Factors Influencing Loyalty to an Online Clothing Shop among College Students
Article Category: Research Article
Pubblicato online: 22 dic 2022
Pagine: 60 - 65
DOI: https://doi.org/10.2478/ftee-2022-0045
Parole chiave
© 2022 Yajing Shi et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
As online shopping has continuously developed in recent years, the scale of e-commerce in China has rapidly expanded, and clothing e-commerce has markedly prospered. With the gradual increase in the network penetration rate and the continuous improvement of Internet clothing shopping, the number of consumers who patronize clothing e-commerce in China is expected to increase and is estimated to reach 618 million by 2025. The scale of online clothing shopping is predicted to reach 4.17 trillion yuan (US $586 billion). Almost 100% of college students with the ability to purchase fast-moving consumer products are Internet users, which is a huge market. In the early stages of clothing e-commerce, the competition is characterised as mild, and business profit is closely associated with the product, style, quality, market, and promotion of suppliers. Online clothing stores usually gain profit by creating “Clothing style which is very much in vogue now”. However, as competition intensifies, the high traffic cost further reduces the profit of some stores. Loyalty to online clothing stores has gradually become an important indicator of the development prospects. Consumers have repeatedly purchased clothes and accessories from the same online store and have developed a certain degree of trust, commitment, and even emotional dependence on the store. Consumers regard online shops as friends and partners and evolve to form a stable customer group.1 This transformation may follow a path: nonbrand loyalists → habitual buyers → satisfied buyers → emotional buyers → loyal buyers. This process results in a long-term trading relationship. This study evaluates the factors influencing loyalty to online clothing shops among college students and provides a basis for the development of an e-commerce clothing network brand.
On the theme of online store loyalty, Chou S et al's paper focused on female online clothing shoppers and aimed to examine the mediators of e-loyalty in the context of online clothing stores, e-satisfaction and e-trust.2 Pandey S, Chawla D's paper explored the dimensions of online customer experience (OCE) and their impact on satisfaction and loyalty in the clothing e-retail context. Furthermore, it explored the influence of gender on the OCE-satisfaction-loyalty chain.3 Shim et al's study examined the relationships between consumers' skill, perceived challenge, online flow, brand experience, and brand loyalty in the context of online shopping on an apparel brand's website.4 This paper selects college students as the research object and studies the influence value of college students' loyalty to online clothing stores from many perspectives, such as the matchability of clothing in stores, the fashion popularity of clothing, clothing comfort, quality, merchant's logistics speed, customer service attitude, and so on.
This questionnaire survey adopts the form of a questionnaire distributed on the Internet, among which 259 valid questionnaires were collected, of which 134 were males and 125 females. The sample, grouped by grade, consisted of 65 freshmen, 56 sophomores, 72 juniors, and 66 seniors and had a relatively uniform distribution.
To identify the factors affecting customer loyalty among college students to online clothing stores, the responses were examined, compared, and analysed. Subsequently, 12 factors were extracted: commodity prices, complete range of sizes, discount strength, fashion popularity, new speed, commodity quality, brand influence, strong collocation, service attitude, wearing comfort, logistics and comments from other customers.5
To determine the factors influencing customer loyalty to online clothing stores among college students, we separately distributed Likert-scale questionnaires with a five-level classification, shown in Table 1.6 This kind of questionnaire is suitable for projects adopting the same concept, particularly that in which scores are added. The final total score corresponding to the attitude of each respondent was considered as the attitude associated with each item.
Questionnaire Design of “Likert Scale”
| scores | 1 | 2 | 3 | 4 | 5 |
| You pay attention to fashionable items sold in clothing stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the new speed of clothing stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the quality of the items in clothing stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the brand influence of clothing stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the matching of clothing in stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the service of clothing stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the wearing comfort of clothing in stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the logistics of clothing stores | ○ | ○ | ○ | ○ | ○ |
| You value customer reviews for clothing stores | ○ | ○ | ○ | ○ | ○ |
| You pay attention to the prices of the commodities in clothing stores | ○ | ○ | ○ | ○ | ○ |
A total of 259 valid samples were collected, and survey information on the respondents was analysed using SPSS 20.0.
The reliability of a questionnaire refers to the consistency of the results obtained by repeated tests on the same subjects with the same method. We analysed the questionnaire reliability by using the alpha reliability coefficient method. Cronbach α is the most commonly used reliability coefficient, given by α=(k/(k—1))*(1-(∑Si^2)/ST^2).7 Table 2 lists information on questionnaire reliability, calculated using SPSS.
