English
Chinese
Impact of E-commerce on Customer Satisfaction in the Chinese Online Luxury Fashion Clothing Market
Acknowledgement
Time moves fast. I would like to thank all lecturers, tutors, teachers as well as staffs in Greenwich University. Those people were helped me, taught me and guided me. This dissertation is built based on all knowledges learned during master study. Also, I would like to thank my tutor, who provided constructive suggestions and recommendation when I was confused. His advises are sincere, useful and important. With the submission of this dissertation, the master study is about to end. Thanks Greenwich University again!
Declaration
I have knowledge about the university rules on cheating, plagiarism and appropriate referencing as outlined in my handbook. I declare that the work contained in this assignment is my own.
Abstract
Nowadays, luxury fashion clothing companies must develop an effective method to take advantage of e-commerce in order to gain competitiveness and sustainability. The purpose of this research is to identify an effective approach to improve customer satisfaction toward e-commerce in China’s luxury fashion clothing segment. E-commerce refers to the conduct of business through the internet. Customer satisfaction is a statue that goods and services satisfy the expectation of consumers. Customer satisfaction is critical that motivate customer to be loyal to the company, thus affecting customer retention and customer loyalty. This research will identify the relationships between trust, information quality, logistics service, e-service quality and consumer satisfaction, respectively, basing on positivist philosophy.
Chapter two – Literature review
2.2.2 Consumer behaviour in luxury clothing industry
3.3 Deductive and inductive approach
3.6 Cross sectional time horizon
3.7 Questionnaire as data collection technique
Chapter four – Data presentation
4.4 Demographics of participants
Chapter five – Summary and conclusion
Figure 1: conceptual framework
Figure 5 The distribution of monthly income
Table 8 The criterion for pilot test
Table 9 reliability result of trust section
Table 10 reliability result of information quality
Table 11 the result of logistics service
Table 12 the result of e-service quality
Table 13 the result of consumer satisfaction
Chapter one – Introduction
1.1 Introduction
Given that the electronic commerce (e-commerce) has been fast growing and online sales has been increasingly more prevailing, companies must develop an effective method to take advantage of e-commerce in order to gain competitiveness and sustainability. E-commerce has been adopted as a regular strategy by most of industry, as it has remarkable effectiveness and consumer preference has been moving to online shopping. In China, online buyers have been continuingly increasing. They are more willing to choose online purchase due to its benefits and conveniences, such as global purchase with fast delivery service, availability of customised goods and service, instant communication with sellers (Bakos and Brynjolffsson, 2000). In China, netizen population reached 668 million in 2015 and 594 million of them employ smartphone to access the internet. 292 million netizens employ the internet payment and 205 million of them access the internet by smartphone. However, many marketers have no awareness of the variables that impact on customer satisfaction in the online shopping market.
E-commerce refers to a type of business conduct that involves information searching, information diffusion, purchase and exchanging goods and services, customer relationship maintaining in the internet (Tan and Tung, 2009). Customer satisfaction is the outcome of a customer’s experience in his or her purchasing process with a company (Anderson and Sullivan, 1993). Trust is related to customer satisfaction, which contributes to customer satisfaction (Jiradilokm et al., 2014). In e-commerce, customer satisfaction also relates to information quality, logistics service, and e-service quality. Customers desire to acquire detailed information and high quality information about products and services so that they can make wise buying decision, otherwise they lack information to make purchase decision (Oliver, 1980). Furthermore, customers expect high logistics service so that they can receive products in short term. E-service quality has relationship with customer satisfaction (Schaupp and Bélanger, 2005).
This dissertation aims at the appreciated method to enhance the effectiveness of e-commerce in China’s luxury fashion industry by identifying the relationship between e-commerce and customer satisfaction. Thus, this dissertation will critically review the existing theories of customer satisfaction and e-commerce, and then adopt quantitative method to measure the relationship between trust, information quality, logistics service, e-service quality and customer satisfaction respectively basing on positivism.
1.2 Research significance
It is imperative to measure customer satisfaction in the context of e-commerce because customer satisfaction significantly affect the performance of a company (Meuter et al., 2010). Customer satisfaction is significant in the context of e-commerce and contributes to business performance and corporate sustainability (Schaupp and Bélanger, 2005).
Furthermore, e-commerce in China is becoming increasingly more important because the population of netizens is continuingly fast rising. Meanwhile, the demand for luxury products has been continuingly rising, with the development of Chinese economy, particular in the flourishing stock market (Euromonitor, 2015). The increasing disposable income also motivate China’s consumers to purchase luxury goods and service. Although Chinese stock market collapses in the latter half of 2015, China’s luxury goods still grew to 11.5 billion yuan in 2015, however the number only reached 3.5 billion yuan in 2009 (Statista, 2016). The market of luxury goods has been booming, thus stimulating competition in the segment (Scmp, 2016). In the aspect of consumer, market volume of the online luxury shopping sector in China reached 28.5 billion yuan in 2015. The market volume growth of the online luxury market was 33.4% in China (Eurmonitor, 2015). There are remarkable growths in the market of luxury goods and that of online luxury shopping. Luxury fashion industry as a vital component of luxury goods industry is highly related to the growth in online shopping. The competition in luxury products industry also has been increasing, especially in niche luxury segment. Hence, increasing customer satisfaction has become a significant challenge for fashion luxury players against competition and business success.
Consumers and luxury product offers also concern e-commerce (Prnewswire, 2012; and Chevalier, 2012). According to Eurmonitor (2015), luxury companies raise their involvement and commitment in e-commerce, thus improving their performance. Furthermore, sufficient academic scholars support the contribution of customer satisfaction (Dawson, 2000). Customer satisfaction is essential indicator of corporate performance, because it provides behavioural and economic outcomes, which are beneficial to companies (Anderson et al., 1994). Adequate researches and studies demonstrate that the growth in customer satisfaction increases customer loyalty (Meuter et al., 2010). Basing on the improvement in customer loyalty, customer satisfaction contributes to the improvement in corporate revenues (Bakos and Brynjolfsson, 2000).
Therefore, the growing luxury goods industry and intensive competition arouse the importance of e-commence. Luxury goods providers need to involve in e-commerce (Chevalier, 2012), which is an opportunity to obtain competitive advantages and business success.
1.3 Research purpose
The purpose of this research is to identify an effective approach to improve customer satisfaction toward e-commerce in China’s luxury fashion clothing segment. In doing so, this research will identify the relationships between trust, information quality, logistics service, e-service quality and consumer satisfaction, respectively. Basing on these relationships, this research will generate an effective approach to improve customer satisfaction for luxury fashion clothing players in Chinese market.
In order to achieve the research purpose, this research have three research objectives:
1) To critically review the existing academic researches and materials in order to identify the relationship between e-commerce and customer satisfaction;
2) To identify the relationship between trust, information quality, logistics service, e-service quality and customer satisfaction; and
3) To generate an effective approach for luxury fashion players in China to improve their e-commerce practices.
1.4 Research hypothesis
Basing on the research objectives, this research has four groups of research hypotheses in order to identify the four relationships.
Hypothesis 1:
H0: there is a relationship between trust and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
H1: there is no relationship between trust and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
Hypothesis 2
H0: there is a relationship between information quality and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
H1: there is no relationship between information quality and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
Hypothesis 3
H0: there is a relationship between logistics service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
H1: there is no relationship between logistics service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
Hypothesis 4
H0: there is a relationship between e-service and customer satisfaction toward e-commerce in China’s luxury fashion industry.
H1: there is no relationship between e-service and customer satisfaction toward e-commerce in China’s luxury fashion industry.
1.5 Conceptual framework
This research will adopt the following conceptual framework, and identify the relationship between independent variables (trust, information quality, logistics quality, and logistics service) and dependent variable (customer satisfaction).
