COMPETITOR-BASED MARKETING MIX STRATEGIES AND PRODUCTION ACTIVITIES IN MANUFACTURING AND RENEWABLE ENERGY

The experience of using e-commerce platforms affects the online purchase intention of customers in the FMCG (Fast moving consumer goods) sector


Introduction
People today are living in a period of strong development in technology and digital transformation.Currently, there are substantial consumers demands for shopping through the Internet, which has led to the explosion of e-commerce platforms.In addition, with the appearance of the Covid-19 pandemic in 2020, many countries, including Vietnam, had to implement social distancing, negatively affecting the world economy, and people's consumption behavior is also forced to change to fit the situation.
From a comprehensive perspective, the e-commerce market in Vietnam has been developing, especially since 2015.Between 2018 and the end of 2019, the growth rate of ecommerce platforms seems to have slowed down; although the pandemic outbreak in early 2020 has severely affected the economy, the revenue level of the business-to-customer (B2C) ecommerce industry still achieved impressive results.The needs and consumer trends of Vietnamese people are changing markedly through the number of visitors on e-commerce platforms.
However, Vietnam's e-commerce platforms have just grown strongly in recent years.The Covid-19 pandemic has impacted and changed humans' lives as well as consumption and shopping behaviors and helped people adapt to digital transformation and accept technology.Moreover, consumers are now more interested in their personal experience of using when participating in shopping than they are interested in discounts and promotions.In addition, the trend of buying and consuming fastmoving consumer goods is being shifted to the online sales market with the presence of many famous FMCG firms on e-commerce platforms.In such circumstances, the research will examine the impacts of consumers' experience of using e-commerce platforms in Ha Noi based on the following theories: Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and E-Commerce Acceptance Model (ECAM).
In the world, there have been many research studies analyzing the effects of e-commerce on consumer demand and buying behavior.For example, Aladwani and Palvia (2002) began to develop a sound tool to measure the quality of an e-commerce platform from the user's point of view and identify four fundamental aspects: technical adequacy, content quality, specific content, and form.Wu et al. (2013) suggested that the layout and space of a website can give users a special emotion, thereby increasing the likelihood that they will shop on the website.
The research gaps that the article is aimed at: Does the experience of using e-commerce platforms affect the purchase intention of consumers?What factors are affected by the experience of using and how does the experience of using affect consumer purchase intention?

Theoretical framework:
Theory of Planned Behavior (TPB) Ajzen proposed the theory of planned behavior (TPB) (Ajzen, 1991) as an improved version of the theory of rational action (TRA) (Fisbein & Ajzen, 1975) to overcome the limitation of the previous theory of rational human behavior and predict behaviors with behavioral and planned modifications.The theory of planned behavior is widely accepted and used in the study of human behavior.There have been many studies showing that this model is suitable for studying consumer behavior when participating in technology-related activities, for example, online purchases (Al-Jabari, Othman, and Nik Mat, 2012).

Technology Acceptance Model (TAM)
The Technology Acceptance Model (TAM) was introduced by Davis in 1989 to explain and predict technology adoption and use behavior.The theoretical foundation of TAM is the theory of rational action TRA (Fishbein & Ajzen, 1975).Perceived usefulness and perceived ease of use are two factors that can influence users' attitudes and intentions when they interact with technology (Davis, Bagozzi & Warshaw, 1989).

Electronic Commerce Acceptance Model (ECAM)
By combining the TAM model of Davis (1989) when adjusted with the theory of risk perception, Joongho Ahn et al (2001) have proposed the ECAM e-commerce acceptance model.The ECAM model also provides insights into the factors that can turn Internet users into potential future customers.Perceived ease of use and perceived usefulness positively influence customer buying behavior.Meanwhile, risk perception, in general, harms customers' shopping behavior.

