Örebro University
Örebro University School of Business Informatics, Thesis, Second level Supervisor: Mathias Hatakka Examiner: Shang Gao
Spring semester / 2018.06.20
Comparing trust towards American and Chinese online
retail companies from students’ perspective in Sweden
Simeon Karašov Date of birth (77/09/01)
ABSTRACT ... 2
INTRODUCTION ... 2
THEORETICAL FRAMEWORK ... 5
TRUST ... 5
TRUST IN E-COMMERCE CONTEXT ... 6
CONCEPTUAL FRAMEWORK FOR MEASURING CONSUMER TRUST IN INTERNET VENDOR ... 7
Trust-related factors ... 8 METHODOLOGY ... 10 ONLINE SURVEY ... 11 SAMPLING ... 12 STATISTICAL ANALYSIS ... 12 RESULTS ... 12 DISCUSSION ... 15 CONCLUSION ... 17 REFERENCES ... 18 APPENDIX 1 ... 22
Abstract
The e-commerce market has been growing rapidly over the past years and there is a constant increase in the number of consumers favoring the online shopping. In the light of understanding the key issues in building relationships with the customers over the Internet, the concept of trust has been recognized as fundamentally important and is the most cited reason why consumers do not purchase from Internet stores. We have sought to investigate the level of trust students in Sweden exhibit towards the Chinese and the American online retail companies. An online survey was executed and 94 participants took part in the study. The questionnaire was structured in order to investigate the perceived level of trust by measuring six different antecedents of the trust construct. Data on demographics and modifying factors such as, trust propensity and trust in internet shopping was also collected. Mean scores of the measured constructs were calculated and non-parametric tests were employed for data analysis. No difference was measured between the trust level of the students towards the USA and Chinese online stores. The constructs integrity and security were significantly different between the two markets. There were gender and age differences between trust propensity and trust in internet shopping, which was also influenced by the education level as well. Further research is needed to explore the effect modifying factors have on the overall level of perceived trust and its constructs.
Keywords: E-commerce, internet shopping, customer trust, integrated model, empirical.
Introduction
In the recent years, the Internet has become one of the most important platforms for selling, trading and distributing products between organizations, consumers, or among organizations and consumers. This process of carrying our business transactions between enterprises and customers using an electronic medium is also known as electronic commerce (E-commerce) (Keeney, 1999). E-commerce has been recognized as the key to future economic growth on global level (Zhu and Yan, 2016), especially with the rapid growth of the Internet. It helps change trade forms, reduces the costs of production, improves market competitiveness, overcomes the space and time limitations and provides more choices to both the sellers and the customers (Zhu and Yan, 2016). The nature of the transactions in E-commerce depends on the
participants and it can be divided in different categories: Business-to-Customer (B2C), Business-to-Business (B2B), Peer-to-Peer (P2P), Customers-to-Customer (C2C) and Government-to-Customer (G2C) (Turban et al., 2009) The model of interest in this paper is B2C in which businesses sell their products or services directly to individual shoppers. E-commerce has become and important tool for small and large businesses all over the world, with not just providing an opportunity for doing business, but also building a platform to better engage both of the parties in the process of online transactions (Eisingerich, 2008).
The E-commerce market has been growing rapidly over the past years and there is constant increase in the number of consumers favoring the online shopping. The global trends, both in the developed and the emerging economies show continuous expanding of the online sales. Cumulative data from Statista (2018) anticipates the global retail E-commerce sales to reach
$4.5 trillion by 2021 which is an increase of 246.15% in worldwide sales from 2014. According to a survey done by Eurostat in 2016, the highest proportions of e-shoppers among internet users was found in the 16-24 (68%) and 25-54 (69%) age groups (Eurostat, 2016).
Sweden has a leading position as an E-commerce nation compared to the rest of the Nordic countries. It has the highest percentage of consumers who shop online in the whole Nordic region (Ecommerce in the Nordics, 2018). The online shopping in Sweden is widespread thanks to the mail order tradition and the strong retail brands in the country. According to a survey done in 2013, there are about 8.7 million internet users which is 94% of the total population of the country (Ecommerce News Europe, 2016). In their 2018 report for Ecommerce in the Nordics, Postnord inform that the percentage of internet users that shop online each month has increased from 30% in 2013 up to 66% for 2017. 31% of the Swedish internet users shop online from abroad each month and 16% of the sum is spent on online purchases abroad. Top 5 most popular countries to shop from in Sweden are: China (36%), UK (24%), Germany (21%), US (15%) and Denmark (7%). This increase in the online purchases among consumers in Sweden is in part because the advantages of the online shopping are perceived as greater that then advantages of the physical retail. The Swedish consumers appreciate the ability to shop at any time, something that E-commerce offers as a benefit compared to traditional shopping. Among the other advantages of shopping online is the larger offering and lower prices of goods as well as that E-commerce is perceived as more convenient and time-saving than shopping in regular stores (Ecommerce in the Nordics, 2018).
