Is There a Place for Hedonic Consumption in On-Line Shopping Addiction? ()
1. Introduction
The widespread use of the internet in digital life has led individuals to shop online, bringing about significant changes for consumers and meeting their physiological needs. The consumer, who spends all of his time in this environment, directs his shopping expenditures to both psychological and physiological needs, depending on the process. The attractive behavior of hedonic consumption, also known as the consumer’s spontaneous decision to make purchases without prior planning, appeals to individuals. The purpose of this study is to assess the impact of consumers’ addiction to online shopping on the process of hedonic consumption. The questionnaire form, which is a quantitative research method, was organized on Google form in this process and data were collected by applying the form to internet consumers in Istanbul. The results suggest that online shopping addiction has a positive effect on consumer’s hedonic shopping consumption behavior.
2. Online Shopping Addiction
Since the start of the new millennium, the Internet has swiftly permeated every aspect of life, and as a result, the world has begun to undergo significant transformations. The Internet has started providing consumers with the chance to shop at their convenience, in every aspect of their corporate and individual lives, including business and social settings (Süzen & Başal, 2023) . The most important use of the Internet is e-marketing (Murray, Gao, & Kotabe, 2011: pp. 252-269) . Since the end of 1990, the proportion of consumers shopping online for diversified products has been increasing. Research on the dynamics that encourage consumers to shop online has gained momentum as it is important for businesses to acquire and retain customers (Zhou et al., 2007: pp. 41-63) . Online shopping behavior is the act of purchasing products or services over the internet and is also referred to as “online buying behavior”. This process has some similarities with traditional shopping behavior (Liang & Lai, 2000: p. 10) . The consumers start the typical online shopping process by searching for online information about the products and services they need. They then examine a wide range of products and evaluates them in more depth, identifying suitable alternatives. They make comparisons between products and buy the most suitable one according to their own criteria (Häubl & Trifts, 2000: 4; Li & Zhang, 2002: 508) . Online consumer behavior is significantly different from traditional consumer behavior and has become an indispensable marketing channel for commercial enterprises. The development and popularity of social media platforms has led to rapid change in the marketing industry (Fong & Yazdanifard, 2014: 1-4) . Consumers use social media platforms for shopping and exchanging information about brands, products and services (Zhou et al., 2007: pp. 41-63) . Individuals may experience negative social and financial impacts over time due to uncontrollable shopping impulses. Historically, different terms have been used for this condition, such as oniomania, compulsive consumption, impulsive shopping and shopping addiction (Black, 2007: pp. 124-132) . The most important symptom of discomfort with non-purchase is the desire to buy and the feeling of relief after the purchase (Dittmar, 2004: pp. 411-450) . Unsuccessful efforts to control shopping are also an important indicator (O’Guinn & Faber, 1989: pp. 147-157) . Individuals with compulsive shopping disorder are constantly focused on the act of shopping (Faber & O’Guinn, 1992: pp. 459-469) . Consequences of compulsive shopping include debt, bankruptcy, criticism, criminality, legal and financial problems (Koran et al., 2006: pp. 1806-1812) . These serious results have attracted the attention of researchers and the consensus is that compulsive shopping disorder is a serious problem (Black, 2007) . Hedonic consumption is an activity that a person tries to do in order to eliminate the negative emotions he experiences instead of fulfilling his functional needs. In this behavior, when the consumer has to make a decision when purchasing the product, he generally prefers to buy the product that will benefit him. Trying to motivate himself by doing the opposite of this situation in order to get rid of negative emotions can be said as the side effects of this behavior. This behavior, which is an abnormal contradiction, has negative social and economic consequences as side effects.
