On gender differences in consumer behavior for online financial transaction of cosmetics

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Contents lists available atSciVerse ScienceDirect

Mathematical and Computer Modelling

journal homepage:www.elsevier.com/locate/mcm

On gender differences in consumer behavior for online financial

transaction of cosmetics

Wan-Yu Liu

a

, Chun-Cheng Lin

b

, Yang Sun Lee

c

, Der-Jiunn Deng

d,∗

a_{Department of Tourism Information, Aletheia University, Tainan, Taiwan}

b_{Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan} c_{Department of Information and Communication Engineering, Chosun University, Gwangju, Republic of Korea}

d_{Department of Computer Science and Information Engineering, National Changhua University of Education, Chanhua, Taiwan}

a r t i c l e i n f o

Article history:

Received 1 July 2011

Received in revised form 15 August 2012 Accepted 26 August 2012 Keywords: Online shopping Customer satisfaction Cosmetics Consumer behavior

a b s t r a c t

The popularity of the Internet has enabled a wide variety of services. Due to increasing pricing levels and material costs over years, enterprises have intended to lower their financial costs by Internet marketing and online financial transactions, by which renting cost, facility setup cost and manpower cost can be saved, and advertising cost is lowered for increasing the number of potential customers. Hence, Internet marketing and online financial transactions have become a market territory for which each enterprise competes. In the market, male consumers no longer mainly shop for 3C products online, and now are becoming more diverse in their shopping selections. Male cosmetics and skincare products comprise a market with great growth potential that is yet to be developed. The purpose of this study is to explore whether gender differences exist or not in perception, importance and satisfaction for online financial transactions of cosmetics. The online questionnaire survey method was used for this study. A total of 600 surveys were distributed. Once the invalid replies were excluded, a total of 567 effective samples were recovered. The results from this study show significant gender differences in the ‘‘amount of money spent per purchase of cosmetics’’, ‘‘the most recent online purchase of cosmetics’’, ‘‘the time spent on cosmetics’’, ‘‘amount of money spent each month on cosmetics’’, ‘‘amount of money spent per time on cosmetics’’, ‘‘the time spent on buying cosmetics online’’ and ‘‘the satisfaction with the most recent online purchase of cosmetics’’. There were also significant differences in the level of importance assigned to ‘‘brand reputation’’, ‘‘fresh scent’’, ‘‘natural ingredients’’, ‘‘reasonable price’’, ‘‘suitable skin type’’, ‘‘professionalism of service personnel’’, ‘‘recommended by advertising’’ and ‘‘ease of use’’.

1. Introduction

As the Internet and wireless network technologies have a had lot of advancement in decades, e.g., see the notable studies in [1,2], their increasing use has resulted in more online commercial activities, in terms of consumers navigating websites and making financial or nonfinancial transactions. The growing online consumer market allows consumers to make financial transactions online anywhere in the world regardless of their locations. The Internet therefore offers enterprises a growing market with limitless opportunities that they can tap into by providing consumers with online shopping services.1

∗_{Corresponding author.}

E-mail addresses:derjiunn.deng@gmail.com,djdeng@cc.ncue.edu.tw(D.-J. Deng).

1 The consumer online shopping process can be divided into the following steps: Identification of requirements, product brokering, merchant brokering, price negotiation, purchase & delivery and product services & evaluation.

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While enterprises can efficiently and economically conduct their marketing activities through Internet, a challenge in this massive and growing market is to identify potential consumers through appropriate marketing planning and market segmentation [3]. Due to increasing pricing levels and material costs over years, enterprises have intended to lower their financial costs by Internet marketing and online financial transactions, by which renting cost, facility setup cost and manpower cost can be saved, and advertising cost is lowered for increasing the number of potential customers. Hence, Internet marketing and online financial transactions have become a market territory for which each enterprise competes, and the implementation for Internet marketing is to provide online shopping services for customers. Simply speaking, online shopping makes financial transactions over the Internet, in which electronics commerce is derived. It simplifies the process, and further saves logistics and manpower costs. It allows convenient and real-time response to the inquiries from customers, even negotiation of prices, and lowest achieved costs, to be the main line of increasing shopping services. In addition, Internet marketing and financial transactions provide services to customers with low costs, and efficiently raises the sales of the enterprises. Kalakota and Robinson [4] indicated that electronics commerce can solve financial problems, including shortening delivery time, decreasing the procurement cost, decreasing unconfirmed orders (for receiving payment first and then shipping the goods), integrating back-end system effectiveness, increasing the control ability for the supply chain, to electronizing the operations of transactions, transportation, storehouse, and payments to analyze customers’ procurement data with precise prediction on the supply to customers, etc.

The Taiwanese Internet population is growing, and the time period spent online is increasing as well. Around 6.27 million people in Taiwan used the Internet frequently in 2000, and had grown to 10.25 million by 2008. The proportion of frequent Internet users in the Internet population grew from 28% in 2000 to 45% in 2008 [5]. People use the Internet for all kinds of activities like shopping through online platforms [6]. As the number of Taiwanese online consumers increases, the integration of virtual and physical channels together with the forming of the community-based word-of-mouth shopping model produces an increase in the proportion of purchases made online as well. The strength of the Taiwanese online shopping market can be seen in how its size grew explosively from NT $3.89 billion in 2004 to NT $108 billion in 2007 [6].

The data from the Institute for Information Industry (III) indicated that the majority of Taiwanese online shopping consumers made use of ‘‘auction websites’’ and ‘‘shopping websites’’, which accounted for 56% and 47.3% of all purchases, respectively, and together made up over 90% of the whole online shopping market. The main product categories for male Taiwanese auction buyers included ‘‘Computer Software/Hardware and PDAs’’ as well as ‘‘Mobile Phone & Communications’’ at 55.3% and 43.3%, respectively. For female Taiwanese auction buyers, the main product categories included ‘‘Women’s Clothing & Accessories’’ and ‘‘Cosmetics and Skincare’’. In 2006, for example, around 81% of the Taiwanese online shopping market was made up of travel, 3C, cosmetics and fashion products. Cosmetics had the fastest growth rate at 90%.2The top three products purchased by male consumers were: 3C, male boutique goods, as well as books & magazines and cosmetics. It is noteworthy that Taiwanese consumers no longer mainly purchase 3C or books & magazines online and are now expanding their choices. According to the statistics made by the market researcher Euromonitor International, the sales of cosmetics-targeting people grew by over 40% between 1998 and 2003. Another market researcher Datamonitor estimated that in 2004, people spent around NT $89 billion on personal cosmetics. As compared to the saturated female skincare product market, it obviously offers an unexploited market with great growth potential [7].

In light of the above, it is discovered that cosmetics are no longer the exclusive province of women and make the causes behind the annual increases in male spending on cosmetics a topic worth examining. Most previous literature focused on the analysis of online shoppers’ level of satisfaction or analyze the marketing methods, transaction platform and key factors in online shopping (e.g., see [8,9]). Relatively few looked at the gender differences in online shopping importance, satisfaction, perception and behavior, though there existed some works on the differences of other traits (e.g., [10,11]) and the gender differences in online selling recommendation services (e.g., [12]). The main purpose of this study is to analyze the gender differences between consumers in perception, importance and satisfaction when buying cosmetics online. Although fewer innovative statistical techniques are involved in this study, a basic statistical method is sufficient to realize the gender difference of consumer behavior when buying cosmetics online. The results from the empirical analysis of this study hopefully provide the relevant government departments and online vendors with a useful reference in their decision-making.