Independent variables: Dependent variable:
Chapter two – Literature review
Chapter two will critically review e-commerce in order to frame the principle and theoretical structure for the research; and it also reviews consumer behaviour, online buying behaviour, and consumer behaviour in luxury fashion industry so as to approach to customer satisfaction. Furthermore, it will explore the progress in customer satisfaction. Through introducing the benefits of customer satisfaction, this chapter will reveal the significant of studying customer satisfaction in the context of e-commerce. Meanwhile, it explores the e-satisfaction basing on offline customer satisfaction. More importantly, this chapter will build conceptual framework, which includes information quality, e-service quality, trust and logistics services.
2.1 E-commerce
E-commerce refers to the conduct of business through the internet, including the following activities: information searching, information transmission, buying and selling products and services, and customer relationship management (Adams, Nelson and Todd, 1992). E-commerce is not the way of conducting business between web retailers and web end customers, however e-commerce includes a whole scope of addressing online business including business to business, business to customers, and business to government (Erdogmus and Cıcek, 2011). Amit and Zott (2001) highlight that e-commerce provides new method to obtain profits in the dynamically, rapidly increasing competitive context.
The term e-commerce involves: electronic trading of goods and services including both physical and intangible goods; all of processes related to trade including online marketing, ordering, payment and delivery; electronic provision of services such as sales support or online legal advices; and electronic support for collaboration among companies such as online design and virtual business consultancy teams (Guda, 2005). Furthermore, e-commerce also can be perceived as the planform for business transactions by telecommunications networks, particular in the internet. E-commerce indicates the purchasing and selling of goods and services, and information through computer networks especially the internet. E-commerce is conducting business electronically. E-commerce also includes the conduct of financial transaction via electronic approaches (Hart, Doherty, and Ellis, 2000).
Moreover, there is a wide scope of e-commerce: it refers to the conduct of business on the internet, including buying and selling, and servicing consumers and cooperating with business partners; it includes customer services (e-services) and intra-business tasks; it refers to the transformation of core business process by the usage of information technologies; both intranet and extranet are important components of e-commerce. E-commerce is highly associated with macro-environment, including society, digital economy, legal and public polices, and telecommunication infrastructure and technology.
E-commerce model consists of business to consumer, business to business, business to government, consumer to government, consumer to consumer, consumer to business, government to business, government to consumer, and government to government (Ramalingam, 2008). B2C model is all transactions or businesses which directly provide goods to the end-consumers, involving no middle party. It is implemented by companies that avoid intermediates in the process of selling goods and services. The B2C model has grown to a wider scope including travel services, internet bank and internet health services and information (Mittal, 2013).
The drives of the development of e-commerce are technological factors, political factors, social factors, and economic factors in enteral environment, while there are internal factors pushing the development of e-commerce, including cost reduction, improvement in efficiency, competition, customer needs, supplier needs, organisational culture, technological equipment, management decision, resource allocation and skilled labour force (Bakos, J.Y. and Brynjolfsson, 2000).
2.2 Consumer behaviour
Wang and Lin (2009) illustrate that Chinese consumer market still remains traditional culture value to western consuming value, even though conservative culture is replacing and vanishing. A large proportion of Chinese consumers advocates saving rather than consuming (Atsmon et al., 2012). Wang et al. (2001) reveal that thrifty is regarded as the most valuable traditional Chinese culture, which despises consumer-borrowing habits (Ajzen, 1991). Meanwhile, Chinese consumers are facing the pressure from the increasing price in real estate: for most Chinese people, house purchase costs almost all dispensable incomes, thus they have less capability for luxury fashion goods (Atsmon et al., 2012). Chen and Liu (2013) reveal that house purchase and investment in real estate still are major intentions and aspirations of Chinese people to save their income.
Bantiwalu (2012) illustrates that Chinese luxury goods buyers are influenced by Western influences and likely to full accept and follow Western lifestyle and Western consumerism. Chinese consumers are more willing to buy those products with global brand, because they believe them as quality insurance and greater prestige (Liang, 2016). Furthermore, the rise of Chinese luxury clothes consumption is stimulated by the growing Chinese middle class. Thus, economic factors significantly affect Chinese luxury good consumption.
2.2.1 Online buying behaviour
Consumer behaviour has been continuingly changing, especially with the rise of globalisation and information technology. New consumer behaviour is a result of globalisation, network, and the progress in information technology (Veilgaard, 2008). The new trend, as a direction of consumer behaviour, is a process of change that can be explained by a variety of viewpoints. The trend refers to a direction or a series of events which is influenced by a certain factor and durability (Kolter, 2010). There are totally ten trends in customer behaviour: the urgency economy, non-commitment culture, eat, pray, tech, de-teching, retail as third space, creative urban renewal, worlds colliding, hy-personalisation, and outsourcing self-control (Bylok, Pabian and Tomski, 2015).
The internet is vital channel for companies to diffuse information and marketing message so as to implement direct marketing. Buyers have been rising their involvement in the internet in order to obtain buying information, while organisations across over all industries also have been rising their engagement in e-commerce (Kau, Tang, and Ghose, 2003). Consumers employ the internet because they are trusted in the internet, which can arouse their desired information. Online consumers have distinctive social and work environment comparing to those offline consumers. Chen (2010) illustrate that online buyers are more powerful, demanding and utilitarian in term of their expectations.
Along with the rise of information technology, increasingly more scholars have been rising their attention to online consumer behaviour (Bylok, Pabian and Tomski, 2005). Through the internet, consumers are able to access database that provide information about product information and marketing information. The most obvious feature of e-consumer behaviour is customisation, meanwhile companies endeavour to meet the demand of customisation (Ziemba, 2014). e-consumption involves in a virtual community that create a cooperative relationship between organisation and consumers, thus promoting consumer buying decisions (Avshalom and Arik, 2007). Bylok, Pabian and Tomki (2015) summarise those variables that motivate consumers to purchase online shops, including convenience and saving of time, ease of purchasing, cost-saving, amusement, selection of products, delivery and availability of information (Thurau and Klee, 1997).
To study online customer satisfaction, it is necessary to identify online buying behaviour. Buyer in online environment are affected by various factors including economic and technological factors, social factors, political and legislative factors, and sociological and psychological factors (Veronika, 2013). Consumers are affected by factors including trust in e-commerce, and trends of e-commerce in e-commerce environment, which consists of social media, internet auction, P2P market and online companies (Bhatnagar, Misra and Rao, 2000). In the process of online buyer decision making, consumers are affected by motives, emotions, socio-culture, lifestyle and psychologies (Koufaris, 2002). In next stage, consumers have either impulsive behaviour and rational behaviour to purchase (Rishi, 2008). In the stage of consumer buying behaviour, consumers share their experience, stories and knowledge about the purchase, products and goods in the internet across internet communities, and social media (Kim and Park, 2005).
2.2.2 Consumer behaviour in luxury clothing industry
Danziger (2004) categorises luxury goods into three forms including home luxury goods, personal luxury goods and experiential luxury goods. Luxury clothes belong to personal luxury goods, which generates an emotional satisfaction of pleasure for customers, and they engender the emotion of high standard of living. Ayupp, Ling and Tudin (2013) introduce a method to measure brand luxury through perceived conspicuousness, perceived uniqueness, perceived Extended-Self, perceived hedonism, and perceived quality. Even though consumers are not absolutely affected by these factors, they are likely to concentrate on one factor or focus on some of these factors. Many scholars agree that consumers who purchase luxury clothing industry are not absolutely with high disposable income or upper social class (Danziger, 2004 and Lowther, 2005). Consumers with high education background and knowledge are likely to purchase luxury goods (Danziger, 2004; and Stacy, 2005). Nia and Judith (2000) demonstrate that consumers who purchase luxury goods are motivated by their image, social class and status quo and they expect to be unique and distinctive in luxury clothing industry.
