Original Article
Split Viewer
J Cosmet Med 2023; 7(1): 29-37
Published online June 30, 2023
Influence of consumer innovativeness and cosmetic selection attributes on purchase intention of eco-friendly cosmetics
Su-Jin Park, MA1 
, You-Jeong Kim, PhD2 , Oh-Hyeok Kwon, PhD3 , Jeong-Min Lee, PhD3
1Department of Beauty Art, Graduate School, Hansung University, Seoul, Rep. of Korea
2Department of Associate Degree of Cosmetology, Yeoju Institute of Technology, Yeoju, Rep. of Korea
3Department of Beauty Design Management, Hansung University, Seoul, Rep. of Korea
Correspondence to :
Oh-Hyeok Kwon
E-mail: beauty67@hansung.ac.kr
This article is excerpted from the Master of Arts thesis of Su-Jin Park.
© Korean Society of Korean Cosmetic Surgery and Medicine (KSKCS & KCCS)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: Owing to the COVID-19 pandemic, consumers’ interest in the environment has increased. This has also led to increased interest in eco-friendly products and cosmetics. To increase consumers’ purchase intention of eco-friendly cosmetics, this study explores the influence of consumer innovativeness and cosmetic selection attributes on their purchase intention of eco-friendly cosmetics.
Objective: This study aims to provide practical marketing data for eco-friendly cosmetic companies and contribute to increasing consumers’ purchase intention.
Methods: This study collected data through self-administered surveys and analyzed the collected data using SPSS ver. 24.0.
Results: Our statistical analysis shows that the functional, hedonic, cognitive, and social innovativeness of consumer innovativeness and the brand, quality, and price of cosmetic selection attributes positively (+) influence purchase intention of eco-friendly cosmetics.
Conclusion: Our statistical results show that consumer innovativeness and cosmetic selection attributes positively influence the purchase intention of eco-friendly cosmetics. We expect that targeting consumers who have high consumer innovativeness and favor brand-, quality-, and price-centered marketing can increase consumers’ positive purchase intention.
Keywords: consumer innovativeness, consumer preference, eco-friendly cosmetics, purchase intention, selection attributes
Introduction
Owing to the COVID-19 pandemic in 2020, factories shut down and human activity diminished, significantly reducing air and water pollution [1]. These rapid environmental changes have resulted in enhancing consumer interest in environmental issues. Kearney, a global management consulting firm, reported that half of the US consumers responded that they became more interested in the environment after the COVID-19 pandemic [2]. Consumer interest in the environment, in turn, leads the development of eco-friendly products. Nowadays, consumers are interested not only in the main ingredients of products, but also in the production process. Therefore, the demand for eco-friendly management has grown, resulting in a greater preference for products created using eco-friendly methods that avoid chemical production facilities and animal testing [3]. In the cosmetics market, products made with environmental considerations have received significant attention. Eco-friendly cosmetics, manufactured using natural materials, are evolving into an independent market segment [4].
Consumer innovativeness
Consumer innovativeness is the tendency to adopt new products and embrace change more quickly and easily than other consumers. This definition has attracted the attention of marketers, gained importance, and is being actively researched [5]. Innovativeness is the degree to which one pursues something new, rather than continuing with, or choosing, existing options. Hence, consumer innovativeness can positively impact the intention to purchase new products [6]. Previous studies define consumer innovativeness as the extent to which consumers quickly and easily adopt novelty within a social system [7]. Additionally, it is defined as the preference for purchasing innovative products based on the awareness of, and interest in, the latest products [8]. With reference to these studies, we categorize consumer innovativeness into functional, hedonic, cognitive, and social innovativeness. Functional innovativeness refers to the tendency to seek convenience and efficiency of products. Hedonic innovativeness is the tendency to seek pleasure from one’s purchases. Social innovativeness refers to the tendency to seek differentiation from others in a group, through purchases. Cognitive innovativeness is the tendency to seek logical and intellectual stimulation from a product. Innovation can be applied from various perspectives. However, this does not appear identical for all subjects or fields, and may yield varying results in different categories [9]. Innovative consumers are positive about new experiences and stimuli. Hence, these consumers exhibit more positive attitudes toward new products or services than others [10]. They are open to new things, have a strong sense of adventure and willingness to take risks [11], and share the peculiarity of liking experimental and bold things. These consumers make independent consumption decisions and bear the risks associated with new products. As a result, innovative consumers are proactive and creative people with appropriate information search skills and “trend literacy” [12].
Cosmetic selection attributes
Cosmetic selection attributes refer to factors that consumers value and consider important when purchasing cosmetics. Selection attributes are crucial for product selection. Consumers associate certain attributes with potential outcomes [13]. These attributes provide a method for analyzing consumer behavior, and companies can utilize them as effective marketing factors [14]. Selection attributes are also indispensable for understanding consumers because they are considered important in product selection [15]. Consequently, researchers, including those in the field of cosmetics, have conducted numerous studies on consumer purchase intention related to selection attributes. However, research on eco-friendly cosmetics is limited. Selection attributes are classified into brand attributes, price, quality, trustworthiness, and perceived value [16], and brand, quality, price, and perceived value [3]. Based on prior research, this study divides cosmetic selection attributes into brand, quality, and price. Brand refers to a mark that distinguishes one’s product from others. Quality refers to the features that satisfy consumers (e.g., product ingredients, performance, characteristics, appearance, design, and color). Price signifies the total value that consumers pay for a product.
Purchase intention of eco-friendly cosmetics
With advancing technology, quality differences between products have become negligible, therefore the attribute of quality has become a given. Beyond quality, consumers also seek to interact with products that fit their lifestyles [17]. Earlier, cosmetics were perceived as products used solely for beauty, owing to low awareness about cosmetic ingredients among consumers. However, with heightened environmental awareness in recent times, modern consumers have begun to seek products genuinely intended for humans, leading to the emergence of eco-friendly cosmetics [18]. Changes in consumers’ environmental awareness influence corporate sustainability strategies [19]. In October 2017, Korea Trade-Investment Promotion Agency (KOTRA) hosted the “2017 Global Cosmetic Trends Forum,” which emphasized that harmful effects of environmental pollution on humans are intensifying, but simultaneously, awareness of eco-friendly production and consumption is spreading worldwide [20]. Eco-friendly cosmetics are gaining popularity owing to the public backlash against pollution-causing industries. Consumers desire a clean environment and prefer pure plant-based ingredients [21]. Thus, the eco-friendliness domain has expanded from raw materials to production, manufacturing, and disposal [3]. Previous studies have defined eco-friendly cosmetics as those that are made solely from natural extracts and primarily eco-friendly components, and whose production processes do not harm the environment [22]. Eco-friendly cosmetics are environmentally friendly, and use not only sustainable materials as their main components, but also minimal and recyclable packaging [23]. In this study, the purchase intention of eco-friendly cosmetics refers to consumer willingness to purchase them, which signifies the possibility of purchasing behavior. Purchase intention is crucial for businesses because it helps predict and understand consumer purchase patterns [24]. Marketers consider purchase intention to be the ultimate indicator of advertising effectiveness. Thus, positive purchase intentions among consumers should be prioritized [25]. Therefore, purchase intentions have been widely studied in the field of cosmetics.
Materials and methods
Survey respondents and procedure
For our empirical investigation, we conducted a survey targeting adult males and females, who purchased cosmetics, in South Korea. Self-administered surveys were used to collect the data. We collected preliminary data from 30 surveys from October 14th–16th, 2022. We distributed 301 surveys between October 17th and 24th, 2022. After excluding 10 invalid responses, 291 responses were used as the final data. The study was approved by the Korea Institute of Human Resources Development in Science & Technology (KIRD, 2022-R-40543).
Data analysis method
We analyzed the collected data using the statistical package SPSS Ver. 24.0. We then performed frequency analysis to identify the demographic characteristics of the participants. Factor and reliability analyses were used to analyze the validity and reliability of the measurement tools. We also conducted a correlation analysis to examine the correlation between the independent and dependent variables. Finally, we performed a regression analysis to analyze the impact of consumer innovativeness and cosmetic selection attributes on the purchase intention of eco-friendly cosmetics among customers.
Results
This study investigated the influence of consumer innovativeness and cosmetic choice attributes on the intention to purchase eco-friendly cosmetics. The findings are as follows:
First, consumers’ functional, social, hedonic, and cognitive innovativeness positively influences their intention to purchase eco-friendly cosmetics [11,26]. Thus, it can be said that consumer innovativeness affects the intention to purchase in various fields.
