1 Introduction
The electronic commerce (e-CRM) in China has grown astonishingly in the recent decades, especially after the rise of Alibaba. It has upended the traditional business models and renovated the conventional customer relationships. Due to the features of electronic commerce, e-CRM has been labeled with the business model of being convenient and fast-speededness
[1]. It further changes the relationships among all the e-CRM business entities involved in the value chains in terms of their psychological variables, that is, perceived value, customer satisfaction, and e-trust. This article will expand this theory into the e-CRM of online restaurants.
Based on the new mobile internet technologies of "Internet Plus", the online restaurant's sales have been boosted through mobile Apps technology which further forms an innovative business and marketing model for the traditional restaurants. However, this new business model for restaurants requires tighter and closer cooperations with all the service parties involved, such as mobile apps technologies, online banking systems (Alipay, Wechat pay, etc.), and the simultaneous delivery tracking service, the internet platform systems, etc. These intensive cooperations have, in addition, promoted the massive online restaurant consumptions in return.
Different from the conventional requirements on restaurants, the e-CRM has created new platforms and lines for all the restaurants out of the preliminary requests on locations. The online restaurants are no longer heavily dependent on the locations of the restaurants but mostly affected by the online consumers' satisfaction and trust from the consumers' individual experiences with the online restaurants. Accordingly, restaurants will be more popular if their online feedbacks and satisfaction are higher than the competitors. Furthermore, satisfaction and trusts of the online restaurants are mainly displayed through popularities and ratings which work as the guidance and instructions for the consumers to make their choices among the massive amount of online restaurants.
Scholars of e-CRM mainly focus on the cooperation and management between human and technology in order to maintain a long-term relationship with the customers
[2]. However, there is a research gap in terms of an integrated conceptual model to explain the reasons and causes of long-term commitment and trust between customers and online retailers. To fill this gap, this study concentrates on the psychological variables of perceived value, satisfaction, and trust which affect individual online shopping experiences
[3], in the context of online restaurant sales.
Also, this study will analyze the online restaurant marketing with the research perspective of the relationships among perceived value, satisfaction and e-Trust, corresponding to the cognitive belief, affective experiences and cognitive behavior of e-CRM. It aims to demonstrate the predominant factors affecting the online restaurant sales and further to have a better understanding of the customers' preferences on placing orders and purchases in the online context regarding perceived value, satisfaction and e-trust. The purpose of this is to keep the customer loyalty for future consuming retentions.
2 Theory Background and Literature Review
The "Internet Plus" has improved the business model within more profound and sophisticated aspects which the conventional business model could never have reached. It has extended business and marketing opportunities for all the business entities as well as the consumers by imposing multi-entries and choices. It shifts the marketing model from business to consumer marketing to peer to peer model of sharing online information
[4]. Compared to the conventional marketing, with the technology of "Internet Plus", the consumers now have better knowledge and more choices through the online channels where other consumers' evaluations and reviews are based, regarding their choices of the online business entities
[5]. Amazon was among the first who introduced the review features in 1995 into its online business fronts and lines. This is still regarded as one of the most successful features of Amazon through the online shopping sites.
However, with the further influence of information technologies and the newly developed business model, online reviewing marketing mode has rapidly and broadly expanded into other business fields, in particular those business industries which are highly affected and influenced by the customer loyalty and commitments, such as the hospitality and service industries, such as hotel, restaurant, bookstores, etc
[6]. Researches on travel-related industries have confirmed that the online users' reviews and satisfaction can highly influence the consumers' intentions and their actual purchases
[7].
In China, the excessive development of the information technologies has turned another new page in the online shopping experiences. Due to the statistics report of PWC China and Hongkong, the online sales in China has raised from 0.8 trillion in 2011 to 7.5 trillion in 2018, with a CAGR of 138% (see Figure 1).
Figure 1 China's online retail market transaction scale in 2011–2018 |
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Among all the business fields, the online restaurant sales have mounted to a height that never attained before. According to the Statistics from Ministry of Commerce of China, Department of Trade in Service and commercial services by August 2017, due to the boost of Internet Plus, the integration between the new technology and the online restaurants has reached a new peak. In 2016, the online restaurant sales have reached 209.2 billion CNY, which takes 5.8% of the total revenue of the Food industry.