2.3 Customer satisfaction
In short definition, customer satisfaction is a statue that goods and services satisfy the expectation of consumers (Colman, 2015). The modern theory related to customer satisfaction can be traced to Cardozo (1965) and Howard and Sheth (1969). Campo and Yague (2009) illustrate that original studies regard customer satisfaction as phenomenon satisfaction. The more conventional and traditional models advocate customer satisfaction implicitly as an outcome of cognitive processes, however studies in the 1990s focus on the development of concept to develop an effective process for estimation and definition of customer satisfaction (Westbrook & Oliver, 1991).
Customer satisfaction refers to a measurement of performance of perceived product in relation to a customer’s expectation. The gap between customer expectation to a product and the actual quality of the product they perceived determines customer satisfaction. Therefore, the performance of a product under customer expectation will result in customer dissatisfaction. Performance of products above customer expectation will lead to high level of consumer satisfaction.
Consumer satisfaction is an approach on the basis of two different criteria: conceptual and referential criterions. Conceptual criterion illustrates that customer satisfaction is explained by forms or processes of responses created by consumers, while referential criterion indicates the aspects of a situation in which may emerge a response. However, the two criteria are not absolutely mutually exclusive and many definitions from existing studies have complementary and distinct methodologies. Recently, the studies of customer satisfaction coincide with the original researches, suggesting that expectation is the most significant factor affecting consumer satisfaction.
Companies are naturally emphasising on customer satisfaction as the general assessment of a company’s goods and services, instead of a certain individual’s assessment of a detailed transaction (Lim and Ting, 2012). Customer satisfaction is an essential and critical indicator of a company’s performance because it relates with behavioural and economic consequences, which are beneficial to the company (McKinney, Yoon, and Zahedi, 2002).
2.3.1 Benefits
Customer satisfaction is critical that motivate customer to be loyal to the company (Kotler, 2001). Customer satisfaction strongly affect customer retention and customer loyalty. Customer satisfaction promotes customer retention and customer satisfaction (Bhatnagar et al., 2000; and Shankar et al., 2003). Customers who are satisfied with products and services are likely to be loyal to the provider (Doyle, 2002). Furthermore, Riel et al. (2004) highlight that satisfied customers have various features, which are beneficial to companies, including long term loyalty, the increase in purchase, appreciated word-of-mouth, and the reduction in the attention to competitive brands and marketing activities. In addition, maintaining a loyal customer is much more cost effective than gaining a new customer, while the company needs to satisfy customers’ needs and wants, and also meet customers’ expectation (Bowman and Ambrosini, 2000). Adequate evidences suggest that customer satisfaction positively affects customer loyalty (Jiradilok et al., 2014). In general, customer trust and customer satisfaction positively affect customer loyalty. Maintaining customer satisfaction is the most effective competitive advantages against competitors. Customers are loyal and willing to afford premium for those product which make them satisfaction (Gupta et al., 2003). There is an interrelationship among customer satisfaction, customer trust and customer loyalty (Giese and Cote, 2000).
Customer satisfaction enables companies to ensure future revenues, reduce the costs of transactions, decrease price elasticities and reduce the likelihood customers perceive quality falters (Guo, Ling and Liu, 2012). Improvement in customer satisfaction cuts down the costs related to defective products, including warranty costs, field service, reworking/ replacing, and managing complaints (Santouridis and Trivellas, 2010).
Moreover, word of mouth from satisfied customers effectively attracts new customers and thus improves corporate reputation, meanwhile unsatisfied consumers will naturally spread negative information about the products and brand, thus damaging brand image and reputation (Tam, 2004). Superior quality leads to greater economic returns (Westbrook and Oliver, 1991). Eid (2011) illustrates that e-customer satisfaction strongly positively affect customer loyalty, but consumer trust also has impact on the customer loyalty. Subramanian et al. (2014) highlight that consumer satisfaction in e-commerce improve repetitive purchase, positive word of mouth and the increase in profits.
2.3.2 E-satisfaction
Consumers are concerned with products and services offered by the specific website because satisfied customers tend to be loyal and repetitively buy, consequentially promoting the profitability of that specific e-commerce company (Chodzaza and Gombachika, 2013). E-satisfaction is highly related to e-commerce, which assists to establish customer trust, improve favourable word of mouth, bring repeat purchase, and forecast buying behaviour. There are four proposed dimensions of online shopping quality, involving website quality, e-service quality, trust and personalisation, which all have distinctive impact on e-satisfaction. In online customer relationship, trust is regarded as the most vital and critical factors of online shopping quality, and has the most significant impact on customer perception of e-commerce quality (Meuter et al., 2010).
Singh (2002) highlights the significance of e-services particular in B2C e-commerce business. E-service contributes to customer relationship, thus positively affecting sales performance. Singh (2002) finds that e-service plays an important role in customer satisfaction and summaries that e-service composes online payment system, high transparent and efficient e-transaction record and trust. One of the critical variables affects B2C e-commerce is information quality. Customers expect more and more specific and critically true information relates products and services in websites and even social media, thus information quality is significant in customer satisfaction. Gefen and Straub (2003) illustrated that customer trust is one of the significant variables determining customer satisfaction. In another perspective, trust refers to a customer who has transaction with a company, meanwhile he or she expects to achieve his or her expectations and will generate dissatisfied emotions and feelings about any fraudulent and undesirable terms (Anderson, 1994).
There is a significant variant of customer satisfaction between online and offline purchase (Shankar et al., 2003). Online customer satisfaction has stronger capability to push customer loyalty than offline customer satisfaction. Zhang et al. (2006) illustrate that perceived service quality and security significantly affect e-commerce satisfaction, and that the security is determined by the website and customers’ feelings and experience. Lin (2007) highlights that website quality including design and information offered is important and predominant for customer satisfaction in e-commerce, meanwhile security settings of websites and social media enables companies to obtain trust from consumers. Anderson and Srinivasan, (2003) demonstrate five factors that positively affect customer satisfaction on e-commerce, including website design, service offered to buyers, information quality, and website intelligence and security. Bagdoniene and Jakstaite (2007) highlight that information quality on e-commerce, e-commerce satisfaction and e-commerce trust significantly affects e-commerce satisfaction basing on global level research toward the sale of e-commerce.
2.4 Conceptual framework
This conceptual framework consists of trust, information quality, logistics service, and e-service quality.
A) Trust
Trust refers to the willingness to endure risks in any forms of relationship, basing on the positive expectation (Mayer et al., 1995). Dina et al (2004) illustrate that buyers and sellers are unable to implement face-to-face interactions in online business environment so that trust becomes a critical factor. Geykens et al. (1996) illustrate that trust refers to the belief or expectation of a buyer, which the sellers will fulfil their promises and not damage the interests of consumers in the future, in business field. Fuentes-Blasco et al. (2010) explain that customer satisfaction acts critical role in corporate performance, because it improves customer trust. Geysken et al. (1996) illustrate that customer satisfaction associates with interpersonal trust. It seems that customer satisfaction is the pre-condition to build trust (Sonja et al., 2008). Dina et al. (2004) underline that customer satisfaction has a positive impact on trust in e-commerce, while customers also need to trust an online retailer before purchase. Pavlou (2003) finds that there is interrelationship between trust and customer satisfaction, because customers always choose to purchase from the online retailer who they trust and customer satisfaction will reinforce the trust. Liu et al. (2008) illustrate that customer satisfaction is the outcome of a customer’s experiences in his or her purchasing process. In customer’ experience, trust plays an important role. Meanwhile, Gefen and Straub (2004) also agree that trust is the first step to start a relationship in the internet, and consumers are afraid of online frauds. It is important for online retailers to build trustworthy brand image by providing sufficient information, and purchase and return policy, securing and protecting the interest of buyers and developing safe online payment process.
