19Figure 8 Research model of Ganesh Dash, Kip Kiefer và Justin Paul 2021...20Figure 9 Research model of Nguyen To Nhu, Nguyen To Uyen, Dang Thi Kim Ngan 201721Figure 10 Research method..
INTRODUCTION
Reason for choosing the topic of the research paper
According to Holmlund et al (2020), with the rapid development of online shopping, customer experience gradually became the main source of a retailer's sustainable competitive advantage through providing differentiated values Retailers needed to pay attention to changes in the customer experience to increase customer satisfaction in order to gain a long-term sustainable competitive advantage (Arijit et al., 2020) According to research conducted in 2013 by Trueman et al., studying the factors that create the online customer experience was an area that plays an extremely important role in marketing research Although sales in the online retail industry are still experiencing safe growth, online retailers are still facing major challenges From a customer perspective, it costed them very little (even zero) to switch between online stores (Mutum et al., 2014) So, to attract and retain customers, online retailers need to create a more enjoyable and amazing shopping experience than the competition This means that they must understand the online experience to nurture customer loyalty.
Most research investigating factors that influence online customer experience had a tendency to focus on the pre-purchase and purchase stages, such as retail website features, including website design and performance, information quality, ease of use, and security (Turban et al (2000), Srinivasan et al (2002), Park and Kim (2003), Pereay Monsuwé et al (2004), and Rose et al (2012)) These studies had paid little attention to the post-purchase phase Additionally, studies examining customer satisfaction across all stages of the online shopping process are still limited Only Rao et al (2011) examined the impact of retailers' ability to fulfill orders; Griffis et al.
(2012) examined the impact of merchandise returns on online customer satisfaction.
Besides, Liu et al (2008) along with Thirumalai and Sinha (2011) were the only two research groups that are trying to combine many different elements of the entire online shopping process However, their study overlooked an important factor in the post- purchase period, which is the customer's experience of product returns.
If only looking at one component of the entire online customer experience process, it would be difficult for retailers to fully understand the whole process so that they can recommend effective business strategies to improve customer satisfaction, customer experience and enterprise sales (Liu et al., 2018).
Specifically, after analyzing research papers and scientific articles in the field of Customer Satisfaction and Online Purchase Intention of customers, the authors has found 8 related articles.
1.1 Research objective 1.1.1 General research objective
Analyze the factors and evaluate their influence on customer satisfaction, thereby affecting the online purchase intention of people in Da Nang city.
- Research relevant literature to propose theoretical research models.
- Determining the factors affecting customer satisfaction, thereby affecting the online purchase intention of Da Nang people.
- Assess the influence of factors on customer satisfaction, thereby affecting the online purchase intention of Da Nang citizens Determine which factors have the strongest influence on customer satisfaction.
- Assessing the influence of customer satisfaction on the online purchase intention of Da Nang inhabitants.
- Propose administrative implications for businesses to improve online customer experience, impact customer satisfaction, thereby leading to online purchase intention of consumers living and working in Da Nang city.
- Which factors affect customer satisfaction, thereby affecting the online purchase intention of Da Nang people?
- What is the influence of these factors on customer satisfaction?
- Which factor has the strongest influence on customer satisfaction?
- How does customer satisfaction affect online purchase intention?
- What should businesses do to influence consumer satisfaction, thereby affecting the online purchase intention of Da Nang people?
- What should businesses do to improve the likelihood of consumers buying online in Da Nang?
Research subject and scope
Factors affecting customer satisfaction, thereby affecting the online purchase intention of consumers in Da Nang city.
2.2 Research scope 2.2.1 Scope of research in terms of space
This research studies consumers in Da Nang city.
2.2.2 Scope of research in terms of time
This research collects data from October 2022 to December 2022.
Research method
This study uses a combination of both qualitative and quantitative research methods.
- Desk research: Collecting documents and research articles available in
Vietnam and abroad to have an overview of the research problem and understand the theoretical bases for the research topic.
- Interviewing experts: Interviewing experts who are lecturers of the Faculty of
E-commerce in order to complete the theoretical basis, research models on the factors affecting customer satisfaction, thereby affecting the customer's online intention to purchase In addition, the authors also conduct interviews with people doing online business in Da Nang city to understand the actual situation of the topic better, thereby offering suitable solutions for the research.
- Group discussion: Participate in discussions with experts and lecturers in the industry to perfect the theoretical basis Besides, the research members also cooperate with each other, discussed and exchange to develop the topic as well as complete the survey questionnaire.
- Observation: Observe consumer interactions on websites, e-commerce sites and Fanpages of online businesses in Da Nang to capture customer trends of online shopping behavior today.
- Quantitative research method is to collect and analyze information based on data collected from the market - Da Nang city, specifically, consumers answering the study's questionnaire The data that is collected in this research is primary data Data will be collected through surveys sent to online consumers by Google Forms.
- This method is implemented through the process of collecting and analyzing data in order to test the model, verify the scale, confirm the hypothesis and answer the research questions that have been set out previously.
- After collecting, the team will review the valid data to perform data encryption.
The authors use SPSS to make descriptive statistics, evaluate the research scale, analyze relationships and finally draw conclusions This investigation helps to understand the market situation to come up with appropriate solutions and business models better.
