Consumers ’ Demand and Online Promotion of the Food Retailing Through the E-Commerce Websites in China

Over the last decade online shopping provides an open window for producers who will market their products and becomes one of the most rapidly growing forms of shopping. In order to take full advantage of the potential offered by the internet, it is essential that the e-commerce websites meet the customer requirements and be prepared and organized with highly usable manner. This study is an attempt to identify the factors that may have an impact on consumers’ probability to buy food through the internet and investigate the current issues and challenges for the top 10 B2C e-commerce websites in terms of promoting food retailing in China. Fuzzy TOPSIS is employed to evaluate the quality of these websites based on the conceptual model of willingness to buy products through internet for the online consumers. The managerial implications and suggestions for future research are also discussed.


INTRODUCTION
Over the past several years e-commerce has changed the way business transaction occur for its convenience of ordering and paying for the products online and have them delivered to the doorstep.As one of the developing countries that experience the highest online population growth rates in China.According to a report by the China Internet Network Information Center (CNNIC, 2013), there are 242 million Internet users engaging in e-commerce activities in China and the e-commerce market racked up a whopping 190 billion USD worth of transactions in 2012, an increase of 66.5% over 2011′s total.According to Ystats (2013), it is expected to grow by more than 30% annually between 2013 and 2016.
In terms of population, China is the largest country in the world and thus the food is in great demand.However, with the rapidly development of the ecommerce, the online food shopping is not as popular as the other categories such as fashion, shoes and bags, as well as computers and household appliances.Morganosky and Cude (2002) argue that online shoppers are better educated, had relative higher incomes and tend to be somewhat younger, implying that the online consumers' demand is different from the general populations.It is necessary to identify the main factors effecting consumer willingness to buy online products.However, the related research is still in its infancy (Morganosky and Cude, 2002).E-commerce website quality has become one of the critical factors in attracting online shoppers to visit a company's online store and learn more about its products and services, with possible follow-up purchase (Korner and Zimmermann, 2000;Geissler, 2001).From observations, however, there exist many issues and challenges in the current e-commerce websites regarding the actual performance in terms of the effectiveness of their promotional effort.In order to provide practical insight and guidelines for improving the effectiveness of the e-commerce in food retail market, an empirical study to investigate the demand of the online shoppers and evaluation these e-commerce websites is needed, which is the primary motivation of this research.

LITERATURE REVIEW
As the increase of the income, particularly of the lower and middle-income households, there is a significant impact on the food demand and the consumers have now become more discriminating in their food product choices and have started emphasizing more on the quality, freshness and convenience (Ali et al., 2010), determining the online food retailing through the e-commerce is getting more and more popular.
There is not a widely accepted definition for ecommerce, which is generally classified as B2B, B2C, C2C and C2B e-commerce (Madu and Madu, 2002).2002) define e-commerce as a process to buy and sell products through computerized business transaction.Choi et al. (1997) distinguish in their e-commerce model three elements: product, agent and process and they argue that the transactions where one of the above elements involves the internet will be e-commerce.According to this definition, buying food from a vending machine with a smart card can be seen as e-commerce (Turban et al., 2002).In this study, online consumers are restricted to those who buy products via internet websites.
The consumer online behavior is studied by many researches.Szymanski and Hise (2000) study more than a thousand online consumers and find perception of convenience is the most important factor in terms of esatisfaction assessments.This conclusion has been supported by the research of Corbett (2001), indicating convenience and time saving factors are the primary motivators of the online consumers.Mathwick (2002) study more than 800 shoppers and argues that consumers enter into online purchasing because they expect to receive positive value from their online participation.Sindhav and Balazs (1999) propose a conceptual model for on-line retailing, including three factors affect the growth of e-commerce: the company, the environment and the perceived consumer benefits.Perceived consumer benefits are, in their model, in turn seen as related to the medium, the consumer and the product.Grunert and Ramus (2005) review literature on factors that may have an impact on consumers' probability to buy food over the internet and suggest a modified model that delineates five groups of factor affecting perceived consumer benefits (Fig. 1).A research by Singh (2002) argues that e-services are important in B2C e-commerce for managing customer relations and enhancing sales.Park (2002) puts forward a model of consumer buying intention online which includes five main factors that influence online purchase: product type, product interest, shopping orientation, experience of online buying and website trust.
While it is generally acknowledged that the ecommerce website is one of the major factor to improve the willingness to buy products through internet and many related researches have been done on improving effectiveness of the e-commerce websites (Thorleuchter and Poel, 2010;Li and Li, 2011;Nielsen, 1999;Nielsen and Tahir, 2001;Aladwani and Palvia, 2002;Kim and Stoel, 2004;Koufaris, 2002;Soliman and Youssef, 2003).However, a study by Elliot and Fowell (2000) show that the online customers have been relatively frustrated with the quality of the websites they visited.Davidavičienė and Tolvaišas (2011) describe the quality factors of an e-commerce website and services based on the survey of Lithuanian online store visitors.Cao et al. (2005) identify factors of effect the ecommerce web site quality using an IS success model which include: system quality, information quality, service quality and attractiveness.The study by Lin (2007) shows that website design, interactivity, in formativeness, security responsiveness and trust affect customer satisfaction, while empathy does not have a statistically significant effect on customer satisfaction.Swaminanthan et al. (1999) argue that consumers evaluate websites when they make purchase decisions and the perception of their shopping experience at the websites plays a major role in creating demand for online purchasing.The research of Zhang et al. (2011) shows that perceived website usability positively impacted customer repurchase intention.Investigating online consumers' website evaluation criteria is important for the companies to develop a website which can attract online consumers and communicate successfully with them, which eventually helps the company to sell its products and retain its online customers.However, most of the researches in the area indicate that this is a complicated task (Jones and Hughes, 2001;Sigman and Boston, 2013), in the mean time, Goi (2012) observes that although website design and development is concerned, few sets of criteria are available on the web and from the researchers' website evaluation criteria.
In summary, the online promotion of B2C ecommerce websites both in theory and in practice has proven to be very important and since China is one of the developing countries which experience the highest online population growth, it is necessary to study the online customer behavior and online promotion of the e-commerce websites in China's market.However, there are few studies focusing on the food retailing market in terms of online consumer demand and online promotion of the B2C e-commerce websites in China, which is the primary motivation of this research.