Second, the brand, quality, and price of cosmetics have a positive impact on the intention to purchase eco-friendly cosmetics [17,27]. In other words, the brand, quality, and price among cosmetic choice attributes significantly influence the intention to purchase cosmetics, suggesting a need for marketing strategies that utilize these attributes.
One limitation of this study is that the sample group was concentrated in their 20s, and empirical analyses of other age groups were lacking. In future research, it will be necessary to collect data from a balanced representation of all age groups for a more comprehensive study.
Demographic characteristics of respondents
Of the respondents, 72.5% and 27.5% were female and male, respectively. In terms of age, 46.4%, 23.0%, 18.2%, and 12.4% of the participants were in their 20s, 40s, 50s or older, and 30s, respectively. Regarding the highest level of education, 52.9% were currently attending, or had graduated from, a four-year university. This was followed by 17.2% of the respondents, who were currently attending, or had graduated from graduate school, 15.8% who had graduated from high school, and 14.1% who were currently attending or had graduated from a 2-year college. Regarding marital status, 59.1% and 40.9% of the respondents were unmarried and married, respectively, indicating a higher proportion of unmarried respondents. Regarding monthly income, 43.3% earned less than 2 million KRW (Korean won), 21.6%, earned 2 million to less than 3 million KRW, 14.1% earned 3 million to less than 4 million KRW, 13.1% earned 5 million KRW or more; and 7.9% earned 4 million to less than 5 million KRW. Regarding current occupation, 30.2% were students, 22.7% were office workers, 11.3% were in other professions, 10.7% were service workers, 10.0% were professionals, 9.6% were self-employed, and 5.5% were homemakers (Table 1).
-
Table 1 . Demographic characteristics of survey participants
Item Number % Sex 291 100 Male 80 27.5 female 211 72.5 Age (yr) 291 100 20s 135 46.4 30s 36 12.4 40s 67 23.0 ≥50 53 18.2 Education 291 100 High school graduation 46 15.8 Completed/graduate from a two-year college 41 14.1 Completed/graduate from a university 154 52.9 Enrolled in/completed/graduate school 50 17.2 Marital status 291 100 Single 172 59.1 Married 119 40.9 Monthly average income (Korean won) 291 100 <2 million 126 43.3 ≥2 to <3 million 63 21.6 ≥3 to <4 million 41 14.1 ≥4 to <5 million 23 7.9 ≥5 million 38 13.1 Occupation 291 100 Student 88 30.2 Office worker 66 22.7 Service worker 31 10.7 Professional 29 10.0 Self-employed 28 9.6 Homemaker 16 5.5 Other 33 11.3
Validity and reliability analysis of measurement tools
The total variance that explained consumer innovativeness was 72.170%. The KMO measure of sampling adequacy was 0.873, and Bartlett’s test of sphericity result was χ2=1,872.254, p<0.001, indicating that the factor analysis was appropriate. Previous research has classified confidence interval sub-factors into social, functional, cognitive, and hedonic innovativeness. According to the reliability analysis results, Cronbach’s α was 0.862, 0.741, 0.799, and 0.845 for social, functional, cognitive, and hedonic innovativeness, respectively, indicating the reliability of all items (Table 2).
-
Table 2 . Factor analysis and reliability analysis of consumer innovativeness
Social
innovativenessHedonic
innovativenessCognitive
innovativenessFunctional
innovativenessI enjoy using products that no one else has used before. 0.804 I want to be the first to purchase attention-grabbing products that everyone envies. 0.796 I like products that differentiate me from others. 0.727 I like using products that leave a deep impression on others. 0.714 Having new products always excites me. 0.827 Using new products energizes my daily life. 0.818 Discovering products I didn’t know before is enjoyable and fun. 0.652 I enjoy keeping up with the latest information. 0.871 I often look for media that provides new information. 0.849 I like being exposed to new ideas. 0.652 If a new product is released that saves me time (steps) compared to existing products, I will purchase it right away. 0.846 If a new product is released with new features not found in the one I’m currently using, I will purchase it right away. 0.809 If a new product has better functionality than the one I’m currently using, I will purchase it right away. 0.624 Total 2.817 2.277 2.266 2.021 % Variance 21.670 17.516 17.433 15.550 % Cumulative 21.670 39.186 56.620 72.170 Cronbach’s α 0.862 0.845 0.799 0.741
The total variance explained by the selection attributes was 65.106%. The KMO measure of sampling adequacy was 0.815, and Bartlett’s test of sphericity result was χ2=1,710.755, p<0.001, indicating that the factor analysis was appropriate. Previous research has shown that the subfactors of selection attributes are quality, price, and brand. The reliability analysis results showed that Cronbach’s α was 0.884, 0.752, and 0.744 for quality, price, and brand, respectively, indicating the reliability of all items (Table 3).
-
Table 3 . Factor analysis and reliability analysis of cosmetic selection attributes
Quality Price Brand Quality is important when purchasing eco-friendly cosmetics. 0.851 Functionality is important when purchasing eco-friendly cosmetics. 0.801 Feel is important when purchasing eco-friendly cosmetics. 0.794 Ingredients are important when purchasing eco-friendly cosmetics. 0.787 Availability of price discounts is important when purchasing eco-friendly cosmetics. 0.824 Price per volume is important when purchasing eco-friendly cosmetics. 0.757 Price is important when purchasing eco-friendly cosmetics. 0.709 Availability of samples is important when purchasing eco-friendly cosmetics. 0.546 Brand is important when purchasing eco-friendly cosmetics. 0.779 Brand recognition is important when purchasing eco-friendly cosmetics. 0.751 I compare brands when purchasing eco-friendly cosmetics. 0.640 Brand endorsement models are important when purchasing eco-friendly cosmetics. 0.602 When purchasing eco-friendly cosmetics, I make a purchase after seeing the brand’s advertisement. 0.579 Total 3.477 2.505 2.481 % Variance 26.748 19.271 19.086 % Cumulative 26.748 46.020 65.106 Cronbach’s α 0.884 0.752 0.744
The total variance explaining the intention to purchase eco-friendly cosmetics was 68.180. The KMO measure of sampling adequacy was 0.872, and Bartlett’s test of sphericity yielded the result, χ2=743.504, p<0.001, indicating that the factor analysis was appropriate. The reliability analysis results showed that Cronbach’s α was 0.882, indicating the reliability of all items (Table 4).
-
Table 4 . Factor analysis and reliability analysis of purchase intention of eco-friendly cosmetics
Factor loading I am willing to recommend eco-friendly cosmetics to others. 0.893 I plan to invest time in purchasing eco-friendly cosmetics. 0.840 I intend to purchase eco-friendly cosmetics. 0.812 I will consider purchasing eco-friendly cosmetics first when purchasing cosmetics. 0.796 I am willing to gift eco-friendly cosmetics to acquaintances. 0.784 Total 3.409 % Variance 68.180 % Cumulative 68.180 Cronbach’s α 0.882
Analysis of correlations between measurement variables
Functional innovativeness of consumer innovativeness showed positive correlation with hedonic (r=0.466, p<0.001), social (r=0.417, p<0.001), and cognitive innovativeness (r=0.411, p<0.001), which belong to the same variable. Moreover, it showed positive correlations with the brand (r=0.326, p<0.001), quality (r=0.354, p<0.001), and price (r=0.214, p<0.001) selection attributes. Additionally, we found a positive correlation with purchase intention (r=0.488, p<0.001).
Hedonic innovativeness was positively correlated with social (r=0.672, p<0.001) and cognitive innovativeness (r=0.454, p<0.001), which belong to the same variable. Moreover, it showed positive correlations with the brand (r=0.402, p<0.001), quality (r=0.303, p<0.001), and price (r=0.223, p<0.001) selection attributes. In addition, we found a positive correlation with purchase intention (r=0.452, p<0.001).
Social innovativeness was positively correlated with cognitive innovativeness (r=0.464, p<0.001), which belongs to the same variable. Moreover, it showed positive correlations with the brand (r=0.379, p<0.001), quality (r=0.266, p<0.001), and price (r=0.244, p<0.001) selection attributes. In addition, we found a positive correlation with purchase intention (r=0.394, p<0.001).