The quality of the e-commerce platform affects trusts and risk perception
The quality of the e-commerce platform acts as the store's atmosphere (E thier et al., 2006).A well-designed e-commerce platform can increase the probability of a favorable impression as viewers respond to visual cues, and viewers with a good impression of the e-commerce platform are more likely to return.become more customers (Albert, 2004); In addition, Napier et al. (2001) show that perceived e-commerce platform quality is positively related to both trust and intention to trust because the use of an e-commerce platform brings the first experience of the supplier's presence reinforces the first impression.Besides, the study by Hsin Hsin Chang and Su Wen Chen (2008) showed that website quality contributes to consumers' trust and perceived risk, and thus, purchase intention.In addition, Lim (2003) argues that the risks perceived by consumers are technology-related and include issues such as slow downloads, interface limitations, search problems, and incomplete measurements.enough about web application success, security weaknesses, and lack of internet standards.Through the above studies, the research team put forward the first two hypotheses: H1: Perception of the quality of the e-commerce platform has a positive (+) positive effect on consumers' trust in the e-commerce platform.H2: Perception of e-commerce platform quality has a negative (-) effect on consumers' perceived risk to e-commerce platforms.

Attitude to information affects purchase intention
According to Le Minh Chi and Le Tan Nghiem's research in 2017, when an individual has a positive attitude and has a need to search for the electronic word of mouth information on social networks, they tend to evaluate eWOM information.This is useful and therefore the likelihood of accepting the information is higher.According to a study by Nguyen Dinh Yen Oanh et al ( 2018) on attitudes towards online advertising: The factor that has the strongest influence on the intention to continue buying carbonated soft drinks (β=0.449;p= 0.000).The results of this study once again confirm the relationship between attitude and repeat purchase intention towards the carbonated beverage industry in Vietnam, consistent with Ajzen and Fishben's theory of TRA in 1975.From there, the research team hypothesized: H3: Attitudes about information have a positive (+) positive impact on consumers' online purchase intention on e-commerce platforms.

Trust affects purchase intention
In their research, Hong and Cha (2013) have shown that in addition to being affected by risk perception, trust also has a direct impact on consumers' purchase intention when shopping online.In addition, Pavlou and Fygenson (2006) argue that trust helps reduce the perceived risks of customers when sharing personal information and making purchases.In addition, Hsin Chang and Wen Chen ( 2008) also conducted research and proved the relationship between trust and purchase intention: trust has a positive impact on purchase intention.Through the above studies, the research team proposes the following hypothesis: H4: Trust has a positive (+) impact on consumers' purchase intention on e-commerce platforms.

Perceived risk affects purchase intention
In the buying process, customers can always encounter barriers and risks that cause discomfort.Cox (1967) added consumer intent to the research and further development of risk perception, he showed that customers will act based on their shopping intent.If customers realize that their shopping goals are hard to come by, the perception of risk begins to emerge.Chiu et al. (2012) found that consumers' shopping experience has a positive impact on quality perception and thereby significantly reduces customer perceived risk.Then, Kamalul Ariffin et al.

Perceived usefulness affects purchase intention
Around the world, there have been studies showing that perceived usefulness has a strong impact on consumer's intention to purchase online.Vijayasarathy (2004).Chen et al. (2002) studied consumer behavior towards an online store belonging to a non-profit organization.They found that perceived usefulness was an important factor in predicting the intention to participate in shopping in this organization's online store, which was also shown in the study of Koufaris (2002).Then, Vijayasarathy (2004) also studied the online shopping intentions of adults and showed that perceived usefulness has a positive (+) impact on the intention to participate in online shopping.In addition, the studies of Childers et al (2001), Gefen andStraub (1997), andO'Cass andFenech (2003) have confirmed the relationship between perceived usefulness and purchase intention.From the above studies, the final hypothesis is put forward: H6: Perceived usefulness has a positive (+) positive impact on consumers' purchase intention on e-commerce platforms.
From the research hypotheses mentioned above, the authors propose a proposed research model as follows:

Research Methods
The research team first developed a draft scale 1 from previous studies both at home and abroad about the customer's experience on e-commerce platforms in the FMCG (Fast Moving Consumer Goods), adjusted to the current situation status in Vietnam.These scales were completed after consulting with experts in marketing and consumer intention and behavior: Associate professor Ph.D. Pham Van Tuan and Master Nguyen Viet Dung.Through interviews with experts to check the logic of the relationship between factors as well as the content of variables.When the scale has been calibrated, the research team continues to interview consumers to ensure that the author decides to remove inappropriate factors to proceed with building the official scale.After that, the complete research questionnaire will be included in the official quantitative survey between January 14, 2021, and February 14, 2022.The object of the study is all consumers who have experience on e-commerce platforms and have shopping needs on e-commerce platforms in Hanoi City, Vietnam.The research team plans to collect a sample of 400, and as a result, 375 responses were collected.After screening and removing invalid votes, the author uses 350 valid responses to use in official research.The sample size includes 350 consumers, of which the number of men accounts for 39.3%, and the number of women accounts for 54.7%.The age of the survey participants is mainly 15-24 years old (73.5%), and the other age groups are below 17%.In addition, the research team asked survey participants about the tendency to use online commerce platforms.The obtained results show that Shopee is the most chosen e-commerce platform with 313/350 participants.
To test the scale model and proposed hypotheses, the author uses the analytical method through the following steps: 1.Preliminary assessment of the scale as well as the reliability of the measured variables through Cronbach's Alpha reliability coefficient and exploratory factor analysis (EFA); 2. Test the scale by confirmatory factor analysis (CFA); 3. Verify the model by SEM in AMOS.

Meta-analysis of scale reliability and total variance explained by scales
By using SPSS 25.0 software, the author obtained the results of scale reliability (Cronbach's Alpha) and the results of exploratory factor analysis (EFA) to help remove some observed variables and increase the accuracy in the assessment of factors.Cronbach's Alpha standard is ≥ 0.6 and the total variance extracted is more than 50%.Specifically, the overall results of the scale are as shown below: The results show that the factors with Cronbach's Alpha coefficient are all greater than 0.6.Therefore, the author considers the scale to be good and continues to test Item-Total to see which observed variables have unsatisfactory correlation coefficients, then they will proceed with that variable.The observed variables all have a total correlation coefficient greater than 0.3 and all are smaller than the common Cronbach's Alpha value.Therefore, the author concludes that the factors are suitable for the study.

Test the scale by confirmatory factor analysis (CFA)
After testing the scale, the authors used AMOS software version 24.0 to conduct CFA test for the scale to measure the suitability of the research model and hypotheses.The test criteria include Chi-square adjusted for degrees of freedom (CMIN/df); Tucker and Lewis index; Comparative Fit index, mean square error approximation (RMSEA); composite reliability coefficient CR; Average Variance Extracted AVE.The model will be considered suitable when the Chi-square value is P ≥ 0.05.However, the disadvantage of Chi-square is its dependence on the sample size.The larger the sample size, the larger the chi-square, thereby reducing the fit of the model.Therefore, in addition to Pvalue, the authors use CMIN/df.Some practical studies show that the model will be considered suitable when ÷2/df < 5 (with sample size N>200); or < 3 (with sample size N < 200), (Kettinger and Lee, 1995).In this study, because the sample size was N=350 (N>200), according to Kettinger and Lee (1995), CMIN/df < 5; GFI, TLI, CFI ≥ 0.9 (Bentler and Bonett, 1990); RMSEA ≤ 0.08 indicates that the research model is appropriate.The CFA results from the scale are presented below: CFA allows to test the convergent and discriminant value of the scale without losing much effort and time like the traditional method (Multitrait -Multimethod).Furthermore, CFA tests the theoretical structure as well as the relationships between research concepts without bias due to measurement error (Steenkamp & Van Trip, 1991).Therefore, the author uses CFA to test the appropriateness of the scale model with the data collected after preliminary evaluation by Cronbach's Alpha and EFA.
CFA testing criteria: according to Hu & Bentler (1999), Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling indicators considered to evaluate the popular Model Fit include: (1) CMIN/df ≤ 3 is good, CMIN/df ≤ 5 is acceptable; (2) CFI 0.9 is good, CFI ≥ 0.95 is very good, CFI 0.8 is acceptable (CFA ranges from 0 to 1) (3) GFI ≥ 0.9 is good, GFI ≥ 0.95 is very good; (4) TLI ≥ 0.9 is good; (5) RMSEA ≤ 0.06 is good, RMSEA ≤ 0.08 is acceptable; (6) PCLOSE 0.05 is good, PCLOSE 0.01 is acceptable According to Hair et al. (2010), Multivariate Data Analysis, the indicators considered to evaluate Model Fit include: (1) CMIN/df ≤ 2 is good, CMIN/df ≤ 5 is acceptable; (2) CFI 0.9 is good, CFI ≥ 0.95 is very good, CFI ≥ 0.8 is acceptable (CFA ranges from 0 to 1); (3) GFI ≥ 0.9 is good, GFI ≥ 0.95 is very good; (4) RMSEA 0.08 is good, RMSEA ≤ 0.03 is very good.After using the data collected from the sample N=350, the results obtained by the author were satisfactory.However, the results can still be improved, in particular, the smaller the Chisquare index, the more beneficial.By using the model editing suggestions from MI (Modification Indices), the author was able to achieve the desired results than before.