METHODOLOGY
There are many factors influencing the quality of ecommerce, which determines that the issue is Multiple Criteria Decision-Making (MCDM) (Vincke, 1992).The TOPSIS method selected for the data analysis in this research was first proposed in 1981 (Hwang and Yoon, 1981) and it is employed to solve the related MCDM problems under the fuzzy environment (Muralidhar et al., 2013;Ataei et al., 2008;Zeki and Rifat, 2012).

Fuzzy sets and fuzzy numbers:
Definition 1: A Fuzzy set ܽ in a universe of discourse X is characterized by a membership function ߤ ‫)ݔ(‬ which associates with each element x in X, a real number in the interval (0, 1).The function of ߤ ‫)ݔ(‬ is termed the grade of membership of x in ܽ (Zadeh, 1965).The present study uses triangular Fuzzy numbers.ܽ can be defined by a triplet (a 1 , a 2 , a 3 ).Its conceptual schema and mathematical form are shown as below: b 3 ) be two triangular fuzzy numbers.According to Wang (2009), a distance measure function (ܽ , ܾ ෨ ) can be defined as below: Definition 3: Let a triangular Fuzzy number ܽ , then αcut defined as below: b 3 ) be two triangular Fuzzy number and ܽ ఈ , ܾ ෨ ఈ be α-cut, ܽ and ܾ ෨ , then the method is defined to calculate the divided between ܽ and ܾ ෨ as follows: So the approximated value of ܽ /ܾ ෨ will be: The basic operations on Fuzzy triangular numbers are as follows (Yang and Hung, 2007): For approximation of multiplication: For addition:

Fuzzy membership function:
In the evaluating process, the weights expressed with the linguistic terms, represent the important degrees of criteria from experts via surveys on subjective assessments.These linguistic terms are categorized into Very Low (VL), Low (L), Medium (M), High (H) and Very High (VH).Assume that all linguistic terms can be transferred into triangular fuzzy numbers and these fuzzy numbers are limited in (0, 1).As a rule of thumb, each rank is assigned an evenly spread membership function that has an interval of 0.30 or 0.25 (Yang and Hung, 2007).Based on assumptions above, a transformation table can be found as shown in Table 1. Figure 2 illustrates the Fuzzy membership function (Yang and Hung, 2007).
Fuzzy TOPSIS model: It is formulated that a Fuzzy Multiple Criteria Decision Making (FMCDM) problem about the comparative evaluation of the selected websites.The FMCDM problem can be concisely expressed in matrix format as follows: are linguistic triangular Fuzzy numbers: ( , , ) The normalized Fuzzy decision matrix is denoted by: The weighted Fuzzy normalized decision matrix is shown as follows: 1 31 2 32 3 33 3 Given the above Fuzzy theory, the proposed Fuzzy TOPSIS procedure is then defined as follows: Step 1: Choose the x ij , i = 1, 2, …, m; j = 1, 2, …, n for alternatives with respect to criteria and ‫ݓ‬ , j = 1, 2, …, n for the weight of the criteria.
Step 2: Construct the weighted normalized Fuzzy decision matrix V.
Step 4: Calculate separation measures.The distance of each alternative from A + and A -can be identified as follows: Step 5: Calculate the similarities to ideal solution: Step 6: Rank alternatives according to CC i in descending order (Yang and Hung, 2007).