the Internet, the concept of trust has been recognized as fundamentally important as being the basic principal in every business transaction (Hart and Saunders, 1997). This is even more true in such a buyer-seller’s relationships as there are in the E-commerce market interactions, since the element of risk is perceived to be greater in the online transactions. When engaging in online shopping, the customers do not know in advance whether they will receive exactly what they have ordered, so they need to rely on the promises given by the retailer (Nitse et al., 2004). As the virtual, online environment features many possibilities for fraud, it takes time for the consumers to get to know the vendors and build certain level of trust towards them (Grazioli and Wang, 2001). The lack of trust is one of the most cited reasons why consumers do not purchase from Internet vendors (Lee and Rha, 2016).
Today, China is the most popular country for the Swedish customers as well as the worlds biggest E-commerce market with annual online sales of $672 billion mostly led by E-commerce subsidiaries of Alibaba group, such as: Taobao, Alibaba.com, Tmall and others. China is also the fastest growing E-commerce market with an annual growth of 35%. It took this place from the United State’s online market, which dropped on the second place in the world with $340 billion of annual online sales. The USA e-commerce market is led mostly by commercial giants, such as: Amazon and eBay (Business.com, 2017). According to eMarketer estimates, first in the US E-commerce market for the year 2017 was Amazon generating $197 billion with a market share of 43.5% in the US, while eBay was in second place with $ 31 billion generated and a market share of 6.8% (eMarketer Retail, 2018). Amazon currently dominates North America and Europe and is competing with Alibaba for shares in the Indian and Australian E-commerce markets (Cbinsights Research, 2018).
According to the CupoNation analysis from may 2017 of the most visited foreign e-commerce websites by Swedish customers, Aliexpress.com came on the second place with approximately 7 364 000 number of visits for the first quarter of the year, while Amazon.com hit double the number of visits (15 704 000) for the same period (CupoNation, 2017). Nonetheless, Aliexpress.com has jumped from the sixth to the second place in less than a year and represents a real threat to the traditional owner of the first place of preferable online vendors among the Swedish consumers.
Despite the huge amount of theoretical literature in the field of customers trust in online shopping, there is a lack of empirical research on the level of trust towards specific online retail companies. Thus, the purpose of this study is to measure and compare the perceived level of trust among the Swedish customers towards online merchants from the two leading
E-commerce markets in the World. This aim will be addressed by answering the following question: What is the perceived trust level towards the American and Chinese online retail companies among the students in Sweden?
Theoretical framework
Trust
The concept of trust has been studied in a number of different disciplines such as psychology, sociology and marketing, as well as under various contexts, organizations (Mayer et al., 1995), industrial buyer-seller relationships (Donney and Cannon, 1997), distribution channels (Dwyer et al., 1987), romantic relationships (Rempel et al., 1985) etc. Trust has been understood both as a state and as a trait. Interpersonal trust is an example of trust as a trait and it represents a generalized expectancy about the behavior of others (Rotter, 1967). Other authors have conceptualized trust as a state, thus defining it in different manners. For the purpose of this study Mayer et al.’s definition of trust will be used where the notion of trust is not only a willingness to take risks in a relationship, but also a ‘willingness to be vulnerable to the actions of another party based on the expectation that the other party will perform a particular action important to the trustor irrespective of the trustor’s ability to monitor or control their behavior (Mayer et al., 1995). Furthermore, trust has been viewed as a set of beliefs of the trustor about the possession or lack of certain qualities of the trustee that result from cognitive evaluations. (Mayer et al., 1995).
There are different theoretical perspectives employed by different disciplines and as such they project fundamentally different views of trust. These theoretical perspectives may be grouped in three categories:
a) Personality theorists conceptualize trust as a personal belief, expectancy or feeling deeply rooted in the personality and depending mostly on early developmental experiences, personality types, cultural backgrounds etc. They define trust as expectations, assumptions or beliefs about the likelihood that the other party’s future actions will be beneficial, favorable or at least not detrimental to one’s interests (Robinson, 1996). This personal trait is what ultimately defines the individual’s
b) Social psychologists study trust at the interpersonal and group levels, especially how the contextual factors enhance or inhibit the development of that trust (Lewicki et al., 1995). They define trust as an expectation about the behavior of the other party in the particular transaction, a level of trustworthiness and identify three most frequently used attributes of the trustworthiness in the trustee: ability, benevolence and integrity (Mayer et al., 1995).
c) Sociologists and economists scrutinize trust at the institutional level and study this concept in terms of trust within and between institutions as well as the individual’s trust towards those institutions (Lee and Turban, 2001).
