3.0 Research Methodology

3.0 Research Methodology

The online sourcing individuals on learning language in China find it interesting shopping online, exploring new things while looking for merchandise with quality and affordable goods and services, which are the base of their satisfactory level. Initially, in the literature review, we tried to look into factors that influence online buyers’ intentions, especially when sourcing online language learning in China. Different theories and models were engaged in providing evidence of the matter and suggesting ways in which individual aspects may be improved. Our key aim will be arrived at by pursuing the effects of Technology oriented factors which deeply was concerned about the critical model (Technology Acceptance Model), Online purchasing intention, perceived usefulness which centered the relationship between PU and PI, perceived ease of use which centered the relationship between PEUO and PI it also pointed out the relationship between PEUO and PU. The study went further and explored the subjective norm of online language buyers. This outlined the relationship between SN and PU, the relationship between SN and PI.

Consequently, the research checked trust-oriented factors as the perceived trust for online language learner consumers; its antecedents and theories. Conclusively, the study researched extensively on perceived risk, which we found to be a determining factor of online language learning buyers in China, which directed us to explore the relationship between PR and trust and the relationship between PR and PI. All these being variables to online purchasing intentions determinants and so they are the hypotheses of the research. All the factors mentioned above were valued at a 5-rate of Likert scale, which articulates that ‘5’ represents strongly agree, and ‘1’ as strongly disagree. Additionally, we applied Anderson and Srinivasan to measure the buyers’ intention and satisfaction regarding online language learning. Consecutively, we noted down the demographic biodata of people interviewed. About 26 questions were structured for respondents to provide their feedback on factors influencing the intention of the purchase of internet language learning in China.

Fifty articles were identified using various academic sources from the internet, including IEE Explore, Springer, Elsevier, EBSCO, and Blackwell, by applying specific primary terms TAM and technology acceptance through its model for period between1979 to 2006.

These 50 articles were thoroughly published in the journals highlighted below in Table 1.

The majority of the above articles were about different models identified in our literature review, for instance; Subjective norm, Purchase intention, Technology oriented factors, TAM, Perceived usefulness, and PEUO.

This part will strictly elaborate on the methods for conducting the research. We will identify the research design for our study, target sample, and data collection techniques; the section will focus on the methods we are going to use for data analysis.

3.1. Sampling

The majority of our study consumers are scholars, and a few office staff who range between 18-46 years old. The students were much of a target for the study since they are eager to try new things such as buying online language learning at a low price. Consecutively, office employees are sourced online for perceived quality goods along with comparative prices. Almost more than half of internet consumers in China are between the age of 21 and 42 (77). Therefore, for these cases, our target population for the research included Chinese between18 to 31 and above years and as indicated in the questionnaire. The sample population targeted the incredible cities in China, such as Shanghai, Beijing, Guangzhou, and Wuhan). The internet users who were in the system of online purchase of language learning and equipped with the experience of perception were selected to complete our questionnaire dully. The approach was considered appropriate since several researchers have in mind that consumer satisfaction is based on personnel transactions.

3.2 Research design

De (2005) defined research design as a method of attaching the research hypotheses in research. Kazdin (2017) clarifies that research design compliments a guide to the study for data collection and interpretation of the data outcomes. Significant factors in this section are descriptive, exploratory, and interpretive Kazdin (2017). For our part, the focus will be on a descriptive survey as a method to analyze data. The technique was found suitable because its complex with exploratory and preliminary research in inclusive, which made more detailed collecting data in the field, facilitated arrangement of tables, presentation, and interpretation of various data from the analysis.

We concentrated on the primary data source for our dissertation. The data was collected from students in various learning institutions and civil servants in town, those with interest and perception experience in online shopping of language learning in China. Concerning the topic of our study, the study design facilitated us with quick knowledge of the determinants of online consumer’s intentions when going for language learning in China. Furthermore, the dissertation will engage descriptive procedural techniques for tabling out the processed data by the use charts and graphs for the presentation of subsequently generated data.

