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The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.

A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.

The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.

The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.

This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.

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.

Motivated by the wide application of procurement strategies in retailing, this paper aims to examine the effect of procurement strategies on decisions and profits and strategic inventory (SI) is considered.

The game-theoretic models are developed under a two-period fresh product supply chain (FSC), and consist of the mode of purchasing products only in the first period without SI (Scenario S), the mode of purchasing products in every period without SI (Scenario T) and the mode of purchasing products in every period with SI (Scenario TS).

Conducting the calculating and comparing, some major findings can be concluded. In general, two-period purchasing strategies (Scenarios T and TS) promote a higher freshness-keeping effort than the single buying strategy (Scenario S). Regarding the pricing strategy, SI and Scenario S can both contribute to obtaining a lower wholesale price, the retailer's pricing is relatively complicated and hinges on the consumer's sensitivity to freshness-keeping effort and the holding cost. Besides, comparing the sales quantity and the profit, the authors find that Scenario TS stimulates more demands and brings more profits for the manufacturer. However, Scenario TS is not the optimal selection for the reason that SI sometimes hurts the retailer and even the whole supply chain. Whereas, when the holding cost is in a certain range, Scenario TS will lead to a win-win situation.

The main findings of this study can give the enterprises some advice on the procurement strategies of fresh products and the decisions of pricing and the freshness-keeping effort.

This paper evaluates consumers' responses to claims regarding fruit sustainability. The authors compared the effects of this factor on consumers' moral satisfaction and purchase intention with respect to 12 sustainability claims.

A mixed-model experiment was conducted with seven fruits (i.e. guava, pineapple, red apple, green apple, red grape, green grape and avocado) to evaluate the effects of the 12 sustainability claims on purchase intention through moral satisfaction, relative to a control condition.

The results show that claims of supporting local farmers are those that move consumers the most. Claims regarding local farmers' production positively affect moral satisfaction and purchase intention.

This paper takes a consumer behavior approach to sustainability, enabling organizations to consider consumer behavior outcomes that could affect their strategic investments and commitment to social responsibility.

Food-related studies have not produced consistent results with respect to the relevance that sustainability claims have for consumers. This study differs from previous studies, as it focuses on fruit, a product that is important for social and environmental sustainability issues. This study demonstrates that, in the case of fruit, sustainability arguments are meaningful to young consumers through the mediating effect of moral satisfaction. Thus, the effect of claims is predicted by the meaning these arguments have for the consumer.

Este artículo evalúa las respuestas de los consumidores a los argumentos de sostenibilidad en una fruta. Se comparan los efectos de este factor en la satisfacción moral y la intención de compra de los consumidores con respecto a 12 argumentos de sostenibilidad.

Se realizó un experimento de modelo mixto con siete frutas (guayaba, piña, manzana roja, manzana verde, uva roja, uva verde y aguacate) para evaluar los efectos de los 12 argumentos de sostenibilidad sobre la intención de compra a través de la satisfacción moral, en relación con una condición de control.

Los resultados muestran que las afirmaciones de apoyo a los agricultores locales son las que más influyen en los consumidores. Las afirmaciones relativas a la producción de los agricultores locales afectan positivamente a la satisfacción moral y a la intención de compra.

Este trabajo adopta un enfoque de la sostenibilidad basado en el comportamiento del consumidor, lo que permite a las organizaciones considerar los resultados del comportamiento del consumidor que podrían afectar a sus inversiones estratégicas y a su compromiso con la responsabilidad social.

Los estudios relacionados con la alimentación no han arrojado resultados consistentes respecto a la relevancia que los argumentos de sostenibilidad tienen para los consumidores. Este estudio difiere de los anteriores, ya que se centra en la fruta, un producto importante por cuestiones de sostenibilidad social y medioambiental. Este estudio demuestra que, en el caso de la fruta, los argumentos de sostenibilidad son significativas para los consumidores jóvenes a través del efecto mediador de la satisfacción moral. Así, el efecto de los argumentos se predice por el significado que estos tienen para el consumidor.

With the empirical evidence on the purchase behaviour of tinned tomatoes, food labelling and the safety consciousness of consumers in Ghana were examined.

Primary data were obtained from 130 consumers. Descriptive statistics, factor analysis and multinomial probit analysis were applied.

Consumers use tinned tomatoes for cooking because of its easy accessibility in nearby shops, guaranteed constant supply, attractive package, it being affordable/cheaper, its better colour, advertisement/promotion, and longer shelf life. There is a low level of food safety consciousness among consumers since only one-fifth read labels on tinned tomatoes very often, and one-fifth do not read labels at all. Consumers frequently check on tinned tomatoes' most essential information: brand/type, manufacturing and expiry dates, and weight/volume. Age, residential status, contact information, nutritional benefits and affordability influence the choice of retail brand of tinned tomatoes. The health label consumer segment and conventional label consumer segment were identified, with the majority being the former.