Research paper layout
Chapter 1: Theoretical basis and research model Chapter 2: Research method and measurement Chapter 3: Research results
Chapter 4: Conclusion and management implications
CONTENT OF THE REPORT
The rapid change of technology has led to a significant change in the purchasing behavior of consumers Instead of shopping directly at the store, many people have turned to online shopping because of its convenience Moreover, the customer's store-to-store switching costs are nearly zero This has posed a big challenge for e-retail businesses in understanding the factors affecting customer satisfaction, thereby leading to online purchase intention.
Based on the idea of Dynamic Model of Online Customer Experience, this study has explored the satisfaction and purchase intention of Da Nang consumers from the perspective of considering factors belonging to three different stages (4 elements of the pre-purchase stage, 2 elements of the buying stage and 3 elements of the post- purchase stage) of the customer journey.
A questionnaire was designed to confirm the proposed hypotheses The results of the study will show that e-retail businesses should invest their company's resources in improving which factors in which stage to improve customer experience; thereby, increasing customer satisfaction and stimulating online purchase intention.
2 Overview of current online shopping behavior
Online shopping is currently the most popular trend in the digital age because of the tremendous development of technology and the conveniences it brings, including the ability to save time, money, effort, money and many other benefits This is reflected in the percentage of consumers who shop online as well as the income generated by online retail, both of which are constantly increasing over time (Germany et al., 2022).
According to the Vietnam E-commerce Association (VECOM), the average growth rate of e-commerce from 2016 to 2019 was about 30% Retail e-commerce of consumer goods and services had grown in size, from $4 billion in 2015 to about
$11.5 billion in 2019 Vietnam's e-commerce grew by about 15% in 2020, and reach about 13.2 billion USD By 2021, the growth rate of Vietnam's e-commerce had reached over 20% and surpassed the 16 billion USD mark Thanks to the effective management of the Covid-19 epidemic and the growth drivers from the second wave
Theoretical basis and research model
Overview
The rapid change of technology has led to a significant change in the purchasing behavior of consumers Instead of shopping directly at the store, many people have turned to online shopping because of its convenience Moreover, the customer's store-to-store switching costs are nearly zero This has posed a big challenge for e-retail businesses in understanding the factors affecting customer satisfaction, thereby leading to online purchase intention.
Based on the idea of Dynamic Model of Online Customer Experience, this study has explored the satisfaction and purchase intention of Da Nang consumers from the perspective of considering factors belonging to three different stages (4 elements of the pre-purchase stage, 2 elements of the buying stage and 3 elements of the post- purchase stage) of the customer journey.
A questionnaire was designed to confirm the proposed hypotheses The results of the study will show that e-retail businesses should invest their company's resources in improving which factors in which stage to improve customer experience; thereby, increasing customer satisfaction and stimulating online purchase intention.
2 Overview of current online shopping behavior
Online shopping is currently the most popular trend in the digital age because of the tremendous development of technology and the conveniences it brings, including the ability to save time, money, effort, money and many other benefits This is reflected in the percentage of consumers who shop online as well as the income generated by online retail, both of which are constantly increasing over time (Germany et al., 2022).
According to the Vietnam E-commerce Association (VECOM), the average growth rate of e-commerce from 2016 to 2019 was about 30% Retail e-commerce of consumer goods and services had grown in size, from $4 billion in 2015 to about
$11.5 billion in 2019 Vietnam's e-commerce grew by about 15% in 2020, and reach about 13.2 billion USD By 2021, the growth rate of Vietnam's e-commerce had reached over 20% and surpassed the 16 billion USD mark Thanks to the effective management of the Covid-19 epidemic and the growth drivers from the second wave of the epidemic, this rate will continue to increase significantly in this 2022 (VECOM, 2022)
Figure 1 Growth rates of some regions in 2020 and 2021
For consumers, 2020, 2021 and 2022 mark a change in consumption habits, as online shopping has become popular thanks to the convenience of online transactions and attractively promotional programs The traditional purchasing behavior is gradually decreasing, especially due to the impact of the Covid-19 outbreak in an environment of limited travel and contact (Tam and Hien, 2022) According to Nielsen research, when Covid-19 occurred, more than 50% of customers reduced the frequency of going to the store and 39% increased the frequency of shopping via the internet Notably, 64% of consumers said they would continue to shop online more often after Covid-19 (Nielsen, 2020) As can be seen from the above data, the buying habits of Vietnamese consumers had changed significantly (UK, 2021).
Some related concepts
Customer experience had always been an important subject of research in the field of marketing, because attracting customers through creating a positive experience can directly increase a company's profits (Hoffman et al., 2000; Grứnholdt et al., 2015) It had become an important factor for retailers to implement differentiation strategies to gain a sustainable competitive advantage (Artusi et al., 2020) Also according to Artusi et al (2020), with the context that customers were living in a developed economy, the competitive advantage of businesses would come from creating experiences based on products or services to attract customers Hult et al (2019) argued that customer experience was an intrinsic and subjective response in the process of direct and indirect contact between customers and businesses, including many aspects of service quality provided by the company such as advertising, packaging, functionality, user-friendliness as well as reliability of products and services Sebald, Jacob (2020) and De Keyser et al (2015) proposed that customer experience originates from consumers' emotions at different levels, including rational, emotional, psychological, physical and senses According to a study conducted in 2018 by Otterbring and Lu, customer experience involved all touchpoints from the moment a customer sees a product or service The customer experience can result in the consumer's emotional and cognitive interactions with the company (Godovykh and Tasci, 2020) The results of these interactions will be able to make an impression in the minds and hearts of consumers; thereby, may influence their assessment of the company's products or services According to research conducted in 2020, Godovykh and Tasci suggest that customer experience can also be measured by 4 components: cognitive, affective, sensory and visual It can be said that the customer experience has become an important part of the value creation process of retailers During the shopping process, that businesses actively creating positive emotional experiences is able to shape customer satisfaction and loyalty (Vakulenko, 2019).