3.3. Data Collection

Concerning the model structure, a symbolic questionnaire with detailed 26 questions was used. This was attached at the end of the paper in appendix 1. This was structured to collect data for determining the nature of individual models. Our study’s data were collected through physical approach, mail dispatch in various Institutions for students, and working civil servants in the offices among the identified cities in China (Beijing, Shanghai, Guangzhou, and Wuhan). One hundred twenty questionnaires were allocated for contact interviews. We conducted a physical interview with respondents on a face-to-face basis where we visited offices, learning institutions, and people in public places. Another 80 questionnaires were sent via the emails to relevant respondents in the cities, collected back through the town’s parcel offices. This exercise was done from early 20^th August 2020 to 25^th August 2020

5. Data Analysis and Results

The latter section explained the data analysis; this enabled us to reach our target of research. A descriptive research technique serves a fundamental purpose of integrating both the primary and secondary sources of data. The secondary information in our study was generated from the internet database of Chinese Communication technology.

5.1. Demographic Characteristics

The field research shows that female gender is the majority among the entire group, this was represented by ( 63.5%) . while the male was identified as a minority in the category where only (36.5%) this were accompanied by the respondents level of education were; the diploma holders  ( 13.3%), 23% respondents were high school and below, Bachelor holders ( 56.28%), master holders (36.7%) and lastly the Ph.D. holders were ( 27.2%).

Who were of age bracket 18 to 31 and above years old. The research shows that most respondents were educated up to a bachelor’s level with a representation of 56.28%. Among the respondents, about 30.3% had a household income of 50,000 and below, 23.1% had 50,000-100,000, 32.2% of respondents had an income of between 100,000 to 150,000, 21.1% had a household income of between 150,000 to 200,000, lastly; 65.5% respondents had a household income of more than 200, 000. Consequently, respondents were asked to identify if they had used the online language learning before, about 78% of the respondents said yes, while only 22% of respondents said no. Furthermore, the researcher sought to know if the respondent had ever paid for online language learning before. From these perspectives, 86% of respondents said yes, while only 23% said no to the concern. At the same time, we intended to seek the purpose at which respondents purchase online language learning. From the data collected, 56.7% of the respondents suggested that they access online shopping to pass the language exam for studying abroad, 23.5% of respondents said they purchase online language learning for passing the English entrance examination for graduate students in Chinese universities. 25.2% of respondents detailed they are buying online language learning to improve the English business skills; conclusively, 53.8% of respondents said they are buying online language learning to get a language certificate. The research had in mind the types of language respondents could be going for in the internet shopping. The questionnaire had to focus on online language courses that respondents usually purchase. In this context, we found out that 77.6% respondents shop online for the English language, 32.3% go for French, and 33.1% go for Korean, 22% respondents shop for the Japanese language, 66% shop online for the German language while only a few 2% shop online for other languages.

Moreover, we needed to check on the significance of the variables in our study. We could not find any significant differences in a demographic section of our research ( for example, gender, age, level, course, types of language on the purchase, the usability of online purchase, level of household income, and online transactions). These non- differences insignificant points of view show that the data collected was likely to be sufficient and fair to represent our study’s target population.

. 5.2. Validity and Reliability

We exhausted the functionality of SPSS 20.0 and confirmatory functions with the use of LISREL 9.2. Analysis of the confirmatory section recorded a significant foundation for the six models, as shown in Table 2 below.

Table 1. Demographic Factors sample (n = 200).

To check the variables’ reliability and Consistency, we included Cronbach’s coefficient alpha, where the standardized items were evaluated for every model, ranging from 0.72 – 0.87. After reviewing the average model significance, the next step was to estimate the composite structure to check the reliability of models. Every structure reliability test was assembled at 0.72 – 0.87. As seen in Table 2 below. This was beyond the actual predictable level of 0.700. Hence, the composite reliability of the valuation theories was perfect. Additionally, we analyzed the average variance extracted (AVE) and later related to the squared coefficient correlation data among the construed facilities in measuring the discriminants strength among structures. As recorded in Table 2 below, the collection of average variance extracted data was beyond 0.50 standards as profound by Fornell and Larcker [78] as paramount to be referred to internal convergent strength.

