A study on personality traits and shopping online

Uşaklı, Hakan

doi:10.34739/zn.2019.48.05

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…McCrae and Costa (2003) determined a framework in the personality model based on personality theory consisting of openness to experience agreeableness, conscientiousness, neuroticism, and extraversion. Extraversion is defined as excitability, sociability, talkativeness, assertiveness, and a high level of emotional expressiveness in a person (Usakli, 2020). Extraverted people prefer interpersonal relationships (Mooradian & Swan, 2006).…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

The influence of hedonic values and extraversion on online impulse buying: Empirical evidence from Indonesia

Helmi

Oesman

Kaltum

et al. 2023

Innovative Marketing

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The purpose of this study is to analyze Indonesian consumer hedonic values, extraversion, and online impulse buying, as well as to examine the influence of consumer hedonic values and extraversion personality on impulsive online buying. This study uses a quantitative research method that employs descriptive and associative tools. The primary data were gathered through social media surveys of Indonesian consumers who buy goods through e-commerce. Of the 440 respondents who received questionnaires, only 400 completed them accurately. According to the survey, at least 75% of respondents shop online regularly. The study’s findings describe three types of Indonesian online consumers: those with hedonic values, those with reasonably high extrovert personalities, and those prone to online impulse buying. Path analysis results indicate that both hedonic value and extraversion have a significant influence on online impulse buying. Hedonic consumers enjoy online shopping, and as a result, they discover items they had not previously considered purchasing without careful consideration. On the other hand, extroverted consumers who are outgoing, passionate, and pleasant in social situations are more likely to be interested in impulsive online buying. These results provide online business owners with necessary guidance by demonstrating the importance of developing a website that is not only informative but also visually appealing and engaging to trigger impulse buying. Acknowledgment This study was supported by a research grant from Universitas Padjadjaran, Indonesia.

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Section: Literature Review and Hypothesesmentioning

confidence: 99%

The influence of hedonic values and extraversion on online impulse buying: Empirical evidence from Indonesia

Helmi

Oesman

Kaltum

et al. 2023

Innovative Marketing

View full text Add to dashboard Cite

show abstract

“…They also express their emotions openly and seek out exciting and stimulating experiences. On the other side, introverts are generally more reserved and prefer quiet environments [22]. Based on the results of this study, it might be summarized that more extroverted individuals would rather react positively if they gain additional articles or accessories appropriate to the already selected product, whereby after optimization Random Forest achieves 71% accuracy of MAPE.…”

Section: Resultsmentioning

confidence: 81%

Predicting User Behavior in e-Commerce Using Machine Learning

Ketipov,

Angelova,

Doukovska

et al. 2023

Cybernetics and Information Technologies

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Each person’s unique traits hold valuable insights into their consumer behavior, allowing scholars and industry experts to develop innovative marketing strategies, personalized solutions, and enhanced user experiences. This study presents a conceptual framework that explores the connection between fundamental personality dimensions and users’ online shopping styles. By employing the TIPI test, a reliable and validated alternative to the Five-Factor model, individual consumer profiles are established. The results reveal a significant relationship between key personality traits and specific online shopping functionalities. To accurately forecast customers’ needs, expectations, and preferences on the Internet, we propose the implementation of two Machine Learning models, namely Decision Trees and Random Forest. According to the applied evaluation metrics, both models demonstrate fine predictions of consumer behavior based on their personality.

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