All of these approaches in defining trust have been employed in the development of models of consumer trust in Internet shopping.
Trust in E-commerce context
The concept of trust is situational and context-specific and as Lewicki and Bunker (1995) have explained it has to be studied under the specific contextual factors. Thus, consumers’ trust in the context of Internet shopping will be influenced, determined and changed by the specific E-commerce parameters. The act of Internet shopping involves a higher degree of uncertainty and
risk when compared to the traditional shopping. Mayer at al. (1995) argue that risk taking is
inherent in most conceptualizations of trust, while Pires et al. (2004) report that risk is even higher in online transactions because of the lack of physical contact between the vendor and the customer. Consumer research demonstrates that it is not the objective risk, but the perceived
risk that matters (Garbarino and Strahilevitz, 2004). In his previous work Mitchell (1999)
reports that there is a strong relation between risk and trust and that the perceived risk is powerful at explaining consumer behavior. In order for a trust to arise there needs to exist a perception of risk from the trustor’s part. Thus, risk is related to trust and represents necessary antecedent for trust to be operative (Mitchell, 1999). Taking risk from consumers means that they are accepting the possibility of adverse consequences while doing the shopping (Mitchell, 1999). Consequently, in their Integrated model of consumer trust in Internet shopping Cheung and Lee (2003) define perceived risk as the perception of the consumer on the possibility of yielding unexpected outcomes or even negative consequences from the Online transaction. Maybe Internet shopping is not such a new form of commercial activity in broader sense, but
there is still a growing number of people that engage in this way of business transaction for the first time suggesting that an important contextual factor which may contribute to the level of trust towards the Internet vendors is the overall trust in the process of Online shopping. This factor is related to the general perceived risk which is associated with the type of the interaction disregarding the particular partner that the consumer engages with (Mayer et al., 1995). Kini and Choobineh (1998) discuss that trust in the Internet vendor is necessary but not sufficient for the online transaction to happen, suggesting that there are other factors that may have an impact on this behavior. Another relevant situational factor that influences consumer trust in Online shopping context is the existence and the effectiveness of third-party
trust-certification bodies (Lee and Turban, 2001). These parties play an important role in building a
positive perception of the consumers in regard to the trustworthiness of the Internet vendor. In the lack of physical contact and more direct interaction, an assurance from an independent reliable company about the intentions of the Internet merchant could strongly influence the development and maintenance of trust in the consumer.
In their model of consumers trust in Internet shopping Lee and Turban (2001) have modified the previous definition of trust proposed by Mayer et al. (1995) in order to fit the specific context of Internet shopping. Thus, consumer trust is defined as the willingness of a consumer to be vulnerable to the actions of the Internet vendor in an Internet transaction, based on the expectation that the Internet vendor will behave in certain agreeable way (Lee and Turban, 2001).
Conceptual framework for measuring consumer trust in Internet vendor
The conceptual model of this paper was built using Cheung and Lee’s Integrated Model of Consumer’s Trust in Internet Shopping (Cheung and Lee, 2003). The Cheung and Lee’s (2003) model was developed for measuring consumers’ trust in Internet shopping. It encompasses two main groups of factors, such as: perceived trustworthiness of the Internet vendor consisting of four antecedents measuring different aspects directly connected to the internet retailers’ abilities, and external environment consisting of constructs measuring the effectiveness of the third party recognition bodies and the effectiveness of the law and the codes established to protect the consumers. They propose a third main factor, perceived risk as necessary antecedent for trust to arise (Mitchell, 1999). In their model trust propensity, has been used as a factor that moderates the effect of the other factors on the overall level of trust. Using this model, we havedeveloped a conceptual framework for measuring the perceived trust towards a specific Internet retailer by measuring the following factors: a) trust-related factors consisting of two groups of constructs directly related to the perceived trust; and b) modifying factors, which have a known moderating effect on the development and maintenance of consumer trust toward specific Internet vendor. The trust-related factors, according to the previously mentioned model are divided in two groups: perceived trustworthiness comprised of: perceived integrity, perceived competence, perceived privacy control and perceived security control; and contextual factors, such as: third party recognition and perceived risk. Third party recognition is a relevant situational factor in e-commerce context that directly influences the consumers’ level of trust (Lee and Turban, 2001), while perceived risk is inherent to the specific context of online shopping. The modifying factors used in this model are: individual trust propensity as suggested by Cheung and Lee (2003) and trust in Internet shopping as having moderating effect to the level of perceived risk as explained by Mayer et al. (1995).