DATA COLLECTION AND RESULTS ANALYSIS
Since this research is mainly focus on the food retailing through the B2Ce-commerce websites in China, the top 10 B2C e-commerce websites in retail market shown in Table 2 are selected based on the transaction size.
The modified model for online retailing proposed by Grunert and Ramus (2005) is adopted in this study.According to this model, there are five groups of factors affecting perceived consumer benefits as shown in Fig. 1.A pre-designed observation sheet including these five groups of factors (medium, consumer, product, firm and environment) is used to collect all necessary data from these e-commerce websites.The selected items from all websites are rated with the widely used Little Scale method, i.e., from a scale of 1 (being the worst) to 5 (meaning excellent) accordingly.
The detailed index for each factor affecting perceived consumer benefit are proposed in this study according to related research and the results of the collected data are summarized in Table 3 to 7. Sinadhav and Balazs (1999) mention three relevant characteristics of the medium: interactivity, variety of channels and   performance as shown in Table 3. Online seller of the website could help the online shoppers to get the exact information they wanted.However, 3 out of 10 selected websites don't have the online sellers, so there is probability that the online shoppers can't acquire the information they wanted to know about the products they intend to buy when they have some questions and finally give up buying them.In addition, the response time of the online sellers as well as the consumers' complaints definitely need to be improved as show in Table 3. Variety of channels refers to the number of channels, e.g., text and video.However, a large proportion (90%) of the selected websites doesn't have video clips, which is clearly more attractive and persuasive to potential online shoppers.Logical capability refers to the opportunity to perform logical operations on the data supplied, e.g., sorting and comparing.
In consumer market, the quality of the service is the most important for establishing loyal relationships between buyer and seller.There are some web-related tools available to provide online services to consumers in e-commerce, e.g., personalized web pages, FAQs (Frequently asked questions), chat room, e-mail and automated response, help desks and call centers (Singh, 2002).However, as shown in Table 4, the application of these e-service tools is not satisfying.For example: more than half of the observed e-commerce websites never apply the help desks and call centers.It is no doubt that the consumers prefer to online shopping because of its convenience.You can get what you wanted at home with the click of the mouse!Nonworking time delivery can help the online shoppers to pick up the packages when they at home.However, 4 of the selected websites don't offer the service.Sindhav and Balazs (1999) discuss two aspects of the environment: critical mass and technical and legal considerations.Critical mass refers to a minimum level of both consumers and retailers on the internet which are regarded as necessary for online shopping to take off, which is less clear, though, where that threshold is.In this research, three measures are employed to assess the popularity of the selected websites in order to make sure that they meet or exceed the minimum level: • Online traffic rank • Daily page-viewing on site • Retail size As shown in Table 5, half of the observed websites (5 out of 10) selected for which daily page-viewing per user is lower than 5 pages, which implying that this part of the visitors don't buy the desired products on these ecommerce websites.Four of the selected website is ranked after 100 based on the number of the visitors, implying that there are not many online shoppers visiting these e-commerce websites frequently.It is hard to identify the retail size of the food retailing for the e-commerce website, so coffee, organic food and international market food as selected as samples to make a rough evaluation.For example, we search for organic in the websites and check the number of the brands sold in these websites.As shown in Table 5, the number of the brands of the organic food in half of the observed e-commerce websites is less than 5.As the increase of the income, there are more and more healthconscious consumers who want to buy organic food or international market food.However, there are not various selections for these consumers.
Average lead-time of main page and security are identified as the measures for technical and legal considerations.One of the e-commerce challenges on the websites is when users experience intolerably long wait for a website's page to load.When the loading time exceeds the time that an online shopper is willing to wait, he will either redirect the web-browser to another website or never use the website again (Weinberg, 2000;Roslow et al., 1992).However, as shown in Table 5, the average leadtime of opening the main page of the observed e-commerce websites is relatively slow.A clear classification of goods and wide variety of products are believed to have an impact on how consumers search for information about products and evaluate them is based on whether they are characterized mainly by search, experience or credence qualities (Darby and Karni, 1973).However, it can be seen again that in this regard, there are many issues and challenges in these websites in terms of product quantities and service.For instant, thirty percent of the selected websites need to improve the classification of products, as shown in Table 6.The variety of food products is not satisfactory for half of the top 10 B2C ecommerce websites.In addition, the product introduction in two of the observed websites is not very detailed, which is definitely very important for ecommerce websites to attract more online shoppers and reduce return possibility.Zott et al. (2000) discuss two factors as success factors in e-commerce for firms: creation of stickiness and enhancing transaction efficiency.The related measures in terms of creation of stickiness and enhancing transaction efficiency are shown in Table 7.
Transaction efficiency is tightly linked to the presence of transparent and efficient logistics systems (Loebbecke and Powell, 1998), which can create additional consumer benefit of online retailing compared to conventional store shopping.However, 3 out of 10 top B2C e-commerce websites need to improve the presence of transparent and almost half of these observed websites (4 out of 10) need to improve the benefits for consumers.