Cognitive innovativeness showed positive correlations with brand (r=0.301, p<0.001), quality (r=0.349, p<0.001), and price (r=0.192, p<0.01) selection attributes. In addition, we found a positive correlation with purchase intention (r=0.437, p<0.001).
Brand selection attributes showed positive correlations with quality (r=0.309, p<0.001) and price (r=0.381, p<0.001), which belong to the same variable. In addition, we found a positive correlation with purchase intention (r=0.416, p<0.001).
Quality of selection attributes showed a positive correlation with price (r=0.394, p<0.001), which belongs to the same variable. In addition, we found a positive correlation with purchase intention (r=0.500, p<0.001). Price was also positively correlated with purchase intention (r=0.336, p<0.001) (Table 5).
-
Table 5 . Correlation analysis
Consumer innovativeness Selection attributes Purchase intention 1 2 3 4 5 6 7 Consumer innovativeness 1 1 2 0.466*** 1 3 0.417*** 0.672*** 1 4 0.411*** 0.454*** 0.464*** 1 Selection attributes 5 0.326*** 0.402*** 0.379*** 0.301*** 1 6 0.354*** 0.303*** 0.266*** 0.349*** 0.309*** 1 7 0.214*** 0.223*** 0.244*** 0.192** 0.381*** 0.394*** 1 Purchase intention 0.488*** 0.452*** 0.394*** 0.437*** 0.416*** 0.500*** 0.336*** 1 Mean 3.44 3.30 3.03 3.53 3.17 4.38 3.52 3.72 Standard deviation 0.969 1.06 1.081 0.963 0.837 0.789 0.892 0.878 1, functional innovativeness; 2, hedonic innovativeness; 3, social innovativeness; 4, cognitive innovativeness; 5, brand; 6, quality; 7, price.
***p<0.001.
Regression analysis results
Through regression analysis, this study aims to verify the influence of consumer innovativeness and cosmetic selection attributes on the purchase intention of eco-friendly cosmetics.
We conducted regression analysis, taking consumer innovativeness and purchase intention as the independent and dependent variables, respectively. The regression model for consumer innovativeness had an F-value of 128.801 (p<0.001) and the Durbin–Watson value was 1.906, which was close to 2, not to 0 or 4. This indicates that there was no correlation between the residuals. Hence, this can be considered an appropriate regression model. This explains 30.8% of the dependent variables. Our analysis showed that consumer innovativeness positively (+) influences purchase intention (β=0.555, p<0.001).
We conducted a regression analysis with the functional innovativeness of consumers as the independent variable, and purchase intention as the dependent variable. The regression model for functional innovativeness has an F-value of 90.519 (p<0.001). The Durbin–Watson value was 1.927, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 23.9% of the dependent variables. Our analysis shows that functional innovativeness positively (+) influences purchase intention (β=0.488, p<0.001).
We conduct a regression analysis using the hedonic innovativeness of consumers as the independent variable and purchase intention as the dependent variable. The regression model for hedonic innovativeness has an F-value of 74.261 (p<0.001). The Durbin–Watson value was 1.940, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 20.4% of the dependent variables. Our analysis shows that hedonic innovativeness positively (+) influences purchase intention (β=0.452, p<0.001).
We conducted a regression analysis with social innovativeness of consumers as the independent variable and purchase intention as the dependent variable. The regression model for social innovativeness has an F-value of 53.056 (p<0.001). The Durbin–Watson value was 1.882, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 15.5% of the dependent variables. Our analysis shows that social innovativeness positively (+) influences purchase intention (β=0.394, p<0.001).
We conducted a regression analysis with cognitive innovativeness of consumers as the independent variable and purchase intention as the dependent variable. The regression model for cognitive innovativeness has an F-value of 68.338 (p<0.001). The Durbin–Watson value was 1.845, close to 2, not to 0 or 4, indicating no correlation between the residuals. Therefore, it can be considered an appropriate regression model. This explains 19.1% of the dependent variables. Our analysis shows that cognitive innovativeness positively (+) influences purchase intention (β=0.437, p<0.001).
We conducted regression analysis with cosmetic selection attributes and purchase intention as the independent and dependent variables, respectively. The regression model for the cosmetic selection attributes had an F-value of 122.518 (p<0.001). The Durbin–Watson value was 1.936, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 29.8% of the dependent variables. According to the analysis, cosmetic selection attributes positively (+) influence purchase intention (β=0.546, p<0.001).
We conducted regression analysis with brand and purchase intention as the independent and dependent variables, respectively. The regression model for the brands had an F-value of 60.465 (p<0.001). The Durbin–Watson value was 1.921, close to 2, not to 0 or 4, indicating no correlation between the residuals. Therefore, this can be considered an appropriate regression model, explaining 17.3% of the dependent variables. The analysis shows that the brand positively (+) influences purchase intention (β=0.416, p<0.001).
We conducted regression analysis with cosmetic quality and purchase intention as the independent and dependent variables, respectively. The regression model for quality had an F-value of 96.487 (p<0.001), and the Durbin–Watson value was 1.833, close to 2, not to 0 or 4. This indicates no correlation between the residuals. Hence, this can be considered an appropriate regression model, explaining 25.0% of the dependent variables. The analysis shows that quality positively (+) influences purchase intention (β=0.500, p<0.001).
We conduct a regression analysis with price and purchase intention as the independent and dependent variables, respectively. The regression model for price has an F-value of 36.887 (p<0.001). The Durbin–Watson value was 1.894, close to 2, not to 0 or 4. This indicates no correlation between the residuals. Hence, this can be considered an appropriate regression model, explaining 11.3% of the dependent variables. According to the analysis, price positively (+) influences purchase intention (β=0.336, p<0.001) (Table 6).
-
Table 6 . Regression analysis results
Unstandardized coefficient Standardized coefficient t p B Standard error β (Constant) 1.730 0.181 9.549*** <0.001 Consumer innovativeness 0.604 0.053 0.555 11.349*** <0.001 F=128.801 (p<0.001), Durbin–Watson=1.906, R2=0.308 (Constant) 2.205 0.166 13.264*** <0.001 Functional innovativeness 0.442 0.047 0.488 9.514*** <0.001 F=90.519 (p<0.001), Durbin–Watson=1.927, R2=0.239 (Constant) 2.490 0.151 16.511*** <0.001 Hedonic innovativeness 0.375 0.043 0.452 8.617*** <0.001 F=74.261 (p<0.001), Durbin–Watson=1.940, R2=0.204 (Constant) 2.756 0.141 19.484*** <0.001 Social innovativeness 0.320 0.044 0.394 7.284*** <0.001 F=53.056 (p<0.001), Durbin–Watson=1.882, R2=0.155 (Constant) 2.318 0.177 13.122*** <0.001 Cognitive innovativeness 0.399 0.048 0.437 8.267*** <0.001 F=68.338 (p<0.001), Durbin–Watson=1.845, R2=0.191 (Constant) 0.982 0.252 3.899*** <0.001 Selection attributes 0.752 0.068 0.546 11.069*** <0.001 F=122.518 (p<0.001), Durbin–Watson=1.936, R2=0.298 (Constant) 2.343 0.184 12.732*** <0.001 Brand 0.436 0.056 0.416 7.776*** <0.001 F=60.465 (p<0.001), Durbin–Watson=1.921, R2=0.173 (Constant) 1.286 0.252 5.095*** <0.001 Quality 0.556 0.057 0.500 9.823*** <0.001 F=96.487 (p<0.001), Durbin–Watson=1.833, R2=0.250 (Constant) 2.561 0.198 12.938*** <0.001 Price 0.331 0.054 0.336 6.074*** <0.001 F=36.887 (p<0.001), Durbin–Watson=1.894, R2=0.113 Dependent variable: purchase intention.
***p<0.001.
Discussion
Consumer innovativeness has been identified as a significant factor influencing purchase intention, and previous studies have been conducted in various related fields. However, research on intention to purchase cosmetics has been limited. In this regard, this study is significant in examining the relationship between consumer innovativeness, cosmetic choice attributes, and the intention to purchase eco-friendly cosmetics.
This study can serve as foundational academic material for the cosmetics industry, and the results indicate that the significant influence of consumer innovativeness and cosmetic choice attributes on the intention to purchase eco-friendly cosmetics can also be applied in the formulation of marketing strategies by companies.
Conflicts of interest
The authors have nothing to disclose.