With advents of the new mobile internet technologies and the widespread use of the smartphone in China, the online shopping experiences extend from the websites to the mobile Apps. This has evidently improved the accessibility of the internet which was limited to the computers in the past. Meanwhile, the detailed contents on the apps with the reviews for the menus, the online operations, the delivery services, the customer services, and other services related have established an exclusive online restaurant marketing with profound administrations and operations.
At present, two predominant online restaurant apps in China, known as ELE and MEITUAN, are broadly used across the country. Both of these two apps are from the same parent company: The MEITUAN Group. According to the statistics of QuestMobile in January 2018, the active consumers of MEITUAN has reached 290 million in December 2017, and the MAU has increased by 40 million. Among all the Apps the group owner, Meituan delivery and ELEM delivery, the two online restaurant marketing fronts are the few apps obtaining new installations in December 2017, reached at 11.2 million, compared to the status that the new installations of other apps actually decline instead. Moreover, due to the statistics of Ministry of Commerce, ELEM in 2016 has expanded to 1.3 million online restaurants with more than 75 million orders daily.
Figure 2 Typical life service independent APP monthly active user size and activity rate*Data source: QuestMobile TRUTH, China Mobile Internet Database, December 2017 |
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Figure 3 Typical life service independent APP new installation active users and new installation active conversion rate*Data source: QuestMobile TRUTH, China Mobile Internet Database, December 2017 |
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The popularity of these Apps is certainly attributed to its well-functioned operations behind. Surely, these restaurants usually feature a variety of filtering services designed to help the consumers to narrow down their search options
[8] in order to match the consumers' requests and demands. For example, the flavor of food can be input as a choice of selection, such as chilli or spicy, or typical local food, or desserts, or afternoon tea, etc. On the list, there appears the addresses of the restaurants, the reviews from consumers, the daily and monthly sales, the distance and time for the delivery to your location. Furthermore, a detailed information will be popped out immediately once the particular restaurant is selected, regarding the online reviews from previous consumers, the best-selling dishes of the restaurant, the reviews on the delivery service, the recommendations etc. The ratings and the number of reviews, as well as the number of orders dedicated to this restaurant clearly indicate the popularity and customer trust and loyalty of this particular online restaurant which are supposed to highly influence the online marketing.
As far as it is mentioned, online popularity certainly reflects the perceived value, consumer's satisfaction and consumer's trust and loyalty to this restaurant. Trueman, et al.
[9] stated that the popularity provides the incremental power of the perceived value of the product and service. Also, internet enterprises are keen on attracting its audience and building up their loyalty and trust with its consumers as early as possible and these are supposed to be the two main goals for the online business to be successful
[10].
Provided that the massive amount of online restaurants alternatives and the rapid and impatience of consumers' choices, the key of the studies has been driven by the relationships between perceived values, satisfaction, and e-trust in the e-CRM environment in order to have a comprehensive understanding of the online consumption process and consult more competitive online marketing strategies regarding the online restaurant.
Previous research has found that online reviews can predominantly affect the popularity and sales of the online shopping, especially the online restaurants
[11]. As far as it is concerned, the online reviews mainly refer to consumers' satisfaction with their own online shopping experiences. Moreover, if the consumer's satisfaction is positive, consumers will contribute their trust to these particular online restaurants which will further conduct their future retentions on these restaurants.
As stated above, the rapid evolution of mobile internet technology and the online restaurants retailing has urged the need of filling in the research gap of finding the reasons and causes which are used to manage and establish the long-term relationships between the online restaurants and the consumers. Moreover, the mobile internet technology is based on "Internet Plus" which is now predominant in e-CRM. However, this new model of e-CRM is not only referring to the new internet technologies but also to the new marketing strategies in online worlds
[12].