This study is divided into five sections. Section1gives the introduction to our study. Section2gives the review of literature. Section3gives the research methodology and survey design. Section4gives analysis of survey results. Section5

consists of the conclusion and suggestions.

2. Literature review

2.1. Definition of e-commerce

Electronic commerce (or e-commerce) carries out traditional commercial activities through the new medium of the Internet. E-commerce can be defined as any commercial transaction conducted in an electronic format. Kalakota and

2 In 2008 for example, the growth rates for travel, 3C products and cosmetics were 53 %, 63% and 90%, respectively, with sales of skin-care cosmetic products achieving the highest rate of growth.

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Whinston [13] suggested that e-commerce is the use of the Internet for purchasing, selling or trading products and services. The aim is to reduce costs, shorten product lifecycles, speed up customer feedback and improve the quality of service. E-commerce is the process of online transactions between individuals and enterprises. These include Business-to-Business (B2B) transactions, Business-to-Consumer (B2C) retail sales (or e-retail) and Consumer-to-Consumer (C2C) transactions.

2.2. Strengths of online shopping

As the Internet is immediate, interactive, low-cost, available 24 h, and not restricted by space or national boundaries, online shopping has become the most popular shopping method in recent years. Online shopping is an important application of e-commerce through which consumers can use the Internet to conveniently make online transactions with online shops through electronic catalogs and web pages designed by using Internet protocols [14]. The Internet allows the enterprises to provide more product information online at a cost far lower than other conventional forms of popular media. It enables the enterprises to manufacture, market and sell products as well as provide customers services in a more efficient and pervasive manner while strengthening existing channels at the same time [15]. Most experts believe that price [16,17] and convenience [18,19] are the main advantages in online shopping. Also, trust plays an important role on consumer Internet shopping as e-commerce success is determined in part by whether consumers trust sellers [20]. According to the analysis of [21] on the consumer behavior of online shoppers, the main driving forces in the online shopping market included: helping Internet users overcome psychological barriers, defining the pricing strategy, selecting suitable products, providing a variety of options and personalization services, building a comfortable shopping environment and designing an attractive website that matches the Internet users’ habits [21].

2.3. Online shopping outside Taiwan

The III estimated that in 2008, the US online shopping market was worth approximately US$264.7 billion. The US online vendors have gradually accumulated a better understanding of consumers’ online shopping preferences and are now able to attract them to use more accurate marketing methods and retain them by providing a wide variety of services. As the Internet becomes more widespread and users gain more experience, an increasing number of Internet users are now experimenting with online shopping. The US online shopping market is therefore expected to grow steadily and surpass US$300 billion by 2011.

In Europe, extensive networking infrastructure and rapid growth in the population of Internet users mean that an increasing number of Internet users are beginning to experiment with online shopping. In 2006, the European online shopping market was worth 102.6 Euro and will grow to 228.9 billion Euro in 2010. The UK, in particular, has better Internet penetration and infrastructure, in comparison to the European average. With an Internet penetration rate of 67% as early as 2005, online shopping developed earlier in the UK compared to other European countries. In 2006, the British online shopping market was the largest in Europe with 42% of the European market.

The III Market Intelligence & Consulting Institute (MIC) estimated the Taiwanese online shopping market to be worth NT $243 billion3_{in 2008, an increase of $32.3 on 2007. Online shopping accounted for NT $136 billion while online auctions}

accounted for NT $107 billion. Online shopping sales were also expected to continue growing. The MIC data shows that online shopping’s share of the retail industry had increased from 3.3% in 2007 to 4.0% and then 4.7% in 2009, growing despite the economic recession. In 2008, the average amount spent online per person actually increased over 2007. Up to 57% had spent more than NT $3000 online and Internet users over the age of 50 spent on average nearly NT $20,000 online [6]. Online transactions have therefore become an important component of modern economic activity. According to the III, the Taiwanese C2C market in 2007 had grown to NT $110 billion in 2007. The market has grown at an average rate of 56% per year since 2004 with almost a half of all the shoppers coming from the 20- to 29-year-old demographic. As the number of non-adults who used to access the Internet continues growing, the online shopping market has expanded as well, producing drastic changes in shopping habits and structure [6].

The online shopping product categories seeing faster growth were clothing fashion and cosmetics products with a Compound Annual Growth Rate (CAGR) of 88% and 49%, respectively. Growth in 3C and travel products was slowed by the state of the economy so they were 25% and 21%, respectively. According to the data from the III, in 2008 the increasing convenience of the Taiwanese online shopping market, the lower product prices of some products compared to retail channels as well as the increasing variety of online merchandise available meant that an increasing number of consumers are now turning to the Internet instead [6].

3 In Taiwan shopping websites can be divided into three types: Shopping centers, shopping platforms and auction platforms. The first two are similar to physical shopping malls and stores, except their catalogs and transaction information are made available online. Auction platforms, on the other hand, are quite different from their real-world counterpart. On the auction platform, consumers can compare product prices in a very low-cost manner. At the end of April 2009, the largest online auction platform was Yahoo which was established in September, 2001. In 2007, Yahoo’s auction revenues were NT $7.5 billion, and this grew by 30% in 2008. By 2009, revenues totaled NT $15 billion, surpassing department stores such as the Breeze Centre, Shin Kong Mitsukoshi’s Taichung Store and Shin Kong Mitsukoshi’s Nanjing W. Rd. Store [22].

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Fig. 1. The research framework of this study.

2.4. Literature on purchasing behavior for cosmetics

Cosmetics can be divided into skin-care, hair-care and facial-care cosmetic products, depending on their purposes. Cosmetics here refer to the cosmetics that can be used to hide facial flaws, highlight the features and make the wearer look more elegant. From previous literature, Wang and Yeh [14] studied consumers’ perception of website attributes as well as the pricing and convenience of online shopping. The previous studies on online Taiwanese user groups [21] found that online vendors currently target white collar workers and students, with students accounting for 61.54 % because they are the most frequent Internet users [23]. As young people account for the majority of Internet users, the development of the Internet and e-commerce has given rise to a new breed of Internet-savvy users familiar with games, chat rooms and browsing. They are particularly attracted to mail orders and online shopping and so will form the largest potential market for online shopping in the future. Wang and Yeh [14] defined these young Internet users as university students with Internet experience aged between 20 and 30. They then studied the consumer attributes and consumer intent of online shopping from the perspective of these young Internet users. Wang and Ho [3] explored the key factors influencing purchasing amount, product, website and purchasing frequency during the decision-making process for online shopping. Previous literature on cosmetics included: examination of the factors that influence female consumers’ selection of cosmetic retail channel [24]; analysis of demographic variables and purchasing behavior for female consumers who purchase cosmetics online [25]; an examination of brand and sales channel’s influence on female consumers’ purchase of cosmetics from a consumer behavior [12], as the product brand determines the success of E-commerce in part (e.g., see [8]).