References
- Wikipedia. Impact of the COVID-19 pandemic on the environment [Internet]. San Francisco (CA): Wikimedia Foundation; c2023 [cited 2022 Sep 13].
Available from: https://en.wikipedia.org/wiki/Impact_of_the_COVID-19_pandemic_on_the_environment. - Kearny. Sustainability [Internet]. Chicago (IL): Kearny [cited 2022 Sep 13].
Available from: https://www.kearney.com/service/sustainability. - Pae S. The effects of environmental awareness, consumption values, and selection criteria on eco-friendly cosmetic purchase behaviors [dissertation]. Seoul: Konkuk University; 2022.
- Paek HY. A study on how to activate eco-friendly cosmetics in the Korean cosmetics market. Korean Soc Cosmet Cosmetol 2020;10:123-31.
- Kim YJ. A study on the suitability of hair color image and consumer type: focusing on self-interpretation level and consumer innovation tendency [dissertation]. Seoul: SeoKyeong University; 2019.
- Xu D. The influence of the brand equity and consumer innovativeness on the consumer's purchase intention [dissertation]. Busan: Pusan National University; 2017.
- Kim Y. Image fitness between five star hotels and kids brands influencing brand attitude and evaluation of brand alliance - kids brand familiarity and consumer innovativeness as moderating variables - [dissertation]. Seoul: Sejong University; 2019.
- Park HJ. The influence of the smartphone design on the consumers' perception of the design attributes and product preference: moderating effects of consumer innovativeness [dissertation]. Seoul: Hanyang University; 2018.
- Seo S. The effects of shopping value on the usage intention of unmanned fashion stores -application of technology acceptance model-. J Fash Bus 2019;23:140-55.
- Yuecan. The effects of consumer innovation and type of advertisement, fashion product type on Chinese consumers' attitude [dissertation]. Seoul: Sungkyunkwan University; 2019.
- Kim YG. Relationship among consumer innovativeness, emotional consumption value, and purchase intention of coffee shop [dissertation]. Gwangju: Honam University; 2018.
- Lee HG. Design trend analysis preferred by innovators who spread trends. The 12th Korean Academic Society of Business Adiministraion 2010;2010 August 16-18;Pyeongchang, Korea. p. 1-6.
- Song KS. Effects of wine selection attributes on satisfaction and repurchase intention -focused on the moderating effect of wine involvement-. J Korea Contents Assoc 2012;12:431-46.
- Lee IH. Selection attributes and purchase behavior for cosmeceuticals by adult women's lifestyle [dissertation]. Seoul: Konkuk University; 2019.
- Cho HS. A study on the skin care center, according to the lifestyle choice properties and consumer behavior [dissertation]. Yangsan: Youngsan University; 2018.
- Kim JS. The effect of personalized cosmetics selection attributes on the consumer's intention -focusing on consumers in their 20s to 50s- [dissertation]. Seoul: Hansung University; 2021.
- Cho M. The effects on customized cosmetics selection attributes and safety perception on purchase behavior intention [dissertation]. Seoul: Konkuk University; 2020.
- Kim H. A study on the effects of service quality on customer satisfaction and behaviors after purchase: focused on eco-friendly cosmetics [dissertation]. Seoul: Kyung Hee University; 2009.
- Lee K, Park J. Eco-friendly corporate design identity based on customers' awareness and behavior of natural cosmetic brands. J Korea Des Forum 2010;27:75-86.
- Son EH. A study on the consumer's perception and purchasing behavior of environmentally friendly container cosmetics [dissertation]. Seoul: Sungshin Women's University; 2021.
- Kim CK. Effects of eco-friendly products with green marketing on customers attitude: a focus on cosmetic brands [dissertation]. Seoul: Sungkyunkwan University; 2011.
- Han SH. The influence of consumption value factors and extended planned behavior on intention to buy eco-friendly cosmetics [dissertation]. Seoul: Konkuk University; 2022.
- Kim HJ. The effect of consumption value for eco-friendly cosmetics on norms and purchasing behavior of female college students [dissertation]. Seoul: SeoKyeong University; 2020.
- Kim YM. The effects of characteristics of collaboration products in cosmetics brands on perceived value and purchase intention [dissertation]. Gyeongsan: Daegu Catholic University; 2019.
- Park YI. The effects of parasocial relationship and YouTube use motives on attitude toward advertisement & products, and purchase intention in YouTube influencer marketing: using persuasion knowledge model [dissertation]. Seoul: Yonsei University; 2019.
- Lee HJ. A study on effects of repurchase intention of consumer innovativeness and website characteristics -focused on consumer of overseas direct purchase- [dissertation]. Gongju: Kongju University; 2021.
- Yoo M. The effect of online purchasing consumer's consumption orientation on product attribute and repurchase intention of functional cosmetics: based on new and medium priced brand [dissertation]. Wonju: Yonsei University; 2020.
PDF
Standard view
Export citation
Share Article
Original Article
J Cosmet Med 2023; 7(1): 29-37
Published online June 30, 2023 https://doi.org/10.25056/JCM.2023.7.1.29
Copyright © Korean Society of Korean Cosmetic Surgery and Medicine (KSKCS & KCCS).
Influence of consumer innovativeness and cosmetic selection attributes on purchase intention of eco-friendly cosmetics
Su-Jin Park, MA1 , You-Jeong Kim, PhD2 , Oh-Hyeok Kwon, PhD3 , Jeong-Min Lee, PhD3
1Department of Beauty Art, Graduate School, Hansung University, Seoul, Rep. of Korea
2Department of Associate Degree of Cosmetology, Yeoju Institute of Technology, Yeoju, Rep. of Korea
3Department of Beauty Design Management, Hansung University, Seoul, Rep. of Korea
Correspondence to:Oh-Hyeok Kwon
E-mail: beauty67@hansung.ac.kr
This article is excerpted from the Master of Arts thesis of Su-Jin Park.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: Owing to the COVID-19 pandemic, consumers’ interest in the environment has increased. This has also led to increased interest in eco-friendly products and cosmetics. To increase consumers’ purchase intention of eco-friendly cosmetics, this study explores the influence of consumer innovativeness and cosmetic selection attributes on their purchase intention of eco-friendly cosmetics.
Objective: This study aims to provide practical marketing data for eco-friendly cosmetic companies and contribute to increasing consumers’ purchase intention.
Methods: This study collected data through self-administered surveys and analyzed the collected data using SPSS ver. 24.0.
Results: Our statistical analysis shows that the functional, hedonic, cognitive, and social innovativeness of consumer innovativeness and the brand, quality, and price of cosmetic selection attributes positively (+) influence purchase intention of eco-friendly cosmetics.
Conclusion: Our statistical results show that consumer innovativeness and cosmetic selection attributes positively influence the purchase intention of eco-friendly cosmetics. We expect that targeting consumers who have high consumer innovativeness and favor brand-, quality-, and price-centered marketing can increase consumers’ positive purchase intention.
Keywords: consumer innovativeness, consumer preference, eco-friendly cosmetics, purchase intention, selection attributes
Introduction
Owing to the COVID-19 pandemic in 2020, factories shut down and human activity diminished, significantly reducing air and water pollution [1]. These rapid environmental changes have resulted in enhancing consumer interest in environmental issues. Kearney, a global management consulting firm, reported that half of the US consumers responded that they became more interested in the environment after the COVID-19 pandemic [2]. Consumer interest in the environment, in turn, leads the development of eco-friendly products. Nowadays, consumers are interested not only in the main ingredients of products, but also in the production process. Therefore, the demand for eco-friendly management has grown, resulting in a greater preference for products created using eco-friendly methods that avoid chemical production facilities and animal testing [3]. In the cosmetics market, products made with environmental considerations have received significant attention. Eco-friendly cosmetics, manufactured using natural materials, are evolving into an independent market segment [4].