The data analyzed under confirmatory perspectives in this research demonstrates that the Goodness-of-fit-index of the theoretical fit range is 0.96, NFI is 0.93, and CFI is 0.92. CFA in the process was used to furnish the field to develop the scale’s congeneric dimensions features (9). Research by Bagozzi and Yi (2001) shows that if the representation –fair value is near or beyond 0.9 in the average limit, the exact quantities’ CV conforms with the given range.

Table 2. Means, standard deviations, composite reliabilities, and correlations.

N/B: CR = Composite Reliabilities; Ave = Average Variances Extracted; STD = Standard Deviations. Correlations are below the diagonal, and all values are significant at p.

4.3 Industry Specific Factors That Influence the Consumers Intentions to Purchase online language learning in China

 4.3.1 Analysis of the Findings

This section sought to know from the respondents if various specific factors affect the consumer’s intentions to purchase online language learning and to what degree. The 18 industry-specific factors highlighted were within; perceived use, purchase Intention, Trust, perceived risk, Subjective norm, and perceived ease of use. Below are the result

Table 4.4: Industry-Specific Factors.

Table 4.4 above summarizes the respondent’s views on industry-specific determinants of online language learning intentions.

The critical variable is affecting consumers’ purchase intention of online language learning in China.  Most interviewees agreed that purchasing online foreign language learning courses helps them achieve their learning goals faster; the responses were; 58% strongly agreed, and 34% agreed. This is a compliment of the literature of our research on perceived ease of use, which shows that purchasing online foreign language increases the speed and ease of learning, hence reaching your goals faster. The research also sought to know if purchasing online language learning courses improves consumer’s performance in language study. The responses were 30% strongly agreed to this point, while 20 % agreed and only 10% Disagreed.

Consequently, the study sought to know if respondents would intend to purchase online language learning services. Out of these, 63% of respondents agreed, 22% strongly agreed, while only 15% disagreed. The research also found the following while analyzing if it’s likely for consumers to purchase online language learning courses, strongly agree 38%, agreed 12%, and 10% disagreed. The study published that respondents were comfortable with the online company; this was evident by 62% of respondents strongly agree, 30% agreed, and only a few respondents disagreed with this statement by 8%.  Consecutively, the research sought to know if online shopping secures the personal privacy of the consumers. From these, 48% strongly agreed, 50% agreed, and 2% strongly disagreed. Hence, we can conclude from this aspect that online firms ensure the privacy of users’ data.

The context behind not achieving the expectant purpose when shopping online seemed to have little impact on consumers. So do the worthiness of paying for online services when shopping for foreign language courses. There was also a positive impact behind the behavior influencers encouraging on purchasing online language learning. The majority of respondents think it is more comfortable using the online system when purchasing a foreign language were; 40% strongly agreed, and 30% agreed. And conclusively, there was a positive impact on the clarity of interaction with online shopping when going for foreign language services.

One of the key strands of literature on the factors affecting consumers’ purchase intention of online language learning in China has looked into the determinants of consumer’s specific factors such as the perceived usefulness and perceived ease of use to define the differences in the consumer’s intentions on online purchasing in China.

This dissertation is subjected to the latter research, which pointed out that consumers’ specific factors tend to impact the consumer’s intentions related to the companies and other external variables. However, there are some alternative online company’s factors which the interviewee felt they possess some influence on the consumer’s intentions to shop online. Furthermore, the increasing competitiveness in the online companies industry results in certainties where these companies are needed to improve on their strategies to sustain their online customers. The latter specifically purchase their products for self-improvement or instead benefit (Karasulu, 2001).