The above research also showed that customer experience was the most important determinant of customer satisfaction This experience was also an important and strategic differentiator for retail companies to differentiate themselves from current and potential competitors in the business market
In recent years, online customer experience had become the focus of service marketing researchers (Nambisan and Watt, 2011) When competition among online retailers became more intense, it was important to gain more knowledge about the online customer experience in the digital environment to improve sales, profits and grow loyal customer base (Jun, Yang and Kim, 2004) Cho and Park (2001) argued that online customers were not simply shoppers but also information seekers or technology users Therefore, we could see that the online customer experience was more complex than the online shopping experience (Constantinides, 2004) The online shopping interaction did not take place at the retailer's store; therefore, the e-retailer may not have complete control over all aspects of shaping the online customer experience (Verhoef et al., 2009).
Rose et al (2012) said that online customer experience was a “psychological state of the user, expressed as a subjective response to the website” Customer experience in e-retail can be measured in two dimensions, namely emotional experience and cognitive experience (Tyrvọinen, Karjaluoto and Saarijọrvi, 2020) The premises of customer experience in e-retail were customer service, website experience, product experience, delivery experience and brand experience (Singh and Sửderlund, 2020) According to a number of studies conducted, variables that were likely to affect customer experience can also be website aesthetics, ease of use or ease of customization (Martin et al., 2015; Trevinal and Stenger, 2014; Rose et al., 2012;
Hoffman and Novak, 2009) Customers' online purchasing behavior would be influenced by a positive online customer experience (Bridges and Florsheim, 2008)
A positive online customer experience facilitated long-term brand loyalty (Brodie et al., 2013; Wirtz et al., 2013) Bilgihan et al (2016) had shown that repurchase intention was one of the main consequences of improving online customer experience.
Yap, Ramayah and Shahidan (2012) gave the definition that satisfaction was the overall attitude of customers towards a service provider In 2004, a study researched by Liang and Wen-Hung explained customer satisfaction as a measured evaluation after consumption Similarly, Ningsih and Segoro (2014) defined satisfaction as the attitudes, evaluations and emotional responses expressed by consumers after the purchase process Fornell (1992) considered customer satisfaction as an attitude formed on the basis of the experience after a customer bought a product or used a service and paid for it According to Pan and Nguyen (2015), customer satisfaction was defined as an assessment based on the comparison between customer expectations and actual experience Oliver et al (1997) defined customer satisfaction as “the positive response of meeting customer needs.” Furthermore, in research conducted in 2003, Wong and Sohal stated that meeting more consumer expectations while providing products or services creates a higher probability of repurchase for a company Most studies confirmed that satisfied customers were more likely to repurchase and have a good relationship with an organization (Blodgett and Anderson,2000; Maxham and Netemeyer, 2002) In addition, Martínez and del Bosque (2013) found that customer satisfaction can be used as an important indicator of the overall performance of the business Customer satisfaction had a positive influence on customer trust, retention and repurchase intention, so satisfaction was considered as a key determinant of customer loyalty (Gustafsson) et al., 2005; Liang and Wen-Hung, 2004) Similarly, in the 1997 study conducted by Heskett, Sasser and Schlesinger, they also demonstrated that customer loyalty was measured as a direct result of customer satisfaction Also in this study, the authors had shown that customer satisfaction influenced purchase intention and determined future purchasing power.
For purchase behavior, purchase intention was defined as an individual's willingness to purchase an item (Tirtiroglu and Elbeck, 2008; Raza et al., 2014).
Consumer purchase intention was important in predicting consumer behavior.
According to Meskaran et al (2013), online purchase intention was derived from purchase intention Meskaran (2013) and Pavlou (2003) defined that online purchase intention was a customer's willingness to purchase a product or service via the internet This term was used when customers were willing to search, select and purchase products through the Internet The way a business operates could be assessed based on the purchase intention of the customer (Howard and Sheth, 1967) For e- commerce businesses, determining customer intent was even more important.
According to He et al (2008), lack of online purchase intention was a serious obstacle in e-commerce development and would have a serious negative effect on online business According to research done by Blackwell et al (2001), shopping intention was one of the two factors that directly affect the buying behavior of consumers.
Based on the research of Delafrooz et al (2011), we can see that online shopping intention was an important step to make a specific purchase behavior over the Internet.
Online purchase intention can be measured by shopping expectations and consumers' consideration for that item/service (Laroche, Kim and Zhou, 1996) The intention to buy online begins with the product review To make the assessment, individuals used their current knowledge, experience and external information (Bukhari et al., 2013) According to David et al (2002), customers' intention to shop online was influenced by many factors such as personal characteristics (gender, age, marriage, education, religion, occupation and income, personality and lifestyle); environmental factors (family, society and community); factors from the seller (price,advertising, trade promotion, brand, technical support activities via website, delivery,payment and customer services) These factors directly and indirectly affected the purchase intention of customers In addition, according to the research results of
Xiang Yan and Shiliang Dai (2009), online purchase intention was influenced by two groups of factors: perceived benefits and perceived risks Perceived benefits positively affected online shopping intention and perceived risks negatively affected customers' online shopping intention (Xiang Yan and Shiliang Dai, 2009).
