• The Journal of Fisheries Business Administration
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• v.50 no.3
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• pp.43-57
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• 2019

Recreation specialization and consumptive orientation are two important constructs to understand anglers' attitudes and behaviors. Although theoretical explanations and previous studies in different countries addressed the relationships between the two constructs, limited support has been provided in a context of anglers in Korea. This study developed a conceptual model explaining the causal relationships between recreation specialization, anglers' preferences (activity-specific and activity-general) and consumptive orientation. An on-site survey was conducted to anglers in the city of Busan and Gyeongnam province in 2018. A total of 614 data were analyzed using Structural Equation Modeling The study results showed that recreation specialization positively and indirectly influenced consumptive orientation via anglers' activity-specific and activity-general preferences. Theoretical and practical implications are further discussed.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.161-166
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• 2017

In recent times, many people have problems of nutritional imbalance; lack or surplus intake of a specific nutrient despite the variety of available foods. Accordingly, the interest in health and diet issues has increased leading to the emergence of various mobile applications. However, most mobile applications only record the user's diet history and show simple statistics and usually provide only general information for healthy diet. It is necessary for users interested in healthy eating to be provided recommendation services reflecting their food interest and providing customized information. Hence, we propose a menu recommendation method which includes calculating the recommended calorie amount based on the user's physical and activity profile to assign to each food group a substitution unit. In addition, our method also analyzes the user's food preferences using food intake history. Thus it satisfies recommended intake unit for each food group by exchanging the user's preferred foods. Also, the excellence of our proposed algorithm is demonstrated through the calculation of precision, recall, health index and the harmonic average of the 3 aforementioned measures. We compare it to another method which considers user's interest and recommended substitution unit. The proposed method provides menu recommendation reflecting interest and personalized health status by which user can improve and maintain a healthy dietary habit.