Consumer innovativeness
Consumer innovativeness is the tendency to adopt new products and embrace change more quickly and easily than other consumers. This definition has attracted the attention of marketers, gained importance, and is being actively researched [5]. Innovativeness is the degree to which one pursues something new, rather than continuing with, or choosing, existing options. Hence, consumer innovativeness can positively impact the intention to purchase new products [6]. Previous studies define consumer innovativeness as the extent to which consumers quickly and easily adopt novelty within a social system [7]. Additionally, it is defined as the preference for purchasing innovative products based on the awareness of, and interest in, the latest products [8]. With reference to these studies, we categorize consumer innovativeness into functional, hedonic, cognitive, and social innovativeness. Functional innovativeness refers to the tendency to seek convenience and efficiency of products. Hedonic innovativeness is the tendency to seek pleasure from one’s purchases. Social innovativeness refers to the tendency to seek differentiation from others in a group, through purchases. Cognitive innovativeness is the tendency to seek logical and intellectual stimulation from a product. Innovation can be applied from various perspectives. However, this does not appear identical for all subjects or fields, and may yield varying results in different categories [9]. Innovative consumers are positive about new experiences and stimuli. Hence, these consumers exhibit more positive attitudes toward new products or services than others [10]. They are open to new things, have a strong sense of adventure and willingness to take risks [11], and share the peculiarity of liking experimental and bold things. These consumers make independent consumption decisions and bear the risks associated with new products. As a result, innovative consumers are proactive and creative people with appropriate information search skills and “trend literacy” [12].
Cosmetic selection attributes
Cosmetic selection attributes refer to factors that consumers value and consider important when purchasing cosmetics. Selection attributes are crucial for product selection. Consumers associate certain attributes with potential outcomes [13]. These attributes provide a method for analyzing consumer behavior, and companies can utilize them as effective marketing factors [14]. Selection attributes are also indispensable for understanding consumers because they are considered important in product selection [15]. Consequently, researchers, including those in the field of cosmetics, have conducted numerous studies on consumer purchase intention related to selection attributes. However, research on eco-friendly cosmetics is limited. Selection attributes are classified into brand attributes, price, quality, trustworthiness, and perceived value [16], and brand, quality, price, and perceived value [3]. Based on prior research, this study divides cosmetic selection attributes into brand, quality, and price. Brand refers to a mark that distinguishes one’s product from others. Quality refers to the features that satisfy consumers (e.g., product ingredients, performance, characteristics, appearance, design, and color). Price signifies the total value that consumers pay for a product.
Purchase intention of eco-friendly cosmetics
With advancing technology, quality differences between products have become negligible, therefore the attribute of quality has become a given. Beyond quality, consumers also seek to interact with products that fit their lifestyles [17]. Earlier, cosmetics were perceived as products used solely for beauty, owing to low awareness about cosmetic ingredients among consumers. However, with heightened environmental awareness in recent times, modern consumers have begun to seek products genuinely intended for humans, leading to the emergence of eco-friendly cosmetics [18]. Changes in consumers’ environmental awareness influence corporate sustainability strategies [19]. In October 2017, Korea Trade-Investment Promotion Agency (KOTRA) hosted the “2017 Global Cosmetic Trends Forum,” which emphasized that harmful effects of environmental pollution on humans are intensifying, but simultaneously, awareness of eco-friendly production and consumption is spreading worldwide [20]. Eco-friendly cosmetics are gaining popularity owing to the public backlash against pollution-causing industries. Consumers desire a clean environment and prefer pure plant-based ingredients [21]. Thus, the eco-friendliness domain has expanded from raw materials to production, manufacturing, and disposal [3]. Previous studies have defined eco-friendly cosmetics as those that are made solely from natural extracts and primarily eco-friendly components, and whose production processes do not harm the environment [22]. Eco-friendly cosmetics are environmentally friendly, and use not only sustainable materials as their main components, but also minimal and recyclable packaging [23]. In this study, the purchase intention of eco-friendly cosmetics refers to consumer willingness to purchase them, which signifies the possibility of purchasing behavior. Purchase intention is crucial for businesses because it helps predict and understand consumer purchase patterns [24]. Marketers consider purchase intention to be the ultimate indicator of advertising effectiveness. Thus, positive purchase intentions among consumers should be prioritized [25]. Therefore, purchase intentions have been widely studied in the field of cosmetics.
Materials and methods
Survey respondents and procedure
For our empirical investigation, we conducted a survey targeting adult males and females, who purchased cosmetics, in South Korea. Self-administered surveys were used to collect the data. We collected preliminary data from 30 surveys from October 14th–16th, 2022. We distributed 301 surveys between October 17th and 24th, 2022. After excluding 10 invalid responses, 291 responses were used as the final data. The study was approved by the Korea Institute of Human Resources Development in Science & Technology (KIRD, 2022-R-40543).
Data analysis method
We analyzed the collected data using the statistical package SPSS Ver. 24.0. We then performed frequency analysis to identify the demographic characteristics of the participants. Factor and reliability analyses were used to analyze the validity and reliability of the measurement tools. We also conducted a correlation analysis to examine the correlation between the independent and dependent variables. Finally, we performed a regression analysis to analyze the impact of consumer innovativeness and cosmetic selection attributes on the purchase intention of eco-friendly cosmetics among customers.
Results
This study investigated the influence of consumer innovativeness and cosmetic choice attributes on the intention to purchase eco-friendly cosmetics. The findings are as follows:
First, consumers’ functional, social, hedonic, and cognitive innovativeness positively influences their intention to purchase eco-friendly cosmetics [11,26]. Thus, it can be said that consumer innovativeness affects the intention to purchase in various fields.
Second, the brand, quality, and price of cosmetics have a positive impact on the intention to purchase eco-friendly cosmetics [17,27]. In other words, the brand, quality, and price among cosmetic choice attributes significantly influence the intention to purchase cosmetics, suggesting a need for marketing strategies that utilize these attributes.
One limitation of this study is that the sample group was concentrated in their 20s, and empirical analyses of other age groups were lacking. In future research, it will be necessary to collect data from a balanced representation of all age groups for a more comprehensive study.
Demographic characteristics of respondents
Of the respondents, 72.5% and 27.5% were female and male, respectively. In terms of age, 46.4%, 23.0%, 18.2%, and 12.4% of the participants were in their 20s, 40s, 50s or older, and 30s, respectively. Regarding the highest level of education, 52.9% were currently attending, or had graduated from, a four-year university. This was followed by 17.2% of the respondents, who were currently attending, or had graduated from graduate school, 15.8% who had graduated from high school, and 14.1% who were currently attending or had graduated from a 2-year college. Regarding marital status, 59.1% and 40.9% of the respondents were unmarried and married, respectively, indicating a higher proportion of unmarried respondents. Regarding monthly income, 43.3% earned less than 2 million KRW (Korean won), 21.6%, earned 2 million to less than 3 million KRW, 14.1% earned 3 million to less than 4 million KRW, 13.1% earned 5 million KRW or more; and 7.9% earned 4 million to less than 5 million KRW. Regarding current occupation, 30.2% were students, 22.7% were office workers, 11.3% were in other professions, 10.7% were service workers, 10.0% were professionals, 9.6% were self-employed, and 5.5% were homemakers (Table 1).
-
Table 1 . Demographic characteristics of survey participants.
Item Number % Sex 291 100 Male 80 27.5 female 211 72.5 Age (yr) 291 100 20s 135 46.4 30s 36 12.4 40s 67 23.0 ≥50 53 18.2 Education 291 100 High school graduation 46 15.8 Completed/graduate from a two-year college 41 14.1 Completed/graduate from a university 154 52.9 Enrolled in/completed/graduate school 50 17.2 Marital status 291 100 Single 172 59.1 Married 119 40.9 Monthly average income (Korean won) 291 100 <2 million 126 43.3 ≥2 to <3 million 63 21.6 ≥3 to <4 million 41 14.1 ≥4 to <5 million 23 7.9 ≥5 million 38 13.1 Occupation 291 100 Student 88 30.2 Office worker 66 22.7 Service worker 31 10.7 Professional 29 10.0 Self-employed 28 9.6 Homemaker 16 5.5 Other 33 11.3
Validity and reliability analysis of measurement tools
The total variance that explained consumer innovativeness was 72.170%. The KMO measure of sampling adequacy was 0.873, and Bartlett’s test of sphericity result was χ2=1,872.254, p<0.001, indicating that the factor analysis was appropriate. Previous research has classified confidence interval sub-factors into social, functional, cognitive, and hedonic innovativeness. According to the reliability analysis results, Cronbach’s α was 0.862, 0.741, 0.799, and 0.845 for social, functional, cognitive, and hedonic innovativeness, respectively, indicating the reliability of all items (Table 2).
-
Table 2 . Factor analysis and reliability analysis of consumer innovativeness.