Due to the widespread use of the Internet, compulsive shopping behavior has transitioned to the online shopping environment and has expanded significantly (Dittmar, 2004: pp. 411-450) . Online shopping has started to replace traditional shopping and has transformed shopping processes over the last decade (Li & Zhang, 2002: pp. 508-517) . The presence of features like user-friendliness, shopping incentives through notifications, and streaming capabilities to promote more purchases has resulted in a conducive environment for addiction (LaRose et al., 2003: pp. 225-253) . This has led to shopping addiction being considered as a subset of behavioral addictions (Grant et al., 2010: pp. 233-241) . However, it is now emphasized that this condition should be studied as a separate mental disorder (Maraz et al., 2016: pp. 408-419) . The widespread use of the Internet in digital life has led individuals to shop online, causing significant changes for consumers and meeting their physiological needs. As a result of digitalization, the internet has become a part of life by being widely used in all areas of life. Individual customers are increasingly using virtual stores to meet all their needs, including their basic physiological needs, online through these channels.
Studies on compulsive online shopping behavior have increased recently; however, there are limited studies in the literature. The Bergen Shopping Addiction Scale (BSAS) is one of the most fundamental studies of compulsive shopping behavior (Andreassen et al., 2016: 252-262) . When we look generally at the factors affecting the compulsive purchasing behavior, which is known as the type of shopping where the consumer uses his emotions rather than logic during purchasing, it can be said that there are demographic and social factors in addition to post-modern consumption, psychological states, personal factors, technology, promotional efforts and the brand. While there is post-modern consumption known as pleasure, entertainment and respect, stress, distress and depression also create psychological states. Personal factors such as mentality and understanding, as well as digitalization and technology, which are the innovations of the age, are also included among these factors. In addition to promotion and creating value for the brand, which will affect the purchase of the product and service by delivering it to the consumer, all cultural, social and demographic factors, in short, can be counted as factors in compulsive purchasing (Günaydin, 2021) . As research on compulsive shopping behavior progresses, it has been found that this disorder may apply to internet shopping as well, and this is because of the nature of the disorder and the advancement of technology, suggesting that it should possess more robust psychometric properties (Rose & Dhandayudham, 2014: pp. 83-89) . Today, the increasing prevalence of the internet and social media has led to a greater focus on compulsive shopping addiction. More research is needed to prevent and treat this addiction, which is particularly prevalent among young people and adults (Sahin & Süzen, 2023) . Increasing studies in this field will contribute to the development of more effective intervention and treatment methods for shopping addiction. Utilitarian values can influence consumers’ loyalty to a shopping website and their tendency to recommend it to others (Omarli & Parıltı, 2017: pp. 91-109) . Hedonic value perception is more effective in recommending shopping sites to others (Uygun et al., 2011: pp. 373-385) . Consumers’ attitudes, behaviors and opinions about online shopping play an important role in the design of websites, product differentiation, advertisements on digital platforms and strategic decisions of businesses (Turan, 2008: pp. 723-731) .
3. Hedonic Consumption
Hedonic consumption refers to a pleasure- and gratification-oriented approach and includes consumption tendencies towards individuals’ psychological desires and pleasures beyond their physical needs (TDK, 2023) . Hedonism, which is viewed as a moral philosophy centered around the ideas of pleasure and happiness derived from pleasure, can be classified into two categories: psychological hedonism and philosophical hedonism (Fettahlıoğlu, Yıldız, & Birin, 2014: pp. 307-331) . In modern societies, consumption is associated with psychological needs and hedonistic tendencies rather than basic physical needs. Hedonic consumption is based on pleasure and enjoyment rather than the tangible benefits of products and services (Özcan, 2010: pp. 29-39) . The attitudes of consumers towards products and their purchasing behavior are influenced by various factors including hedonic and utilitarian constructs, their living environment, preferences for online and offline shopping, and personal characteristics. By developing strategies based on these different motivations and preferences of consumers, businesses can achieve more effective marketing and sales results. Complex processes in the formation of consumers’ attitudes towards products can influence consumer tendencies and purchase intentions. In particular, hedonic and utilitarian constructs are important and independent components of attitudes towards products (Voss et al., 2003: pp. 310-320) . However, hedonic consumption can lead