An overview of the theoretical background of online customer experience
The dynamic model of online customer experience studied by Klaus' (2013) overcomes the limitations of the model studied by Chircu and Mahajan (2006) when determining the online purchasing process including three different stages which are before, during and after the purchase stages.
- Pre-purchase stage: This phase included activities such as information search and information evaluation Previous studies had shown that various retail website features including site performance, ease of use, site appearance, information quality, and customization created the experience of the customers in the pre-purchase period and had a positive influence on customer satisfaction for e-retailers (Srinivasan et al., 2002; Liu et al., 2008 and Rose et al., 2002;
- Purchase stage: This phase included activities such as product selection, ordering, and payment It involved the shopper performing activities such as choosing a shipping method, filling out details and confirming the order at checkout (Kotler, 1997a,b).
- Post-purchase stage: This phase involved activities such as product reviews and returns The post-purchase experience was an important part of the online consumer experience because it was only at this stage that the online customer can check the product (Kotler, 1997a,b).
Table 1 Synthesis of studies using customer experience theories in research on customer satisfaction and online purchase intention
Author Basis theory Independent variables
Thi Song Hanh Pham, Mohammad Faisal Ahammad (2017)
Dynamic model of online customer experience
- Product information- Ease of use- Security assurance- Customization
- Website appearance - Order fulfillment - Ease of Return - Ease of check out - Responsiveness of customer service
Nguyen To Nhu, Nguyen To Uyen, Dang Thi Kim Ngan (2017)
- Information quality- Website design- Product characteristics- Reputation of supplier- Ability to trade- Feedback- Security/Privacy- Payment methods- Delivery stage- Customer service- Product quality
Related research models
a Research model of Thi Song Hanh Pham và Mohammad Faisal Ahammad(2017)
Figure 2 Research model of Thi Song Hanh Pham và Mohammad Faisal Ahammad
With the rapid development and fierce competition of the retail industry, business owners are always trying to create a competitive advantage by enhancing the customer experience in the interaction and purchase journey The purpose of this research paper was 1) seek the way to broaden consumers' knowledge about the online shopping experience, 2) identify the most important factors that affect customer satisfaction, from the entire online shopping process, 3) fill the gap in research by looking at pre-purchase, purchase and post-purchase experience simultaneously, 4) contribute to the e-retail literature by developing and testing a new model, 5) suggest important governance implications that e-retailers should focus on in their business practices to enhance customer satisfaction and lead to the loyalty of the customer.
(Dynamic model of online customer experience) of Klaus' (2013) was used as the theoretical framework for this study The sample study included UK online shoppers The sample size was 600 people surveyed through a questionnaire.
The results from this study showed that a positive relationship existed between high quality product information, ease of use, customization, ease of order fulfillment,security assurance, high order fulfillment, responsive customer service, ease of product return with customer satisfaction Besides, the relationship between website interface and customer satisfaction were not supported in this study In addition, customer satisfaction will have a positive impact on customers' repurchase intention and their word of mouth On the contrary, satisfaction will not make customers willing to pay more to buy from the business This study demonstrated that product category can also have certain effects in regulating the relationship between variables.
Specifically, it had a role in regulating the relationship between product information and customer satisfaction, the relationship between customizability and customer satisfaction, the relationship between order fulfillment and customer satisfaction, the relationship between customer service responsiveness and customer satisfaction The remaining relationships were not subject to the moderating effect of the product category variable.
The findings of this study are expected to provide strategic implications that retailers in general and e-retailers in particular can use to develop their online services to increase customer experience to bring satisfaction to customers. b Research model of Ting Chi (2018)
Figure 3 Research model of Ting Chi (2018)
The general purpose of this research paper was to better understand the important issues related to apparel e-commerce Specifically, this study aimed to experimentally determine the impact of apparel mobile websites' key features on U.S. consumer satisfaction, which in turn influences apparel purchase intention via mobile devices Regarding specific objectives, this study consisted of three parts: 1) through identifying the main features of mobile apparel websites, this study proposed a research model illustrating the relationship between quality apparel sites, consumer satisfaction and consumer purchase intention, 2) examine the psychometric properties of the previously developed model using consumer survey data (main data were collected in the United States), 3) provide some management suggestions for marketers and companies based on the research findings.
The theory of self-regulation proposed by Bagozzi (1992) and the WebQual Scale proposed by Loiacono et al (2002); Loiacono, Watson, and Goodhue (2007):
Extension from the Technology Acceptance Model (TAM) were used as the theoretical framework for this study Data collected included 293 consumers who used apparel e- commerce in the United States.
In this study, while the relationship between response time, brand trust and customer satisfaction was rejected, the relationships between the visual attractiveness of the website, the attractive appearance of clothes, the quality of information on the site, the security of the site with customer satisfaction were proven to exist In addition, customer satisfaction was also found to have a positive influence on the intention to use apparel on mobile commerce in the future Age groups, genders, ethnic groups, education levels, or income levels did not make a significant difference among U.S consumers in regard to their satisfaction with apparel mobile websites.