All above evidences suggest that trust is a critical factor that relate to customer satisfaction, and it is the first step to build a relationship in the internet. In return, customer satisfaction also enhances trust.
B) Information quality
Sufficient researches investigate the relationship between information quality and customer satisfaction (Aladwani and Palvia, 2002). Taylor (1986) illustrates that information quality refers to valuable information, which are concerned by people. Hilligoss and Rieh (2008) reveal that individual needs are predominant, and that information quality is users’ subjective evaluation of goodness and usefulness of information. Wang and Strong (1996) define that information quality is fitness for use, meaning that quality relies on the fitness of the information to a certain use or an evaluation of value. Eppler (2006) perceives information quality as the degree to which the information satisfies the expectations of the user, and the degree to which the information satisfies the requirements of the certain activity which the user is involved. Information quality is the main factor in the study of information service and it has a significant relationship with customer satisfaction (Delone and McLean, 2002). A website needs to have a clear, useful and accurate approach to provide information in order to form great consumer attitudes and intentions. In online environment, information quality means consumers’ evaluation of the online products or e-services’ information (Kim et al., 2005). Furthermore, Kim et al. (2005) illustrates that online retailers should be aware of information dimensions including accuracy, format, and completeness. McKinney et al. (2002) explain online information quality as online buyers’ perception of the information quality on a website. Guo et al. (2012) highlight that online information quality is the useful information about the features of a product to assist buyers to assess the product. Mai (2013) points out that there is no universal criterion of online information quality. Many scholars support that online information quality has been becoming increasingly more important (Metzger, 2007).
C) Logistics service
Mentzer et al., (1989) observes that in B2C ecommerce, there are three essential dimensions including availability of products, delivery time, and delivery quality, and online retailers assess the three dimensions to measure the physical distribution service quality. Emerson and Grimm, (1996) illustrate that communication is the fourth dimension to highlight the significance of order status information in improvement in service quality. Xing and Grant (2006) and Xing et al. (2011) conclude e-PDSQ measurement, which examines availability, timeliness, condition and return.
Sufficient researches on logistics service emphasises the relationship between logistics service quality and customer satisfaction (Mentzer et al., 2001; Stank et al., 2003; Saura et al., 2008; Bienstock and Royne, 2010). There is a positive effect of logistics service quality on customer satisfaction (Mentzer et al., 2001). Furthermore, Mentzer et al., (2001) recommend that online retailers should customise their logistics services in order to satisfy various requirements of various customer segments. Saura et al. (2008) observes that logistics service quality has four dimensions including timeliness, personnel, information, and order quality, and it directly, strongly, positively and significantly affect customer satisfaction. Stank et al., (2003) prove that customer satisfaction resulted from logistics service significantly and positively affects customer loyalty and market. Bienstock and Royne (2010) demonstrate that industrial customers perceive logistics service quality as the vital factor pushing their satisfaction in the ecommerce. Bode et al. (2011) observe that personal contact quality positively affects customer satisfaction and buying behaviour. Sauar et al. (2008) prove that there is positive relationship between customer satisfaction resulted from logistics services and customer loyalty, and the logistics services are improved by the implementation of information and communication technology, however Bouzaabia et al. (2013) suggest that various dimensions including operational and relational dimensions of logistics service quality have distinct effects on customer satisfaction and customer loyalty in various countries.
D) E-service quality
Abundant researches investigates on the relationship between service quality and customer satisfaction as well as customer loyalty (Zeithaml et al., 1996; Olorunniwo et al., 2006; Kitapci et al., 2013). Parasuraman et al., (1988) argue that the delivery of high service quality improves brand image and business performance in service encounters. Perceived service quality positively affects customer satisfaction, or it is perceived as the pre-condition of customer satisfaction (Lee et al., 2000; Tam, 2004; Pan et al., 2010). Furthermore, many researches elaborate that customer satisfaction has direct or indirect relationship with customer loyalty, and it leads to a series of customers’ beneficial behaviours: repurchase intention, and positive word of mouth (Zeithaml et al., 1996; Cronin et al., 2000; Ladhari, 2009). Positive behaviour contributes to the growth of profits (Zeithaml, 2000). Service quality also is related to customer loyalty and retention (Imrie et al., 2000). Customer satisfaction however has less effect on customer loyalty in retail sector (Sivadas and Baker-Prewitt, 2000). Sivadas and Baker-Prewitt (2000) illustrate that customer loyalty can be improved by cultivating preferable attitude and motivating customers to recommend online shop to others.
In the context of ecommerce, some determinants of service quality, such as cleanness, are not applicable (Cox and Dale, 2001), therefore it is necessary to further identify the determinants of service quality for online environment. Many scholars have studied service quality and some of them concentrated on customer online experiences (Santos, 2003) and logistics experience (Mentzer et al., 1989). Collier and Bienstock (2006) observe that a few of researches integrate two aspects into service-quality framework. Service quality should be divided into e-service quality and logistics service quality to identify the complicated nature of the interaction in the online environment (Lee and Lin, 2005).
Figure 1: conceptual framework
Chapter three – Methodology
3.1 Research onion
Saunders, Lewis, and Thorhill (2009) propose a research onion that summarises all available research methods for business research. This research will adopt positivism philosophy, deductive approaches, survey, mono-method, cross-sectional time horizons, and questionnaires as date collection techniques and procedures.
Source from: (Saunders, Lewis, and Thorhill, 2009)
3.2 Research philosophy
Positivism refers to a type of research philosophy that adopt a scientific approach to answer research questions and research hypothesises. According to positivism philosophy, researchers comply with natural scientific perspective to employ observable social realities to generate and exploit new findings Tashakkori and Teddlie, 1998). Due to its scientific perspective, these findings are law-like universalisations (Robson, 2002). The requirement of adopting positivism is the capability to gather credible data. In order to form a research strategy, researchers collect previous theories and research findings to build theoretical framework and then collect quantitative to test research hypothesis, in positivist researches. Basing on the result of hypothesis test, researchers will identify new theories and generate new knowledge. More importantly, researchers avoid to involve personal feeling and subjectivism during the implementation and analysis of the research. It means that researchers are unable to influence their research, and in return research has no impact on them, because researchers are independent from the research. Especially for data collection, researchers have no relationship with data collection, which ensure the reliability of data thus contributing to the accuracy of research result and the validity of findings. Positivist researchers employ a set of well-established and close methodologies to investigate research hypothesis, and the data collected by the research can be tested by other scholars, and also by further researches (Patton, 2002). Positivist research generally employs quantifiable observations, which can be analysed by statistical analysis in fast manner. Even though positivist research requires a large amount of time to build research methodologies, the result can be analysed shortly.
On the other hand, interpretive philosophy is on the oppose side of positivist philosophy. Interpretivsm highlights that it is significant for scholars and researchers to perceive and consider variants in human role as social actors, through feelings and subjectivism. Instead of using scientific approach to explore knowledge, interpretivsm exploits experience and human behaviour and the way of research targets to experience, reflect, involve sensory perception, imagination, action, preference, mind, behaviour, emotion, and feelings (Westfall, 1997). Interpretivist philosophy criticises that business and management are so distinctive and diverse that scientific methods are insufficient to exploit and identify human issues, and positivism may ignore important variables, leading to unappreciated observation and evaluation of human behaviour (Zahayi, 2003). Interpretivist philosophy requires researchers to adopt their feelings and subjectivism to interpret and explain a real life phenomenon. Given that it adopts a more loosen research structure, it is more likely to fully identify research variables than positivist philosophy. Positivism builds well-structured methodologies for research basing on existing theories and findings before data collection, however the structure may constrict researchers to realise new variables (Saunders and Lewis, 2012). However, positivist researchers judge that interpretivist researches are so dependent on feeling and subjectivism that endanger the validity and reliability of research result. Furthermore, interpretivist researches are more easily to incur criticism and question than positivist research, and the findings of interpretivist researches are arguable basing on each researcher’s subjectivism and feelings. By contrast, positivist research is far more objective that adopt quantitative data and analysis, which is more convincible and persuasive. However, Creswell (2007) argues that empiricism and objectivism from positivism are unsuitable to explore social phenomenon and human behaviour, because they are unable to engage in social and natural science research. Thus, the result of positivist research is likely to miss important variables. Creswell (2007) also criticises that empiricism and objectivism damages the accuracy of data, because of unreliable questionnaires, inauthentic answers, and unsuitable research design (Haworth, 1984).