The use of cosmetics is no longer exclusive to women. Lai [26] indicated that 80 % of men use male cosmetics. Most tend to be under 25 years of age, and facial care products are the main type used. Many brands have also launched male cosmetics as well. Jian [27] analyzed men’s use of cosmetics and looked at the differences in products used among men in northern Taiwan with different lifestyles. Lai [26] studied the purchasing motivations and consumer characteristics of male consumers in the northern, central and southern regions of Taiwan when buying cosmetics, respectively. Lai [28] analyzed the factors governing the success of men’s skin-care product market and showed that men’s skin-care product market as well as men’s purchase of cosmetics has become increasingly important issues. An analysis of past literature shows that most research focused mainly on female consumers, but fewer on male consumers. There has also been no literature that compared differences between men and women’s online shopping behaviors when buying cosmetics. This study therefore conducted a comparative analysis of gender differences in consumer habits, characteristics, perception, importance and satisfaction in buying cosmetics online. The goal is to gain a better understanding of gender differences in consumer behavior when buying cosmetics online.

3. Methodology and survey design

An online questionnaire survey was used in this study with the primary purpose of investigating gender differences in the consumer behavior when buying cosmetics online. The research framework is shown inFig. 1.

This study developed the six questions below based on the above.

H1: Do significant gender differences exist in consumers’ perception for online shopping? H2: Do significant gender differences exist in consumers’ importance for online shopping? H3: Do significant gender differences exist in consumers’ satisfaction for online shopping?

H4: Do significant gender differences exist in consumers’ perception of online shopping for cosmetics? H5: Do significant gender differences exist in consumers’ importance when purchasing cosmetics online? H6: Do significant gender differences exist in consumers’ satisfaction when purchasing cosmetics online?

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3.1. Research subject and scope

Since the previous studies on consumer behavior of online shopping were conducted by questionnaire surveys in general, this study continues applying the questionnaire survey to conduct our analysis. This study consisted of an online survey that did not specifically require the consumers with online shopping experience, and also had no gender restrictions, in order to increase the depth and breadth of the analysis. As there are many potential consumers among Internet users, the level of acceptance for online shopping among those without online shopping experience can also serve as a reference during decision-making. Consumers with no experience in shopping for cosmetics online can also be used for differential analysis of their socio-economic backgrounds. To avoid repeating respondents and to make the best use of limited resources and time, the convenience sampling method was used to conduct an online survey of consumers in the hopes of acquiring sufficient samples. Note that convenience sampling is a type of non-random sampling method and based purely on convenience.

3.2. Number of surveys distributed

Since the population for the online questionnaire survey conducted in this study is ‘‘the consumers who had experience of online shopping’’, this study applies the My3q system (which is one of the most convincing online questionnaire platforms in Taiwan) to conduct our online questionnaire survey. On distributing the online questionnaire survey, the beginning of the questionnaire reminds the respondents that ‘‘only the consumer who had the experience of online shopping is able to respond to this questionnaire’’, and hence, there is no response from those who did not have any experience of online shopping, assuming that each respondent can be trusted. Since the size of the population for this study cannot be known, the sample size is calculated as follows:

n

=

Z

2

α/2

·

p

(

1

−

p

)

d2

where n is the number of effective samples when the population is unknown, Z

α/

2 is the standard normal distribution (1.96 with a confidence interval of 95%), d is the allowable sampling error of 0.05, and p is the representative probability (generally 0.5). Assuming a confidence interval of 95% with a sampling error of 5%, we require at least 384 effective samples by using the above formula. A recovery rate of 95% was assumed for this study, so 384 surveys should be distributed. To reduce the error, 600 surveys were distributed for this study to reach the standard for validity.

3.3. Survey design

This survey was divided into four parts. The detailed survey design is shown inTable 1. Part 1 consists of the respondents’ basic details, part 2 checks whether the respondents had any online shopping experiences, part 3 looks at the respondents’ perception, importance and satisfaction with online shopping, while part 4 looks at the respondents’ perception, importance and satisfaction with online shopping for cosmetics. The design of this study’s survey was based on the relevant literatures and research framework. A Likert 5-point scale was used, with 1 meaning ‘‘strongly disagree, very unimportant, very dissatisfied’’, 2 meaning ‘‘disagree, unimportant, dissatisfied’’, 3 meaning ‘‘average’’, 4 meaning ‘‘agree, important, satisfied’’ and 5 meaning ‘‘strongly agree, very important, very satisfied’’. The survey consisted of four dimensions, including previous online shopping experiences, personal characteristics, seller services and external incentives.

4. Survey results

4.1. Reliability analysis

The results from the reliability analysis of the survey were shown inTable 2. The analysis shows that the reliability of the results was high. The reliability for agreement with online shopping was 0.874, that for importance in online shopping was 0.955, and that for satisfaction with online shopping was 0.920. As for the respondents with no online shopping experience, reliability was 0.807. Finally, the reliability for experience with online shopping for cosmetics was 0.919, so the survey designed and distributed for this study possessed a certain level of reliability.

4.2. Descriptive analysis of survey sample

Since we require at least 384 effective samples as mentioned above, a greater number of surveys should be distributed to increase the response rate of effective samples. Hence, in our study, a total of 600 surveys were distributed for this study. A total of 567 effective samples were recovered after the invalid responses were eliminated. Provided below is a description of the sample data on gender, age, occupation, education, place of residence, place of birth, marital status and monthly family income. As shown inTable 3, in gender ‘‘female’’ was the majority with 340 responses (60%) while ‘‘male’’ had 227 responses (40%). For age, the ‘‘21–25’’ bracket was the largest age group with 255 responses (45%), followed by ‘‘under 20’’ with 132 responses (23.3%). Occupation-wise, ‘‘student’’ was the majority with 300 responses (52.9 %) followed by the

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Table 1

The dimensions of this study’s survey design.

Dimension Category Question

Online shopping experience Have online shopping experiences Have purchased products online (of any type)

Level of satisfaction with most recently purchased product (of any type) Still willing to purchase products online (of any type)

Have purchased cosmetics online

Level of satisfaction with mostly recently purchased cosmetics Still willing to purchase cosmetics online

No online shopping experiences Not as fun as window shopping Cannot see the actual product

Website contents are provided for reference only Product delivery speed

Worried about product guarantee

Questions about the seller’s quality of service Concerns about security of payment method Risk of not receiving products

Worried about of personal details being compromised No guarantee on after-sales service

Have online shopping experiences for cosmetics Brand reputation Obvious effect Attractive packaging Fresh scent Natural ingredients Reasonable price Spokesperson Suitable skin type Come with gifts

Professionalism of service personnel Recommended by advertising Recommended by experts Product’s source country Ease of use

Personal characteristics Demographic variables Gender Age Occupation Education Place of residence Place of birth Marital status Monthly family income Frequency of Internet use Hours spent online each day

Number of shopping site views each day Number of hours spent on shopping sites each day Seller service Ordering Convenient return or replacement process

Payment method Diversification of payment methods Can pay online by credit card

Can pay in installments with zero interest rate Delivery Diversification of delivery methods

Fast delivery

Reasonable delivery costs Guarantee Transparent seller record

Security of online transactions Website design Diversification of seller websites

Elegant website design Easy to search for products Service Fast response to questions

Easy to communicate with seller External incentives Price More product specials or promotions

More products with free shipping Price cheaper than physical stores Promotion Easily attracted by webpage advertising

Provide special product bundles Product attributes Diversification of products

Easy to buy

Product not easy to buy on the market Product only available online

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Table 1 (continued)

Dimension Category Question

Quality Better product quality

Brand Product is purchased according to the notability of brands Source of opinion Easy to find users’ reviews

Wide diversification of advertising

Table 2

Reliability analysis of the survey.