Social
innovativenessHedonic
innovativenessCognitive
innovativenessFunctional
innovativenessI enjoy using products that no one else has used before. 0.804 I want to be the first to purchase attention-grabbing products that everyone envies. 0.796 I like products that differentiate me from others. 0.727 I like using products that leave a deep impression on others. 0.714 Having new products always excites me. 0.827 Using new products energizes my daily life. 0.818 Discovering products I didn’t know before is enjoyable and fun. 0.652 I enjoy keeping up with the latest information. 0.871 I often look for media that provides new information. 0.849 I like being exposed to new ideas. 0.652 If a new product is released that saves me time (steps) compared to existing products, I will purchase it right away. 0.846 If a new product is released with new features not found in the one I’m currently using, I will purchase it right away. 0.809 If a new product has better functionality than the one I’m currently using, I will purchase it right away. 0.624 Total 2.817 2.277 2.266 2.021 % Variance 21.670 17.516 17.433 15.550 % Cumulative 21.670 39.186 56.620 72.170 Cronbach’s α 0.862 0.845 0.799 0.741
The total variance explained by the selection attributes was 65.106%. The KMO measure of sampling adequacy was 0.815, and Bartlett’s test of sphericity result was χ2=1,710.755, p<0.001, indicating that the factor analysis was appropriate. Previous research has shown that the subfactors of selection attributes are quality, price, and brand. The reliability analysis results showed that Cronbach’s α was 0.884, 0.752, and 0.744 for quality, price, and brand, respectively, indicating the reliability of all items (Table 3).
-
Table 3 . Factor analysis and reliability analysis of cosmetic selection attributes.
Quality Price Brand Quality is important when purchasing eco-friendly cosmetics. 0.851 Functionality is important when purchasing eco-friendly cosmetics. 0.801 Feel is important when purchasing eco-friendly cosmetics. 0.794 Ingredients are important when purchasing eco-friendly cosmetics. 0.787 Availability of price discounts is important when purchasing eco-friendly cosmetics. 0.824 Price per volume is important when purchasing eco-friendly cosmetics. 0.757 Price is important when purchasing eco-friendly cosmetics. 0.709 Availability of samples is important when purchasing eco-friendly cosmetics. 0.546 Brand is important when purchasing eco-friendly cosmetics. 0.779 Brand recognition is important when purchasing eco-friendly cosmetics. 0.751 I compare brands when purchasing eco-friendly cosmetics. 0.640 Brand endorsement models are important when purchasing eco-friendly cosmetics. 0.602 When purchasing eco-friendly cosmetics, I make a purchase after seeing the brand’s advertisement. 0.579 Total 3.477 2.505 2.481 % Variance 26.748 19.271 19.086 % Cumulative 26.748 46.020 65.106 Cronbach’s α 0.884 0.752 0.744
The total variance explaining the intention to purchase eco-friendly cosmetics was 68.180. The KMO measure of sampling adequacy was 0.872, and Bartlett’s test of sphericity yielded the result, χ2=743.504, p<0.001, indicating that the factor analysis was appropriate. The reliability analysis results showed that Cronbach’s α was 0.882, indicating the reliability of all items (Table 4).
-
Table 4 . Factor analysis and reliability analysis of purchase intention of eco-friendly cosmetics.
Factor loading I am willing to recommend eco-friendly cosmetics to others. 0.893 I plan to invest time in purchasing eco-friendly cosmetics. 0.840 I intend to purchase eco-friendly cosmetics. 0.812 I will consider purchasing eco-friendly cosmetics first when purchasing cosmetics. 0.796 I am willing to gift eco-friendly cosmetics to acquaintances. 0.784 Total 3.409 % Variance 68.180 % Cumulative 68.180 Cronbach’s α 0.882
Analysis of correlations between measurement variables
Functional innovativeness of consumer innovativeness showed positive correlation with hedonic (r=0.466, p<0.001), social (r=0.417, p<0.001), and cognitive innovativeness (r=0.411, p<0.001), which belong to the same variable. Moreover, it showed positive correlations with the brand (r=0.326, p<0.001), quality (r=0.354, p<0.001), and price (r=0.214, p<0.001) selection attributes. Additionally, we found a positive correlation with purchase intention (r=0.488, p<0.001).
Hedonic innovativeness was positively correlated with social (r=0.672, p<0.001) and cognitive innovativeness (r=0.454, p<0.001), which belong to the same variable. Moreover, it showed positive correlations with the brand (r=0.402, p<0.001), quality (r=0.303, p<0.001), and price (r=0.223, p<0.001) selection attributes. In addition, we found a positive correlation with purchase intention (r=0.452, p<0.001).
Social innovativeness was positively correlated with cognitive innovativeness (r=0.464, p<0.001), which belongs to the same variable. Moreover, it showed positive correlations with the brand (r=0.379, p<0.001), quality (r=0.266, p<0.001), and price (r=0.244, p<0.001) selection attributes. In addition, we found a positive correlation with purchase intention (r=0.394, p<0.001).
Cognitive innovativeness showed positive correlations with brand (r=0.301, p<0.001), quality (r=0.349, p<0.001), and price (r=0.192, p<0.01) selection attributes. In addition, we found a positive correlation with purchase intention (r=0.437, p<0.001).
Brand selection attributes showed positive correlations with quality (r=0.309, p<0.001) and price (r=0.381, p<0.001), which belong to the same variable. In addition, we found a positive correlation with purchase intention (r=0.416, p<0.001).
Quality of selection attributes showed a positive correlation with price (r=0.394, p<0.001), which belongs to the same variable. In addition, we found a positive correlation with purchase intention (r=0.500, p<0.001). Price was also positively correlated with purchase intention (r=0.336, p<0.001) (Table 5).
-
Table 5 . Correlation analysis.
Consumer innovativeness Selection attributes Purchase intention 1 2 3 4 5 6 7 Consumer innovativeness 1 1 2 0.466*** 1 3 0.417*** 0.672*** 1 4 0.411*** 0.454*** 0.464*** 1 Selection attributes 5 0.326*** 0.402*** 0.379*** 0.301*** 1 6 0.354*** 0.303*** 0.266*** 0.349*** 0.309*** 1 7 0.214*** 0.223*** 0.244*** 0.192** 0.381*** 0.394*** 1 Purchase intention 0.488*** 0.452*** 0.394*** 0.437*** 0.416*** 0.500*** 0.336*** 1 Mean 3.44 3.30 3.03 3.53 3.17 4.38 3.52 3.72 Standard deviation 0.969 1.06 1.081 0.963 0.837 0.789 0.892 0.878 1, functional innovativeness; 2, hedonic innovativeness; 3, social innovativeness; 4, cognitive innovativeness; 5, brand; 6, quality; 7, price..
***p<0.001..
Regression analysis results
Through regression analysis, this study aims to verify the influence of consumer innovativeness and cosmetic selection attributes on the purchase intention of eco-friendly cosmetics.
We conducted regression analysis, taking consumer innovativeness and purchase intention as the independent and dependent variables, respectively. The regression model for consumer innovativeness had an F-value of 128.801 (p<0.001) and the Durbin–Watson value was 1.906, which was close to 2, not to 0 or 4. This indicates that there was no correlation between the residuals. Hence, this can be considered an appropriate regression model. This explains 30.8% of the dependent variables. Our analysis showed that consumer innovativeness positively (+) influences purchase intention (β=0.555, p<0.001).
We conducted a regression analysis with the functional innovativeness of consumers as the independent variable, and purchase intention as the dependent variable. The regression model for functional innovativeness has an F-value of 90.519 (p<0.001). The Durbin–Watson value was 1.927, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 23.9% of the dependent variables. Our analysis shows that functional innovativeness positively (+) influences purchase intention (β=0.488, p<0.001).
We conduct a regression analysis using the hedonic innovativeness of consumers as the independent variable and purchase intention as the dependent variable. The regression model for hedonic innovativeness has an F-value of 74.261 (p<0.001). The Durbin–Watson value was 1.940, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 20.4% of the dependent variables. Our analysis shows that hedonic innovativeness positively (+) influences purchase intention (β=0.452, p<0.001).
We conducted a regression analysis with social innovativeness of consumers as the independent variable and purchase intention as the dependent variable. The regression model for social innovativeness has an F-value of 53.056 (p<0.001). The Durbin–Watson value was 1.882, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 15.5% of the dependent variables. Our analysis shows that social innovativeness positively (+) influences purchase intention (β=0.394, p<0.001).