people and societies towards a narcissistic structure and lead to unsatisfied desires (Dal, 2017: 1-21) . Hirschman and Holbrook (1982) argued that the hedonic approach exhibits a more complex and emotional consumer behavior than traditional approaches. Consumers living in urban centers have higher hedonic shopping motivations, and consumers living in large cities are more likely to use shopping for entertainment purposes (Kim, 2006) . A study conducted by Türk (2018) discovered that consumers who have a high hedonic value tend to steer clear of online shopping. Retailers can use strategies such as store design, product display, packaging design and merchandising to encourage positive emotions in consumers (Park et al., 2006: 433-446) . Rook (1987) stated that hedonic factors are effective in consumers’ unplanned purchase behavior. Batra and Ahtola (1990) observed that hedonic factors determine preferences for some products and utilitarian factors determine preferences for other products. Dhar and Wertenbroch (2000) found that hedonic motivation is more dominant in decision-making or abandonment situations. Hausman (2000) stated that unplanned shopping is triggered by hedonic motivation, which affects product selection and leads to purchase behavior. Arnold and Reynolds (2003) emphasized that different customer segments have different hedonic motivations and store atmospheres should be organized according to these differences. Ahtola (1985) stated that hedonic and utilitarian attitudes are not the only factors determining consumer behavior, but they are one of the important factors. Consumer-related factors are equally as effective as technical factors when it comes to online shopping (Özcan, 2010: 29-39) . Utilitarian consumers prioritize factors like ease of use, product information, and online traffic features, whereas hedonic consumers prioritize enjoying their shopping experience (Doğrul, 2012: 321-331) . Sarkar (2011) stated that the perceived risk of online shopping is a problem for both hedonic and utilitarian consumers. According to Urminsky and Kivetz (2003) , consumers are more inclined to buy utilitarian goods at a faster rate than hedonic goods when considering the involved costs. The environment in which consumers live also influences their purchasing behavior. According to the study conducted on female academics working in state and foundation universities, it was found that there were variances in terms of hedonic motives between these two groups, despite Eken and Yazıcı (2015) stating that hedonic and utilitarian motives have an impact on purchasing behavior (Külter, 2016: 246-269) .
4. Method
Purpose and Importance of the Research
Thanks to this study, it has been determined that digitalization, which is evident in all sectors, brings about alterations in the shopping process of consumers. In this process, this study is carried out in order to determine to what extent it causes a change in the consumption habits of online shoppers in their instant shopping. The aim of this study is to determine the extent to which shopping addiction, together with its sub-variables, affects hedonic consumption, considering that it will be valuable for businesses as it will provide guidance in the later stages.
5. Population Sampling
All consumers who shop online in Istanbul province were included in the process as the population. The sample, consisting of 326 respondents aged 18 - 65, was randomly selected from the population using the descriptive analysis method. Sampling aims to represent the diversity of consumers in the population and collect data. Since the study could not reach all online users in Türkiye, the study was conducted on a sample basis. The researchers utilized the convenience sampling method. The population and sample used in the study were selected to reflect the online shopping behavior of Instagram users in Istanbul. In order to ensure the representation of consumers in the population, a certain number of respondents was selected by sampling method. The population in the province of Istanbul is represented by consumers who shop online on the Instagram platform, with a sample size of 326 respondents aged between 15 and 65 used for the study. In studies conducted in social sciences, the margin of error is generally accepted as 5%. For infinite degrees of freedom, t value is taken as 1.96 for a = 0.05 margin of error (Saruhan & Özdemirci, 2011: p. 198) . In studies conducted in social sciences, 95% or 99% is mostly used for confidence intervals. The most frequently used confidence interval is 95% (Gegez, 2015: p. 266) . In this study, in line with this information, it was deemed appropriate to use a 95% confidence interval.
6. Research Model
The conceptual model given in Figure 1 below investigates the impact of hedonic consumption habits and demographic variables in today’s world, based on the research model, and this model is especially related to consumers who prioritize pleasure and enjoyment in online shopping activities in the digital age.
7. Research Hypotheses
H1: Consumers’ online shopping addiction has an impact on consumers’ hedonic consumption.
H2: Demographic variables affect consumers’ online shopping addiction.
H3: Demographic variables are influential in the hedonic consumption process.
