Food Industry

In recent years, global reports on the irreparable damage of human economic activities to the environment, the need for efficient management systems capable of reducing pollutants and waste management and the optimal use of non-renewable resources, more than any other another time is needed. Therefore, in order to achieve this, a study was presented with the aim of designing and validating a model for green quality management in the food industry. The present study is an exploratory combination that through qualitative strategies with library study methods and grounded theory, a conceptual model is obtained and then through a quantitative strategy of structural equations with Smart PLS approach, the conceptual model of the research is tested and its goodness is calculated. Is. In the qualitative section, after extensive study in the theoretical literature on the subject and taking notes, as well as through theoretical and purposeful sampling with a selection of 24 experts and officials, a semi-structured interview was conducted. In the quantitative part, according to the Vinzy rule, 192 managers and experts of the food industry have been selected as a sample and the data have been collected using a researcher-made questionnaire. According to the findings of the qualitative section and after coding, finally 5 main categories and 19 sub-categories were extracted that green management of human resources from causal conditions and green management thinking as underlying conditions, technology management and environmental management system as intervening conditions. Green management innovation was selected as a strategy and also green supply chain as a consequence of green quality management model. The results show that the conceptual model designed with grounded theory approach was approved by experts and the GOF criterion was used to validate the model, which is higher than the level of fit classification based on the theory of Wetzel’s et al. (2009) which indicates that has it.

The purpose of this study is evaluate the out-of-home advertising model of consumer products in the food industry of Fars province. The model under test was designed using the grounded theory method through interviews with 20 marketing and advertising experts. Structural equation analysis has been used to analyze the data and according to the proposed model in relation to the effect of latent variables. Data were collected by distributing a questionnaire among the marketing and sales staff of Fars food industry companies. The statistical population of this study includes the employees of the marketing and sales department of Fars food industry companies. Due to the unlimited number of statistical population, a cluster model was used to select the sample. For this purpose, 246 people were selected and evaluated in a targeted manner, but in the end, 227 completed and returned questionnaires were statistically analyzed. According to the results, the two important models of model fit (RMSEA) and (CMIN / DF) and other indicators are in an acceptable range, which can be said that the model has a good fit. Also, the research results showed that Out-Of-Home advertising can It should lead to customer loyalty, credibility, mental engagement, intention to buy and increase sales.

This study will seek to provide the best and most efficient ordering policies for different levels of the perishable food supply chain in order to maximize the overall profit of the chain, and minimize social and environmental damage. Our supply chain includes a four-level supply chain of suppliers, manufacturers, distributors and retailers. In addition to the components of perishable products, the dimensions of sustainable development have been fully investigated and taken into account in the entire chain. In this study, due to the main nature of perishable materials, the statistical population includes 9 dairy companies and 9 meat and protein companies, which in total 18 dairy, meat and protein companies in Fars province, Iran, were studied. Network Data Envelopment Analysis (DEA) was used to analyze the data and WinQsb was used to model and solve it. According to the results, the average efficiency of the supply chain of production and distribution of perishable products in the financial year studied by the research in the suppliers sector was equal to 0.9634. This average was equal to 0.9899 in the producers sector, 0.9903 in the distributors sector and 0.9707 in the retailers sector. Therefore, the average efficiency in the study shows that the most inefficiency problems of the studied companies are related to the supplier sector. Also, the overall average efficiency is equal to 0.9950.

This paper discusses the application of the Technology Development Envelope (TDE) as a road mapping tool in combination with the Delphi method and the Analytic Hierarchy Process (AHP). The method helps policy and decision-makers in organizations strategically manage emerging technologies by mapping their anticipated development path. The paper focused on creating a Technology Development Envelope (TDE) for artificial intelligence (AI) technologies in the food industry. In the first step, an expert panel identified a list of AI technologies applicable to the food industry. A hierarchical decision-making model, comprising 5 criteria and 24 sub-criteria for technology evaluation, was extracted from the literature and validated using the Delphi method. The Analytic Hierarchy Process (AHP) was used to determine the relative importance of criteria and sub-criteria for evaluating the identified technologies. At this stage, the most important criteria considered were food safety and social and political acceptance of the technology. The expected value of each technology was calculated over different periods, resulting in the development of the Technology Development Evaluation (TDE) for AI technologies in the food industry within a ten-year horizon. The analysis of the future indicates that technologies such as computer vision, robotics, industrial automation, and machine learning will undergo continuous improvements over time and eventually become dominant technologies in the food industry. These advancements can lead to an increase in quality and efficiency within the food industry. Finally, sensitivity analysis was conducted to test the model's sensitivity and explore how policymakers' extreme strategies affect the model's outputs.