We conducted a regression analysis with cognitive innovativeness of consumers as the independent variable and purchase intention as the dependent variable. The regression model for cognitive innovativeness has an F-value of 68.338 (p<0.001). The Durbin–Watson value was 1.845, close to 2, not to 0 or 4, indicating no correlation between the residuals. Therefore, it can be considered an appropriate regression model. This explains 19.1% of the dependent variables. Our analysis shows that cognitive innovativeness positively (+) influences purchase intention (β=0.437, p<0.001).
We conducted regression analysis with cosmetic selection attributes and purchase intention as the independent and dependent variables, respectively. The regression model for the cosmetic selection attributes had an F-value of 122.518 (p<0.001). The Durbin–Watson value was 1.936, close to 2, not to 0 or 4, indicating no correlation between the residuals. Hence, it can be considered an appropriate regression model. This explains 29.8% of the dependent variables. According to the analysis, cosmetic selection attributes positively (+) influence purchase intention (β=0.546, p<0.001).
We conducted regression analysis with brand and purchase intention as the independent and dependent variables, respectively. The regression model for the brands had an F-value of 60.465 (p<0.001). The Durbin–Watson value was 1.921, close to 2, not to 0 or 4, indicating no correlation between the residuals. Therefore, this can be considered an appropriate regression model, explaining 17.3% of the dependent variables. The analysis shows that the brand positively (+) influences purchase intention (β=0.416, p<0.001).
We conducted regression analysis with cosmetic quality and purchase intention as the independent and dependent variables, respectively. The regression model for quality had an F-value of 96.487 (p<0.001), and the Durbin–Watson value was 1.833, close to 2, not to 0 or 4. This indicates no correlation between the residuals. Hence, this can be considered an appropriate regression model, explaining 25.0% of the dependent variables. The analysis shows that quality positively (+) influences purchase intention (β=0.500, p<0.001).
We conduct a regression analysis with price and purchase intention as the independent and dependent variables, respectively. The regression model for price has an F-value of 36.887 (p<0.001). The Durbin–Watson value was 1.894, close to 2, not to 0 or 4. This indicates no correlation between the residuals. Hence, this can be considered an appropriate regression model, explaining 11.3% of the dependent variables. According to the analysis, price positively (+) influences purchase intention (β=0.336, p<0.001) (Table 6).
-
Table 6 . Regression analysis results.
Unstandardized coefficient Standardized coefficient t p B Standard error β (Constant) 1.730 0.181 9.549*** <0.001 Consumer innovativeness 0.604 0.053 0.555 11.349*** <0.001 F=128.801 (p<0.001), Durbin–Watson=1.906, R2=0.308 (Constant) 2.205 0.166 13.264*** <0.001 Functional innovativeness 0.442 0.047 0.488 9.514*** <0.001 F=90.519 (p<0.001), Durbin–Watson=1.927, R2=0.239 (Constant) 2.490 0.151 16.511*** <0.001 Hedonic innovativeness 0.375 0.043 0.452 8.617*** <0.001 F=74.261 (p<0.001), Durbin–Watson=1.940, R2=0.204 (Constant) 2.756 0.141 19.484*** <0.001 Social innovativeness 0.320 0.044 0.394 7.284*** <0.001 F=53.056 (p<0.001), Durbin–Watson=1.882, R2=0.155 (Constant) 2.318 0.177 13.122*** <0.001 Cognitive innovativeness 0.399 0.048 0.437 8.267*** <0.001 F=68.338 (p<0.001), Durbin–Watson=1.845, R2=0.191 (Constant) 0.982 0.252 3.899*** <0.001 Selection attributes 0.752 0.068 0.546 11.069*** <0.001 F=122.518 (p<0.001), Durbin–Watson=1.936, R2=0.298 (Constant) 2.343 0.184 12.732*** <0.001 Brand 0.436 0.056 0.416 7.776*** <0.001 F=60.465 (p<0.001), Durbin–Watson=1.921, R2=0.173 (Constant) 1.286 0.252 5.095*** <0.001 Quality 0.556 0.057 0.500 9.823*** <0.001 F=96.487 (p<0.001), Durbin–Watson=1.833, R2=0.250 (Constant) 2.561 0.198 12.938*** <0.001 Price 0.331 0.054 0.336 6.074*** <0.001 F=36.887 (p<0.001), Durbin–Watson=1.894, R2=0.113 Dependent variable: purchase intention..
***p<0.001..
Discussion
Consumer innovativeness has been identified as a significant factor influencing purchase intention, and previous studies have been conducted in various related fields. However, research on intention to purchase cosmetics has been limited. In this regard, this study is significant in examining the relationship between consumer innovativeness, cosmetic choice attributes, and the intention to purchase eco-friendly cosmetics.
This study can serve as foundational academic material for the cosmetics industry, and the results indicate that the significant influence of consumer innovativeness and cosmetic choice attributes on the intention to purchase eco-friendly cosmetics can also be applied in the formulation of marketing strategies by companies.
Conflicts of interest
The authors have nothing to disclose.
-
Table 1 . Demographic characteristics of survey participants.
Item Number % Sex 291 100 Male 80 27.5 female 211 72.5 Age (yr) 291 100 20s 135 46.4 30s 36 12.4 40s 67 23.0 ≥50 53 18.2 Education 291 100 High school graduation 46 15.8 Completed/graduate from a two-year college 41 14.1 Completed/graduate from a university 154 52.9 Enrolled in/completed/graduate school 50 17.2 Marital status 291 100 Single 172 59.1 Married 119 40.9 Monthly average income (Korean won) 291 100 <2 million 126 43.3 ≥2 to <3 million 63 21.6 ≥3 to <4 million 41 14.1 ≥4 to <5 million 23 7.9 ≥5 million 38 13.1 Occupation 291 100 Student 88 30.2 Office worker 66 22.7 Service worker 31 10.7 Professional 29 10.0 Self-employed 28 9.6 Homemaker 16 5.5 Other 33 11.3
-
Table 2 . Factor analysis and reliability analysis of consumer innovativeness.
Social
innovativenessHedonic
innovativenessCognitive
innovativenessFunctional
innovativenessI enjoy using products that no one else has used before. 0.804 I want to be the first to purchase attention-grabbing products that everyone envies. 0.796 I like products that differentiate me from others. 0.727 I like using products that leave a deep impression on others. 0.714 Having new products always excites me. 0.827 Using new products energizes my daily life. 0.818 Discovering products I didn’t know before is enjoyable and fun. 0.652 I enjoy keeping up with the latest information. 0.871 I often look for media that provides new information. 0.849 I like being exposed to new ideas. 0.652 If a new product is released that saves me time (steps) compared to existing products, I will purchase it right away. 0.846 If a new product is released with new features not found in the one I’m currently using, I will purchase it right away. 0.809 If a new product has better functionality than the one I’m currently using, I will purchase it right away. 0.624 Total 2.817 2.277 2.266 2.021 % Variance 21.670 17.516 17.433 15.550 % Cumulative 21.670 39.186 56.620 72.170 Cronbach’s α 0.862 0.845 0.799 0.741
-
Table 3 . Factor analysis and reliability analysis of cosmetic selection attributes.
Quality Price Brand Quality is important when purchasing eco-friendly cosmetics. 0.851 Functionality is important when purchasing eco-friendly cosmetics. 0.801 Feel is important when purchasing eco-friendly cosmetics. 0.794 Ingredients are important when purchasing eco-friendly cosmetics. 0.787 Availability of price discounts is important when purchasing eco-friendly cosmetics. 0.824 Price per volume is important when purchasing eco-friendly cosmetics. 0.757 Price is important when purchasing eco-friendly cosmetics. 0.709 Availability of samples is important when purchasing eco-friendly cosmetics. 0.546 Brand is important when purchasing eco-friendly cosmetics. 0.779 Brand recognition is important when purchasing eco-friendly cosmetics. 0.751 I compare brands when purchasing eco-friendly cosmetics. 0.640 Brand endorsement models are important when purchasing eco-friendly cosmetics. 0.602 When purchasing eco-friendly cosmetics, I make a purchase after seeing the brand’s advertisement. 0.579 Total 3.477 2.505 2.481 % Variance 26.748 19.271 19.086 % Cumulative 26.748 46.020 65.106 Cronbach’s α 0.884 0.752 0.744
-
Table 4 . Factor analysis and reliability analysis of purchase intention of eco-friendly cosmetics.