2.1 E-CRM
E-CRM refers to electronic commerce which is a newly developing customer-oriented business model. It focuses on customer relationship management techniques which aim to improve customer satisfaction, loyalty, and retention about the products and services
[13]. It is considered as a cognitive process through the stages of cognitive, affective and cognitive which eventually results in the satisfaction and future loyalty of the products and services
[14]. The cognitive process, also known as perceived value, refers to the knowledge, awareness, or beliefs from customers' previous shopping experiences or the feedbacks from other customers
[15]. This process undergoes all the online shopping phases, such as information research, placing an order, post-purchase service, delivery, and payment
[16].
Besides the cognitive process, the effective experience is another predominant facet. According to Oliver, effective experience mainly refers to customer satisfaction which determines the potential intention and actual purchase of a product or a service
[17]. Previous researchers have stated that satisfaction is regarded as an effective response to an expectant behavior in a cognitive process
[18]. As far as it is concerned, customer satisfaction is mainly evaluated through three degrees: Positive, neutral, and negative following the customer's every experience with the product and service
[19].
However, satisfaction would not be effective in a long-term business relationship
[20]. Customer's long-term commitment to a product and service relies mainly on trust, rather than satisfaction
[21]. It is stated that mutual trust will establish long-term relationships with retailers and consumers in terms of product and service loyalty
[22]. Moreover, trust in online customer relationship is deemed as the process of cognitive response to cognitive beliefs, that is, to transfer the trust and loyalty to the perceived values of product and service
[23]. Business week has stated that customers are willing to frequently buy from the most trusted websites or online shops. Thus, online enterprises strongly rely on the trust of their customers with respects to the customer retentions on the product and service. In addition, according to Kim, et al.
[20], perceived value is related to cognitive belief, while satisfaction is seen as an effective experience, while trust would be regarded as conative behaviors.
2.2 Relationships Between Perceived Value, Satisfaction, and E-Trust
Dennis, et al.
[24] have proposed a conceptual framework for attitude, intention, actual behavior, experience and trust in terms of marketing and customer behaviors. Based on this literature, the perception of online shopping is attributed to perceived value, perceived ease of use, and perceived usefulness
[25], that is, product benefits, online shopping convenience and comfort, and satisfaction
[26].
As mentioned above, the positive perceived value would contribute satisfaction or even trust in relation to the customer relationships. Nevertheless, the perceived value is distinct from satisfaction. Perceived value is generated through the value creation processes, including the pre-buy stage
[27] since the value can be perceived without the buying of the product or service
[28]. However, satisfaction is referred to as a post-purchase and evaluation of the product or service
[17]. It relies on the individual experiences on previous purchases or uses of products and services. Accordingly, satisfaction is considered as a linear structure which shifts from unfavorable to favorable
[29] and it is largely seen as a feedback, outcome and a summary in terms of the purchased products and services, as well as a reflection on value
[30].
The attitude is further shaped by the perceived value, ease of use and usefulness. The favorable attitude which is also known as satisfaction is most likely to promote the online shopping behaviors while unfavorable attitude will direct the customers to others and even eliminate the behaviors
[25].
In addition, trust is a cumulative and repeated satisfactions the consumers commit to the product and service
[20]. Satisfaction over the previous shopping experiences promotes the confidence of the retailers in sales. It is stated that trust is based on satisfaction
[31]. Scholars have contributed customer satisfaction to future interactions and commitment to the product and service
[32].
In this study, we will focus on the customer's satisfaction and trust from their online shopping experiences, especially related to the online restaurant's sales. Indeed, the experience of online shopping will either enhance or ruin the potential or the retention of the behaviors and will directly influence the online marketing depending on the nature of the experience.
3 Hypotheses and Conceptual Model
3.1 Commitment
Commitment generally refers to an successful exchange and cooperation between difference relationship partners in order to maintain an effective and active relationship. This definition states that the commitment aims at the successful relationships and the efforts for all the partners to maintain this positive relationship among them. Furthermore, commitment is specifically related to an ongoing and active marketing relationship, according to Morgan and Hunt
[21]. Meanwhile, Meyer and Herscovitch
[33] defined commitment with a conceptual perspective that commitment is a behavioural action between individuals and the cooperations which are mostly distinguished from motivations and attitudes. However, commitment can be independent beyond motivation and attitudes in terms of a long-term relationship
[22]. Some scholars also define commitment as a psychological attachment regarding the favourable reflections on the desires and contributions towards certain relationships as well as the efforts to maintain these relationships.