There is no perfect research philosophy, however sufficient researches that involve in e-commerce and consumer behaviour employ positivism, survey and questionnaires (Riel et al., 2004; Lordorfos et al., 2006; Chang et al., 2009and Zhang et al., 2015). More importantly, about 96 per cent of American journals implement positivism as research philosophy, and only less than 4 per cent of American journals are consistent with interpretivist research philosophy and adopt interviews and other qualitative data collection tools. Positivist philosophy enables inquirers to collect a large amount of information from a large amount of participants, which significantly improves repetitiveness of data, to identify research hypothesis and address research question (Orlikowshi and Baroudi, 1991). Benbaset et al. (1987) support that all research philosophies and research methods have intrinsic flaws and researches should choose suitable philosophy and research methods basing on the feature of their researches. This research will adopt positivism so that reduces the negative impact of subjectivism to study the impact of e-commerce and consumer satisfaction.
3.3 Deductive and inductive approach
Deduction approach refer the method that examines existing theories and adopts existing theories to explain a phenomenon. Deduction approach starts with collection of existing theories, then following hypothesis, observation, discussion, and confirmation. Academic scholars review theories and assumptions and then reduce the scope of topic to a specific topic, meanwhile they categorise a whole research topic into a few of hypotheses and explore the research topic by identifying them respectively. However, inductive approach adopts observation for a specific research topic, and then generate universal theories, through observation, pattern, tentative, hypothesis, and theory (Collis and Hussey, 2003).
On the other hand, deductive approach implements quantitative approach to collect data, and then identifies the relationship between independent variables and dependent variables. Saunders and Lewis, (2012) highlight that deductive approach is straightforward to identify research questions and time-saving. In inductive approach, scholars deal with phenomenon to seek new theories and knowledge. Even though the phenomenon is real and the inductive approach is effective and valid, the findings are not necessarily right and universal (Collis and Hussey, 2003). The validity of findings resulted from inductive approach is dependent on persuasive and reliable evidences from a variety of surveys and investigations. A single inductive research is incapable to generate convincible and undoubtable result.
This research will adopt deductive approach to collect data for the impact of e-commerce on customer satisfaction in China, however there are scholars who point out the flaws of deductive approach. Collis and Hussey (2003) illustrate that deductive researches may adopt old theories to analyse current or new phenomenon, however these theories may be unappreciated and unsuitable for the contemporary phenomenon. Deductive approach employs current theories and principles to interpret a phenomenon (Collis and Hussey, 2003). In nature, this research will exploit new theories through identifying research hypotheses. Meanwhile, this research also adopts many previous theories, which may not be consistent with contemporary issues. Hence, this research will gather the latest knowledge and theories to identify these hypothesises so as to avoid the flaws of deductive approach. Furthermore, it is reasonable to adopt deductive approach. The purpose of this research is to seek and assess the effect of e-commerce on customer satisfaction in China’s luxury fashion industry. Deductive research is suitable for the pattern of this research. Unlike inductive approach, deductive approach secures the accuracy of research result as long as there are suitable theories, proper research methodologies, and effective sample and sufficient data size.
3.4 Survey
Survey refers to a rigorously structured framework that clarifies sampling techniques and data collection methods, which ensures a systematic research (Heron, 1996). Johnson and Clark (2006) highlight that survey research gathers data through standardised process and method, thus preventing inquirers’ subjectivity. Johnson and Clark (2006) highlight that the design of survey research is fixed and invariable as survey research is highly routinized.
Survey is consistent with positivist research, because it allows researchers to adopt subjective methods to collect data. Inquirers can extract their feelings and personal bias in research process by an exclusive framework of research methodologies. Robson (2002) highlights that scientific and objective methodologies constitute a survey. Survey also includes qualitative research strategy, such as interview, while quantitative research assembles and measures numerical data, which can be assessed by statistic package. To be noticed, the techniques of quantitative data could be so complex that cause errors (Robson, 2002).
This research will adopt survey as data collection technique to collect a large amount of information from a large amount of participants in short term. Survey assists researchers to gather representative data and adequate sample size in limited time (Creswell, 2007). Creswell (2007) highlights that quantitative research develops convincible findings, and it is hard for other scholars to overthrow it, whereas the findings from qualitative research are likely to suffer debate. Even though this research will engender some limitations due to quantitative research, further research can cover these limitations. More importantly, they can adopt this research’s data to implement further investigation through statistic package (Creswell, 2007).
3.5 Mono-method
This research will adopt mono-method to collect and analyse data to identify the relationship between e-commerce and customer satisfaction, and it will only employ questionnaires, one of quantitative method to collect information. Meanwhile, the data will be analysed in numerical manner by statistical software package. Hence, this research will closely comply with positivist philosophy.
3.6 Cross sectional time horizon
This research will adopt cross sectional time horizon, which means that it will only collect data in one-time period. Given that this research will collect primary data to identify the relationship and it has time limitation, it is unable to implement longitudinal time horizon. Longitudinal time horizon means that inquirers assemble or employ data in different time period, which requires to adopt historical data and design a research has a long range of time. However, this research only focuses on current China’s luxury fashion clothing industry, and involves on comparison of its historical performance and its current performance. Hence, it is unnecessary to implement longitudinal time horizon.
3.7 Questionnaire as data collection technique
Questionnaires collects data via a set of questions, which has strong capability to represent a research population given that it can collect a large amount of information from a large amount of population in short term. With large sample size, the research will be more representative, and thus it can indicate more accurate features of the research population (Collis and Hussey, 2003). Heron (1996) suggests that researchers have to design suitable questions in order to collect reliable data and prevent the stimulation of participants’ resistance and negative emotions and feelings. Questionnaires allows inquirers to spend less time to collect a large scale of information, which is much faster and far more economical than interviews. However, Johnson and Clark (2006) highlights that the data collected from questionnaires is not absolutely reliable: even though the questionnaires are effective and reliable, participants may irresponsibly fill those questions, be unable to understand the question, and have inadequate information. Even worse, researchers are unable to explain questionnaires for participants in most circumstances, especially in the internet questionnaires. Meanwhile, researchers also cannot observe the response of participants and perceive their emotion.
On the other hand, interviews is consistent with both qualitative and quantitative techniques. Interviews collects data through the conservation between interviewers and respondents. Interviews enable inquirers to explain questions to participants and then ask further questions basing on interviewees’ responses (Healey and Rawlinson, 1993). Through interviews, inquirers can observe interviewees’ expression and emotion during they are addressing those questions. However, interviews needs specific questioning skills and communication techniques, and also it costs a large amount of time to gather information. In general, interviews is used as a subjective method to collect information, while it involves inquirers’ personal bias and feelings, which could damage the reliability of data. Interviews as an qualitative technique is related to interpretivist philosophy, so it has no complicated structure. Nevertheless, Tashakkori and Teddlie (1998) argue that the main risk of adopting interviews is that inquirers are unable to identify or realise the negative impact of their subjectivity on data collection.
