Impact of Attitude towards Eco-Friendly Products on Dining Intention and Willing to Pay Premium in order to Improve Dining Behavior among Consumers in Russia Far-East

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Nasser Alafes, Siti Aida Samikon


Restaurant industry causes lots of environmental problems. Green attributes implementation addresses these problems in order to illuminate or lessen restaurant environmental impact. Restaurants and dining industry is an important sector in Far East Russia especially with the dining habits of citizens.  If emerged with the fact that restaurants are one the highest sectors in harming the environment, the eco-friendly dining behaviour of customers and food providers become essential to protect the environment. Identifying the effect of attitude, practices, and personal traits on the intention and behaviour of dining can contribute to the local and international efforts to save environment. The study aims to measure the antecedents of consumers’ intention and actual behaviour in choosing restaurants and foods based on eco-friendly consideration in Russia Far East. The proposed model for this study includes attitude towards eco-friendly products, intention to eco-friendly dining, willing to pay premium, and dining behavior. The research design considered for this study is classified under exploratory study and hypothesis testing; therefore, the research is mainly belongs to the quantitative approach. The population for this research is all the residents who live in a Russia Far East. According to the official Russian statistics, there are around 8.4 million people living in the Russia Far East, distributed among different age groups. The targeted sample size is 385 subjects that respect the G*Power effective sample size (153) and the minimum sample size for PLS analysis (40). While the target sample is 385, but the plan is to collect 150% of the sample to secure enough proper sample after data screening. Data obtained from the survey is analyzed by utilizing the software Statistical Package for the Social Sciences (SPSS 25) and SmartPLS 2.0.

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