As a result, commitment is considered to be vital to relationship marketing as it is considered as the successful contribution to achieve the product values through consumer's purchasing towards the business entity. Moreover, commitment is also the determinant to the long-term customer orientation and retention towards a specific business and the long-term relationships and trust are based on the commitment
[22] and further develop this relationship into productive and effective relational exchanges
[21]. Conceptually, commitment is considered as a conative correspondent to cognitive beliefs and affective experiences, which are also known as perceived values and satisfactions respectively in marketing research field
[23]. In conclusion, commitment is defined as the implementation of relationships between business partners and individuals, regarding their purchasing behaviours through shared values, it is formed as a multidimensional framework including affective commitment
[33], value commitment
[34], moral commitment
[35], and normative commitment
[36] with the perspectives of psychology
[37], organizational behaviours
[38], and marketing
[39].
In addition, the trust commitment is particularly important in the online business context regarding the business relationship between the online retailers and the customers. Since most of the online retailers are highly influenced by the consumers' post-purchasing satisfactions, which refers to the reviews, comments and ratings, most of the commitments are built on the good satisfactions which orient other consumers' online business behaviours as well as customer retentions. Thus, the commitment and trust work as the key mediating variables which consist the predominate nature of successful relationship marketing
[21]. This is because the commitment encourages and orients the consumers and their purchasing investment and contributions into the relationship marketing and further directly affect the relationship marketing cooperatively and effectively
[21].
According to Morgan and Hunt
[21], the precursors of commitment can be demonstrated as relationship termination costs, relationship benefits, shared values, communication and cooperation
[21]. Relationship termination costs refer to the switching costs for the termination of a relationship and the alternation to a new one
[40]. Relationship benefits concern the advantages from competitors and the strategy to sustain the benefits derived from these advantages
[21]. Shared values depend on the perceived values shared by all parties in terms of goals, behaviours, policies, and all the perceptions in common
[40] which further become the essential variable for organizational commitment where group values are shared
[41]. Communication evidently presents the communications among different partners regarding the information that leads to the relationship behaviours
[42]. Past communication heavily influences the relationship commitment, that is, positive past communication affects the commitment positively while the negative one leads to a negative relationship action. Finally, cooperation regards the working collaborations among all parties which ensure to achieve the same business goal
[42]. In short, relationship termination costs and relationship benefits affect commitment directly, while shared values affect both commitment and trust directly. However, communication and cooperation affect the trust directly but indirectly on commitment
[21].
This study aims at commitment as a mediating variable that affects an individual behavioural intention towards a business entity, exclusively in the online retailing context. As far as it is concerned, commitment heavily influences customer's intention to continue a relationship service, that is, customer retentions and their attitudes and contributions towards relationship services. It reflects the motivations to maintain a long-term relationship and sustain trust and loyalty
[43]. Moreover, in the online retailing, the relationship marketing is highly dependent on the commitment through perceived value, customer satisfaction, together with the service quality and price.
3.2 Perceived Value
Perceived value defined as the customers' consumption behaviors on the particular product or service in regards to the receiving-giving procedures
[15] related to perceived requirements in the shopping experience
[14]. It compares the procedure between the value-receiving and the value giving, which is also regarded as the ratio or a trade-off between quality and price, with the perspective between value and money
[44].
Evidently, quality and price indeed have various impacts on perceived values for money
[28]. However, different consumers have their different perceived values on quality and price, that is, the different focus on the obtained value from 'get' and 'give'
[15]. For example, some consumers might have perceived value only when there is a low price, while others might have perceived values when there is a balance between quality and price
[45]. Nevertheless, perceived value is much more sophisticated than just the simple measure of quality and price since the value is created throughout the whole production of the goods and service
[46].