Factor loading I am willing to recommend eco-friendly cosmetics to others. 0.893 I plan to invest time in purchasing eco-friendly cosmetics. 0.840 I intend to purchase eco-friendly cosmetics. 0.812 I will consider purchasing eco-friendly cosmetics first when purchasing cosmetics. 0.796 I am willing to gift eco-friendly cosmetics to acquaintances. 0.784 Total 3.409 % Variance 68.180 % Cumulative 68.180 Cronbach’s α 0.882
-
Table 5 . Correlation analysis.
Consumer innovativeness Selection attributes Purchase intention 1 2 3 4 5 6 7 Consumer innovativeness 1 1 2 0.466*** 1 3 0.417*** 0.672*** 1 4 0.411*** 0.454*** 0.464*** 1 Selection attributes 5 0.326*** 0.402*** 0.379*** 0.301*** 1 6 0.354*** 0.303*** 0.266*** 0.349*** 0.309*** 1 7 0.214*** 0.223*** 0.244*** 0.192** 0.381*** 0.394*** 1 Purchase intention 0.488*** 0.452*** 0.394*** 0.437*** 0.416*** 0.500*** 0.336*** 1 Mean 3.44 3.30 3.03 3.53 3.17 4.38 3.52 3.72 Standard deviation 0.969 1.06 1.081 0.963 0.837 0.789 0.892 0.878 1, functional innovativeness; 2, hedonic innovativeness; 3, social innovativeness; 4, cognitive innovativeness; 5, brand; 6, quality; 7, price..
***p<0.001..
-
Table 6 . Regression analysis results.
Unstandardized coefficient Standardized coefficient t p B Standard error β (Constant) 1.730 0.181 9.549*** <0.001 Consumer innovativeness 0.604 0.053 0.555 11.349*** <0.001 F=128.801 (p<0.001), Durbin–Watson=1.906, R2=0.308 (Constant) 2.205 0.166 13.264*** <0.001 Functional innovativeness 0.442 0.047 0.488 9.514*** <0.001 F=90.519 (p<0.001), Durbin–Watson=1.927, R2=0.239 (Constant) 2.490 0.151 16.511*** <0.001 Hedonic innovativeness 0.375 0.043 0.452 8.617*** <0.001 F=74.261 (p<0.001), Durbin–Watson=1.940, R2=0.204 (Constant) 2.756 0.141 19.484*** <0.001 Social innovativeness 0.320 0.044 0.394 7.284*** <0.001 F=53.056 (p<0.001), Durbin–Watson=1.882, R2=0.155 (Constant) 2.318 0.177 13.122*** <0.001 Cognitive innovativeness 0.399 0.048 0.437 8.267*** <0.001 F=68.338 (p<0.001), Durbin–Watson=1.845, R2=0.191 (Constant) 0.982 0.252 3.899*** <0.001 Selection attributes 0.752 0.068 0.546 11.069*** <0.001 F=122.518 (p<0.001), Durbin–Watson=1.936, R2=0.298 (Constant) 2.343 0.184 12.732*** <0.001 Brand 0.436 0.056 0.416 7.776*** <0.001 F=60.465 (p<0.001), Durbin–Watson=1.921, R2=0.173 (Constant) 1.286 0.252 5.095*** <0.001 Quality 0.556 0.057 0.500 9.823*** <0.001 F=96.487 (p<0.001), Durbin–Watson=1.833, R2=0.250 (Constant) 2.561 0.198 12.938*** <0.001 Price 0.331 0.054 0.336 6.074*** <0.001 F=36.887 (p<0.001), Durbin–Watson=1.894, R2=0.113 Dependent variable: purchase intention..
***p<0.001..
References
- Wikipedia. Impact of the COVID-19 pandemic on the environment [Internet]. San Francisco (CA): Wikimedia Foundation; c2023 [cited 2022 Sep 13]. Available from:
https://en.wikipedia.org/wiki/Impact_of_the_COVID-19_pandemic_on_the_environment . - Kearny. Sustainability [Internet]. Chicago (IL): Kearny [cited 2022 Sep 13]. Available from:
https://www.kearney.com/service/sustainability . - Pae S. The effects of environmental awareness, consumption values, and selection criteria on eco-friendly cosmetic purchase behaviors [dissertation]. Seoul: Konkuk University; 2022.
- Paek HY. A study on how to activate eco-friendly cosmetics in the Korean cosmetics market. Korean Soc Cosmet Cosmetol 2020;10:123-31.
- Kim YJ. A study on the suitability of hair color image and consumer type: focusing on self-interpretation level and consumer innovation tendency [dissertation]. Seoul: SeoKyeong University; 2019.
- Xu D. The influence of the brand equity and consumer innovativeness on the consumer's purchase intention [dissertation]. Busan: Pusan National University; 2017.
- Kim Y. Image fitness between five star hotels and kids brands influencing brand attitude and evaluation of brand alliance - kids brand familiarity and consumer innovativeness as moderating variables - [dissertation]. Seoul: Sejong University; 2019.
- Park HJ. The influence of the smartphone design on the consumers' perception of the design attributes and product preference: moderating effects of consumer innovativeness [dissertation]. Seoul: Hanyang University; 2018.
- Seo S. The effects of shopping value on the usage intention of unmanned fashion stores -application of technology acceptance model-. J Fash Bus 2019;23:140-55.
- Yuecan. The effects of consumer innovation and type of advertisement, fashion product type on Chinese consumers' attitude [dissertation]. Seoul: Sungkyunkwan University; 2019.
- Kim YG. Relationship among consumer innovativeness, emotional consumption value, and purchase intention of coffee shop [dissertation]. Gwangju: Honam University; 2018.
- Lee HG. Design trend analysis preferred by innovators who spread trends. The 12th Korean Academic Society of Business Adiministraion 2010;2010 August 16-18;Pyeongchang, Korea. p. 1-6.
- Song KS. Effects of wine selection attributes on satisfaction and repurchase intention -focused on the moderating effect of wine involvement-. J Korea Contents Assoc 2012;12:431-46.
- Lee IH. Selection attributes and purchase behavior for cosmeceuticals by adult women's lifestyle [dissertation]. Seoul: Konkuk University; 2019.
- Cho HS. A study on the skin care center, according to the lifestyle choice properties and consumer behavior [dissertation]. Yangsan: Youngsan University; 2018.
- Kim JS. The effect of personalized cosmetics selection attributes on the consumer's intention -focusing on consumers in their 20s to 50s- [dissertation]. Seoul: Hansung University; 2021.
- Cho M. The effects on customized cosmetics selection attributes and safety perception on purchase behavior intention [dissertation]. Seoul: Konkuk University; 2020.
- Kim H. A study on the effects of service quality on customer satisfaction and behaviors after purchase: focused on eco-friendly cosmetics [dissertation]. Seoul: Kyung Hee University; 2009.
- Lee K, Park J. Eco-friendly corporate design identity based on customers' awareness and behavior of natural cosmetic brands. J Korea Des Forum 2010;27:75-86.
- Son EH. A study on the consumer's perception and purchasing behavior of environmentally friendly container cosmetics [dissertation]. Seoul: Sungshin Women's University; 2021.
- Kim CK. Effects of eco-friendly products with green marketing on customers attitude: a focus on cosmetic brands [dissertation]. Seoul: Sungkyunkwan University; 2011.
- Han SH. The influence of consumption value factors and extended planned behavior on intention to buy eco-friendly cosmetics [dissertation]. Seoul: Konkuk University; 2022.
- Kim HJ. The effect of consumption value for eco-friendly cosmetics on norms and purchasing behavior of female college students [dissertation]. Seoul: SeoKyeong University; 2020.
- Kim YM. The effects of characteristics of collaboration products in cosmetics brands on perceived value and purchase intention [dissertation]. Gyeongsan: Daegu Catholic University; 2019.
- Park YI. The effects of parasocial relationship and YouTube use motives on attitude toward advertisement & products, and purchase intention in YouTube influencer marketing: using persuasion knowledge model [dissertation]. Seoul: Yonsei University; 2019.
- Lee HJ. A study on effects of repurchase intention of consumer innovativeness and website characteristics -focused on consumer of overseas direct purchase- [dissertation]. Gongju: Kongju University; 2021.
- Yoo M. The effect of online purchasing consumer's consumption orientation on product attribute and repurchase intention of functional cosmetics: based on new and medium priced brand [dissertation]. Wonju: Yonsei University; 2020.
