No 2/2024, June

Analysing Purchase Preference Towards Geographical Indications (GIs) Using Consumer Segmentation Approach

ABSTRACT

Consumers of local food products often face a dilemma regarding their purchase decisions due to the non-availability of information that is required to assess the quality of the product. To reduce this information asymmetry, the Geographical Indication Registry in India issues a Geographical Indication tag (GI tag) as a community right to the growers of local special products originating from a region, town or country. The GI tag symbolises uniqueness, curtails counterfeit products' spread, and reduces information asymmetry. This study has taken a select case of Udupi Mattu Gulla Brinjal, a GI horticulture produce grown by a community-based enterprise (CBE) in the Udupi District of South India. This research work aims to study and analyse consumer preference towards Udupi Mattu Gulla Brinjal (GI) using a consumer segmentation approach. The Principal Component Analysis technique has been used to identify statements with discriminatory power. Subsequently, the statements of research importance have been used to identify consumer segments using a two-step clustering approach. The study results have identified three important consumer clusters based on the analysis of consumer preference characteristics. Thereafter, marketing strategies have been proposed after analysing the profile of each segment. The study is undertaken as a response to an initiative from the Sustainable Development Goals (SDGs) Coordinating Centre, Government of India, to partner the development of agriculture in the local area of Udupi District. The objectives of the study are consistent with SDG goal 11 (sustainable communities) and SDG goal 12 (responsible consumption).

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Factors Affecting the Adoption of Recommended Fertilizer Doses by Wheat Farmers in the Casablanca-Settat Region of Morocco

ABSTRACT

Despite the economic advantages of introducing new agricultural technologies into the production system, their rate of adoption in Morocco remains relatively low. The objective of this article is to study the factors that hinder the adoption of these new technologies. We address the case of the recommended fertilizer doses (RFD). The study employs a probit model with a stratified random sampling approach.The data were collected from 297 farmers in the Casablanca-Settat region using a face-to-face interview method and analyzed through R software. The results of the study show that the main barriers are related to access to information and bank credit, government incentive, production orientation, distance to the market as well as age, and level of education.

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Increasing or Decreasing Scale? The Pros and Cons of Farm Size for Financial Sustainability

ABSTRACT

The article focuses on the question of optimal farm size in the context of contemporary agricultural challenges such as rapid population growth, climate change, and limited natural resources. The analysis shows that farm economic size can have a significant impact on financial performance indicators including productivity, profitability, liquidity, solvency, and sustainability. The article provides a detailed overview of the pros and cons of different farm economic sizes and their impact on financial sustainability, drawing on academic literature, available data, and statistical methods. The results indicate that larger farms have lower factor productivity but higher solvency. Smaller farms on the other hand have higher profitability and productivity. Medium-sized farms are characterized by high liquidity and financial autonomy.

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Modeling Asymmetric Effects of Exchange Rate Fluctuations on Agricultural Trade Balance: Evidence from Iran and Iraq

ABSTRACT

The exchange rate plays a crucial role in foreign trade and has asymmetric effects. This study examines the asymmetric effects of exchange rate volatility on the trade balance in the agricultural sector between Iran and Iraq, using the non-linear ARDL model from 1998 to 2020. The results show that Iraq's GDP and oil price fluctuations positively affect the trade balance. In contrast, Iran's GDP and the U.S. economic sanctions against Iran have negative and significant effects on the trade balance of Iran with Iraq in the agriculture sector. The results do not confirm the existence of the J-curve effect in the trade relations between Iran and Iraq, because an increase in the bilateral exchange rate, in both the long-run and short-run, improves the trade balance of Iran with Iraq in the agriculture sector. Furthermore, the positive and negative fluctuations of the bilateral exchange rate have different effects on the trade balance. While the devaluation of the national currency does not cause a downward trend in the short run, the exchange rate policy can improve the trade balance from the beginning.

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Practical use of Agriculture 4.0 digital technologies to meet the EU's strategic goals in Czech agriculture

ABSTRACT

The implementation of precision technology procedures is declared in EU documents, including the implementation of these technologies in all areas of production, production, trade, including all areas of everyday life of the population. The article deals with the use of IT technologies in activities dealing with land management: i.e. crop production including landscape maintenance. In this context, precision technologies are used in agriculture, crop and livestock production, horticulture, forestry and comprehensive maintenance of the agricultural landscape. With remote sensing, all land areas are monitored, data is stored, and the whole process takes place continuously. The data is displayed in information maps that perfectly map the properties of the monitored area. Today, the development of the information society and specialized internet services of the state administration would not be possible without precise technologies and information portals. These are portals for the public needs of citizens or a specific professional community, and these must be user-friendly, clear, intuitive, visually interesting, trustworthy and complete in content. The article deals with a detailed analysis of the Czech Farmer's Portal from multiple angles, including state-of-the-art tools such as the AMS system (AMS, 2023). This is a new way of monitoring agricultural areas using a satellite system. On the basis of the analysed services, deficiencies are identified and suggestions for improvement are presented.