Trust-related factors Perceived trustworthiness
The perceived trustworthiness of the Internet vendor is thought to be an important antecedent of trust. As already defined by social psychologists it encompasses certain attributes and traits of the Internet vendor that are fundamental for the building of trust. There are four main elements of trustworthiness that are specific for the Internet vendor as identified by the conceptual framework.
a) Perceived integrity is the customer’s perception concerning the honesty of the Internet merchant. It proposes that the vendor will be honest and adhere to an acceptable set of principles and its actions towards the consumer will be fair (Lee and Turban, 2001). b) Perceived competence refers to the customer’s opinion on the skills and expertise of the
Internet merchant, whether it posses the necessary capabilities to complete the Internet transaction (Cheung and Lee, 2003).
These two concepts are elements of another very important factor for the development of consumers trust – reputation. Vendor’s reputation is found to be fundamental component of their image of trustworthiness and a driver of relationship building with the customers. Reputation is defined as the extent to which customers believe that the firm is honest and concerned about their needs (Doney and Cannon, 1997).
c) Perceived security control applies to the perception Internet consumers have on the Internet merchant’s abilities to protect them in the business transaction process. d) Perceived privacy control is connected to the customer’s perception to whether the
Internet vendor is concerned about their consumers’’ privacy and their capabilities to keep their personal data safe.
Contextual factors
Because of the lack of physical presence, the Internet environment is considered to be quite specific and context-oriented factors need to be taken in consideration when doing empirical studies. This model accounts for two context-specific factors:
a) Third party recognition from third party certification bodies, especially their reputation and adequacy in assuring the trustworthiness of the Internet vendor.
b) Perceived risk of shopping at that Internet vendor, as defined by Cheung and Lee (2003).
Modifying factors
The impact of the above mentioned antecedents of trust can be influenced by a number of modifying factors. These can moderate the level of perceived trust the customer has toward a particular Internet vendor. In the conceptual model of this paper, two moderating factors are measured:
a) Trust propensity as a personality trait that moderates the effect of trustworthiness attributes in the formation of trust (Mayer et al, 1995). This trait is dependent on cultural background, personality type, early psychological development experience etc. (Hofstede, 1980). Trust propensity moderates the trustworthiness attributes in a way of magnifying or reducing the cues that the consumer is looking for on whether and/or how much to trust the Internet vendor. The higher the level of trust propensity, the greater the impact of the trust attributes on the formation of trust (Lee and Turban, 2001). b) Trust in Internet shopping refers to the customers’ opinion on the overall process of
shopping on the Internet. Moreover, it applies to their perception on how reliable, secure and trustworthy shopping over Internet is.
Other factors
When executing empirical studies, other factors need to be considered as control variables. Such control variables are: sex, age, Internet usage experience, etc. (Lee and Turban, 2001).
Figure 1: Conceptual model for customer trust in Internet vendor (modified version of Cheung and Lee’s
Integrated Model of Consumer’s Trust in Internet Shopping (Cheung and Lee, 2003).
Methodology
For the purpose of addressing the research question quantitative methods were employed in this study. The data collection was executed using questionnaires which were distributed among the Swedish universities’ students. This part of the population was selected as belonging in the age groups that hold the highest percentage of internet users and online shoppers among different ages (Eurostat, 2017). Perceived integrity Perceived competence Perceived security control Perceived privacy control P er ce ive d trus tw or thi ne ss Trust propensity Trust in Internet shopping Perceived risk Third party recognition Customer trust in Internet vendor
Online survey
The data collection for this study was done using an online survey. This method was chosen as offering a number of advantages. By taking advantage of the Internet it provides access to specific groups and individuals that may be difficult to reach by more traditional methods of performing a survey (Garton et al., 1999). It may also save time for the researchers by allowing quick access to the target group that needs to be surveyed (Taylor, 2000). This method is also cost-effective and can help researchers save money (Llieva et al., 2002). The instrument was developed and distributed using SurveyMonkey.com which is an online survey development cloud-based software. The questionnaire was distributed by sharing the link to the survey on different students’ groups on Facebook as well as via personal contact on the premises of Örebro University using the QR code linked to the survey. The social media-based student groups were on country’s level having students from different Universities in Sweden as members, which has enabled for the survey to reach somewhat above 17.000 potential participants.
