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Online Shopping Addiction: Symptoms, Causes and Effects

dc.authorwosid Doğan Keskin, Ayten/Aab-4389-2020
dc.contributor.author Gunuc, Selim
dc.contributor.author Keskin, Ayten Dogan
dc.date.accessioned 2025-05-10T17:39:40Z
dc.date.available 2025-05-10T17:39:40Z
dc.date.issued 2016
dc.department T.C. Van Yüzüncü Yıl Üniversitesi en_US
dc.department-temp [Gunuc, Selim] Yuzuncu Yil Univ, Dept Comp & Instruct Technol Educ, TR-65100 Van, Turkey; [Keskin, Ayten Dogan] Univ Hlth Sci, Ankara Numune Training & Res Hosp, Republ Turkey Minist Hlth, Turkish Inst Publ Hosp, Ankara, Turkey; [Keskin, Ayten Dogan] Univ Hlth Sci, Ankara Numune Training & Res Hosp, Ankara, Turkey en_US
dc.description.abstract One of the various forms of technology used to make life easier is online shopping. Reasons for which one might prefer online shopping over real life shopping include such factors as ease of search, lower prices, a variety of goods, time saved, ease of use, entertainment, promotions, and impulsive behaviors in the shopper. A number of individuals have found themselves addicted to online shopping due to a lack of self-control. This study aims not only to reveal participants' reasons for preferring online shopping, but also to define and describe the hedonic nature of online shopping addiction. The study follows a mixed method design in which both qualitative and quantitative methods are applied in the data collection process. Qualitative data was collected from a total of 105 participants who had stated that they frequently used the internet to shop using the snowball sampling method. Quantitative data, on the other hand, was collected by asking open-ended questions to 18 randomly selected individuals from the original 105 participants. The researcher collected data through face-to-face and internet interviews over a period of five months. The sample group was composed of 80% women (n = 84) and 20% men (n = 21) with participants' ages ranging from 18 to 55 (mean: 29). The tools used to collect data were an open-ended questionnaire, a form soliciting demographic information, and the Hedonic Shopping Scale. Quantitative data were subjected to descriptive analyses, a t-Test, ANOVA analyses, and in order to classify hedonic shopping scores, to a two-stage clustering analysis. Qualitative data, on the other hand, were analyzed using content analysis. This work concludes with an evaluation of the qualitative and quantitative data on online shopping followed by a discussion on factors contributing to online shopping addiction as well as related concepts. en_US
dc.description.woscitationindex Emerging Sources Citation Index
dc.identifier.doi 10.15805/addicta.2016.3.0104
dc.identifier.endpage 364 en_US
dc.identifier.issn 2148-7286
dc.identifier.issn 2149-1305
dc.identifier.issue 3 en_US
dc.identifier.scopusquality Q4
dc.identifier.startpage 353 en_US
dc.identifier.uri https://doi.org/10.15805/addicta.2016.3.0104
dc.identifier.uri https://hdl.handle.net/20.500.14720/14964
dc.identifier.volume 3 en_US
dc.identifier.wos WOS:000398343200003
dc.identifier.wosquality N/A
dc.language.iso en en_US
dc.publisher Turkish Green Crescent Soc en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Online Shopping Addiction en_US
dc.subject Online Shopping en_US
dc.subject Buying en_US
dc.subject Technology Addiction en_US
dc.subject Hedonic Shopping en_US
dc.title Online Shopping Addiction: Symptoms, Causes and Effects en_US
dc.type Article en_US

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