In today's world, food waste has become a growing concern, mainly due to the behavior of consumers or actors, which poses a serious dilemma for a sustainable food supply. Prior research on food waste management has shed light on a few predictors of food waste behavior (FWB), mainly with a socio-cognitive lens. Thus, this empirical research seeks to explore household food waste determinants in Tehran city, Iran, from a more comprehensive perspective. To this end, food expenditure, purchasing power, food literacy, technical opportunities, awareness of consequences, and economic initiatives are integrated into the theory of planned behavior. Totally, 349 Iranian women, responsible for food preparation from purchasing to disposal in the family, were surveyed. The model developed in this research was tested employing partial least squares structural equation modeling (PLS-SEM). Our study reveals that being aware of the moral consequences (AMCs) is the most influential factor in predicting FWB. The findings show that, except for subjective norms, other main constructs of TPB, namely perceived behavioral control and attitude, considerably affect the behavioral intention to reduce food waste. Our study confirms that households with higher purchasing power are more likely to avoid food waste than those who spend more on food. Our findings suggest that food literacy and technical opportunities play a positive role in reducing food waste. Finally, households that receive economic initiatives are more likely to discard food.

Currently, blockchain adoption as an emerging technology is in its infancy in most developing countries such as Iran. However, there is a current paucity of empirical research focusing specifically on the antecedents of blockchain adoption in the context of these countries. This study aims to investigate the behavioral intention (BI) to use blockchain by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model, incorporating subjective and objective knowledge, trust in technology, and information literacy. The proposed structural model was assessed by partial least squares structural equation modeling (PLS-SEM) using the data from 275 senior managers of Iranian poultry supply chains. The results showed that effort expectancy and performance expectancy were the most influential variables in predicting the BI to use blockchain technology, respectively. Furthermore, objective knowledge had an impact on the intention to use blockchain. However, subjective knowledge was not found to have any effect. The proposed model including the moderating effects of trust in technology and information literacy showed a higher predictive power. Trust in technology moderated the relationship between performance expectancy and behavioral intention, and information literacy moderated the relationship between technical infrastructure, as one of the facilitating conditions, and behavioral intention. The theoretical and practical implications are discussed in the paper.

Context and purpose., The current research was conducted with the aim of identifying and prioritizing strategies for recognizing entrepreneurial opportunities in knowledge-based cooperative companies in the agricultural sector.Methodology/approach. In this research, the strengths, weaknesses, opportunities, and threats of recognizing entrepreneurial opportunities were identified based on theoretical foundations, and finally, using the opinion of 30 experts, it was monitored using the fuzzy Delphi method, and strategies for recognizing entrepreneurial opportunities were extracted. And after finalizing the strategies and giving them coefficient and weight with SPSS software, they were evaluated and ranked through the process of hierarchical analysis with the help of Expert Choice 11 software. At this stage, based on the Karjesi-Morgan table, 165 expert experts of knowledge-based cooperative companies active in the agricultural sector were selected as a statistical sample from among 281 companies.Findings and conclusions. Based on the SWOT analysis, the elements of the entrepreneurial opportunity recognition model were identified and after examining the twenty strategies, using the hierarchical analysis technique, the model elements were ranked and analyzed. The findings showed that agricultural knowledge-based businesses play a key role in creating and developing a knowledge-based economy, and economic growth and job creation are realized in accordance with the capacity of innovation and recognition of opportunities.Originality. This study presents the strategic model of recognizing entrepreneurial opportunities according to internal and external factors in knowledge-based cooperatives in the agricultural sector, which provides recognition of new opportunities and, subsequently, the improvement of knowledge-based management in the cooperative sector.

Food Loss and Waste (FLW), which are presented in the form of food waste, occur in different stages of the supply chain. One of the most important elements of managing food waste along the supply chain is to know the components and causes of this phenomenon. This study aims to Identify the causes of FLW in each stage of the chicken meat supply chain and provide strategies to reduce it. This study was conducted with a quantitative approach. The statistical population of the research consisted of all chicken meat producers in broiler chicken units related to integrated chicken meat supply chains in Mazandaran, Gilan and West Azerbaijan provinces (N = 820), and using Yamane's formula, the sample size was estimated to be 269 respondents. They were selected using available sampling. A questionnaire whose validity and reliability had been confirmed was used to collect data. To analyze the data, the technique of Hierarchical Component Models (HCM) was used according to the partial least squares (PLS) method. The results showed that among the seven causes of FLW, supply and demand changes are the most important causes of this phenomenon in the chicken meat supply chain. Also, weak infrastructures, lack of knowledge and skills, and weak operations and actions are among the other causes, respectively, with a slight difference. In this study, multiple strategies to reduce chicken meat waste are discussed based on the causes of its occurrence in each stage of the supply chain, which can be important for managers and planners.

The coronavirus pandemic (COVID-19) has affected all supply chains through severe disruption of logistics activities, production, and markets. This study aimed to survey the impact of the coronavirus on the poultry supply chain using an exploratory sequential mixed design. We first addressed those stages of the poultry supply chain disrupted in an ongoing pandemic, and then elaborated particular disturbances associated with each stage. This study was based on data collected from Iranian poultry industry owners and experts who had sufficient experience in agricultural supply chains as well. As the qualitative phase, the content analysis was conducted to identify the impacts of the coronavirus on the poultry supply chain. The results and conclusions that emerged from the qualitative phase were refined and weighted by the Fuzzy Delphi Method (FDM) and the Fuzzy Analytic Hierarchy Process (FAHP) respectively, in the quantitative phase. The results suggested that the pandemic has further affected the input supply as a stage in the poultry supply chain. This is probably because of the fact that the poultry industry is heavily dependent on inputs? flow. In addition, supply chain governance was seriously impaired due to the persistence of the pandemic. The coronavirus pandemic has significantly affected the stages that are most reliant on transportation. Finally, we found that a part of the disruptions that occur in the downstream of the supply chain is due to the epidemic?s direct adverse effects, and another part is due to indirect consequences received from the upstream. Our findings and implications can be useful in decision-making procedures during ongoing epidemics.

Nowadays, one of the solutions for companies to achieve collaboration functions, such as knowledge exchange and information sharing, is to take advantage of Mergers and Acquisitions (M & A) strategies. Agricultural Cooperatives are no exception to this, and in order to achieve such functions, they should use M & A strategies. In this regard, the current study aimed to identify the most appropriate Mergers and Acquisitions (M&A) strategy for collaboration of Agricultural Cooperatives from the viewpoint of experts. A multi-criteria decision-making approach based on Analytic Hierarchy Process (AHP) was used to prioritize M & A strategies. 16 executive and collegiate experts in the field of cooperation were purposefully selected and their opinions were gathered through questionnaire. The results revealed that among the six considered criteria for the selection of M & A strategies, the criterion of "identifying market needs" was the first priority. Also, the horizontal and conglomerate M & A strategies were in the first and last priority, respectively, based on the overall criterion.