5.3. Multivariate Regression Analysis

We conducted this regression analysis to evaluate the hypotheses H1, H2, H3, H4, H5, H6, H7, and H8. The objective of fulfilling multivariate regression analysis is to determine the linear inclusivity of the alternative variables that are significant overly and the dependent variable.

By determining the dependent variables’ prediction by the independent variable, we took a step to conduct a stepwise regression analysis. The results are first shortlisted by picking the one (Independent variable) with a more significant correlation to the dependent variable, which shall also be included in the arithmetical functionality for valuation. The remaining variable shall be entered, which is the independent variable that contains a significant partial relationship with the dependent variable, manipulating the initial separate, etc.

The process is carried on once more time at every stage, partial determinants for the past recorded independents until the top-up of the following independent variables never add up on R2 by a significant value (80).

For us to internalize on the determining factors of consumers intention in online buying, we constructed the following arithmetical structure of standard regression which is;

Y =D0+D1X1+D2X2+D3X3+D4X4+D5X5+D6X6+e

Where Y=Consumer intention. D0=Constant, D1= The coefficient of the first; X1=Perceived usefulness,  X2= Perceived ease of use,  X3=Subjective norm,  X4= Trust, X5= Perceived Risk, X6= Purchase Intention. And e=error term.

Table 3 below displays the regression analysis, the concrete hypothesis, theories, and six independent factors were 0.325, 0.322, 0.187, 0.319, 0.219, and 0.752. The data of theses coefficients

Table 3 shows the regression analysis, the theoretical hypothesis, model, and seven independent variable regression coefficients were 0.555, 0544, 0.512, 0.406, 0.326, 0.301,264. The value of this regression coefficient

Table 3. Regression coefficients.

Shows the determinants of factors of general consumers’ intention degree, the more the fixed data is, the much the impact is. By studying the transition directives of standard elements, an absolute value reflects on clarifying factors manipulated by alternative variables testing records as indicated in table 5:  analysis of F-values are more than the recorded value of 32.183 and p-value is 0.000, the identified model is a significant level. The analyzed data reflects complete appropriate degree is greater.

Results drawn from the analyzed data: the first is Perceived usefulness (beta= 0.325, p<0.01), the Perceived ease of use (beta=0.322, p<0.01), the Subjective norm (beta=0.187, p<0.01), the Perceived Risk (beta=0.319, p<0.01), and Trust (beta=0.219, p<0.01), are positively coefficient correlated with customers intention. The record shows that the results support the theoretical perspectives of H1, H2, H3, H4, H5, H6, and H7.

The tabulated data analysis of the customer’s intention is reflected in Table 7 below. The F-data study was more than 7.751, while p-type data is 0.000, identifiably, the model is a significant range. And the complete appropriate degree is greater. Consumer’s intention of the regression correlation is 2.878, showing that consumers’ purchase intention has a significant positive impact, which is in line with the research main content frame; customer’s choice has a direct positive impact on purchasing online language learning in China.

6. Discussion and Conclusions

This research has enlightened the hypotheses to bring its objective to the point of view regarding the structural conceptual review.  There is a massive development in China’s e-commerce, thence, consumers are rapidly going for affordable and quality goods and services, such as the online purchase of language learning in China, which is the subject of discussion. For this to be efficient to customers, the company needs to install better customer service to win the positive impact of consumers’ intention when purchasing online. From the reported tabled by CNNIC, we can provide that majority of the group rating to 80.14 %, which ranges between 20-40 years old, were purchasing through online websites.