Consumer satisfaction was proven to show good predictability for their behavioral intention. c Research model of Shefali Jaiswal và Anurag Singh (2020)
Figure 4 Research model of Shefali Jaiswal và Anurag Singh (2020)
Research conducted by Shefali Jaiswal and Anurag Singh in 2020 in order to 1) explore the factors that influence consumers' e-retail experience, 2) evaluate the impact of these decisive factors belonging to online customer experience on customer satisfaction This study sampled online shoppers 18 years of age and older in Varanasi.
The total number of responses obtained from the survey after removing and filtering incomplete data was 300 Based on the theory of online customer experience research of Cheung and Lee (2008), the authors developed their own research model.
According to the results of the study, the findings indicate that economic value, customization, post-purchase experience and customer service were the factors that directly affect customer satisfaction when shopping online Economic value was the most influential factor of customer satisfaction on digitally mediated platforms and followed by customer service and post-purchase experience In contrast, there was no relationship between website usability, security, customer perception and customer satisfaction.
Retailers can apply the findings of this study to focus on the determinants of customer satisfaction when shopping online Theoretically, while based on research related to online customer experience, this paper provided a model capable of providing insight into the elements of customer experience and determining customer satisfaction intentions From a management perspective, those findings will provide a comprehensive view of the factors customers used to measure their satisfaction, which led to more effective strategies to increase customer satisfaction and their online purchase intention. d Research model of Nan Chen và Yunpeng Yang (2020)
Figure 5 Research model of Nan Chen và Yunpeng Yang (2020)
In the current era, when technology has become an indispensable part of people's lives, consumers' purchasing intentions and behavior have also undergone significant changes Current purchase intention is not only influenced by factors such as the product, service, or supplier unilaterally, it is also influenced by factors of online nature, such as convenience and ease of use of the website, density of the network, etc This article aimed to 1) discuss the influence of network structure on the relationship between customer experience and purchase intention of consumers, 2) investigate the influencing factors of the customer experience that will be affected by different characteristics of the network structure, thereby determining the direction to optimize the network resources of the enterprise To investigate these hypotheses, the authors collected sample data in 2 phases: Phase 1 - 246 responses were collected for the purpose of creating the final complete questionnaire; Phase 2 - Distributed 400 questionnaires and then collected 321 valid copies This study used two theories simultaneously as a theoretical framework for the model, namely Customer satisfaction theory and Network structural embeddedness theory.
The study showed that there is a positive relationship between ease of use of the website, service related to the website, customer fees and purchase intention of consumers The findings also show that the ease of use of the website, the service associated with the website, and the customer cost had a positive impact on the density of the network In addition, the service associated with the website, and customer cost had an impact on the centrality of the network The study determined that network size and network density directly impacted consumer purchase intention.
In contrast, the relationship between ease of use of the website, service to the website, customer cost, and network size was not demonstrated in this study. e Research model of Sanjay Dhingra, Shelly Gupta và Ruchi Bhatt (2020)
Figure 6 Research model of Sanjay Dhingra, Shelly Gupta và Ruchi Bhatt (2020) The SERVQUAL model (Parasuraman et al., 1988) was used as the background theory for this study The authors distributed 350 questionnaires (mostly students and working people from the millennial generation) In which, 278 valuable responses were collected for analysis.
Research model and hypothesis development
Through the process of analyzing and synthesizing domestic and foreign projects, it can be seen that there exists a relationship between factors belonging to the customer experience at 3 different stages of the customer journey to customer satisfaction and thereby influence their online purchase intention In addition, the gaps in previous studies highlight the need to conduct research in Da Nang on this relationship.
From the research objects which are factors belonging to customer experience that can affect customer satisfaction, thereby leading to online purchase intention as well as the context of Da Nang market in particular, In the Vietnamese market in general, this study will inherit, develop and test the influence of the above factors on customer satisfaction and the relationship between customer satisfaction and online purchase intention The authors will perform:
- (i) Test the influence of 4 factors of the pre-purchase process on customer satisfaction when shopping online of Da Nang consumers, including: website design, ease of use, information quality and brand reputation, in which, all 4 factors are inherited from previous studies.
Specifically: website design and information quality inherit from research by Thi Song Hanh Pham and Mohammad Faisal Ahammad (2017), research by Ting Chi (2018) and research by Nguyen To Nhu, Nguyen To Uyen and Dang Thi Kim Ngan (2017); the ease of use inherits from the study of Thi Song Hanh Pham and Mohammad Faisal Ahammad (2017) and the study of Nan Chen and Yunpeng Yang (2020); brand reputation inherited from research by Ganesh Dash, Kip Kiefer and Justin Paul (2021) and research by Nguyen To Nhu, Nguyen To Uyen and Dang Thi Kim Ngan (2017).
- (ii) Test the influence of two factors in the buying process on customer satisfaction when shopping online of Da Nang consumers, including: ease of check out and security, in which, both factors are inherited from previous studies.
Specifically: ease of use inherits from the study of Thi Song Hanh Pham andMohammad Faisal Ahammad (2017); security inherits from the research of Thi
Song Hanh Pham and Mohammad Faisal Ahammad (2017), research by Ting Chi (2018), research by Shefali Jaiswal and Anurag Singh (2020) and research by Nguyen To Nhu, Nguyen To Uyen and Dang Thi Kim Ngan (2017).
