อิทธิพลของการรับรู้ความเสี่ยงต่อการตัดสินใจซื้อสินค้าออนไลน์จากธุรกิจขนาดย่อมของผู้บริโภคในเขตกรุงเทพมหานคร: Influence of Consumer Perceived Risk on Online Shopping Decisions from Small Businesses in Bangkok - Niwarat Wijitkusawat นิวรัตน์ วิจิตรกุลสวัสดิ์; Pratuang Phumpatrakom ประเทือง ภูมิภัทราคม; Puttipong Amsintonr พุฒิพงศ์ เอี่ยมสินธร; Laddawan Munkkunk ลัดดาวัลย์ มั่งคั่ง (SOCIAL SCIENCES RESEARCH AND ACADEMIC JOURNAL, 2023)
The objectives of this research were 1) to study consumers’ perceived risk of puying online products from small businesses; 2) to study consumers’ decision to buy online products from small businesses; 3) Study the relationship between perceived risk of online shopping decisions from small businesses. and 4) Create a forecasting equation for risk perception that influences consumers’ decision to buy online products from small businesses in Bangkok. The sample group is 385 consumers in Bangkok who have experienced online shopping from small businesses. The tools used for data collection were item survey questionnaires and 5-level estimating scales, divided into 3 sections. Statistics used in data analysis were frequency, percentage, mean, and standard deviation. Pearson correlation coefficient and multiple regression analysis. From the research, it was found that 1) Consumers’ perceived risk of buying online products from small businesses 2) Studying consumer’s decision to buy online products from small businesses whole were at a high level 3) Puying decision online products from small businesses of consumers whole were at a high level was found to have a positive correlation statistically significant at the 0.01 level. 4) The results of a study of risk perception influencing consumers’ decision to buy online products from small businesses in Bangkok. There were 6 variables with statistical significance at the 0.05 level, which can be sorted in descending order as follows: safety risks, financial risk, psychological risk, outcome risk, social risk and opportunity/time risk Accordingly, the forecasting equations can be written in the form of raw scores and standard scores, respectively, as follows: = 0.020+0.330(X6)+0.218(X2)+0.139(X4)+0.117(X1)+0.099(X3)+0.086(X5) 2Ŷ= 0.365(X6)+0.242(X2)+0.153(X4)+0.143(X1)+0.105(X3)+0.078(X5)