8. Data Collection Tool
The data of the study were collected within a one-month period between 01.30-March-2023 by applying the questionnaires prepared in Google Form to 326 respondents between the ages of 18 - 65 among the consumers who are online shoppers in the province of Istanbul. The questionnaire consists of two parts. The first part includes questions on demographic characteristics such as gender, age, education level, marital status, having children, employment status, income level and monthly online shopping amount. The second part includes the “Berger Shopping Addiction Scale” and “Hedonic and Utilitarian Consumption Behaviors” scale statements. The first variable, Bergen Shopping Addiction Scale (BSAS), is a scale developed by Andreassen et al., in 2016 . It was adapted into Turkish by Bozdağ and Alkar in 2018 . This scale is used to assess compulsive online shopping behavior. The scale has 28 questions in total and uses a 5-point Likert scale. Respondents rate each item on a scale of 0 to 7. The rating scale is based on 0 being “Strongly Disagree” and 7 being “Strongly Agree”. The Bergen Shopping Addiction Scale consists of six dimensions: mood modification, conflict, tolerance, relapse, withdrawal and problem. This scale is used to determine whether individuals’ online shopping has a compulsive nature. Scores obtained from the scale range from 0 to 112 and higher scores indicate an increased level of online compulsive shopping disorder. In this study, the reliability of the Bergen Shopping Addiction scale was found to be high as Cronbach’s Alpha = 0.886. The other variable, Hedonic and Utilitarian Consumption Behaviors Scale, was developed by Coşkun and Marangoz (2019) to measure the hedonic and utilitarian consumption behaviors of the respondents, and this scale was examined in two main dimensions: hedonic consumption and utilitarian consumption. Hedonic consumption is evaluated on five different sub-dimensions. These are Hedonic effect (7 items): Measuring the level of pleasure and enjoyment derived from consumption,
Hedonic adaptation (7 items): Measurement of post-consumption pleasure decline,
Passivity (6 items): Measuring the consumer’s feeling of being uncontrolled and dependent in the consumption process,
Impulsive tendency (6 items): Measuring spontaneous and impulsive behaviors in consumption,
Identity projection (6 items): Measuring the relationship between consumption and personal identity expression.
Utilitarian consumption is analyzed in two sub-dimensions: Goal orientation (5 items): Measures the realization of consumption in line with specific goals and needs. In this study, the reliability of Hedonic and Utilitarian Consumption Behaviors scale was found to be high as Cronbach’s Alpha = 0.899. Control orientation (5 items): It measures that control and rationality are prioritized in the consumption process. In the scale, a 5-point Likert scale was used and respondents rated the statements between 1 (“strongly disagree”) and 5 (“strongly agree”). In this study, the reliability of the Hedonic and Utilitarian Consumption Behaviors scale was found to be high as Cronbach’s Alpha = 0.899. Time and cost are the most important limitations in data collection.
9. Statistical Analysis of Data
The data collected from the respondents in the study were compiled using Microsoft Excel 2010 program and evaluated in computer environment with SPSS 22.0 statistical program. Frequency and percentage analyzes were used to determine the descriptive characteristics of the respondents. Mean and standard deviation statistics were used in the evaluation of the scale. The relationships between the dimensions determining the scale levels of the respondents were examined with the help of Pearson correlation and linear regression analyses. Missing value analysis and normality test were performed after collecting the data, before conducting the test. The findings section presents both the results of the data analysis and the comments regarding these results.
10. Findings
The findings regarding the descriptive characteristics of the respondents are as follows.
Distribution of Respondents According to Descriptive Characteristics
According to gender, 162 (49.7%) of the respondents were male and 164 (50.3%) were female. According to age, 21 (6.4%) 18 - 25, 44 (13.5%) 26 - 30, 71 (21.8%) 31 - 35, 77 (23.6%) 36 - 40, 56 (17.2%) 41 - 45, 57 (17.5%) over 45. According to educational status, 25 (7.7%) of the respondents completed high school and below, 26 (8.0%) completed associate degree, 213 (65.3%) completed undergraduate, and 62 (19.0%) completed graduate. According to marital status, 192 (58.9%) of the respondents were married and 134 (41.1%) were single. According to having children, 199 (61.0%) of the respondents said yes, 127 (39.0%) said no. According to employment status, 202 (62.0%) of the respondents said yes, 124 (38.0%) said no. According to the income level of the respondents, 102 (31.3%) of them (31.3%) said their expenses were higher than their income, 139 (42.6%) said their expenses were equal to their income, and 85 (26.1%) said their income was higher than their expenses.