Category αvalue

Agreement with online shopping 0.874 Importance in online shopping 0.955 Satisfaction with online shopping 0.920 Without online shopping experiences for cosmetics 0.807 With online shopping experiences for cosmetics 0.919

‘‘service industry’’ with 91 responses (16.0%).4_{In education, the largest group was ‘‘university’’ with 388 responses (68.4%).}

In place of residence, the largest group was ‘‘North’’ with 330 responses (58.2%) followed by the ‘‘South’’ with 172 responses (30.3%).5_{For marital status, the overwhelming majority were ‘‘unmarried’’ with 478 responses (84.3%). ‘‘Married’’ had just}

89 responses (15.7%). For monthly family income, the largest group was ‘‘$50,000–70,000’’ with 161 responses (28.4%).6

4.3. Gender differences in experiences for Internet use and online shopping

The t-test of mean difference was carried out to determine if the respondents’ experiences varied due to gender. Gender shows that statistically significant differences exist in ‘‘average amount of money spent on online shopping’’ and ‘‘amount of money spent on recent online purchase of cosmetics’’. The mean value for ‘‘average amount of money spent on online shopping’’ was NT $710.661 for male respondents and NT $1,338.841 for female respondents.Table 4shows that statistically significant difference exists. The mean value for ‘‘amount of money spent on recent online purchase of cosmetics’’ was 3.28 for male respondents and 3.53 for female respondents with a P value of 0.007, so the difference was statistically significant. There was no statistically significant difference between the genders for ‘‘the number of hours spent online each day’’, ‘‘the frequency of browsing the shopping site every day’’ and ‘‘the number of hours spent on shopping sites each day’’.

4.4. Gender differences in cosmetics shopping experiences

Table 5shows statistically significant differences between genders on ‘‘time spent on cosmetics’’, ‘‘amount of money

spent on cosmetics each month’’ and ‘‘amount of money spent on purchasing cosmetics each time’’. The mean value for ‘‘time spent on cosmetics’’ was 4.90 for male respondents and 6.54 for female respondents. The P value was 0.000, so the difference was statistically significant. The mean value for ‘‘amount of money spent on cosmetics each month’’ was 612.34 for male respondents and 1132.94 for female respondents. The P value was 0.000, so the difference was also statistically significant. The mean value for ‘‘amount of money spent on cosmetics each time’’ was 742.81 for male respondents and 958.98 for female respondents. The P value was 0.000, so the difference was statistically significant.

4.5. Gender differences in cosmetics online shopping experiences

Table 6shows that statistically significant differences between genders for both ‘‘time spent purchasing cosmetics online’’

and ‘‘level of satisfaction with the most recent online purchase of cosmetics’’. The mean level of satisfaction with ‘‘time spent purchasing cosmetics online’’ was 1.64 for male respondents and 2.01 for female respondents. The P value was 0.003, so the difference was statistically significant. The mean level of satisfaction for ‘‘the most recent online purchase of cosmetics’’ was 3.28 for male respondents and 3.73 for female respondents. The P value was 0.000, so the difference was also statistically significant. There was no significant gender difference for ‘‘amount of money spent on cosmetics online each month’’.

4 In Taiwan, it is reasonable that the university students account for a higher ratio of online shopping and Internet using. Hence, the result conducted by this study is consistent with our expectation.

5 In general the residence places of Taiwan are divided into five regions: north, central, south, east, and offshore. In terms of population, the people in the north region of Taiwan are the most (accounting for 1/3 of Taiwan). Therefore, the result of this study in which those in the north region of Taiwan have the most experience of online shopping is consistent with our expectation.

6 According to the ‘‘Survey on Internet Users in Taiwan’’ conducted by the Institute for Information Industry in 2011, it was shown that over 30% of the Internet users are students (referring tohttp://distance.shu.edu.tw/98dmcix/d01.htm). Although the student samples account for a higher ratio of the total samples (close to 50%), it still falls into a reasonable range. In addition, since most of the samples are no more than 35 years old, the unmarried samples accounting for a higher ratio of the total samples are consistent with our expectation.

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Table 3

Analysis of respondents’ background.

Variables Frequency (person) Percentage (%) Gender Male 227 40.0 Female 340 60.0 Age Under 20 132 23.3 21–25 255 45.0 26–30 103 18.2 31–35 31 5.5 36–40 15 2.6 Over 41 31 5.5 Occupation Unemployed 20 3.5 Retired 9 1.6 Service industry 91 16.0 Casual 57 10.1 Manufacturing industry 19 3.4 Primary industry 2 0.4 Public service 15 2.6 Healthcare 18 3.2 Finance 10 1.8 Student 300 52.9 Homemaker 8 1.4 Other 18 3.2 Education

Below junior high school 33 5.8 Senior high school/vocational 114 20.1

Undergraduate 388 68.4 Postgraduate 32 5.6 Place of residences South 172 30.3 Central 46 8.1 North 330 58.2 East 5 0.9 Offshore 14 2.5 Marital status Married 89 15.7 Unmarried 478 84.3

Monthly family income

Less than NT $10,000 84 14.8 NT $10,000–30,000 76 13.4 NT $30,001–50,000 132 23.3 NT $50,001–70,000 161 28.4 NT $70,001–90,000 75 13.2 More than NT $90,001 39 6.9 Table 4

Gender differences in online experience and online shopping experiences.

Dimension Gender Frequency Mean Standard deviation T value Significance The number of hours spent online each day Male 227 3.90 1.457 1.007 0.315

Female 340 3.78 1.474

The number of shopping site views each day Male 227 3.12 2.611 −1.732 0.084 Female 340 3.52 2.687

The number of shopping site views each day Male 227 2.37 0.828 −1.468 0.143 Female 340 2.49 0.970

Amount of money spent on online shopping each month (NT $) Male 227 710.661 561.23 −3.491 0.001*** Female 340 1338.841 899.41

Level of satisfaction with the most recent online purchase (Likert 5 points) Male 157 3.28 0.919 ₋ 2.708 0.007** Female 254 3.53 0.888 ∗ P<0.05. **_P_<₀_._01. ***_P_<₀_._001.

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Table 5

Gender differences in cosmetics shopping experiences.