This research will follow positivist philosophy so that it is unsuitable to adopt interviews to collect qualitative data. More importantly, this research needs a time-constricted survey, whereas interviews is time-costly. Furthermore, questionnaires require no skills to spread and implement but it only depends on the precise design. However, the effectiveness of interviews relies on conservation skills and communication techniques. This research is carried by one student and one tutor, so it has insufficient labour to employ interviews. Moreover, China, as the research’s location, has large tertiary, so it is impossible for one research to collect data from a wide range of Chinese cities in short time. However, through the internet, questionnaires can be spread in fast manner, which is not constricted by time and location.
3.9 Data analysis technique
Many reliable researches use regression analysis and correlation analysis to study on e-commerce and customer behaviour (Riel et al, 2004; Chang et al., 2009; Lordorfos et al., 2006; and Zhang et al., 2015). It proves that the two data analysis techniques are effective and suitable to address this research’s topic. According to Neuman (2005), correlation analysis mainly is used to measure the strength of the relationship among variables, and regression analysis is adopted to measure the significance of the relationship between independent variables and dependent variable. Both correlation analysis and regression analysis conform to positivist research (Ackroyd and Hughes, 1992).
3.8 Self-selection sampling
Self-selection sampling will be used in this research for data collection, Cooper (2002) illustrates that sampling method can be categorised into probability and non-probability. Probability sampling is typically associated with survey -based research, which researchers must make inference for research population to address research question and accomplish research objectives. Probability sampling requires researchers to build a sampling frame (Guest, Bunce, and Johnson, 2006). Inquirers must establish a sampling frame through reviewing existing database and then assemble data via the sampling frame. However, Hewson et al. (2003) reveal that existing database have flaws and problems: individual databases are incomplete; the information in databases is not invalid; and the information may be out of date. Primary data is much more reliable if there is no suitable database for China’s luxury fashion clothing industry. After research, the suitable database is not existing, and thus probability sampling method is not appreciated in this research.
In general, business researches and markets are unable to establish a sampling frame, whereas non-probability sampling also provides an alternative technique to collect samples in term to researchers’ subjective judgement (Patton, 2002). Sanders and Lewis (2012) conclude all forms of sampling techniques, including quota, snowball, self-selection, convenience and purposive sampling techniques. Stutely (2003) highlighs that quota sampling coincides with interview surveys. Purposive sampling whereas appears with case study to address small samples and special case. This research adopts survey to collect a large amount of information so that it is unsuitable to adopt purposive sampling method.
Self-selection sampling is the most suitable sampling approach for this research. Self-selection sampling enables researchers to collect a large amount of data, because all people are welcomed to engage in the research (Miller, Le Breton-Miller and Scholnick, 2008). Furthermore, participants are voluntarily involving in surveys so that they are likely to be more willing to fulfil questionnaires respectively. Inquirers can dismiss questionnaires via a variety of approaches, because the autonomy of self-selection sampling is high enough (Kervin, 1999).
Neuman (2015) however criticises that self-selection sampling technique has low capability to represent research population. The intrinsic weakness of self-selection sampling is unavoidable; however, this research can enlarge the sample size in order to minimise the weakness and increase repetitiveness. Self-selection sampling is much more convenient and easier to implement than any one of probability sampling techniques (Ackroyd and Hughes, 1992). This research can use self-selection sampling technique to cover the large China’s tertiary.
Chapter four – Data presentation
The data collection part will present data for correlation analysis and regression analysis, and also examine demographics of participants through frequent analysis. Furthermore, this research will adopt reliability test to ensure the validate of the research result.
4.1 Correlation analysis
Creswell (2007) proposes a criterion to identify the strength of correlation.
|
Correlation Coefficient |
Strength of Correlation |
|
1.00 |
Perfect |
|
0.70 - 0.99 |
Strong |
|
0.40 - 0.699 |
Moderate |
|
0.1 - 0.399 |
Weak |
|
0 – 0.99 |
No relationship |
(Source from: Creswell, 2007)
Hypothesis 1:
H0: there is a relationship between trust and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
H1: there is no relationship between trust and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
According to the table 1, the value of correlation is 0.838, thus there is a strong relationship between trust and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry. Basing on the data, it is obvious that H0 is accepted but H1 is rejected.
|
Correlations between trust and customer satisfaction |
|||
|
|
|
Trust |
Customer Satisfaction |
|
Trust |
Pearson Correlation |
1 |
0.838** |
|
Sig. (2-tailed) |
|
0.000 |
|
|
N |
406 |
406 |
|
|
Customer Satisfaction |
Pearson Correlation |
0.838** |
1 |
|
Sig. (2-tailed) |
0.000 |
|
|
|
N |
406 |
406 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
Hypothesis 2
H0: there is a relationship between information quality and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
H1: there is no relationship between information quality and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
As table 2 shows, the result of correlation is 0.907, suggesting that there is a strong relationship between information quality and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry. Therefore, it is reasonable to accept H0 and reject H1.
|
Correlations between information quality and customer satisfaction |
|||
|
|
|
Information quality |
Customer satisfaction |
|
Information quality |
Pearson Correlation |
1 |
0.907** |
|
Sig. (2-tailed) |
|
0.000 |
|
|
N |
406 |
406 |
|
|
Customer Satisfaction |
Pearson Correlation |
0.907** |
1 |
|
Sig. (2-tailed) |
0.000 |
|
|
|
N |
406 |
406 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
Hypothesis 3
H0: there is a relationship between logistics service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
H1: there is no relationship between logistics service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
As table 3 shows, the value of correlation analysis reaches 0.761, thus there is a relationship between logistics service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry. Hence, H0 is accept while H1 is rejected.
|
Correlations between logistics service and customer satisfaction |
|||
|
|
|
Logistics service |
Customer Satisfaction |
|
Logistics service |
Pearson Correlation |
1 |
0.761** |
|
Sig. (2-tailed) |
|
0.000 |
|
|
N |
406 |
406 |
|
|
Customer Satisfaction |
Pearson Correlation |
0.761** |
1 |
|
Sig. (2-tailed) |
0.000 |
|
|
|
N |
406 |
406 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
Hypothesis 4
H0: there is a relationship between e-service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
H1: there is no relationship between e-service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
Table 4 shows that the strength of the relationship is 0.897, proving that there is a strong relationship between e-service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry. Hence, H0 is accept while H1 is rejected.
|
Correlations between e-service and customer satisfaction |
|||
|
|
|
E-service Quality |
Customer Satisfaction |
|
E-service Quality |
Pearson Correlation |
1 |
0.897** |
|
Sig. (2-tailed) |
|
0.000 |
|
|
N |
406 |
406 |
|
|
Customer Satisfaction |
Pearson Correlation |
0.897** |
1 |
|
Sig. (2-tailed) |
0.000 |
|
|
|
N |
406 |
406 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
4.2 Regression analysis
As the table 5 shows, the R reaches 0.949, which suggests that there is a positive and strong relationship between independent variables and dependent variables.
|
Model Summary |
||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
0.949a |
0.901 |
0.900 |
0.34559 |
|
a. Predictors: (Constant), E-service quality, Logistics service, Trust, Information quality |
||||
|
ANOVAb |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
436.533 |
4 |
109.133 |
913.758 |
0.000a |
|
Residual |
47.893 |
401 |
0.119 |
|
|
|
|
Total |
484.425 |
405 |
|
|
|
|
|
a. Predictors: (Constant), E-service quality, logistics service, Trust, Information quality |
||||||
|
b. Dependent Variable: Customer satisfaction |
||||||
According to table 7, the result of logistics service is 0.585, which is larger than 0.05. Hence, the relationship between logistics service and customer satisfaction is insignificant. Meanwhile, other variables including trust, information quality, logistics service, and e-service quality have own values of Sig. which are all below 0.05. Hence, it is safe to conclude that trust, information quality, and e-service quality can significantly affect customer satisfaction toward e-commerce in China’s luxury fashion clothing industry
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
0.075 |
0.056 |
|
1.334 |
0.183 |
|
Trust |
0.605 |
0.042 |
0.588 |
14.543 |
0.000 |
|
|
Information quality |
0.238 |
0.046 |
0.246 |
5.223 |
0.000 |
|
|
Logistics service |
0.014 |
0.025 |
0.015 |
0.546 |
0.585 |
|
|
E-service quality |
0.128 |
0.044 |
0.129 |
2.894 |
0.004 |
|
|
a. Dependent Variable: Customer Satisfaction |
||||||
4.3 Reliable test
This research has a reliability test that investigates 30 participants in order to identify the reliability of the questionnaire. Creswell (2007) develops a criterion to assess the reliability of questionnaire for pilot test, as table 8 shows.