According to the monthly online shopping amount, 153 (46.9%) of the respondents have 1000 TL and below, 70 (21.5%) have 1001 - 2000 TL, 35 (10.7%) have 2001 - 3000 TL, 68 (20.9%) have over 3000 TL.
Online shopping addiction and hedonic consumption behavior average scores are given in Table 1 below. For the respondents, it was determined that the mean of “online shopping addiction” is 16.325 ± 16.229 (Min = 0; Max = 71), the mean of “hedonic consumption behavior” is weak 2.086 ± 0.675 (Min = 1.03; Max = 4.09), the mean of “hedonic effect” is weak 2.012 ± 0.677 (Min = 1; Max = 5), the mean of “hedonic adaptation” is weak 1.989 ± 0.666 (Min = 1; Max = 4. 4), “passivity” mean was weak 2.419 ± 0.897 (Min = 1; Max = 4.88), “impulsive tendency” mean was weak 2.072 ± 0.854 (Min = 1; Max = 4.83), “identity projection” mean was weak 1.872 ± 0.679 (Min = 1; Max = 4.62).
Correlation analysis data between online shopping addiction and hedonic consumption behavior scores is given in Table 2. When examining the correlation analyses between online shopping addiction, hedonic consumption behavior, hedonic effect, hedonic adaptation, passivity, impulsive tendency, and identity
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Table 1. Online shopping addiction, hedonic consumption behavior score averages.
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Table 2. Correlation analysis between online shopping addiction, hedonic consumption behavior scores.
*<0.05; **<0.01; Pearson Correlation Analysis.
projection scores, a weak positive correlation of r = 0.324 (p = 0.000 < 0.05) was found between hedonic consumption behavior and online shopping addiction, a weak positive correlation of r = 0.334 (p = 0.000 < 0.05) between hedonic effect and online shopping addiction, a very weak positive correlation of r = 0.245 (p = 0.000 < 0.05) between hedonic adaptation and online shopping addiction, a weak positive correlation of r = 0.262 (p = 0.000 < 0.05) between passivity and online shopping addiction, a weak positive correlation of r = 0.297 (p = 0.000 < 0.05) between impulsive tendency and online shopping addiction and a weak positive correlation of r = 0.302 (p = 0.000 < 0.05) between identity projection and online shopping addiction.
Data regarding the variables of the effect of online shopping addiction on hedonic consumption behavior can be seen in Table 3. The regression analysis conducted to determine the cause and effect relationship between online shopping addiction and hedonic consumption behavior was found to be significant (F = 38.026; p = 0.000 < 0.05). 10.2% of the total change in Hedonic Consumption Behavior is explained by online shopping addiction (R2 = 0.102). Online Shopping Addiction increases the level of hedonic consumption behavior (ß = 0.324).
The regression analysis conducted to determine the cause and effect relationship between online shopping addiction and hedonic effect was found to be significant (F = 40.772; p = 0.000 < 0.05). 10.9% of the total change in Hedonic Effect is explained by online shopping addiction (R2 = 0.109). Online Shopping Addiction increases the level of hedonic affect (ß = 0.334).
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Table 3. The effect of online shopping addiction on hedonic consumption behavior.
The regression analysis conducted to determine the cause and effect relationship between online shopping addiction and hedonic adaptation was found to be significant (F = 20.636; p = 0.000 < 0.05). 5.7% of the total change in Hedonic Adaptation is explained by online shopping addiction (R2 = 0.057). Online Shopping Addiction increases the level of hedonic adaptation (ß = 0.245).
The regression analysis conducted to determine the cause and effect relationship between online shopping addiction and passivity was found to be significant (F = 23.972; p = 0.000 < 0.05). 6.6% of the total change in the level of Passivity is explained by online shopping addiction (R2 = 0.066). Online shopping addiction increases the level of passivity (ß = 0.262).