Test models and research hypotheses 4.3.1. Testing the research model
The results of testing the scales, EFA and CFA show that the scales have the reliability value as well as the discriminant value to run the SEM model.The SEM model allows to simultaneously estimate the elements in the overall model, estimate the causal relationship between the concepts, and measure the stable (recursive) and the unstable (non-recursive) relationships.The SEM model allows the flexibility to find the most suitable model among the proposed models.
At the same time, on this basis, the research team conducted an SEM test to check the fit and accuracy of the model and obtained the following results:

Test the research hypotheses
After analyzing the linear structural model, we get the following test results:  3, the author can comment that the regression weights of the relationships in the two hypotheses H1 and H2 are equal to 0.476 and -0.150, respectively, showing a positive impact of e-commerce platforms quality on trust and the negative impact of e-commerce platform quality on perceived risk.The higher the quality of the e-commerce platforms, the greater the trust and vice versa.Besides, the poorer the quality of the e-commerce platform, the higher the perceived risk and vice versa.
The regression weights of the relationships in the 3 hypotheses H3, H4, and H6 are all greater than 0 (0.230, 0.445, and 0.517).From there, it shows the positive influence of attitude towards information, trust, and perceived usefulness on purchase intention.This is an important factor because when consumers have a good attitude towards the information or have strong trust or perceived its usefulness, it will positively affect their purchase intention and vice versa.Besides, the regression weight of the relationships in hypothesis H5 has a value less than 0 (-0.156), which shows the negative impact of perceived risk on purchase intention.When the perceived risk is higher, the purchase intention of consumers decreases and vice versa.From here, the authors draw the comments that the research hypotheses are reasonable.