As Sheth, et al. stated, the consumer's perception of value relies on several dimensions, such as social, emotional, functional, epistemic and conditional value
[47]. These dimensions correspond to the purchasing behaviors based on utilities, the product types, and the brand preferences which give a development on the value creation through various research fields such as economics, social and clinical psychology.
All the dimensions interact through the value creation process
[46] while functional value seems to be the predominant one among all the dimensions
[28]. Functional value mainly refers to the reliability, durability, and price of the product and service which is further classified as quality and price with either a positive or a negative effect on the product
[47]. For example, the decision on a particular purchase, such as a purchase on a fashion, may interplay the functional value, together with emotional (personal preference), social and other values. However, the impacts of different dimensions refer to the decision on consumption as well as the type of product and service
[28] which will further interact with commitments in the organizations
[48], working well-beings
[49], retail service quality
[50], and mental imagery through the communications among all the entities
[51]. Customer perceived value can affect the loyalty of the product and service
[52]. Perceived value helps the customer to build their trust and reliable satisfaction towards their shopping experiences and their purchases of product and service
[53]. If the perceived value is positive, it will lead to the positive intentions of a long-term relationship and commit their action purchases with one or several particular online retailers. Thus, following are the hypotheses proposed:
H1a: Perceived value will inspire satisfaction.
H1b: Perceived value will inspire e-Trust.
H1c: Perceived value will inspire customers' commitment to a relationship.
3.2.1 Satisfaction
Satisfaction refers to the extent of customer perception and their prior expectations for a product or service during actual use
[14]. It is included the fulfillment of a purchase behavior as well as an individual review on the shopping experience
[17]. Thus, satisfaction is seen as the evaluation and feedbacks of the emotions the consumers reflect towards their shopping experiences towards the products and services
[54]. Also, satisfaction has been conventionally considered as the determinant factor for the relationships between the retailers and the consumers
[55]. The related hypothese are claimed as follow:
H2a: Satisfaction will positively influence e-Trust.
H2b: Satisfaction will lead to the commitment to a relationship.
3.2.2 E-Trust
Trust is defined as a set of specific and long-term relationships between customers and retailers integrated with their benevolence, competence, and predictability of a retailer with regards to the customer's purchases
[14].
According to Wu and Cavusgil, trust is considered to be essential for long-term customer retention
[22]. This is further developed into commitment-trust theory (CTT) to describe the fundamental knowledge of mutual trust in terms of relationships between customers and enterprises in the conventional business model. Within the e-CRM, this relationship becomes extremely crucial for the development of the online business and implementation of e-CRM strategies. Furthermore, on the basis of CTT, scholars have illustrated the significance of trust in an online business environment as a conative behavior to cognitive beliefs and affective experiences which are also known as perceived value and satisfaction respectively
[23]. In addition, potential hypothese are stated here:
H3: E-trust will positively affect the consumer commit to a relationship.
3.3 Conceptual Model
With regards to the online shopping, especially the online restaurant marketing lines, this study will propose following hypotheses concerning the relationships among perceived value, satisfaction, and e-trust. A structural framework of the hypotheses is illustrated as in Figure 1 below.
As shown in
Figure 4, This study focuses on the customer's cognitive beliefs (perceived value), emotional experience (satisfaction) and cognitive behavior (e-trust) to propose a comprehensive model of e-CRM. This model identifies a series of connections among three psychological variables: Perceived value, satisfaction, and e-trust. Perceived value is considered as the preliminary influencing satisfaction, e-trust, and commitment. Satisfaction will further lead e-trust and commitment to a relationship. Satisfaction will positively contribute commitment to a relationship. In addition, the integrated model considers three key exogenous variables that affect the online restaurant consumption experience. Most studies focus on quality of service when examining external factors that influence customer commitment
[56, 57]. A lot of attention has been paid to the quality of service, which emphasizes the quality of service is a necessary but not sufficient factor, leading to customer commitment to long-term relationships
[54, 58]. Perceived product quality is also seen as an important exogenous factor associated with customer commitment
[59]. Price fairness has proven to be another important factor influencing customer commitment in previous studies
[60].