Calculation of questionnaire reliability data
| You pay attention to discounts offered by clothing stores | 0.781 | 0.956 | 0.959 |
| You pay attention to fashionable items sold in clothing stores | 0.808 | 0.956 | |
| You pay attention to the new speed of clothing stores | 0.788 | 0.956 | |
| You pay attention to the quality of the items in clothing stores | 0.794 | 0.956 | |
| You pay attention to the brand influence of clothing stores | 0.755 | 0.957 | |
| You pay attention to the matching of clothing in stores | 0.851 | 0.954 | |
| You pay attention to the service of clothing stores | 0.783 | 0.956 | |
| You pay attention to the wearing comfort of clothing in stores | 0.846 | 0.954 | |
| You pay attention to the logistics of clothing stores | 0.813 | 0.956 | |
| You value customer reviews of clothing stores | 0.848 | 0.954 | |
| You pay attention to the prices of the goods in clothing stores | 0.734 | 0.958 | |
| You pay attention to the size of the clothing store | 0.769 | 0.957 | |
| Standardized Cronbach α tacoefficient: 0.960 | |||
IF the Cronbach α value is less than 0.6, it indicates that the questionnaire has poor reliability; if the value ranges between 0.6 and 0.7, the reliability is acceptable; if the value ranges between 0.7 and 0.8, the reliability is good; and if it is higher than 0.8, the reliability is high. Moreover, if the correction item total correlation (CITC) of an item is below 0.3, this item may be deleted.8
As shown in table 2, the Cronbach α is 0.960, which is greater than 0.9. Therefore, the reliability of the questionnaire data is very high. The CITC value of each item is greater than 0.4, indicating a good correlation between each item. In summary, the quality of the research data is high and thus can be used for further analysis.
The validity analysis of the questionnaire refers to the extent to which the measurement method or tool can accurately count the respondents. It is mostly used to explore the rationality of the design of attitude scale questionnaires. Table 3 lists the results of validity testing, calculated using SPSS.
Questionnaire validity test results
| You pay attention to the size of the clothing store | 0.83 | 0.688 |
| You pay attention to discounts offered by clothing stores | 0.872 | 0.761 |
| You pay attention to fashionable items sold in clothing stores | 0.849 | 0.721 |
| You pay attention to the new speed of clothing stores | 0.839 | 0.705 |
| You pay attention to the quality of the items in clothing stores | 0.859 | 0.738 |
| You pay attention to the brand influence of clothing stores | 0.816 | 0.666 |
| You pay attention to the matching of clothing in stores | 0.879 | 0.773 |
| You pay attention to the service of clothing stores | 0.887 | 0.787 |
| You pay attention to the wearing comfort of clothing in stores | 0.862 | 0.744 |
| You pay attention to the logistics of clothing stores | 0.839 | 0.705 |
| You value customer reviews of clothing stores | 0.879 | 0.772 |
| You pay attention to the prices of goods in clothing stores | 0.787 | 0.619 |
| Eigenvalue (before rotation) | 8.678 | – |
| Variance explanation rate% (before rotation) | 72.31% | – |
| Cumulative variance explanation rate% (before rotation) | 72.31% | – |
| Eigenvalue (after rotation) | 8.678 | – |
| Variance explanation rate% (after rotation) | 72.31% | – |
| Cumulative variance explanation rate% (after rotation) | 72.31% | – |
| KMO value | 0.965 | – |
| Bartlett's spherical value | 2988.732 | – |
| Df | 66 | – |
| P value | 0 | – |
Note: The load coefficient denoted in blue is higher than 0.4, and that in red indicates that the commonality (common factor variance) is less than 0.4.
Validity analysis uses factor analysis to analyse data and performs comprehensive analysis based on the Kaiser–Meyer–Olkin (KMO) value, variance explanation rate, factor load coefficient, and other indicators to verify the validity level of the data.9
The KMO value is often used to evaluate the questionnaire validity. Questionnaire validity varies depending on the KMO value, as follows: KMO value < 0.6, poor validity; 0.6 < KMO value <0.7, relatively general validity; 0.7 < KMO value < 0.8, good validity; and KMO > 0.8, it indicates that the questionnaire is effective. Meanwhile, commonality is used to exclude unreasonable choices in the questionnaire. The variance explanation rate describes the level of information extraction in the questionnaire.10 The factor load coefficient refers to the corresponding relationship between the factor and the item.