The sample size used for the study could be improved in terms of number and geographical coverage. This is because the study was limited to only one main urbanised area in Ghana. Therefore, it will be worthwhile for a further study to be conducted by comparing urban and rural consumers in Ghana and other countries within Africa, to either validate or reveal a different trajectory of consumer behaviour relevant to marketing, policy and practice.

Tomato paste (tinned tomatoes) is consumed in almost all homes in Africa, but there are food scare concerns about tinned tomatoes due to reported cases of adulteration with unhealthy materials such as starch and food colour, leading to negative health implications on consumers. This makes the reading of tinned tomato labels very crucial. Thus, it is of policy relevance to investigate consumers' reading behaviour of label information on tinned tomatoes in Ghana. However, previous studies on food labelling focussed on food and nutrition labelling and implications of food labelling on consumers' purchase behaviour, with most of them outside Africa.

This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.

A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.

Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.

The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.

This study aims to identify the importance of agricultural and rural modernization and propose ways to accelerate such modernization.

The authors systematically examine the crucial role that the modernization of agriculture and rural areas plays in China, discuss the current issues in China's modernization from the perspective of agricultural and rural fields and propose practical measures to accelerate agricultural and rural modernization.

This study emphasizes the importance of China's agricultural and rural modernization in five aspects: the significance inherent in theories and experiences, the high complexity of the modernization work, the extreme difficulty of the task, the particular sluggishness of the process and its specific impact on the overall development. Numerous shortcomings in domestic agriculture and rural areas have been identified. The following actions can help achieve modernization: strengthening strategic leadership, providing policy support and constructing supportive measures.

This paper summarizes the significance of agricultural and rural modernization, highlights the issues regarding such modernization and suggests effective solutions.

Artificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of such a new advanced technology. The aim of the paper is to map the state-of-the-art of AI applications in agriculture, their advantages, barriers, implications and the ability to lead to new business models, depicting a future research agenda.

A structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.

Findings underline the multiple uses and advantages of AI in agriculture and the potential impacts for farmers and entrepreneurs, even from a sustainability perspective. Several applications and algorithms are being developed and tested, but many barriers arise, starting from the lack of understanding by farmers and the need for global investments. A collaboration between scholars and practitioners is advocated to share best practices and lead to practical solutions and policies. The promising topic of new business models is still under-investigated and deserves more attention from scholars and practitioners.

The paper reports the state-of-the-art of AI in agriculture and its impact on the development of new business models. Several new research avenues have been identified.

Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management. However, the agricultural insurance and futures markets in China are incomplete. This study aims to analyze the price-risk-management behaviors of large-scale farmers under incomplete market conditions, with a focus on the interconnections between large scale farmers' subjective preferences (risk preferences, time preferences), liquidity constraints and their price risk management.

The authors construct an analysis framework to reveal the impact of large-scale farmers' risk preferences, time preferences and liquidity conditions on their price-risk-management behaviors under incomplete market conditions. Using data from field surveys and subjective preference experiments involving 409 large-scale grain farmers in China, an empirical analysis was conducted using the bivariate probit model.

The results show that risk-averse farmers will use risk transfer (such as contract farming) and risk diversification (such as multi-period sales) to avoid price risk. However, farmers subject to liquidity constraints and strong time preferences will not choose risk diversification, and the interaction between time preferences and liquidity constraints will strengthen this decision. The larger the farm-management scale, the greater the impact.

The authors focus on rapidly developed large-scale farm management in China. Appropriate price risk management is required by large-scale farmers due to their substantial operating risks. Considering the incomplete conditions of agricultural insurance and futures markets, the results of this study will help identify behavioral characteristics of large-scale farmers and optimize their price-risk-management strategies, further stabilizing large-scale farm management.

This study aims to investigate the intention of adopting a technological service innovation that is a mix-mode consumer shopping service in the retailing context.

A modified extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model is tested by using data on a real example named “Mkolay” which is a new mix-mode consumer shopping service. Data are collected from 217 participants and analyzed by using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Research findings show that the customers' intention to use the new mix-mode consumer shopping service is particularly influenced by performance expectations, effort expectations, social influence and personal innovativeness.

In designing a mix-mode consumer shopping service, keeping the design as simple and easy to use as possible seems to increase the intention of adoption. Additionally, collaborating with reference figures or influencers could be instrumental to spread the new service to a wider audience hence increase the likelihood of adoption. Practitioners should also use new technologies in different ways to attract and surprise customers, especially taking into account the technological profile of potential users.

This study contributes to the literature of technological service innovation adoption by revealing the factors affecting the intention of adoption of mix-mode consumer shopping service in the retailing context with a modified UTAUT2 model.