The data reflected by the samples in the study reinforce the aim behind the consumer’s intention to purchase online through e-commerce websites. Reference to these can be depicted from the analysis conducted on areas such as discriminant strength, reliability, and the Confirmatory factor analysis, which inclusively were significant on the construct of 5-measures alleged benefits, and 1-measure apparent risk. Potential benefits were presumed as a significant indicator of consumers’ intention, while likely risk was assumed insignificant to consumers’ choice. Conclusively, a construed benchmark of these measurements reported that online user’s purpose might be achieved by measuring high the benefits and lower the risk for consumers’ online purchase intention. The report of our hypotheses Table, nine via the regression examination, alleged benefits H1, H2, H3, H4, H5, and H6 were positively recommended. It depicts that  Trust, Subjective norm, perceived usefulness, ease of use, and purchase intention are paramount for online users’ intent to purchase language learning (Table 10).

This finding on consumers’ purchase intention is of interest by the research of Thomas and Harry [81], showing that individuals on interview and with extreme experience in internet shopping are much likely to be in persuade of usefulness for intention to purchase in online platforms. Equally, the data of measurement in the hypotheses Table3 by regression assessment alleged risk H7 and H8 are significantly in the recommendation and signify that perceived risk about PR, Trust and PI are negatively impacted to consumers intention ( Table 7) and e-shopping websites administrators need to cut down these risks to construct online users purchase intent.

Table 4.6: ANOVA Model

The representation detailed above (ANOVA) is usually in place to detect on point variation and variables through the reflection of coefficients but not the null hypothesis. This is a not significant coefficient (Ayres and Thomas, 1990).  The displayed Table shows the meaningful relationship among variability upon research. The model necessitates us to point out the considerable correlation in various variables. After we shall object any related hypotheses with null characteristics, such assumption displays zero value or insignificant term of regression.

We can mold our measurement pointing the hypotheses on record, by agreeing with the variables carrying positive results in correlation (Post and Bondell, 2013). Reflecting on our research, the perceived usefulness, subjective norm, trust, perceived ease of use and purchase intention were theoretically reported displaying positive correlation, which confirms the aim of our research that the perceived usefulness, subjective norm, trust, perceived ease of use and purchase intention have some impacts on consumers intention to purchase online language learning in China. Referring to the hypotheses detailed above, we can relate that increase in perceived usefulness, subjective norm, trust, perceived ease of use, and purchase intention will increase the positive intent of consumers when sourcing for online language learning and vice versa by  Mori (2009) and Al-Kunari (2010). Who researched and discussed that more of the above hypotheses with a significant positive effect would accelerate the consumer intention to purchase online goods and services because the online user will be motivated by the qualitative features identified in our theoretical framework instead of looking at their perception and make a judgment. (Maxwell, Delaney and Manheimer, 1985)

Graham et al. (2005)discovered from the conceptual view that there was an insignificant relationship between perceived risk and online consumers’ purchase intention. This is a critical point as a determinant of consumers’ preference, primarily to company owners. They need to take it as a challenge to do away with these drawbacks or instead try and reduce them to win the trust of its customer’s time.

Drawing from the research, we can relate that online websites with improved perceived ease of use tend to have more capabilities of accommodating more online customers sourcing for their products and services. On the contrary, firms not displaying these characteristics are at a high level of losing clients to the ones with compelling standards and efficiency of systems.

The research conducted in China from about 200 respondents in online consumers’ intention to purchase has proven that trust is determinant of online users’ intent to buy in any e-commerce platform in China. No one would wish to spend his/her money in an online store with the tarnished name; therefore, the company has a role to play in keeping their trust at maximum level; this will ease online users’ intention to transact with the company. Consequently, the subjective norm has recorded a positive correlation with the purpose of online consumers on the purchase of goods and services, these social factors are consistent with John ( 2013),

Purchase intention is confirmed as positively correlated to online consumers’ choice when sourcing for e-commerce services, especially foreign language courses.  Therefore this is construed as an accurate determinant of online user’s perception. Nevertheless, perceived risk as insignificant to online users’ intention remains a determining factor to enable any consumer to assess the e-commerce company’s susceptibility before committing his/her money for services and goods purchase purposes.

