease technical efficiency. Additionally, agricultural subsidies not only increased the output variability but also lowered technical efficiency

First, the authors evaluate the effect of market deregulation on technical efficiency and production risk under a stochastic frontier framework that simultaneously accounts for both production performance metrics, which is important from a statistical point of view. Further, the authors exploit both cross-sectional and time-series variations in a panel setting to more accurately estimate the technical inefficiency scores and production risk for individual farmers, and investigate how the exogenous land and labor market reforms influence these two production performance measures in China's rice farming. This is the first study in the literature to analyze these questions under a panel framework.

The purpose of this paper is to document the level of risk in the Québec egg sector (conventional and specialty eggs) and analyze the optimal choices of Québec egg producers that must allocate limited resources to production of different types of eggs.

A quadratic programming approach applied to expected mean-variance models is used to analyze the impact of risk on decision to invest when the resources must be allocated to different type of production that have different risk levels. The model is calibrated using monthly data from 2009 to 2016.

Results indicated multiple uncertainty sources (technological, cost of production, price of eggs) that vary according to the types of eggs. Given risk aversion parameters, producer would favor production modes with the lowest producers’ price variance, which correspond to free-run eggs. Results also indicated that in response to a greater intensity of risk aversion, the course of action producers may choose is to increase the relative production of free-run eggs.

The empirical limits of this research are found in the lack of quality data on producer prices and costs for specialty eggs. Future research could explore the relationship between the growing impact of egg for processing, which price is based on the US price, and its relationship with specialty eggs.

The findings of the study will be useful for policy makers and managers of eggs supply chain. This is important, given the recent announcement by Canadian’s large retailers and fast food companies to increase cage free eggs offering and, in some cases, eventually only selling these types of eggs.

This study adds to the understanding of the role of risk and uncertainty in the investment decision of egg producers and different mode of production, as well as in the development of the growing production of specialty eggs in Canada. It fills a gap in the literature regarding the impact of risk in Canadian egg production. This gap is likely explained by the perception of a lack of risk in this supply managed sector in Canada and its small size relative to other supply managed sector.

High risk is one of the most prominent characteristics of the Chinese construction industry, and it poses a significant threat to construction projects. Owing to initiatives aimed at achieving high efficiency, low carbon emissions, etc., industrialization of the construction industry has become an inevitable trend in China. However, it remains to be discussed whether industrialization of construction can reduce the risks entailed in construction projects compared with traditional construction. The paper aims to discuss these issues.

Based on the theory of risk life cycle, this paper proposes a practical risk assessment technique to assess the risk life cycle, including the risk occurrence time and potential financial losses. This technique is then applied to assess the differences between the risks involved in an engineering, procurement and construction (EPC) project executed via traditional and industrial production modes.

The results show that the total duration of risks in the industrial construction project is half of that in the traditional project. In addition, the expected financial loss entailed in the industrial construction project is 29 percent lower than that in the traditional construction project. Therefore, industrial construction has the potential to optimize risk performance.

There is no significant difference between the traditional and industrial construction models in terms of probability of risk. The maximum total loss might occur in the procurement stage in the case of industrial production, and in the construction stage in the case of traditional production. Moreover, the total expected loss from risk in the EPC project in the industrial production mode is only half of that in the traditional production route. This study is expected to provide a new risk evaluation technique and promote an understanding of the life cycle of risk management in the construction industry.

In the presence of “real effects” of disclosure in a production economy, this research aims to investigate the link between disclosure and cost of capital relating to different time periods: namely the post-disclosure cost of capital (the cost of capital subsequent to disclosure), the pre-disclosure cost of capital (the cost of capital for the period leading up to disclosure) and the overall cost of capital (the cost of capital across both periods). The author also extends the analysis to whether and how in the presence of a real effect of disclosure, investors' ex ante welfare might be affected.

This research is conducted via stylized models.

The author demonstrates that, first, in contrast to findings in a pure-exchange economy, in a production-based economy where disclosure affects firms' investment decisions, both the overall cost of capital and the investors' ex ante welfare can be affected by disclosure quality. As disclosure quality improves, the post-disclosure cost of capital may either increase or decrease, as may the pre-disclosure cost of capital. The change in the post-disclosure cost of capital is not fully offset by the change in the pre-disclosure cost of capital, and therefore the overall cost of capital can either increase or decrease. Second, a firm's profitability of existing and new production are critical factors in determining whether cost of capital increases or decreases with disclosure quality. The author characterizes conditions under which higher disclosure quality increases or decreases the disclosing firm's cost of capital over different time periods. Third, when disclosure affects interrelated firms' production decisions, the disclosing firm's overall cost of capital changes with disclosure quality, even when the marginal (unconditional) distribution of the disclosing firm's cash flow is not affected by the disclosure.

This research contributes to a largely unexplored but important area: the real effect of disclosure on the cost of capital.

The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.

From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.

This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.

The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.