- (iii) Test the influence of 3 factors in the post-purchase process on customer satisfaction when shopping online of Da Nang consumers, including: order fulfilment, customer service and ease of return, in which, all 3 factors are inherited from previous studies.
Specifically: order fullfilment inherits from the study of Thi Song Hanh Pham and Mohammad Faisal Ahammad (2017), the study of Muh Haerdiansyah Syahnur, Jafar Basalamah and Ackhriansyah Ahmad Gani (2020); customer service inherited from the study of Thi Song Hanh Pham and Mohammad Faisal Ahammad (2017), the study of Shefali Jaiswal and Anurag Singh (2020), the study of Nan Chen and Yunpeng Yang (2020); ease of return inherited from the study of Thi Song Hanh Pham and Mohammad Faisal Ahammad (2017).
With the aim of developing a holistic view of the entire online customer experience, the authors tries to avoid missing out on any elements that customers may encounter during their online shopping Therefore, in combination with the research gaps that have been explored and studied, this study applies the model of Klaus (2013) along with the definition of the online shopping experience (which is an overall set of customer experiences resulting from their interactions with resellers from e-retail sites during their shopping process from pre-purchase, purchase to post-purchase) to create a research model.
Following that orientation and on the basis of the research overview, this research paper proposes the research model and corresponding hypotheses:
1.1 Pre-purchase stage and customer satisfaction 1.1.1 Website design
The importance of aesthetics in e-commerce websites had been demonstrated by Tractinsky and Lowengart (2007) in their research paper They found that the developer of an e-commerce website must consider the aesthetics and ease of use of the website According to De Angeli, Sutcliffe and Hartmann (2006), customers will feel satisfied when they linked to a secure, intelligently designed and user-friendly website The website image should be structured by focusing on the type of product and type of customer that the website is aimed at (Wang, Minor and Wei, 2011).
According to Ahn, Ryu and Han (2007), the quality of the website's design affected the way users view the website because it is the portal through which the transaction was made Therefore, website retailers should invest in, adjust and design quality website layouts, in accordance with the needs of customers Quality, user-friendly web design had an important impact on customer experience and product repurchase intention In other words, the customer experience on websites ranged from information search to purchase and posting post-purchase experience, so it was really important to design a quality and attractive website (Wolfinbarger and Gilly, 2003).
Rose, Clark, Samouel and Hair (2012) examined and found that e-retailers that invest in quality website design will provide a better experience for their e-customers.
S McKinney (2004) proved that the aesthetic features of a website including color, graphics, layout and design were the factors that stimulate interest, purchase and satisfaction Rose et al (2012) also found evidence that site aesthetics provided sensory stimuli that support the formation of experiential impressions.
Accordingly, we propose the following hypothesis:
H1: Website design has a positive impact on customer satisfaction.
To be successful, e-commerce websites must be useful, easy to use, easy to navigate and easy to understand – measures of the Technology Acceptance Model (TAM) about Perceived usefulness and Perceived ease of use (Yi-Hsuan Lai, Hsiu- Chin Huang, Ruey-Shan Lu, Chia-Ming Chang, 2013).
Many previous studies (Mpinganjira, 2016; Freeman and Freeman, 2011;
Holloway and Beatty, 2003) had recognized the importance of website design and user interface The ease of use of a website including aspects such as navigation aids, search functionality, and overall functionality gave customers a sense of control over the online customer experience (Rose et al , 2012) According to Ahn, Ryu and Han (2007), they found that perceived ease of use included design, navigational aids, functionality, accurate and reliable information as well as reliability In the study by Rose et al (2012), they examined how ease of use affects customers' perceived control and found a strong positive relationship between them.
Jun, Yang and Kim (2004) conducted a study on online retail in general by sending questionnaires to 260 MBA students in the United States In the study, they found that ease of use was a key factor in determining online retail service quality as well as customer satisfaction The direct relationship between ease of use and online shopper satisfaction had also been demonstrated in the research of Pham and Ahmed (2017).
Accordingly, we propose the following hypothesis:
H4: Ease of use of the website has a positive impact on customer satisfaction.
Research Method and Measurement
Research method and process
The main purpose of this study is to examine the factors affecting customer satisfaction, thereby leading to online purchase intention of consumers living and working in Da Nang city This study uses the quantitative research method as the main method to research the topic Quantitative research method is to collect and analyze information based on data received from the market in Da Nang city Specifically, consumers receive online questionnaires from the authors via the Internet Likert scale system 5 (with 5 numerically coded answers: 1 = Totally agree; 2 = Agree; 3 Neutral; 4 = Disagree; 5 = Totally disagree) is the basis for creating the questionnaire.
After using SPSS software to process information through the reliability of Alpha coefficient, the study will analyze EFA factor, Pearson correlation, and finally analyze multivariate regression to give the final results for the research article.
The process of experimental studies is shown in the diagram.
3 Scale construction and designing the questionnaire 3.1 Sacle construction
With the goal of measuring the influence of factors of customer experience on customer satisfaction, the specific indicators of the scale will be based on latent variables of the dynamic model of research on online customer experience Customer satisfaction is measured through 9 other potential variables that are: website design, ease of use, information quality, brand reputation, ease of check out, security, order fulfillment, customer service, and ease of return.
Table 2 Scale construction: Website design
WD1 The design of this website is attractive to me.