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Product Differentiation in Food-Product Markets: Evidence from the Asian Instant Noodles Industry

ABSTRACT

This study investigates product differentiation, both in vertical and horizontal dimensions, in the instant noodles industry. It first presents theoretical models that predict firms' product differentiation behaviour before testing the theories using the case of instant noodles industries in three Asian countries: Indonesia, India, and Japan. The vertical differentiation behaviour is examined using the ANOVA test followed by the Bonferroni correction to investigate which brands exhibit the most evident vertical differentiation behaviour. The horizontal differentiation strategy is explored using a descriptive analysis method. Using information on the selling prices and product variants of instant noodles leading brands in each country, the empirical findings confirm the models' predictions. The study claims that companies apply the principles of 'minimum differentiation' as their vertical differentiation strategy and 'maximum differentiation' when differentiating horizontally. These strategies are implemented by choosing prices close to each other and producing distinguishable variants from competitors. These findings bring the theories of product differentiation into a real-life application and provide insights into how firms in the food products industry behave in differentiating their products.

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Analysing Household Food Consumption in Turkey Using Machine Learning Techniques

ABSTRACT

The fluctuations in food prices have highlighted the significance of analysing the factors influencing household food consumption. Recent advancements in data analysis have opened new avenues for investigating this subject. While studies have employed novel data analysis methods to examine the factors impacting household food consumption, the effect of the chosen analysis method on the research outcome remains unexplored. In this study, we aimed to investigate household food consumption in Turkey between 2012-2019 using various data analysis techniques (Linear Regression, Support Vector Machine, Random Forest, eXtreme Gradient Boosting, and Multi-Layer Perception). Our findings reveal that income emerged as the most influential factor in household food consumption across all methods. However, the impact of other factors varied depending on the method employed. This suggests that the method chosen to analyse factors other than income in studies of this nature can significantly impact the results. Researchers should exercise caution when selecting their analysis method.

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The Role of Social Media on Green Food Consumption Intention in Hanoi, Vietnam

ABSTRACT

This study aims to discuss the role of social media in shaping consumer attitudes in the Vietnamese context. The research examines the impact of green attitude, green customer value, and social media on environmental concerns, subjective norms, and perceived green value concerning green consumers' food purchase intention. The study utilizes data from a survey conducted among 483 consumers in Hanoi, Vietnam, and adopts the Theory of Planned Behavior (TPB) as the initial framework for studying green food purchase intention. We modify and extend the TPB model by incorporating cultural, social, and personal psychological factors relevant to green food consumption. The findings of this study contribute to the understanding of the factors influencing consumer purchase intention in Hanoi, Vietnam. The results demonstrated the influence of social media on subjective norms, environmental concerns, and perceived green value, which in turn affect green food purchase intention among Vietnamese consumers. These results imply that to increase green food preferences among consumers, governments should also consider social media-based education programs to build an understanding of green food and sustainable consumption and emphasize the outstanding benefits of green products for the environment and society. In addition, marketers should pay attention to providing complete information and advertisements about green food products on social media.

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Fish-NET: Advancing Aquaculture Management through AI-Enhanced Fish Monitoring and Tracking

ABSTRACT

This study seeks to enhance aquaculture and fishery management using artificial intelligence, focusing on Nigerian catfish farming. The methodology encompasses a sequence of steps from data collection to validation. A dataset, primarily composed of aerial imagery from catfish ponds and supplemented with additional data from the internet, formed the foundation of this research. By leveraging computer vision and deep learning techniques, the data were processed to assess the potential of the three distinct cutting-edge object detection models. Based on various evaluation metrics to gauge their effectiveness in fish detection tasks, the Faster R-CNN emerged as the optimal model, boasting a superior balance of precision and recall. This model was subsequently integrated with an object-tracking model and deployed as an application, yielding promising results in terms of fish detection and tracking. The findings in this study suggest that AI-driven tools can automate monitoring processes, significantly increasing accuracy and efficiency in resource utilization.

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The Revealed Comparative Advantage of Agri-Food Industries in Selected Countries in the Central and Eastern Europe: Gross-Versus Value-Added Trade Flows

ABSTRACT

The aim of the article is to interrogate comparative advantage of agrarian and food processing sectors in the context of the agri-food global value chains in particular countries in the Central and Eastern Europe using gross trade and value-added trade data from TiVA database. The Normalized revealed comparative advantage index (NRCA) was applied to analyze comparative (dis)advantage of agrarian and food processing sectors from 1995 to 2020. The article contributes twofold: First, NRCA pairs of indices calculated using gross trade and value-added trade data are mostly consistent. The analysis identifies for what areas and countries there is a discrepancy; second, it reveals comparative advantage of agrarian and food processing sectors in each country separately. It indicates different trajectories of development among countries in the Central and Eastern Europe. These results are complementary to the results of studies that evaluated comparative advantages on the product basis.

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