The questionnaire comprises of 47 items divided in four sections (Appendix 1). The first set of questions was used to collect demographic data on the participants, such as: age, gender and educational level. The second set of questions was used to investigate the modifying factors of perceived trust in the online vendors and perceived trust in the process of internet shopping, as presented in the conceptual framework. The third and the fourth sections of the questionnaire were built in order to collect data on the students’ trust towards the American and the Chinese online stores respectively. For assessment of the modifying and the trust-related factors, a measurement instrument consisting of a specific set of items proposed by Cheung and Lee’s (2001) was used. All of the trust related constraints described previously in the model were measured using multiple items, seven-point Likert scales ranging from Strongly disagree (1) to Strongly agree (7) with Neutral (4) as a mid-point. The Likert scale is the most popular tool for measuring attitude because it is easy for the researcher to prepare and simple for the respondent to answer. The Likert scale gives the researcher the option to consider the responses separately or the option to combine the responses to produce an overall score. The seven-point Likert scale is preferable to the five-point Likert scale due to the smaller standard deviation and the more accurate calibration, giving the respondents possibility to be more accurate in their answers (Kessler and Sheila, 1996).
Sampling
135 students took part in the survey, out of which 94 completed the whole questionnaire. For choosing the participants in the study, the convenience sampling method was used. This method is quite popular among researchers because it is easy, cheap, readily available and extremely cost-effective (Henry, 1990). It needs little preparation which makes it useful in time sensitive research as this study was. Convenience sampling also makes the data readily available for collection since most of it is collected from the populations that are on hand, close to the researcher (Christensen and Johnson, 2012).
Statistical analysis
Analysis of frequencies were used in order to describe the sample group across the age, gender and educational level categories. To be able to investigate the internal consistency of each construct used in the questionnaire, Cronbach’s alpha was calculated for each antecedent of the consumer’s trust. A Cronbach’s alpha ≥ 0.7 was considered to be high enough to ensure that the questions are reliable and helpful in measuring the proposed construct (DeVillis, 2003). Mean scores of all the measured constructs were calculated. The normal distribution of the variables was investigated using the Shapiro-Wilk test for normality. After confirming that the assumption for normal distribution was violated, non-parametric tests were used for analysis of the data. Related-Samples Wilcoxon Signed Rank Test was used for investigating the differences between the trust levels towards the American and the Chinese online stores as well as if there are any statistically significant differences between each of the constructs of trust. Kruskal-Wallis Test was employed for investigating the differences between the educational level groups as well as the age groups concerning the construct of trust propensity and the trust towards internet shopping. In order to examine whether there are any gender differences in the level of trust propensity and trust in Internet shopping, the Mann-Whithey U Test was employed. All statistical analysis was executed using the SPSS software version 23 (IBM Corp.) and the results were considered significant if P < 0.05.
Results
94 subjects participated in this study, with a quite equal distribution between genders. 45 or 47.9% of the participants were female, while 49 or 52.1% were men. The frequency distribution between age groups was as it follows: 18-24 years (18.1%); 25-34 years (38.3%); 35-44 years
(41.5%) and above 45 years of age (2.1%). 40 or 42.6% of the students reported high school degree as their highest educational achievement; 36 participants, or 38.3% have bachelor’s degree as their highest educational level and 18 or 19.1% of the sample group has master’s degree level.
Cronbach’s alpha for each construct from the questionnaire was calculated. All of the scales had a high level of internal consistency as determined by Cronbach’s alpha values higher than 0.7, which confirms that the questions used in this survey measured the constructs they were assigned to. Highest level of reliability 0.85 was estimated for the construct integrity.
No significant difference was measured between the trust levels toward the American and the Chinese online shops among the students in Sweden (Table 1). The mean scores of perceived level of trust for the American and the Chinese online merchants were 4.73 and 4.71 respectively. A statistically significant difference was measured in the construct Integrity of the online shops (p = 0.015) with the Chinese online stores having higher mean score compared to the American stores. The construct Security was also significantly different between the two E-commerce markets (p < 0.001) (Table 1).
Mean ± SD
Trust constructs
N USA shops China shops p value
Integrity 94 4.52 ± 0.92 4.83 ± 0.77 0.015 Competence 94 4.96 ± 0.74 4.96 ± 1.10 0.631 Privacy 94 4.40 ± 0.94 4.59 ± 0.85 0.178 Security 94 5.30 ± 0.95 4.64 ± 0.78 < 0.001 Third party recognition 94 4.53 ± 0.76 4.74 ± 0.80 0.099 Risk 94 4.64 ± 0.85 4.62 ± 0.83 0.993 Overall trust 94 4.73 ± 0.68 4.71 ± 0.68 0.751
The results from the Mann-Whitney U test yielded statistically significant differences between females and males on the Trust propensity construct (p = 0.004), with females having higher level of trust propensity compared to men. The men on the other hand reported significantly higher level of trust towards the process of Internet shopping compared to women (p = 0.001) (Table 2).