Dimension Gender Frequency Mean Standard deviation T value Significance Time spent on cosmetics (hours/each time) Male 227 4.90 3.202 −5.927 0.000***

Female 340 6.54 3.254

Amount of money spent on cosmetics each month (NT $) Male 227 612.34 898.825 −5.222 0.000*** Female 340 1132.94 1310.100

Amount of money spent on cosmetics each time (NT $) Male 227 742.81 329.147 −6.933 0.000*** Female 340 958.98 385.129 ∗ P<0.05. ** P<0.01. ***_P_<₀_._001. Table 6

Gender differences in cosmetics online shopping experiences.

Dimension Gender Frequency Mean Standard deviation T value Significance Time spent purchasing cosmetics online (hours/each time) Male 227 1.64 1.223 −3.012 0.003**

Female 340 2.01 1.531

Amount of money spent on cosmetics online each month (NT $) Male 227 397.37 971.799 −1.249 0.212 Female 340 493.53 845.433

Level of satisfaction with the most recent online purchase of cosmetics (Likert 5 points) Male 106 3.28 0.740 ₋ 4.614 0.000*** Female 188 3.73 0.825 ∗_P_<₀_._05. **_P_<₀_._01. ***_P_<₀_._001.

4.6. Gender differences in agreement with online shopping

The t-test was conducted to determine if there were gender differences between respondents’ level of agreement with online shopping.Table 7shows statistically significant differences between genders for both ‘‘fun of shopping online’’ and ‘‘diversification of payment methods’’. Note that we apply a Likert scale of 1–5 inTable 7. The mean level for ‘‘fun of shopping online’’ was 3.53 for male respondents and 3.70 for female respondents. The P value was 0.025, so the difference was statistically significant. The mean level for ‘‘diversification of payment methods’’ was 3.85 for male respondents and 3.97 for female respondents. The P value was also 0.025, so the difference was statistically significant as well. Statistically significant differences existed between genders on agreement with ‘‘fast delivery’’ and ‘‘reasonable delivery costs’’ for online shopping. The mean level for ‘‘fast delivery’’ was 3.39 for male respondents and 3.62 for female respondents. The P value was 0.004, so the difference was statistically significant. The mean level for ‘‘reasonable delivery costs’’ was 3.40 for male respondents and 3.69 for female respondents. The P value was 0.000, so the difference was statistically significant as well. Significant differences were found in agreement with the five items on online shopping’s ‘‘security of online transactions’’, ‘‘easy to buy’’ and ‘‘better product quality’’. The mean level for ‘‘security of online transactions’’ was 3.32 for male respondents and 3.54 for female respondents. The P value was 0.012, so the difference was statistically significant. The mean level for ‘‘easy to buy’’ transactions’’ was 3.77 for male respondents and 4.28 for female respondents. The P value was 0.048, so the difference was statistically significant. The mean level for ‘‘easy to find user reviews’’ was 3.57 for male respondents and 3.74 for female respondents. The P value was 0.015, so the difference was statistically significant. The mean level for ‘‘better product quality’’ was 3.02 for male respondents and 3.29 for female respondents. The P value was 0.002, so the difference was statistically significant.

4.7. Gender differences for importance in online shopping

The t-test was conducted to determine if there were gender differences between respondents’ level of importance in online shopping. FromTable 8, there was a statistically significant difference between genders on the level of importance of ‘‘fun of shopping online’’. The mean level for ‘‘fun of shopping online’’ was 3.53 for male respondents and 3.70 for female respondents. The P value was 0.171, so the difference was statistically significant. There were no statistically significant differences between genders on the level of importance of ‘‘not limited by time’’, ‘‘convenience of shopping from home’’, ‘‘diversification of payment methods’’, ‘‘can pay online by credit card’’, ‘‘can pay in installments with zero interest rate’’, ‘‘wide diversification of advertising’’, ‘‘easy to search for products’’, ‘‘diversification of products’’, ‘‘easy to buy’’, ‘‘product not easy to buy on the market’’, ‘‘product only available online’’, ‘‘diversification of shopping websites’’, ‘‘more product diversification’’, ‘‘fast response to questions, ‘‘ease of contacting seller’’, ‘‘transparent seller record’’, ‘‘easy to find user reviews’’, ‘‘more products on special’’, ‘‘more products with free shipping’’, ‘‘price cheaper than physical stores’’, ‘‘provide special product bundles’’, ‘‘detailed product specifications and features’’, ‘‘better product quality’’ and ‘‘product purchased according to the notability of brands’’.

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Table 7

Gender differences in agreement with online shopping.

Dimension Gender Frequency Mean Standard deviation T value Significance

Not limited by time Male 227 4.09 0.717 0.342 0.733

Female 340 4.06 0.849

Convenience of shopping at home Male 227 4.00 0.787 0.084 0.933

Female 340 3.99 0.831

Fun for shopping online Male 227 3.53 0.894 −2.240 0.025*

Female 340 3.70 0.891

Diversification of payment methods Male 227 3.85 0.763 −1.961 0.050*

Female 340 3.97 0.758

Can pay online by credit card Male 225 3.80 0.811 0.022 0.983

Female 340 3.80 0.798

Can pay in installments with zero interest rate Male 225 3.84 0.739 1.546 0.123

Female 340 3.74 0.747

Convenient return or replacement process Male 227 3.07 0.916 −0.752 0.453

Female 340 3.14 1.025

Diversification of delivery methods Male 227 3.76 0.740 −1.734 0.084

Female 340 3.87 0.805

Fast delivery Male 227 3.39 0.888 −2.900 0.004**

Female 340 3.62 0.959

Reasonable delivery costs Male 227 3.40 0.788 −4.177 0.000***

Female 340 3.69 0.819

Security of online transactions Male 227 3.32 0.958 −2.527 0.012*

Female 340 3.54 1.005

Elegant website design Male 227 3.62 0.802 −1.380 0.168

Female 340 3.72 0.825

Attracted by webpage advertising Male 225 3.60 0.931 0.215 0.830

Female 340 3.58 0.973

Wide diversification of advertising Male 225 3.80 0.744 −0.483 0.629

Female 340 3.83 0.801

Easy to search for products Male 225 3.75 0.892 −1.384 0.167

Female 340 3.85 0.832

Diversification of products Male 225 4.00 0.698 −0.954 0.341

Female 340 4.11 1.785

Easy to buy Male 225 3.77 0.865 −2.033 0.043*

Female 340 4.28 3.666

Product not easy to buy on the market Male 225 3.87 0.766 0.638 0.524

Female 340 3.83 0.757

Product online available online Male 225 3.83 0.797 0.776 0.438

Female 340 3.77 0.797

Diversification of seller websites Male 225 3.83 0.751 −1.805 0.072

Female 340 3.95 0.793

More product diversification Male 225 3.89 0.757 0.362 0.717

Female 340 3.86 0.790

Fast response to questions Male 225 3.40 0.866 −1.985 0.048*

Female 340 3.55 0.859

Ease of contacting seller Male 225 3.42 0.853 −0.566 0.572

Female 340 3.46 0.887

Transparent seller record Male 225 3.67 0.896 −1.852 0.065

Female 340 3.81 0.876

Easy to find user reviews Male 225 3.57 0.822 −2.438 0.015*

Female 340 3.74 0.846

More products on special Male 225 3.77 0.694 0.626 0.532

Female 340 3.73 0.759

More products with free shipping Male 225 3.47 0.911 −0.147 0.883

Female 340 3.48 0.871

Price cheaper than physical stores Male 225 3.90 0.722 −0.035 0.972

Female 340 3.90 0.746

Provide special product bundles Male 225 3.61 0.794 −0.556 0.579

Female 339 3.68 1.805

Detailed product specifications and features Male 225 3.39 0.900 −1.893 0.059

Female 340 3.54 0.966

Better product quality Male 225 3.02 0.911 −3.181 0.002**

Female 340 3.29 1.021

Product is by well-known brand Male 225 3.56 0.838 −0.988 0.324

Female 340 3.72 2.387

* _P_<₀_._05. **_P_<₀_._01. ***_P_<₀_._001.