Rose et al.(2012), Thirumalai and Sinha (2011)
WD2 I like this website’s colour scheme.
WD3 I feel comfortable when looking at this website.
Table 3 Scale construction: Ease of use
EOU1 This website is convenient and easy to search for a product.
Rose et al.(2012), Thirumalai and Sinha (2011)
EOU2 This website is really easy to navigate to pages I want.
EOU3 This website is user-friendly.
EOU4 This website provides a tool that enables me to compare products.
Table 4 Scale construction: Information quality
IQ1 The information provided at this website is reliable.
IQ2 The information provided at this website is easily understandable
IQ3 I can find all the detailed information of the goods I need.
The information provided at this website is complete for purchase decisions.
Table 5 Scale construction: Brand reputation
I trust when shopping online at e-commerce sites of large and reputable companies in the market.
Lin et al (2010), Ansari et al (2011)
I choose to shop online at a reputable e- commerce site that has its own brand identity, an office and staffs working in a professional process.
BR3 Brand has a great influence on purchase intention.
Renee B Kim and Yan Chao (2019)
BR4 Using/buying the website of brand having high reputation makes me happy.
3.1.5 Ease of check out (CO)
Table 6 Scale construction: Ease of check out
CO1 This website’s order placement procedure is straight forward.
CO2 This website provides order confirmation straight away.
CO3 This website’s payment procedure is straight forward.
This website has complete payment options such as post office remittance, online payment, and cash on delivery, etc.
SE1 I feel secure provide credit card information at this website.
SE2 The website has adequate security features.
SE3 I feel safe when transacting with this website.
SE4 I have not heard any problem about leaking personal information from this website.
Table 8 Scale construction: Order fulfilment
This website ensures that the products I bought will be delivered on time.
Coyle et al (1992), Stock and Lambert (2001), Davis-Sramek et al.
This website ensures that the products I bought will be delivered to the right place.
Quality delivered to me is the same as description on the website.
This website informs me about different stages of order delivery.
Table 9 Scale construction: Customer service
CS1 It is easy for me to find the number of customer service to call to ask. comScore (2014), Liu et al (2008), Hsu (2008)
CS2 The online stores sincerely solves customer’s problems.
CS3 I have received timely service from the online stores.
I can get a solution immediately from the AI/Human customer service ffter asking my question.
Table 10 Scale construction: Ease of return
RE1 I am provided with good amount of time to return an unwanted product.
RE2 This website takes me a little tỉm to get refund for an unwanted product.
RE3 The arrangement for return the product bought from this website is really convenient for me.
RE4 The location of the return policies on this website are customer friendly.
Table 11 Scale construction: Customer satisfaction
I am satisfied with the pre-purchase experience from this website (e.g., product search function, quality of information about products, product comparison on the website).
Magi (2003), Kuo et al (2009), Rose et al (2012)
I am satisfied with the purchase experience from this website (e.g., ordering, payment procedure).
I am satisfied with the post-purchase experience from this website (e.g., after sales support, returns, delivery care).
This website makes me satisfied with my overall experiences when shopping.
Table 12 Scale construction: Online purchase intention
OPI1 I intend to shop online Shu-Hsien Liao et al (2021)
OPI2 I would like to recommend my family and friends to shop via Internet.
OPI3 I will purchase other products or services at this website Hong-Youl Ha (2013)
The pilot survey was conducted by 30 respondents who were students of the University of Economics - University of Danang For the purpose of adjusting the scale and measurement variables to be suitable and easy to understand with the research object
The questionnaire has 50 questions All research questions are closed questions, which makes it easy and convenient for respondents to collect, encode, and analyze information.
The questions are divided into 3 groups, with each objective listed under the heading below:
Group 1: Introduce the survey and give an overview of the purpose of the survey.
Group 2: This group consists of 4 questions about the demographic characteristics of the respondents These questions provide a detailed view of the sample through descriptive statistical data These data are used to conduct statistical analysis on the impact of factors affecting the customer experience at all 3 different stages of the purchase journey on customer satisfaction, thereby affecting online shopping intentions in Da Nang The demographic characteristics of the study include age, gender, income, and occupation.
Group 3: Measuring the impact of factors of the customer experience at all 3 different stages of the buying journey on customer satisfaction, thereby affecting online purchase intention in Danang On the basis of reference to previous studies, the team has synthesized and made statements to measure the influence of factors of the customer experience on customer satisfaction, thereby affecting their online purchase intention This section contains 41 questions.
The structure of the questionnaire consists of 3 parts, as follows:
Part 1: Introduction to the survey Part 2: Customer information
Average monthly income Time scale
Part 3: Measuring the impact of factors of customer experience at all 3 different stages of the buying journey on customer satisfaction, thereby affecting online purchase intention in the Danang city
Part 1: Introduction to the survey The purpose of this section is to provide an overview of the purpose of the survey and the expectations of the surveyor's cooperation and commitment.
In this study, we collect the demographic characteristics of respondents for research purposes, including gender, age, occupation, and average monthly income.
Part 3: Measuring the impact of factors of the customer experience at all 3 different stages of the buying journey on customer satisfaction and thereby affecting online purchase intention in Danang.