Solutions from fuzzy TOPSIS analysis:
To further identify the relative importance of the major measures for evaluating the e-commerce website effectiveness in terms of promotional and marketing power discussed in the earlier section, the fuzzy TOPSIS, as a quantitative tool, is employed in this research.These specific measures are proposed based on the conceptual model suggested by Grunert and Ramus (2005) in Table 8 for the further quantitive analysis: The important degrees of the above sub-criteria weights are given with linguistic terms, i.e., VL, L, M, H and VH, employed by five experts E 1 , E 2 , E 3 , E 4 and E 5 , as shown in Table 9.
The Fuzzy linguistic variable is then transformed into a Fuzzy triangular membership function as shown in Table 12 and then the resulting Fuzzy weighted decision matrix can be derived based on Table 12 and the weights identified before.The distance of each alternative from A + and A − , as well as the similarities to an ideal solution (CCi), is obtained in Table 13.
In order to see the result more clearly, the resulting Fuzzy TOPSIS analysis is shown in Fig. 3.
The result of the top 10 B2C e-commerce websites shows that 6 out of 10 observed e-commerce websites score less than 0.6, implying that these e-commerce websites have a room for a significant improvement through better and improved website design and updates in order to improve the customer loyalty and food sales.

CONCLUSION
This study is an attempt to identify the factors that may have an impact on consumers' probability to buy food through the internet and investigate the current issues and challenges for the top 10 B2C e-commerce websites in terms of promoting food retailing in China.The specific measures are proposed and Fuzzy TOPSIS is employed to evaluate the quality of these websites based on the conceptual model of willingness to buy products through internet for the online consumers (Grunert and Ramus, 2005).The primary data for this research are collected through a pre-designed observation sheet.Fuzzy TOPSIS is employed to evaluate the current status and effectiveness of the selected e-commerce websites.
It can be seen from the result that Jingdong, Dangdang and Tmall score the highest, while Newegg (www.newegg.com.cn)scores the lowest (0.154), which is also the last one in the top 10 B2C ecommerce websites in retail market in terms of transaction size and the main reason for the lowest score is few variety of the food products.It is no doubt that the Newegg in China can improve the transaction size by increasing the product variety and the other

Fig. 1 :
Fig.1: A conceptual model for online retailingVijayaraman and Bhatia (2002) define e-commerce as a process to buy and sell products through computerized business transaction.Choi et al. (1997) distinguish in their e-commerce model three elements: product, agent and process and they argue that the transactions where one of the above elements involves the internet will be e-commerce.According to this definition, buying food from a vending machine with a smart card can be seen as e-commerce(Turban et al., 2002).In this study, online consumers are restricted to those who buy products via internet websites.The consumer online behavior is studied by many researches.Szymanski and Hise (2000) study more than a thousand online consumers and find perception of convenience is the most important factor in terms of esatisfaction assessments.This conclusion has been supported by the research ofCorbett (2001), indicating convenience and time saving factors are the primary motivators of the online consumers.Mathwick (2002) study more than 800 shoppers and argues that consumers enter into online purchasing because they expect to receive positive value from their online participation.Sindhav and Balazs (1999) propose a conceptual model for on-line retailing, including three factors affect the growth of e-commerce: the company, the environment and the perceived consumer benefits.Perceived consumer benefits are, in their model, in turn seen as related to the medium, the consumer and the product.Grunert and Ramus (2005) review literature on factors that may have an impact on consumers' probability to buy food over the internet and suggest a modified model that delineates five groups of factor affecting perceived consumer benefits (Fig.1).A research bySingh (2002) argues that e-services are important in B2C e-commerce for managing customer relations and enhancing sales.Park (2002) puts forward a model of consumer buying intention online which includes five main factors that influence online purchase: product type, product interest, shopping

Fig. 3 :
Fig. 3: Summary of the evaluation of the top 10 B2C ecommerce websites in food retailing

Table 2 :
Top 10 B2C e-commerce websites in retail market in China

Table 3 :
Summary of the medium Alba et al. (1997).Interactivity refers to the work byAlba et al. (1997), who define it by response time and response contingency.Considering the websites perspective in this study, color assortment and visual attraction are included and it can be seen that most of the e-commerce websites (7 out 10) show satisfactory

Table 7 :
Summary of the firm

Table 9 :
The linguistic weights given by five experts