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Table 8

Gender differences for importance in online shopping.

Not limited by time Male 225 4.09 1.017 −0.239 0.812

Female 340 4.06 0.925

Convenience of shopping from home Male 225 4.00 0.913 1.317 0.188

Female 340 3.99 0.978

Fun of shopping online Male 225 3.53 0.927 −1.372 0.171

Female 340 3.70 1.885

Diversification of payment methods Male 225 3.85 0.963 −0.235 0.814

Female 340 3.97 0.964

Can pay online by credit card Male 224 3.80 1.046 −0.871 0.384

Female 340 3.80 1.136

Can pay in installments with zero interest rate Male 224 3.84 1.011 −1.861 0.063

Female 340 3.74 1.143

Convenient return or replacement process Male 225 3.07 0.937 −1.789 0.074

Female 340 3.14 0.970

Diversification of delivery methods Male 225 3.76 1.004 0.287 0.774

Female 340 3.87 0.917

Fast delivery Male 225 3.39 1.015 −1.065 0.288

Female 340 3.62 0.945

Reasonable delivery costs Male 225 3.40 0.992 −1.063 0.288

Female 340 3.69 0.921

Security of online transactions Male 225 3.32 0.982 −2.792 0.005∗

Female 340 3.54 0.934

Elegant website design Male 225 3.62 0.909 −1.194 0.233

Female 340 3.72 0.991

Easily attracted by webpage advertising Male 225 3.60 0.985 −0.138 0.890

Female 340 3.58 1.894

Female 340 3.83 0.970

Female 340 3.85 0.858

Diversification of products Male 225 4.00 0.888 −0.845 0.399

Female 340 4.11 0.892

Easy to buy Male 225 3.77 0.978 −0.935 0.350

Female 340 4.28 0.925

Product not easy to buy on the market Male 225 3.87 0.959 0.988 0.324

Female 340 3.83 0.919

Female 339 3.77 0.833

Diversification of seller websites Male 225 3.83 0.839 0.469 0.640

Female 340 3.95 0.914

More product diversification Male 224 3.89 0.861 −0.713 0.476

Female 340 3.86 0.958

Fast response to questions Male 225 3.40 0.926 −0.545 0.586

Female 340 3.55 0.930

Female 340 3.46 0.923

Transparent seller record Male 225 3.67 0.916 −0.0504 0.615

Female 340 3.81 1.011

Easy to find user reviews Male 225 3.57 0.904 1.007 0.315

Female 340 3.74 0.981

More products on special Male 225 3.77 0.886 0.579 0.563

Female 340 3.73 0.933

Female 340 3.48 0.952

Price cheaper than physical stores Male 225 3.90 0.888 −1.031 0.303

Female 340 3.90 0.942

Provide special product bundles Male 225 3.61 0.937 0.946 0.345

Female 340 3.68 0.926

Detailed product specifications and features Male 225 3.39 0.930 −0.247 0.805

Female 340 3.54 0.951

Better product quality Male 225 3.02 0.953 −0.304 0.761

Female 340 3.29 0.904

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4.8. Gender differences in satisfaction with online shopping

The t-test was conducted to determine if there were gender differences between respondents’ level of satisfaction with online shopping.Table 9shows that statistically significant differences existed between genders on level of satisfaction with six items: ‘‘convenience of shopping from home’’, ‘‘fun of shopping online’’, ‘‘can pay in installments with zero interest rate’’, ‘‘convenient return or replacement process’’, ‘‘reasonable delivery costs’’ and ‘‘more products on special’’. The mean level for ‘‘convenience of shopping from home’’ was 3.84 for male respondents and 4.04 for female respondents. The P value was 0.018, so the difference was statistically significant. The mean level for ‘‘fun of online shopping’’ was 3.62 for male respondents and 3.83 for female respondents. The P value was 0.010, so the difference was statistically significant. The mean level for ‘‘can pay in installments with zero interest rate’’ was 3.34 for male respondents and 3.56 for female respondents. The P value was 0.002, so the difference was statistically significant. The mean level for ‘‘convenient return or replacement process’’ was 3.30 for male respondents and 3.58 for female respondents. The P value was 0.043, so the difference was statistically significant. The mean level for ‘‘reasonable delivery costs’’ was 3.36 for male respondents and 3.54 for female respondents. The P value was 0.043, so the difference was statistically significant. The mean level for ‘‘more products on special’’ was 3.43 for male respondents and 3.69 for female respondents. The P value was 0.001, so the difference was statistically significant.

4.9. Gender differences in perceived importance without online shopping experiences

The t-test was conducted to determine if gender differences existed in perceived importance without online shopping experiences. There were statistically significant differences between genders on four items: ‘‘the website contents are provided for reference only’’, ‘‘product delivery speed’’, ‘‘worried about product guarantee’’ and ‘‘questions about seller’s quality of service’’. The mean level for ‘‘the website contents are provided for reference only’’ was 4.17 for male respondents and 3.80 for female respondents. FromTable 10, it can be seen that the P value was 0.002, so the difference was statistically significant. The mean level for ‘‘product delivery speed’’ was 3.76 for male respondents and 3.51 for female respondents. The P value was 0.036, so the difference was statistically significant. The mean level for ‘‘worried about product guarantee’’ was 4.39 for male respondents and 3.99 for female respondents. The P value was 0.002, so the difference was statistically significant. The mean level for ‘‘questions about seller’s quality of service’’ was 4.41 for male respondents and 3.95 for female respondents. The P value was 0.000, so the difference was statistically significant. There were no significant gender differences on importance of ‘‘online shopping not as fun as window shopping’’, ‘‘cannot see the actual product’’, ‘‘concerns about security of payment method’’, ‘‘risk of not receiving product’’, ‘‘worried about personal details being compromised’’ and ‘‘no guarantee on after-sales service’’.