Table 8 The criterion for pilot test
|
Above 0.90 |
Absolutely reliable |
|
0.80 – 0.89 |
Excellent |
|
0.70 – 0.79 |
Acceptable |
|
0.60 – 0.69 |
Arguable |
|
0.50 – 0.59 |
Poor reliability |
|
Less than 0.50 |
Not reliable |
(Source from: Creswell, 2007)
Group: Trust
Table 9 reliability result of trust section
|
Reliability Statistics |
|
|
Cronbach's Alpha |
N of Items |
|
0.801 |
5 |
The result of trust group reliability test is 0.801, suggesting that the reliability of trust group is excellent.
Group: Information Quality
Table 10 reliability result of information quality
|
Reliability Statistics |
|
|
Cronbach's Alpha |
N of Items |
|
0.774 |
4 |
Although the result of information quality is 0.774, this group still is acceptable to develop further analysis. Thence, the data from this group of questions are reliable.
Group: Logistics service
Table 11 the result of logistics service
|
Reliability Statistics |
|
|
Cronbach's Alpha |
N of Items |
|
0.701 |
3 |
As table 11 shows, the result of logistics service reaches 0.701, in the range of acceptable reliability, suggesting that this group of questions is reliable.
Group: E-service quality
Table 12 the result of e-service quality
|
Reliability Statistics |
|
|
Cronbach's Alpha |
N of Items |
|
0.712 |
4 |
Tables 12 shows that the result is 0.712, which also positions in the range of acceptable level, thus this group of questions is reliable to collect data.
Group: Consumer satisfaction
Table 13 the result of consumer satisfaction
|
Reliability Statistics |
|
|
Cronbach's Alpha |
N of Items |
|
0.812 |
4 |
As table 13 shows, the result of consumer satisfaction reaches 0.812 in the range of acceptable reliability. Hence, these questions are reliable.
All above results show that these questions are reliable, thus this questionnaire can be used to collect information. The results of correlation analysis and regression analysis are reliable, because they originate from reliable data.
4.4 Demographics of participants
There are totally 406 participants who filled the questionnaire and met the requirement of being a qualified participant. This research will analyse demographics by frequency analysis in order to check deviation in demographics of participants.
4.4.1 Gender
As figure 3 shows, the distribution of gender is basically normal, even though male participants are larger about 10 per cent than female participants. The imbalance in gender distribution in this survey can be explained by that in Chinese population. In Chinese population, male population is larger than female population. Hence, this gender distribution still is qualified to reflect the consumer satisfaction. The deviation is acceptable and the result is reliable.
|
Gender |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
Male |
223 |
54.9 |
54.9 |
54.9 |
|
Female |
183 |
45.1 |
45.1 |
100.0 |
|
|
Total |
406 |
100.0 |
100.0 |
|
|
4.4.2 Age
According to figure 4, it finds that the age distribution is basic equilibrium, although the participants whose age is older than 50 years are far smaller than any one of other groups. It can be explained by that young and middle age population are more likely to purchase luxury fashion clothes than elder buyers. Furthermore, this survey is implemented via the internet, and elder people have less involvement in the internet and online questionnaire than younger age group. Young and middle age people are more sensitive to the internet than elder people.
4.4.3 Income distribution
Figure 5 shows the distribution of monthly income, and it finds that most of participants has 30,000 to 40,000 Yuan monthly income. This research targets at luxury segment, so it filtrates those participants who purchase no luxury fashion clothing and also those participants who cannot afford luxury goods. Through this way, the data analysed are from those participants who have capability to purchase luxury goods. Those participants are significant for this research.
Figure 5 The distribution of monthly income
Overall, above analysis finds no significant deviation that damage the reliability of this research. Even though there are some imbalances, they are less important. Therefore, this research is able to identify the relationship between e-commerce and customer satisfaction in China’s luxury fashion clothing industry.
Chapter five – Summary and conclusion
5.1 Summary of finding
|
Hypothesis |
Finding |
Correlation analysis |
Regression analysis |
|
Hypothesis 1 H0: there is a relationship between trust and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry. |
Accepted |
0.838 Strong
|
0.000 Significant |
|
Hypothesis 2 H0: there is a relationship between information quality and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry. |
Accepted |
0.907 Strong
|
0.000 Significant |
|
Hypothesis 3 H0: there is a relationship between logistics service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry. |
Accepted |
0.761 Strong
|
0.585 Significant |
|
Hypothesis 4 H0: there is a relationship between e-service and customer satisfaction toward e-commerce in China’s luxury fashion industry. |
Accepted |
0.897 Strong
|
0.004 Significant |
There are significant relationships between trust, information quality, logistics service, e-service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
5.2 Discussion
The discussion will evaluate the academic theories with primary data in relation to research objectives.
1) To critically review the existing academic researches and materials in order to identify the relationship between e-commerce and customer satisfaction
Many researchers prove that customer satisfaction plays an important role in e-commerce (Shankar et al., 2003; Meuter et al., 2010; and Chodzaza and Gombachika, 2013). Sufficient researches prove that there are relationships between trust, information quality, logistics service, e-service quality and customer satisfaction toward e-commerce (Fuentes-Blasco et al., 2010; Gefen and Straub, 2004; Mai, 2013; Bienstock and Royne, 2010; and Imrie et al., 2000). However, these factors affect customer satisfaction in different manners. Information quality, logistics service and e-service quality are developed from SERVQUAL (Parasuraman, Zeithaml, and Berry, 1988). It suggests that customer satisfaction is the result of the gap between perceived quality and expected quality. However, many variables are existing in the internet environment, thus it is necessary to seek new criteria basing on customers’ expectation. Many researchers find that customer needs sufficient information to make buying decision, given that they cannot actually touch the products which sell online. Thus, it is reasonable that consumers need and desire high information quality. If some information about product misleads customers, their buying decisions cost money and time for delivery so that they are likely to be satisfied with the online retailer. Hence, it is important for online retailers to provide detailed information. Furthermore, customers expect to safe and fast delivery service, which ensures and secures their goods. It is understandable that customers are willing to accept a broken product or wait for long time. Additionally, customers also expect to have excellent service in the internet. For example, they expect to easily access to website, to easily operate the site, to enjoy efficient navigation, and to easily contact dealers. Hence, online retailers need to have a great website design that offers great services. More importantly, there is an interrelationship between trust and customer satisfaction in the context of ecommerce. Because consumers have scruple during online purchase, trustworthy image motivates them to purchase. Trust is the beginning of online relationship, and customer satisfaction will enhance the trust in return. Basing on previous studies, trust arouses an online purchase intention, and it can be enhanced by customer satisfaction, which results from great perceived quality including information quality, logistics service and e-service quality.