Figure 4 Variables measurement |
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4 Methodology
The methodology of the research on the relationships among perceived value, customer satisfaction, and e-trust focuses on literature reviews on the related subjects in order to have a comprehensive understanding of the conceptualization of these aspects in terms of psychological variables
[57]. The literature reviews contribute to the identifications of the terms and the academic supports on the relationships and links among all the factors.
A data collection would be applied to the online surveys and data based on the biggest online restaurants app (app ELE) in terms of their customer satisfaction, ratings, daily and monthly sales, and its customer loyalty. It shows that the ratings predominately determine the sales and orders of the restaurants. Moreover, those restaurants which have already established their reputations easily get high ratings and high satisfaction and have also earned more trust online than those new restaurants. However, there are also those restaurants which were anonymous before but have suddenly boosted up because of their high satisfaction with great perceived values.
Table 1 The result of pretest data analysis |
| Endogenous variable | | Variables | References |
| Perceived value | Production quality | | A variety of food choice on the menu of the hotel | Amin, et al., 2013 |
| Quality of the restaurant food |
| Service quality | | Efficient operation of reservation | Amin, et al., 2013 |
| The overall selection of beverages |
| Charges clearly explained |
| Value for money of the restaurant |
| Prompt response from order taker |
| Price fairness | | How fair is its [the items] price? | Babin, et al., 2003 |
| How fair/unfair do you think the price offered to consumers is? |
| How fair/unfair is the price for the consumption? |
| Satisfaction | | Satisfaction with reception | Amin, et al., 2013 |
| Satisfaction with food and beverage |
| Satisfaction with price |
| Overall satisfaction |
| E-trust | | I expect that website has good intentions towards me. | Hwang, et al., 2007 |
| Promises made by the website are likely to be reliable. |
| The website knows how to provide excellent service. |
| The website understands the market they work in. |
| The website knows about products. |
| I do not doubt the honesty of the website. |
| I expect that the website will keep promises they make. |
| I expect that website is well-meaning. |
| Commitment | | Emotionally attached | Walter, et al., 2003 |
| Strong identification |
| Important relationship |
| Relation with personal meaning |
4.1 Pretest of Data
200 questionnaires were issued between January 1st and March 30th, 2018, and 169 valid questionnaires were collected for reliability analysis (see table 2). The overall Cronbach's Alpha of the 26 variables was 0.969, indicating that the overall reliability is ideal. The Cronbach's value of the index is bigger than 0.6, showing its better reliability. Based on this, this study finally focuses on the 26 research factors.
Table 2 Structural equation model results |
| Variable | Average | Variance | Cronbach's α |
| Perceived value | Production quality | : 4.7101 | 2.862 | 0.641 |
| : 4.1893 | 2.512 |
| Service quality | : 4.0651 | 3.145 | 0.842 |
| : 3.5444 | 3.023 |
| : 3.7988 | 3.269 |
| : 4.7160 | 3.157 |
| : 5.0592 | 2.973 |
| Price fairness | : 4.2663 | 3.268 | 0.906 |
| : 4.3846 | 3.214 |
| : 4.0059 | 3.244 |
| Satisfaction | : 4.0414 | 2.778 | 0.863 |
| : 3.7811 | 2.803 |
| : 4.8994 | 3.020 |
| : 4.0888 | 2.831 |
| E-trust | : 3.6686 | 2.568 | 0.941 |
| : 4.3669 | 2.674 |
| : 3.7278 | 2.306 |
| : 3.7515 | 2.545 |
| : 3.6982 | 2.498 |
| : 3.7929 | 2.737 |
| : 4.7751 | 2.675 |
| : 4.4260 | 2.901 |
| Commitment | : 4.1243 | 2.943 | 0.883 |
| : 3.7692 | 2.810 |
| : 4.5503 | 3.392 |
| : 4.7988 | 3.162 |
4.2 Data Collection
Survey on all the online restaurants with over 4.8 ratings and those of lower than 4.5 rating. Compare their daily sales and monthly sales. From April 1st to June 30th, 2018, 600 questionnaires were distributed and 542 valid questionnaires were returned. The effective rate was 90.33%, including 54.20% for males, 45.80% for females, and 96.40% for colleges and above, 100.00% has had a network ordering experience, which basically meets the needs of this research. The statistical analysis results of each variable are similar to those of the previous test, and this section does not show.