The evaluated results in the model (ANOVA) Table 5 depicts hypothesis H1 perceived usefulness directly influences the consumer’s purchase intention in the e-commerce platforms. Many researchers have provided the same on the perceived usefulness of online sourcing; this has been pointed out as the primary predictor of user’s intention to purchase online for language courses. This is the dominant motivation that drives individuals to adopt e-commerce and purchase services and various products. According to Roger’s Innovation Diffusion, Rogers detailed that profound advantage as among the determinants which manipulate users’ choice and contentment desire. Ancient theories of consumer’s intentions, Oliver [7] suggested the Expectancy-Disconfirmation Paradigm (EDP) being more theoretical review in consideration when assessing for consumers’ preference. Conclusively satisfied consumer consumers with particular e-commerce services as of alleged great usefulness will be much loyal to that online company, considering that trust is also inclusive.

This section presented the informative nature of statistics measurements and detailed discussions on every individual part thereto. The next chapter will maneuver through the dissertation’s synopsis, critical discussions, recommendations, and provide room for further studies.

5.2 Managerial Implications

According to this study’s findings, customers consider the product price, convenience, and product information and return policy as essential benefits for customer satisfaction to re-purchase intention in online stores. Similarly, customers feel fear of risks while shopping in e-stores, so there is a need to reduce customer satisfaction to re-purchase purpose in online stores. Keep in mind: online store managers/owners should offer abundant choices to consumers and offer competitive product prices. As we surveyed that Chinese consumers were more sensitive about price. E-store’s managers/owners should influence consumers through social media with ads and promotions for discounts available. Convenience is essential, especially for new consumers; some e-stores make a very lengthy process to buy a product online. As a result, most consumers leave shopping in half due to transfer money and non-acceptance of standard money-paying cards. Detailed and complete product information should be provided. Before the buying process, consumers want to know about product information that is shared by e-stores. Retailers should share more information about products by using short videos about product performance and 3D pictures. Managers should pay more attention to implement return policies to facilitate the customer as if the product performance, damage, and other reasons could be returned.

Customers shopping online do not know physically about the product and performance. They only see the product features and images in e-stores. In e-stores, consumers may develop low trust and perceive elevated high risk because of the lack of physical sense (looking, touching, tasting, and smelling). Therefore, to enhance the customer’s degree of satisfaction, e-store retailers should contribute clear, understandable information. The quality of the product should be the same as described on the company’s website. E-store’s managers/owners should introduce a mechanism (e.g., Alipay by Alibaba Group in China) to improve safety to motivate people to re-purchase online stores. Consumers should not be worried about losing their money and other financial information. Prompt delivery plays a vital role in Chinese customer satisfaction. To satisfy consumers in today’s competitive e-commerce, online store retailers must keep a close eye on timely delivery and customer service. Delayed childbearing and ignorance of customer’s concerns will cause customer dissatisfaction. S. A. Khan et al. 302 Customer satisfaction should be a preference to provide more benefits and less risky shopping environment.

5.2 Limitations of the Study and Future Research

The thesis identified six factors; there could be alternative determinants influencing online users’ perception when intending to do some shopping. However, our research did not look into all other aspects apart from the ones identified in this paper; this was not successful due to a lack of financial resources. We could only manage to make our research cover a few extend in China. Generally, our research scope of study could only be limited to university scholars and office workers. We found it sufficient for our analysis since, according to the research done before, CNNIC published it. I report that; the majority of online users are the young generation and office staff. This was appropriate because we could see them daily doing research and assignments while sourcing relevant information from the internet and when making orders of various resources they could not reach due to location zone or lack of financial resources to access them.

Due to the lapse of time and material costs constriction, we only look into determinants influencing consumer’s intention to purchase online in China, although other states online users might possess alternative features and satisfaction range and purchase intention. Future studies can develop numerous theories that could capture and offer more clarification on determining factors that influence consumer’s choices on e-commerce, such as perceived usefulness, perceived ease of use, perceived risk, and trust.

Appendices A