4.10. Gender differences in importance when purchasing cosmetics online

The t-test was conducted to determine if there were gender differences between respondents on the level of importance when purchasing cosmetics online. There were significant gender differences in the importance of four items: ‘‘brand reputation’’, ‘‘fresh scent’’, ‘‘natural ingredients’’ and ‘‘reasonable prices’’. InTable 11, the mean level for ‘‘brand reputation’’ was 3.92 for male respondents and 3.57 for female respondents. The P value was 0.001, so the difference was statistically significant. The mean level for ‘‘fresh scent’’ was 3.57 for male respondents and 3.78 for female respondents. The P value was 0.048, so the difference was statistically significant. The mean level for ‘‘natural ingredients’’ was 3.67 for male respondents and 4.05 for female respondents. The P value was 0.001, so the difference was statistically significant. The mean level for ‘‘reasonable price’’ was 3.91 for male respondents and 4.17 for female respondents. The P value was 0.030, so the difference was statistically significant. There were also statistically significant differences between the genders for the following four items: ‘‘suitable skin type’’, ‘‘professionalism of service personnel’’, ‘‘recommended by advertising’’ and ‘‘ease of use’’. The mean level for ‘‘suitable skin type’’ was 3.75 for male respondents and 4.18 for female respondents. The P value was 0.001, so the difference was statistically significant. The mean level for ‘‘professionalism of service personnel’’ was 3.66 for male respondents and 3.91 for female respondents. The P value shown inTable 11was 0.010, so the difference was statistically significant. The mean level for ‘‘recommended by advertising’’ was 3.42 for male respondents and 3.72 for female respondents. The P value was 0.012, so the difference was statistically significant. The mean level for ‘‘ease of use’’ was 3.75 for male respondents and 4.02 for female respondents. The P value was 0.019, so the difference was statistically significant.

4.11. Gender differences in satisfaction with cosmetics purchased online

The t-test was conducted to determine if there were gender differences between respondents on the level of satisfaction with cosmetics purchased online. Statistically significant gender differences were found in the level of satisfaction with ‘‘reasonable prices’’, ‘‘product’s source country’’ and ‘‘ease of use’’. The mean level for ‘‘reasonable prices’’ was 3.45 for male respondents and 3.75 for female respondents.Table 12 shows that the P value was 0.015, so the difference was statistically significant. The mean level for ‘‘product’s source country’’ was 3.60 for male respondents and 3.88 for female

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Table 9

Gender differences in satisfaction with online shopping.

Not limited by time Male 157 3.91 0.796 −1.518 0.130

Female 254 4.04 0.817

Convenience of shopping from home Male 157 3.84 0.755 −2.370 0.018*

Female 254 4.04 0.840

Online shopping is fun Male 157 3.62 0.797 −2.587 0.010**

Female 254 3.83 0.819

Diversification of payment methods Male 157 3.73 0.683 −1.020 0.308

Female 254 3.81 0.743

Can pay online by credit card Male 157 3.39 0.799 −1.169 0.243

Female 254 3.50 0.884

Can pay in installments with zero interest rate Male 157 3.34 0.626 −3.066 0.002**

Female 254 3.56 0.740

Convenient return or replacement process Male 157 3.30 0.780 −3.357 0.001***

Female 254 3.58 0.861

Diversification of delivery methods Male 157 3.68 0.818 0.377 0.706

Female 254 3.65 0.739

Fast delivery Male 157 3.48 0.837 0.144 0.885

Female 254 3.47 0.768

Reasonable delivery costs Male 157 3.36 0.848 −2.030 0.043*

Female 254 3.54 0.860

Security of online transactions Male 157 3.52 0.997 −1.109 0.268

Female 254 3.63 0.965

Elegant website design Male 157 3.74 0.681 0.140 0.889

Female 254 3.73 0.776

Easily attracted by webpage advertising Male 157 3.64 0.769 −0.109 0.914

Female 254 3.65 0.805

Female 254 3.73 0.781

Female 254 3.86 0.846

Diversification of products Male 157 3.82 0.715 0.159 0.873

Female 254 3.80 0.770

Easy to buy Male 157 3.87 0.885 −0.469 0.639

Female 254 3.91 0.785

Product not easy to buy on the market Male 157 3.80 0.814 −0.832 0.406

Female 254 3.87 0.837

Female 254 3.63 0.719

Diversification of seller websites Male 157 3.79 0.707 −1.316 0.189

Female 254 3.89 0.772

More product diversification Male 157 3.81 0.744 −1.242 0.215

Female 254 3.91 0.780

Fast response to questions Male 157 3.48 0.837 −1.122 0.262

Female 254 3.57 0.806

Female 254 3.54 0.767

Transparent seller record Male 157 3.64 0.899 0.740 0.460

Female 254 3.57 1.002

Easy to find user reviews Male 157 3.61 0.897 0.376 0.707

Female 254 3.57 0.898

More products on special Male 157 3.43 0.811 −3.408 0.001***

Female 254 3.69 0.711

Female 254 3.42 0.998

Price cheaper than physical stores Male 157 3.74 0.752 1.167 0.244

Female 254 3.65 0.754

Provide special product bundles Male 157 3.61 0.758 −1.436 0.152

Female 254 3.72 0.769

Detailed product specifications and features Male 157 3.57 0.900 0.940 0.348

Female 254 3.48 0.952

Better product quality Male 157 3.25 0.933 −1.534 0.126

Female 254 3.41 1.028

Female 254 3.62 0.820

*_P_<₀_._05. **_P_<₀_._01. ***_P_<₀_._001.

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Table 10

Gender differences in perceived importance without online shopping experiences.

Dimension Gender Frequency Mean Standard deviation T value Significance Online shopping not as fun as window shopping Male 70 2.94 0.832 −1.201 0.232

Female 86 3.10 0.841

Cannot see the actual product Male 70 4.34 0.587 1.170 0.244

Female 86 4.22 0.693

Website contents are provided for reference only Male 70 4.17 0.722 3.230 0.002**

Female 86 3.80 0.700

Product delivery speed Male 70 3.76 0.690 2.111 0.036*

Female 86 3.51 0.747

Worried about product guarantee Male 70 4.39 0.708 3.101 0.002**

Female 86 3.99 0.861

Questions about the seller’s quality of service Male 70 4.41 0.771 3.728 0.000***

Female 86 3.95 0.766

Concerns about security of payment method Male 70 4.00 0.978 −0.577 0.565

Female 86 4.08 0.785

Risk of not receiving product Male 70 4.16 0.773 −0.216 0.829

Female 86 4.19 0.875

Worried about of personal details being compromised Male 70 4.00 0.834 1.026 0.307

Female 86 3.85 0.976

No guarantee on after-sales service Male 70 4.00 0.868 1.096 0.275

Female 86 3.85 0.847

* _P_<₀_._05. **_P_<₀_._01. ***_P_<₀_._001.

Table 11

Gender differences in importance when purchasing cosmetics online.