The regression analysis conducted to determine the cause and effect relationship between online shopping addiction and impulsive tendency was found to be significant (F = 31.298; p = 0.000 < 0.05). 8.5% of the total change in Impulsive Tendency is explained by online shopping addiction (R2 = 0.085). Online Shopping Addiction increases the level of impulsive tendency (ß = 0.297).
Regression analysis to determine the cause and effect relationship between online shopping addiction and identity projection was found to be significant (F = 32.570; p = 0.000 < 0.05). 8.9% of the total change in Identity Projection is explained by online shopping addiction (R2 = 0.089). Online Shopping Addiction increases the level of identity projection (ß = 0.302).
11. Discussion, Conclusion and Recommendations
This study aims to examine the factors associated with online shopping addiction and hedonic consumption, the links and interactions between them. These factors include hedonic consumption behavior, hedonic effect, hedonic adaptation, passivity, impulsive tendency and identity projection. The demographic data of the respondents were evaluated with variables such as age, gender, education level, marital status, having children, employment status and income level. Monthly online shopping amounts of the respondents were also analyzed. The study involved distributing a questionnaire to 326 respondents, and the data collected were analyzed using the statistical program SPSS 22.0. In the study, the demographic characteristics of the respondents were determined through frequency and percentage analyses. The relationships between the research variables were examined using Pearson correlation and confirmatory regression analyses. There will be a constant difference between men and women physically and biologically. For this reason, the concept of gender is effective in many areas. One of them is marketing. People with different sexual identities also show different purchasing behaviors. Therefore, businesses should pay attention to these issues when developing strategies according to their marketing mix. Businesses should pay attention to psychological gender as well as biological gender when segmenting the market. It will be more effective to segment the digital market according to the gender identities of consumers.
According to the research results, there are positive correlations between online shopping addiction and hedonic consumption behavior, hedonic effect, hedonic adaptation, passivity, impulsive tendency and identity projection scores. These results indicate that as online shopping addiction rises, so do hedonic consumption behaviors and other psychological factors. The study reveals that online shopping addiction is an important social and individual problem and has an impact on hedonic consumption behaviors and other psychological factors. In this context, policy makers, educational institutions and families should raise awareness about online shopping addiction and ensure that individuals are aware of hedonic consumption behaviors and other psychological factors to reduce the negative effects of this addiction. Suggestions for future studies include increasing the sample size, examining the relationships between online shopping addiction and hedonic consumption behaviors in different geographical regions and cultures, and conducting comparative studies. Moreover, more comprehensive scales and variables can be used to thoroughly investigate the relationship between online shopping addiction and hedonic consumption behaviors. For example, the relationship between online shopping addiction and specific product and service categories can be examined in terms of consumer profiles and personality traits.
Excessive use of the internet, which is common among adolescents, can limit them socially and make them addicted. In this period when adolescents’ identity formation takes place, they tend to shop online through peer groups and influencers. Excessive time spent on the internet also increases the tendency to addiction there. In this period, it is important to be knowledgeable about only a certain product group and to raise awareness in online shopping among adolescents who are inclined to buy new products on the market. Adolescents’ risk perceptions against online shopping should be created and the time they spend on the internet should be reduced. They should be given the opportunity to make rational and logical decisions rather than emotions in physical, psychological, sociological and economic dimensions.
Experimental studies can be conducted on the effectiveness of interventions and preventive strategies to cope with online shopping addiction. Such studies can contribute to the development of effective practices for managing and reducing online shopping addiction. Educational programs can play an important role in dealing with online shopping addiction. This research is thought to contribute to the literature in order to better understand the relationship between online shopping addiction and hedonic consumption behavior and to develop strategies to manage this addiction. Considering the impacts of online shopping addiction on society and individuals, policy makers and the e-commerce sector should organize appropriate regulations and information campaigns. Furthermore, educational institutions and families should raise awareness of online shopping addiction and work to improve young people’s knowledge and skills in this area.