The purpose of this section is to measure the impact of factors of the customer experience on customer satisfaction, thereby, affecting the online purchase intention of consumers in Da Nang The group first divides the surveyors into two components that have purchased and have not purchased online, thereby measuring respondents who have ever purchased online Next, the group goes through the elements of website design, ease of use of the website, quality of information, brand reputation,speed of transaction completion, security, the ability to fulfill orders, customer service,and ease of product returns Likert measures have 5 levels used to evaluate components, with 1 being completely disagree, 2 being disagree, 3 being neutral, 4 being agree, and 5 being completely agree.
The questions are presented in a reasonable manner to ensure that the respondents' requirements are met as well as to avoid confusion in the process of answering
3.4 Official research 3.4.1 Survey subjects and data collection methods
The survey respondents are consumers in the Da Nang market They can be students or work in jobs such as business, public, official, housewife, and so on that they purchased online Data collection method: through Google Forms, questionnaires will be set up and sent to respondents through means such as social networks and consumer groups such as the Da Nang online market, the Da Nang sales group association, and the online shopping association in Danang.
3.4.2 Sampling method and sample size
The sampling method has a direct effect on the accuracy of the measurements received and the conclusions drawn for the study population Theoretically, there are two main sampling methods: random sampling and non-random sampling In this study, the authors chose a non-random method based on convenience or accessibility to the respondents.
The expected sample size for the study is 450: According to Hair et al (2014), the ratio of observations to one analyte is 5:1 According to this model, there are a total of 42 indicators/observed variables, so at least 42 x 5 = 210 questionnaires need to be surveyed However, a larger sample size increases the accuracy of the PLS-SEM estimate (Raykov and Widaman, 1995) Therefore, the team decided to choose an expected sample size of 450 samples.
This study uses the Partial Least Square approach (PLS) to analyze the data.
According to Garson (2012), PLS is currently the most popular and effective approach in analyzing linear structural models including latent variables The obtained analytical results not only allow us to evaluate the reliability, discriminant and convergent validity of the scales but also estimate the standardized regression coefficients for research relationships in the model PLS can analyze complex models, with many latent variables measured by many different parameters at the same time.
With PLS, both the measurement model and the structural equation modeling are estimated at the same time, allowing to avoid skewed or unsuitable parts of the estimate Smart PLS 3.3.3 software was used for data analysis The significance level of the regression coefficients was calculated by boothstrapping with boothstrapping applied at 5,000 In addition, the mediating effects of the variables in the model are tested according to the technique proposed by Baron and Kenny (1986).
The order of conducting the group's research::
Step 1: Kiểm định mô hình đo lường
The measurement model is tested through internal consistency reliability, convergence accuracy and discriminant accuracy.
Table 14 Internally consistent reliability evaluation criteria
Step 1: Evaluate the reliability of each indicator α ≥ 0.9 Very good DeVellis
0.6 > α ≥ 0.5 Least α < 0.5 Unacceptable Step 2: Aggregate confidence level
CR > 0.9 Unexpected Hair Jr et al.
0.6 ≤ CR ≤ 0.7 Acceptable if used for exploratory research CR < 0.6 Unacceptable
The accuracy of the scales' convergence indicators is tested through the Average Variance Extract (AVE).
To evaluate the discriminant level of the indicators for the scales, our research team relies on three primary tools: comparing the square root of the extracted variance (AVE) with other correlation coefficients, factor loading multiplier (Factor Loading), cross-loading multiplier (Cross Loading), and Heterotrait-Monotrait Ratio (HTMT).
Table 15 Criteria for assessing convergence accuracy and discriminant accuracy
Compare the square root of extracted variance (AVE) with the correlation coefficient to evaluate the discriminant
The square root of extracted variance (AVE) must be greater than the correlation coefficient
The square root of extracted variance (AVE) must be less than the correlation coefficient
Factor Loading and Cross Loading
Factor Loading is > 0.5 and Factor Loading is larger than Cross Loading.
Factor Loading < 0.5 or Factor Loading less than Cross Loading
Does not reach discriminant value Heterotrait-
The HTMT value is lower than the required threshold value of HTMT which is 0.90
HTMT value is higher than the required threshold value of HTMT is 0.90 or more
Does not reach discriminant value
Step 2: Evaluate the structural model
The structural model evaluation procedure was performed in a 5-step sequence as recommended by Hair Jr et al (2016) is:
Figure 12 Structure model evaluation process Table 16 Structural model testing criteria
Threshold to evaluate the degree of multicollinearity
VIF ≥ 5 The possibility of multicollinearity is very high and the model can be severely affected
3 ≤ VIF ≤ 5 The model may encounter multicollinearity VIF < 3 The model may not experience multicollinearity Step 2: Statistical significance level and impact level of regression
The level of impact (direct, indirect, total impact) is statistically significant
Tibshirani, 1986) coefficient: Direct, indirect and total effects
The level of impact (direct, indirect, total impact) is not statistically significant
Step 3: The coefficient of determination R2
R2 > 0.26 High predictability Step 4: The coefficient of assessment of the effectiveness of the impact f2 f2 < 0.02 Ineffective impact Cohen (1988) 0.02 ≤ f2 0.5 High level of forecast accuracy
In chapter 2, the authors designed the research process and presented the research methods used in the research paper After designing the first draft scale, the group conducts a group discussion to adjust the scale Based on two methods of qualitative research and quantitative research to survey the questionnaire and test the scale, thereby giving the official scale The survey subjects, data collection methods,sampling methods and sample sizes, and data analysis methods have also been introduced in this chapter.