Discussion and Conclusion Discussion Research results
Research on customer experience in the field of shopping has been carried out by many domestic and foreign authors.On this topic, there have been many evaluations, analyses, and limitations at the same time, especially when it comes to aspects related to e-commerce.This research has helped to close the research gap on customer experience to shopping intention on e-commerce platforms.From the SEM structural equation model analysis results, it can be seen that the factors directly or indirectly affect the intention to buy.Based on the theory of TPB and TAM, the research work has built a model and tested the correlation between the factors group of ecommerce platform quality, trust, attitude towards information, perceived risks, and perceived usefulness to purchase intention on e-commerce platforms.Besides, trust, attitudes towards information, perceived risk, and perceived usefulness have a direct impact on purchase intention with different influence levels.
E-commerce platform quality has a direct positive impact on the trust factor (0.476), and at the same time harms the perceived risk factor (-0.150).This is an important factor because the website is improved in terms of quality (specifically in this study are the quality of ease of access, content, interface, stakeholder information, multimedia features) helps users tend to trust the supplier's capacity and integrity.In return, website quality also has an indirect influence on risk perception through customers' trust in online retailers.In this study, perceived risks related to personal information security, product/service issues, and financial issues.
Besides, factors of trust, attitude towards information, and perceived risks have a direct positive impact on purchase intention (0.445, 0.230, 0.571 respectively), in which exist the 2 strongest influences of the model.When e-commerce platforms ensure customers' positive attitudes towards information, and the greater the trust and perceived usefulness that they bring, the more motivated people are to use ecommerce platforms and do shopping online.On the contrary, perceived risks harm purchase intention (-0.156).
Though the topic is not innovative, customer experience and e-commerce have not received much attention from domestic and foreign researchers.With this study on how experience on e-commerce platforms affects customers' online purchase intention, the authors hope to contribute new points to the understanding of these two factors.
At the same time, the research team makes some recommendations for businesses participating in the field of ecommerce on four aspects: attitude towards information, trust, perceived risks, and perceived usefulness.
In general, businesses should pay attention to the transparency, accessibility, and integrity of the information appearing on the e-commerce platform; establish agreement policies between suppliers and e-commerce enterprises on the amount of necessary information; assure customers of the credibility of the sales units, and the advertising of products/services; focus on the privacy of users' personal information; diversify forms of payment on e-commerce platforms; upgrade the e-commerce platform system; ensure that services on the e-commerce platforms always meet the needs of customers on time; capture customer psychology through the application of data analysis.
The research authors hope that the information within this work will partly help make the application of improving customer experience an effective strategic tool for individuals and businesses in the future, especially in the community of small and medium enterprises, and start-ups.

Limitations and Suggestions for future research
Despite the expected research results, it cannot be denied that within the group's research work still exist certain limitations: the study sample area is small, the individuals participating in the survey are mainly young people; many difficulties arise in surveying subjects in generations due to the complicated development of the Covid-19 pandemic; the proposed model focuses on the influence of factors such as attitude, trust, customer perception and e-commerce platform quality to predict shopping intention.
With the mentioned limitations above, the research team hopes that future studies will overcome the mentioned problems.Further research in the same field can expand the model by combining factors to create a deeper and more comprehensive view of the customer's experience in online shopping on e-commerce platforms.The authors hope that the new studies will lead to innovative discoveries in this area.
(2018) indicated that consumers with low perceived risk are more likely to generate online purchase intentions.In addition, the study by Rosillo-Díaz et al (2019), they have shown that customer risk perception harms consumers' online purchase intention.In Vietnam, there have been many research studies on the relationship between risk perception and online shopping intention such as research by Hoang Quoc Cuong (2010), Le Ngoc Duc (2008), in addition to Research by Nguyen Le Phuong Thanh (2013).From the above studies, the next hypothesis is proposed: H5: Perceived risk has a negative (-) effect on consumers' purchase intention on e-commerce platforms.https://ijbssrnet.com/index.php/ijbssrInternational Journal of Business and Social Science Research Vol: 3, Issue: 4 April/2022 DOI: http://dx.doi.org/10.47742/ijbssr.v3n4p3https://ijbssrnet.com/index.php/ijbssr

Figure 1 .
Figure 1.The proposed research model Source: The author group

Figure 2 .
Figure 2. CFA test resultsAfter using the data collected from the sample N=350, the results obtained by the author were satisfactory.However, the results can still be improved, in particular, the smaller the Chisquare index, the more beneficial.By using the model editing suggestions from MI (Modification Indices), the author was able to achieve the desired results than before.4.3.Test models and research hypotheses 4.3.1.Testing the research modelThe results of testing the scales, EFA and CFA show that the scales have the reliability value as well as the discriminant

Figure 3 .
Figure 3. SEM Model SEM analysis results show: CMIN/df = 2.123; CFI = 0.920; TLI = 0.910; RMSEA = 0.57 so the model fits the market data.The details of the SEM analysis results are shown in Figure 3.