5 Result Analysis
In this paper, the structural equation model of Figure 4 is constructed based on the six hypotheses derived from the model. The path analysis of the model can be used to test the authenticity and influence range of the model hypothesis as Figure 5, the results of hypothesis and model fix indicators have been shown in Table 3 and Table 4. The model fit also meets the requirement of basic statistics.
Figure 5 Results of Hypothesis |
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| Relationship among variables | Estimate | | Assumption |
| Perceived value | | Satisfaction | 0.567 | *** | approval |
| Perceived value | | E-trust | 0.685 | *** | approval |
| Perceived value | | Commitment | 0.371 | *** | approval |
| Satisfaction | | E-trust | 0.250 | *** | approval |
| Satisfaction | | Commitment | 0.067 | 0.405 | disapproval |
| E-trust | | Commitment | 0.472 | *** | approval |
| Model | CMIN | DF | CMIN/DF | IFI | TLI | CFI | RMSEA |
| Default model | 996.415 | 292 | 3.412 | 0.903 | 0.919 | 0.922 | 0.065 |
According to the test results, it is assumed that the path coefficient of H2b does not reach a significant level, the hypothesis verification is rejected. In addition, the path coefficients of other theoretical hypotheses have reached a significant level, thus, the assumptions of hypothesis H1a, H1b, H1c, H2a, and H3 are tested. The detailed demonstrations are as followed:
If the path coefficient of variables between Y (Perceived value) and Y5 (Satisfaction) reaches 0.680, as a significant level, Hypothesis H1a is approved, that is, Perceived value will affect satisfaction positively.
If the path coefficient of variables between Y (Perceived value) and Y4 (E-Trust) reach 0.570, as a significant level, Hypothesis H1b is approved, that is, Perceived value will positively affect e-Trust.
If the path coefficient of variables between Y (Perceived value) and Y7 (Commitment) reaches 0.371, a significant level, Hypothesis H1c is tested, that is, Perceived value will result in commitment to a relationship.
If the path coefficient of variables between Y4 (E-trust) and Y5 (Satisfaction) states as 0.250, a sufficient level, Hypothesis H2a is claimed, that is, satisfaction will benefit e-trust.
If the path coefficient of variables between Y7 (Commitment) and Y5 (Satisfaction)is 0.067, lower than the sufficient level, Hypothesis H2b is rejected.
If the path coefficient of variables between Y4 (E-trust) and Y7 (Commitment) shows as 0.472, a sufficient level, Hypothesis H3 is agreed, that is, e-trust will further win the commitment to a relationship.
The verification results of the above six hypotheses show that from the perspective of e-CRM for online restaurant consumption, perceived value, satisfaction and e-Trust are the main psychological variables affecting customer commitment. There is a series of connections among them, and most of them are important.
First, the perceived value has an incentive effect on satisfaction, e-trust, and customers' commitment to a relationship. At the heart of customer perceived value is the trade-off between Perceived Benefits and Perceived Sacrifices. To cultivate the core competitiveness of a company based on customer value, the first is to identify and understand the expected value of customers in the target market. By cultivating the industry's insight, surpassing existing products and markets, and looking for value areas that customers have always attached importance to and build superior skills in these areas.
Second, satisfaction has a positive impact on e-trust and leads to the commitment to a relationship. Customer satisfaction has traditionally been regarded as a fundamental determinant of long-term consumer behavior
[55]. Therefore, online restaurant business activities should be based on customer satisfaction, from the customer's point of view rather than the company's own interests and perspectives to analyze customer needs, as far as possible to fully respect and protect the interests of customers. Therefore, the construction of the core competitiveness of an enterprise is a management process of reviewing, analyzing, discovering and innovating.