2) To identify the relationship between trust, information quality, logistics service, e-service quality and customer satisfaction
Basing on the research result, all those independent variables have strong effects on customer satisfaction in China’s luxury fashion clothing industry. It means that Chinese buyers value trust, information quality, logistics service, and e-service quality. Basing on academic theories, Chinese buyers need to trust in a website before they make buying decision. Luxury fashion goods are so costly that input more involvement than normal products. They also are concerned with the information about the products in order to make purchase decision. Especially, some luxury fashion goods are shipped from overseas, which are allowed to be returned. Hence, Chinese players must have sufficient and correct information to make purchase decision. The variant in information about products will lead to wrong purchase decisions, and customers will blame the mistake to the online retailer, thus damaging customer satisfaction. Furthermore, consumers also pay close attention to logistics service. They expect to see the real products as soon as possible, and also they are afraid of lost, and broken products, especially because their products are expensive. Long timelessness of delivery, lost, and damage will result in customer dissatisfaction. Hence, logistics service significantly affects customer satisfaction. Additionally, these customers are purchasing luxury goods when they are browsing those websites so that they also desire to enjoy excellent service and distinctive service. Hence, there is a strong relationship between e-service and customer satisfaction, and it is important for companies to develop e-services.
3) To generate an effective approach for luxury fashion clothing players in China to improve their e-commerce practices
Chinese luxury fashion clothing players should attach importance to trust, information quality, logistics service and e-service. Firstly, they need to build a trustworthy brand image in order to attract consumers to purchase. Through promising the guarantee of product quality, logistics service, and payment security, these companies can convince customers. They also need to develop a set of marketing activities to reinforce this brand image in the mind of consumers. Then, it should measure whether the product information they provide is appreciated, accurate and suitable, and whether it misleads consumers. Online retailers should be aware of information dimensions including accuracy, format, and completeness. They need to improve the information quality that actually solve problems and difficulties consumer faced during making purchasing decision. For example, it suggests that these companies provide instructor and guidance to help customer to choose size of clothes and shoes. Furthermore, these companies must ensure the safety of logistics service and enable customers to check the location of their package at any time. They also should prevent lost and damage. In addition, customers expect to experience distinctive service when buying luxury goods in order to show their personality and status quo. Hence, the e-service must comply with high level of standards, and adopt the most advocated technology.
5.3 Limitation
This research is constricted by time. It is challengeable for researchers to adopt various and more effective data collection methods to improve the effectiveness of research results. Many research methodologies adopted by this research have inherent flaws, which are unavoidable and manageable. Positivist philosophy may miss important variables in the context of China’s luxury fashion clothing industry. Thus, further research should adopt interpretivist philosophy to examine the findings of this research. Furthermore, further researches can employ interviews to collect qualitative data if they have sufficient time. Also, researchers can adopt other non-probability sampling techniques to improve the representativeness of data. More importantly, other researchers can examine other potential factors that affect customer satisfaction in the context of e-commerce. For example, website design, personalisation, customisation, and cultural adaptation could be significant factors affecting customer satisfaction in e-commerce (Collier and Bienstock, 2006; and Arazy et al., 2011). Further researches can develop a variety of research methodologies to identify these factors in order to generate convincible and reliable knowledge for e-commerce.
5.4 Conclusion
Nowadays, luxury fashion clothing companies must develop an effective method to take advantage of e-commerce in order to gain competitiveness and sustainability. It is imperative to measure customer satisfaction in the context of e-commerce because customer satisfaction significantly affect the performance of a company. The purpose of this research is to identify an effective approach to improve customer satisfaction toward e-commerce in China’s luxury fashion clothing segment. It will identify the relationships between trust, information quality, logistics service, e-service quality and consumer satisfaction, respectively.
E-commerce refers to the conduct of business through the internet. Customer satisfaction is a statue that goods and services satisfy the expectation of consumers. Customer satisfaction is critical that motivate customer to be loyal to the company, thus affecting customer retention and customer loyalty. Customers also need to trust an online retailer before purchase in online environment. Information quality is users’ subjective evaluation of goodness and usefulness of information. Online retailers should be aware of information dimensions including accuracy, format, and completeness. Logistics service quality has four dimensions including timeliness, personnel, information, and order quality, and it directly, strongly, positively and significantly affect customer satisfaction. Perceived service quality positively affects customer satisfaction, or it is perceived as the pre-condition of customer satisfaction.
This research adopted positivism philosophy, deductive approaches, survey, mono-method, cross-sectional time horizons, and questionnaires as date collection techniques and procedures. It finds that there are significant relationships between trust, information quality, logistics service, e-service and customer satisfaction toward e-commerce in China’s luxury fashion clothing industry.
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Appendix – Questionnaire
Impact of E-commerce on Customer Satisfaction in the Chinese Online Luxury Fashion Clothing Market
Jingxin Zhang
I am currently collating information for my MSc in International Marketing Dissertation and I would be extremely grateful if you could complete this survey.
The questionnaire consists of 29 questions and should take approximately 5 to 10 minutes to complete.
The survey will be used purely for academic purposes and is wholly confidential.
Section 1
1) Have your ever purchased a luxury clothes in the Internet?
Yes
No
1 = Strongly disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly agree
Trust
|
2) This company gives me a trustworthy impression |
1 |
2 |
3 |
4 |
5 |
|
3) I feel safe in my transactions at this website |
1 |
2 |
3 |
4 |
5 |
|
4) I trust that this company will not misuse my personal information |
1 |
2 |
3 |
4 |
5 |
|
5) I am satisfied with the information about security provided on this website |
1 |
2 |
3 |
4 |
5 |
|
6) I believe this company will keep its promises and commitments |
1 |
2 |
3 |
4 |
5 |
Information Quality
|
7) Delivery information communicated by the company is available (timely, traceable) |
1 |
2 |
3 |
4 |
5 |
|
8) Delivery information communicated by the company is adequate |
1 |
2 |
3 |
4 |
5 |
|
9) Delivery information communicated by the company is accurate |
1 |
2 |
3 |
4 |
5 |
|
10) Delivery information communicated by the company is real |
1 |
2 |
3 |
4 |
5 |
Logistics Service
|
11) The designated delivery contact personnel makes an effort to understand my situation |
1 |
2 |
3 |
4 |
5 |
|
12) Problems are resolved by the designated delivery personnel |
1 |
2 |
3 |
4 |
5 |
|
13) The product knowledge/experience of delivery personnel is adequate |
1 |
2 |
3 |
4 |
5 |
E-Service Quality
|
14) It is easy to get access to the company’s website |
1 |
2 |
3 |
4 |
5 |
|
15) The site is user friendly |
1 |
2 |
3 |
4 |
5 |
|
16) Navigation on the site is easy |
1 |
2 |
3 |
4 |
5 |
|
17) It is easy to find my way on the site |
1 |
2 |
3 |
4 |
5 |
|
18) It is easy to get in contact with this online company |
1 |
2 |
3 |
4 |
5 |
Consumer Satisfaction
|
19) Overall, this purchase experience consistently meets my expectations |
1 |
2 |
3 |
4 |
5 |
|
20) My overall experience with this site is satisfactory |
1 |
2 |
3 |
4 |
5 |
|
21) Overall this company is a capable and proficient service provider |
1 |
2 |
3 |
4 |
5 |
|
22) The e-service is successful |
1 |
2 |
3 |
4 |
5 |
|
23) The online company’s (e-retailer’s) website is enjoyable to use |
1 |
2 |
3 |
4 |
5 |
Section II: Demographics
24) What is your gender?
Male Female
25) What is your age?
18-25 26-30 31-35 36-40 41-45 46- 50 Above 50
26) Monthly income?
Below 10,000 yuan 10,001 – 20,000 20,001 - 30,000 30,001 – 40,000 40,001 – 50,000 50,001 – 6,000 Above 60,001