Mean ± SD
Trust Construct Female Male p value
Trust propensity 4.40 ± 0.17 3.71 ± 0.18 0.004
Trust in Internet
shopping 4.11 ± 0.17 4.80 ± 0.16 0.001
Table 2. Gender differences in the constructs Trust Propensity and Trust in Internet Shopping. Data
presented as Mean ± SD of the mean score for each construct. Statistical significance at p < 0.05
No significant differences were measured on the Trust propensity construct between the different educational level’s groups, still there was significant difference on the level of trust in Internet shopping depending on the level of education of the participants (p = 0.001) (Table 3).
Mean ± SD Trust construct High school
degree Bachelor’s degree Master’s degree p value Trust propensity 4.39 ± 1.23 3.26 ± 1.14 4.83 ± 0.54 0.137 Trust in Internet shopping 4.18 ± 1.28 4.68 ± 1.00 4.70 ± 1.12 < 0.001 N 40 36 18
Table 3. Differences between levels of education in the constructs Trust Propensity and Trust in Internet
Shopping. Data presented as Mean ± SD of the mean score for each construct. Statistical significance at p < 0.05
When these two constructs were investigated across the age groups, the Kruskal-Wallis Test’s results showed significant difference in Trust propensity (p = 0.033) and trust in Internet shopping (p < 0.001) between the different age groups.
Discussion
The main findings in this research show that among the students at Swedish universities, the perceived level of trust towards the USA online shops is not different than the level of trust towards the Chinese online merchants. We have measured six antecedents of the construct of trust: integrity, competence, privacy, security, third party recognition and risk in order to be able to establish the overall trust for the shops from these two different E-commerce markets. The Swedish students perceive that the competence of the US and Chinese internet merchants is on similar level, thus the capabilities as well as the skills and expertise of the shops are similar according to the students’ opinion. The mechanisms for tackling privacy issues between these two different markets is perceived as not having differences. The students stated that both the US and the Chinese online merchants have similar level in their concern about consumers’ privacy issues and abilities for keeping the personal data safe. The reputation and adequacy of the third party recognition as well as the level of risk that shopping at the different shops brings are also not different for our sample group. They have stated that shopping at the US online stores bears the same level of risk as shopping at the Chinese online stores.
Statistical difference was measured between the two E-commerce markets in the level of perceived integrity of the merchant and the level of perceived security. Students at Swedish universities think that the Chinese online stores are more honest and their actions towards them will be more fair than the honesty and fairness of the US merchants. The integrity antecedent is part of the concept of reputation together with the merchant’s competence. This difference in perceived integrity level may be as a result of the differences in reputations among the online stores the students have taken as examples of the E-commerce markets when answering the survey. This may also be the reason for Alibaba.com rising from the sixth to the second place of most preferred online stores from abroad in Sweden. The Chinese E-commerce giants have been introduced in the Swedish online market more recently than the US merchants and are still in the process of building their reputation, as well as trust among the consumers. The rising reputation of these stores may be the reason of the differences measured in the integrity construct in this survey.
Another difference between the two markets was measured in the perceived level of security control. The students perceive the US online stores as having better security control and being able to process security issues better than the Chinese merchants. This may be due to the longer experience the Swedish consumers have with the US stores in general, as well as the tighter cultural gap that exists between Sweden and USA. They might be more familiar with the
payment system used by the American stores, as a result of this longer relationship. The Swedish consumers in general are more familiar with the American market, not just the online, but the traditional in stores shopping as well. This experience might be transferred in the perceived level of security control and that is why they feel more secure when shopping at the US online retailer than the Chinese store. It will be interesting to see whether this difference will persist after certain time, when the Swedish customers get more familiar with the security measures of the Chinese merchants. For the online retailers, the customers’ level of trust and their online behavior is of great interest (Chiu et al., 2009). In order to be able to effectively compete in today’s dynamic environment, they need to focus on the customers’ experiences and their perception of the internet vendor’s trustworthiness (Grewal et al., 2009). In context of understanding the different experiences the students in Sweden have while shopping at the online vendors from these two different E-commerce markets, the results from this study may assist managers in developing and evaluation online shopping strategies.