Third, e-trust positively affects the consumer commitment to a relationship. Trust is a core factor that directly affects relationship commitments. Therefore, online restaurant is critical to building customer trust in a consumer environment. Providing superior value and a satisfying consumer experience are two effective ways to build customer trust.
In addition, the path coefficient of the variable relationship between Y (Perceived value) and Y1 (Production quality) is 0.580, reaching a significant level. The path coefficient of the variable relationship between Y (Perceived value) and Y2 (Service quality) is 0.959, reaching a significant level. The path coefficient of the variable relationship between Y (Perceived value) and Y3 (Price fairness) is 0.821, reaching a significant level. Which shows that Production quality, Service quality and Price fairness have a significant impact on the Perceived value. That is, superior perceived value stems from superior perceived service, product quality, and perceived price fairness. When service quality, product quality and price fairness are considered to be beneficial and satisfactory, the perceived value of online customers is optimal. Therefore, for the online catering industry, the successful implementation of e-CRM should closely integrate business and ICT, and effectively enhance customer value management by providing customized services or products and providing competitive customer value and satisfaction at competitive prices to attract customers' promises.
6 Conclusion
Due to magnificence of the online marketing, especially the online restaurant ordering and selling, this study is going to propose several hypotheses in terms of the relationships among perceived value, satisfaction, and e-trust. These hypotheses are demonstrated both through theoretical and empirical researches, including: 1) Perceived value positively affects trust, satisfaction, and commitment to a relationship; 2) Satisfaction positively affects e-trust and commitment to a relationship; 3) E-trust positively affects commitment to a relationship.
The results indicate that perceived value plays a crucial role on the relationships among perceived value, customer satisfaction, e-trust and commitment in the online business and marketing contexts under the new Internet Plus technology, especially the online restaurants sales. Perceived value leads a direct impact on trust, however, it has an indirect impact on commitment through the trust. As far as it is concerned, perceived value is considered as a cognitive belief which is based on experience.
Furthermore, the research results also demonstrate that perceived value and satisfaction from online consumption lead to trust and loyalty and result in trust-related behavioral intentions, such as attitudinal commitment and long-term relationship engagements and loyalty. In addition, in terms of the three exogenous factors, perceived value has an significant impact on perceived service quality (path coefficient 0.580), perceived service quality (path coefficient 0.959) and perceived price fairness (path coefficient 0.821).
Moreover, there are managerial implications for these findings. First, the SEM model further explains the reasons to maintain long-term exchange relationships between the enterprises and consumers. Lately, the proposed integrated e-CRM model can provide an understanding of the causes of customer's re-engagement. For example, online customers usually commit to an e-store when the service quality, product quality, and price fairness are perceived as beneficial and satisfactory. Therefore, as presented in the model, successful e-CRM are supposed to reinforce their customer value management, customer satisfaction management, and customer trust management through ICT in order to promote and activate potential customer commitments
[58].
In addition, the integrated model suggests that perceived value and e-trust, as cognitive and affective antecedents, influence satisfaction directly. Trust is essential factor that directly lead to a customer's commitment. Thus, it is crucial for online business entities to establish customer trust through their online shopping experiences. With regards to the establishment of customer trust, impressive high value and a satisfying and friendly online shopping experiences, together with a good management of customer service are predominate for the online enterprises, especially for the online restaurants.
Finally, the results clearly indicate that impressive and high value and positive customer satisfaction mainly come from high perceived service or product quality, as well as the perceived price fairness. Thus, the online enterprises should merge together the business contexts with the ICT in order to sustain a successful implementation of e-CRM which will further provide high customer value and satisfaction in terms of customized services or products, and competitive pricing.
Accordingly, these research results present a detailed empirical study for the interacted framework for e-CRM proposed in this study. Meanwhile, these studies provide the potential focuses and essences for the online business management through a well-developed and implemented e-CRM business model.
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Figure 1 China's online retail market transaction scale in 2011–2018
Table 1 The result of pretest data analysis