Brand reputation Male 106 3.92 0.825 3.300 0.001***

Female 188 3.57 0.919

Obvious effect Male 106 4.17 0.798 −1.960 0.051

Female 188 4.35 0.703

Attractive packaging Male 106 3.57 0.926 −0.289 0.773

Female 188 3.60 0.799

Fresh scent Male 106 3.57 1.087 −1.985 0.048*

Female 188 3.78 0.767

Natural ingredients Male 106 3.67 1.030 −3.311 0.001***

Female 188 4.05 0.885

Reasonable price Male 106 3.91 1.167 −2.180 0.030*

Female 188 4.17 0.891

Spokesperson Male 106 3.02 0.995 1.339 0.182

Female 188 2.87 0.843

Suitable skin type Male 106 3.75 1.155 −3.481 0.001***

Female 188 4.18 0.953

Comes with giveaway Male 106 3.32 0.890 −0.090 0.929

Female 188 3.33 0.793

Professionalism of service personnel Male 106 3.66 0.791 −2.581 0.010**

Female 188 3.91 0.823

Recommended by advertising Male 106 3.42 1.068 −2.539 0.012*

Female 188 3.72 0.931

Recommended by expert Male 106 3.76 0.991 −0.251 0.802

Female 188 3.79 0.898

Product’s source country Male 106 3.94 0.815 −1.337 0.182

Female 188 4.09 0.903

Ease of use Male 106 3.75 0.964 −2.365 0.019**

Female 188 4.02 0.907

* _P_<₀_._05. **_P_<₀_._01. ***_P_<₀_._001.

respondents. The P value was 0.015 so the gender difference was statistically significant. The mean level for ‘‘ease of use’’ was 3.72 for male respondents and 3.92 for female respondents. The P value was 0.032, so the difference was statistically significant. As for level of satisfaction with ‘‘brand reputation’’, ‘‘obvious effect’’, ‘‘attractive packaging’’, ‘‘fresh scent’’, ‘‘natural ingredients’’, ‘‘spokesperson’’, ‘‘suitable skin type’’, ‘‘includes giveaway’’, ‘‘professionalism of service personnel’’, ‘‘recommended by advertising’’ and ‘‘recommended by expert’’, there were no statistically significant gender differences.

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Table 12

Gender differences in satisfaction with cosmetics purchased online.

Brand reputation Male 106 3.66 0.755 −0.051 0.959

Female 188 3.66 0.709

Obvious make-up effect Male 106 3.80 0.833 0.690 0.491

Female 188 3.73 0.797

Attractive packaging Male 106 3.59 0.826 1.471 0.142

Female 188 3.46 0.681

Fresh scent Male 106 3.70 0.679 0.016 0.988

Female 188 3.70 0.693

Natural ingredients Male 106 3.79 0.686 1.000 0.318

Female 188 3.70 0.839

Reasonable price Male 106 3.45 1.088 −2.457 0.015*

Female 188 3.75 0.940

Spokesperson Male 106 3.45 0.917 0.112 0.911

Female 188 3.44 0.789

Suitable skin type Male 106 3.76 0.698 −0.842 0.400

Female 188 3.84 0.771

Comes with giveaway Male 106 3.21 0.913 −1.736 0.084

Female 188 3.40 0.905

Professionalism of service personnel Male 106 3.58 0.660 −1.747 0.082

Female 188 3.74 0.800

Recommended by advertising Male 106 3.64 0.733 −0.023 0.981

Female 188 3.64 0.743

Recommended by expert Male 106 3.47 1.044 −1.132 0.259

Female 188 3.59 0.744

Product’s source country Male 106 3.60 0.764 −2.890 0.004**

Female 188 3.88 0.812

Ease of use Male 106 3.72 0.714 −2.159 0.032*

Female 188 3.92 0.807 ∗∗∗ P<0.001. **_P_<₀_._01. *_P_<₀_._05. 5. Conclusion

Due to increasing pricing levels and material costs over years, enterprises have intended to lower their financial costs by Internet marketing, by which renting cost, facility setup cost, and manpower cost can be saved, and advertising cost is lowered for increasing more potential customers. From the aspect of marketing, low advertising cost creates more potential customers. From the aspect of logistics, electronics commerce shortens the delivery, decreases the procurement cost, decreases unconfirmed orders, increases the control ability for the supply chain, electronizes the operations of transaction, transportation, storehouse, and payments to analyze customers’ procurement data with precise prediction on the supply to customers, etc. Hence, Internet marketing has become a market territory for which each enterprise competes. The results from this study show significant gender differences among consumers when purchasing cosmetics in terms of perception, importance and satisfaction. They also show that significant gender differences exist in ‘‘average amount of money spent on online shopping, ‘‘the most recent online purchase of cosmetics’’, ‘‘time spent on cosmetics’’, ‘‘amount of money spent each month on cosmetics’’, ‘‘amount of money spent per time on cosmetics’’, ‘‘the time spent buying cosmetics online’’, and ‘‘satisfaction with the most recent online purchase of cosmetics’’. There were also significant differences in the level of importance assigned to ‘‘brand reputation’’, ‘‘fresh scent’’, ‘‘natural ingredients’’, ‘‘reasonable price’’, ‘‘suitable skin type’’, ‘‘professionalism of service personnel’’, ‘‘recommended by advertising’’ and ‘‘ease of use’’. Marital status made a statistically significant difference to the level of satisfaction with online shopping characteristics such as ‘‘not limited by time’’, ‘‘reasonable delivery costs’’, ‘‘elegant website design’’, ‘‘easily attracted by webpage advertising’’, ‘‘easy to search for products’’, ‘‘diversification of products’’, ‘‘easy to buy’’ and ‘‘price cheaper than physical stores’’. As for the level of satisfaction with purchasing cosmetics online, the difference was statistically significant for ‘‘attractive packaging’’, ‘‘natural ingredients’’, ‘‘spokesperson’’ and suitable skin type’’.

Additionally, in comparison to male respondents, as female respondents attached a higher level of importance to ‘‘security of online transactions’’, online vendors should therefore offer more secure transaction methods for female consumers. Online payment validation should also be used to provide consumers with a more secure payment method. For the ‘‘Price’’ dimension, as compared to male respondents, female respondents exhibited a higher level of satisfaction, which implied relatively higher prices for male cosmetic products. This study, therefore, suggests that online vendors offer better prices on male cosmetic products or offer different discount methods to make male consumers more likely to shop online.

As for ‘‘the website content is provided for reference only’’, ‘‘product delivery speed’’, ‘‘worried about product guarantee’’ and ‘‘questions about the seller’s quality of service’’, male respondents scored higher than female respondents, so online vendors should consider providing more detailed explanations for female consumers and also providing faster and more convenient services for female products. Finally, more comprehensive after-sales support and quality guarantees should

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be offered to make female consumers more likely to shop online. As for perceived importance of ‘‘brand reputation’’, the score was higher among male consumers. This suggests that male consumers pay more attention to the brand reputation of cosmetics when shopping online. Online vendors should, therefore, seek to build a good product reputation for male consumers in order to increase their chances of buying cosmetics online. Here the product’s ‘‘fresh scent’’, ‘‘natural ingredients’’, ‘‘reasonable prices’’, ‘‘suitable skin type’’, ‘‘professionalism of service personnel’’, ‘‘recommended by advertising’’ and ‘‘ease of use’’ show a higher level of perceived importance among female consumers. Online vendors should, therefore, target female consumers by providing products that have a fresher scent, more natural ingredients, more reasonable pricing, and are more suited to female consumers’ skin types. Services, advertising and the method of use need to be better tailored to female consumers as well to increase their chances of purchasing cosmetics online.

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