Our results showed differences in the level of trust propensity between the female and male participants in the study, with the women having higher level of trust propensity than men. This finding is in line with previous research about trust in the consumers’ context. Rempel et al. (1985) have reported that while women tend to be more trusting across a number of trust components, men usually are better at discriminating these elements. Shresta et al. (2013) have also reported that women are more trusty than men in their sample while investigating for gender and country differences in the propensity to trust others. Women are more sensitive to the ethical cues that exist in an environment (Bernardi & Arnold, 1994), which has an effect of trust propensity in the way that it magnifies the cues that women as consumers are looking for on whether or how much to trust the Internet vendor. This may be the reason for the differences measured among female and male of the level of perceived trust in Internet shopping as a whole. The Online shopping environment has an inherent higher level of risk compared to the traditional in stores shopping. This greater number of uncertainties may be perceived by the women to greater extent as a result of their sensitivity to cues in the environment and may lead to a lower level of trust in the whole process through enhancement of those cues. Other studies have also shown that men have a higher level of trust in Online shopping than women (Cho &
Jialin, 2008, Riquelme & Román, 2014). Gender is considered an important variable for market
segmentation (Samuel et al., 2015). The investigation of these differences in E-commerce context enables the development of more effective strategies specifically tailored for the needs of different target groups. The lack of research that will further elucidate the impact gender has on the use of E-commerce and how it affects the factors of trust has been already noted (Richard
et al., 2010; Hernandez et al., 2011). The findings in this paper provide better understanding to how gender can moderate the level of trust towards an Internet vendor.
Further analysis of the sample showed that there is difference in the level of trust in Internet shopping depending on the educational level of the participants. The higher the level of education, the higher the level of trust in this process. There are number of studies exploring the online shopping attitudes and behavior in context of factors which influence the former. Case et al. (2001) have reported that educational level, the internet knowledge and income are especially powerful predictors of internet purchases among university students. This may be the reason for the difference measured between different educational levels and trust in Internet shopping. The extent to which a consumer engages in Internet shopping may be a certain marker of the trust level that consumer possesses toward that process. In that line of thinking, the educational level may be also predictive factor for the level of trust in Internet shopping. Statistical differences were found between trust propensity and the trust in internet shopping between the different age groups among the students. This finding is in line with a number of research done on the impact age has on consumer and internet shopping behaviors. Our sample comprises of different age categories and generations. As Howe and Strauss (1991) have noticed, generations are shaped by a particular span of time and tend to share a collective persona as a group. In that sense, they share similar values, and tend to perceive the world in specific manner. In context of Internet shopping and trust, different generations might exert different behavior, which may be the reason why age was an important factor in the level of trust propensity and trust in Internet shopping in our sample group.
Conclusion
In conclusion, there was no difference between the perceived level of overall trust towards the US and the Chinese online stores among the Swedish students. The perceived integrity level of the Chinese stores among the students was significantly higher compared to the US online merchants. Nonetheless, the students thought that the American online retailers have greater security control over their information and personal data than the Chinese companies. Females were more prone to be trusty in general sense, while the males were more trusty in Internet shopping as a whole. The trust propensity and the trust in Internet shopping were different between the age groups, while trust in Internet shopping seems to depended also on the
educational level of the participants as well. Further research may be directed in better exploring the effect these modifying factors have on the overall level of perceived trust.
Our results provide better insights in the level of trust in shopping in online stores at the biggest E-commerce market in the world among the students in Sweden. We have examined the impact certain demographic factors have on the components that comprise the trust construct or modify the perceived level of trust and by that further contribute to the debate in the field. The results from the present study may help managers to evaluate the present and develop more effective strategies for increasing the customers’ trust towards the Internet retail companies.
There are also certain limitations that need to be considered about this research. One of it is within the sample group, the method used for sampling as well as the number of subjects. A greater number of subjects would have enabled us to investigated the differences with greater sensibility. The second limitation is that the results obtained with this study are only applicable to the age groups that were evaluated and can not be generalized to the whole Swedish population. The use of self-reported scales may also be seen as a limitation of the study, even though the method serves the purpose of the research.
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Appendix 1
Survey Questionnaire Dear participant,
The following survey is intended to help us collect data for a Master thesis research. The aim is to gain better understanding of how You feel about Your experiences while shopping in different online stores, in this case specifically the American (USA) and Chinese e-shops. The collected data will be anonymous. It will take maximum 10 minutes to complete this survey. Thank You for Your time.
To help You with answering the survey, some examples of the different online stores are provided.
American online stores: eBay.com, Amazon.com, Etsy.com, Walmart.com, Staples.com,
Target.com, Toysrus.com, etc.
Chinese online stores: Aliexpress.com, Lightinthebox.com, Miniinthebox.com,
Dealextreme.com, Tmart.com, Newfrog.com, etc.