According to the results of the validity analysis, the commonality of all items in the questionnaire exceeded 0.4, suggesting that research information in the questionnaire could be effectively extracted. Moreover, the KMO value was 0.965, indicating that the validity of the questionnaire was good. Validity analysis also requires Bartlett's test for sphericity—that is, the corresponding ρ value is less than 0.05. As shown in Table 3, the ρ value is 0, which passes the Bartlett spherical value test.11
Responses derived from the questionnaires were collected. The results are summarised in Figure 1.
Fig. 1
Distribution of the number of answers in the questionnaire
Responses to the questions were assigned corresponding points as follows: “Highly disagree,” 1 point; “Comparatively disagree,” 2 points; “Generally agree,” 3 points; “Comparatively agree,” 4 points; and “Highly agree,” 5 points. In addition to the data presented in the chart, the average of each item was calculated using SPSS 20.0. The results are listed in Table 4.
Average score of each questionnaire
| You pay attention to the prices of goods in clothing stores | 4.03 | 4.02 | 4.05 |
| You pay attention to fashionable items sold in clothing stores | 3.98 | 4.01 | 3.94 |
| You pay attention to the wearing comfort of clothing in stores | 3.95 | 3.89 | 4.02 |
| You pay attention to the matching of clothing in stores | 3.95 | 4.00 | 3.90 |
| You pay attention to the brand influence of clothing stores | 3.93 | 3.91 | 3.96 |
| You pay attention to the quality of the items in clothing stores | 3.93 | 3.90 | 3.98 |
| You pay attention to the service of clothing stores | 3.92 | 3.89 | 3.95 |
| You pay attention to the logistics of clothing stores | 3.92 | 3.87 | 3.98 |
| You value customer reviews of clothing stores | 3.92 | 3.88 | 3.96 |
| You pay attention to discounts offered by clothing stores | 3.92 | 3.95 | 3.89 |
| You pay attention to the size of clothing stores | 3.85 | 3.84 | 3.86 |
| You pay attention to the new speed of clothing stores | 3.90 | 3.88 | 3.92 |
| Subtotal | 3.93 | 3.92 | 3.95 |
Based on the calculation results, the average score of the five-level scale is 3.93, and the respondents tended to agree with the factors influencing store loyalty in the questionnaire. An average price exceeding 4.03 points in most stores showed that loyalty to stores with high prices were slightly considered.12 The second choice was the item “value the fashion popularity of the store”, with a score of 3.98, suggesting that the college students surveyed basically agreed that the fashion level of a store could be used as a reference to determine whether to choose the same store many times. The lowest score was 3.85, indicating that the respondents had a higher tolerance for the size completeness of stores than other factors.13
We then divided the respondents by gender and observed the factors that influenced the store loyalty of males and females. As shown in Table 4, most males evaluate a store by prioritising the prices of the goods in it, as well as fashionable items and product matching. The scores of these three choices were 4 or higher. Simultaneously, “discount intensity” was more readily used by males to measure store loyalty, with a score of 3.95.14 The males showed a greater tolerance for whether a complete range of sizes was offered by a store, compared with other factors. The average score obtained was only 3.84, the lowest among all items. Meanwhile, the females showed agreement as to whether the “price of goods sold by the store” and “clothing comfort” influenced their loyalty, with average scores of 4.05 and 4.02, respectively. Females are also less influenced by whether or not a store offers a complete range of sizes for the goods sold, compared with other factors. The lowest average score obtained was 3.86.15
Compared with females, males pay more attention to the matching of clothing and the popularity of goods sold. Compared with males, females tend to pay more attention to comfort, quality, logistics, and service attitude.16 However, both males and females considered the price of goods as their most important index of store loyalty. In addition, all respondents attached significance to the trendiness of a store and had their preferences. They also showed a more tolerant attitude towards the item of whether the shop had a complete range of sizes.
Online shopping cannot only reduce business costs; it also meets the needs of consumers who enjoy shopping from home. Customer loyalty to e-commerce merchants can be regarded as the current driving force for the sustainable development of online stores. College students, representing young people, reveal the factors affecting their loyalty to stores, providing online shopping with a steady stream of profit.17
Analysis of the combined findings indicates that males are more concerned with the fashion attributes of clothing, along with the popularity and strong matchability of clothing. By contrast, females are more concerned about the functional attributes of clothing, including the comfort and quality of goods. Females are also concerned about the service experience during the purchasing process, such as logistics speed and seller attitude.
However, the price of goods is always the primary driving force for consumers, regardless of gender. Male and female respondents alike pursue shops that offer reasonable prices and discounts, which represents the common attribute college students consider in their evaluation of stores. Similarly, consumers are less influenced by store logistics and size, as compared with other factors.
The limitation of this study can be the limited ability to generalise findings to other contexts, given that the context of this study is specific to online clothing shops.