The following questions will help us collect some information about You. Please do try to answer them as accurately as possible by choosing one of the options provided.
1. Have You ever done any online shopping at American and Chinese online stores? If Your answer to this question is Yes, please do proceed with the survey, if not, thank You for Your time.
o No
2. What is Your age? o 18-24 o 25-34 o 35-44 o Above 45
3. What is the highest degree or level of school you have received? o High school degree
o Bachelor’s degree o Master’s degree 4. Gender?
o Female o Male
The following answer option were offered for the next three parts of the survey o Strongly disagree
o Disagree o Mildly disagree
o Neither disagree nor agree o Mildly agree
o Agree
o Strongly agree
I. Internet shopping and trust
Please do try to answer the following questions as accurately as possible by choosing one of the options provided.
1. It is easy for me to trust a person/thing. 2. My tendency to trust a person/thing is high.
3. I tend to trust a person/thing, even though I have little knowledge of it. 4. Trusting someone or something is not difficult.
5. Internet shopping is reliable. 6. Internet shopping can be trusted.
7. In general, I can rely on Internet sellers to keep the promises that they make.
II. Shopping at the American online stores
Keeping in mind the experience You've had shopping at the American online stores, please do try to answer the following questions as accurately as possible by choosing one of the options provided.
To help You with answering these questions, some examples of American online stores are provided, such as: eBay.com, Amazon.com, Etsy.com, Walmart.com, Staples.com, Target.com, Toysrus.com, etc.
1. Have you ever shopped at an American online shop (if you answer no please click next at the bottom of the page)?
2. The (American) internet merchant is honest with their consumers.
3. The (American) internet merchant acts sincerely in dealing with customers. 4. The (American) internet merchant will not charge me more for Internet shopping. 5. The (American) internet merchant has the ability to handle sales transactions on the
Internet.
6. The (American) internet merchant has sufficient expertise and resources to do business on the Internet.
7. The (American) internet merchant has adequate knowledge to manage their business on the Internet.
8. The (American) internet merchant seems concerned about consumers’ privacy.
9. The (American) internet merchant will not divulge consumers’ personal data to other parties.
10. I feel safe about the privacy control of the (American) internet merchant.
11. The (American) internet merchant implements security measures to protect Internet shoppers.
12. I feel secure about the electronic payment system of the (American) internet merchant. 13. The (American) internet merchant usually ensures that transactional information is
protected.
14. There are many reputable third party certification bodies (external security approval) available for assuring the trustworthiness of the (American) internet merchant.
15. Existing third party certification bodies are adequate for the protection of the (American) internet shoppers’ interest.
16. I feel that shopping at the (American) internet merchant is risky.
17. There are negative outcomes on shopping from the (American) internet merchant. 18. I find it is dangerous to shop from the (American) internet merchant.
III. Shopping at the Chinese online stores
Keeping in mind the experience You've had shopping at the Chinese online stores, please do try to answer the following questions as accurately as possible by choosing one of the options provided. The same questions from the block before will be provided.
To help You with answering these questions, some examples of Chinese online stores are provided, such as: Aliexpress.com, Lightinthebox.com, Miniinthebox.com, Dealextreme.com, Tmart.com, Newfrog.com, etc.
1. Have you ever shopped at an Chinese online shop (if you answer no please click finish at the bottom of the page)?
2. The (Chinese) internet merchant is honest with their consumers.
4. The (Chinese) internet merchant will not charge me more for Internet shopping.
5. The (Chinese) internet merchant has the ability to handle sales transactions on the Internet.
6. The (Chinese) internet merchant has sufficient expertise and resources to do business on the Internet.
7. The (Chinese) internet merchant has adequate knowledge to manage their business on the Internet.
8. The (Chinese) internet merchant seems concerned about consumers’ privacy.
9. The (Chinese) internet merchant will not divulge consumers’ personal data to other parties.
10. I feel safe about the privacy control of the (Chinese) internet merchant.
11. The (Chinese) internet merchant implements security measures to protect Internet shoppers.
12. I feel secure about the electronic payment system of the (Chinese) internet merchant. 13. The (Chinese) internet merchant usually ensures that transactional information is
protected.
14. There are many reputable third party certification bodies (external security approval) available for assuring the trustworthiness of the (Chinese) internet merchant.
15. Existing third party certification bodies are adequate for the protection of the (Chinese) internet shoppers’ interest.
16. I feel that shopping at the (Chinese) internet merchant is risky.
17. There are negative outcomes on shopping from the (Chinese) internet merchant. 18. I find it is dangerous to shop from the (Chinese) internet merchant.
