SIMULATION RESEARCH ON THE MOBILE

E-COMMERCE PROCESS OF NON-GRID AND GRID BASED ON

ARENA

Dan Chang, Yan Liang

School of Economics and Management, Beijing Jiaotong University, Beijing, China

Sheng Zeng

School of Economics and Management, Beijing Jiaotong University, Beijing, China

Keywords: Mobile e-Commerce process, Grid management, Arena, Simulation.

Abstract: The research on the process of Mobile E-commerce has become the focus. Both building new process and

optimizing old process, determining the reasonability and reliability of the process by a scientific means is

needed. This paper will finish the task below. Firstly, put in order the process of Mobile E-commerce and

form the appraisal system. Secondly, simulate the model of Grid and Non-grid Mobile E-commerce process.

Finally, appraise the out coming based on the appraisal system and point out the superiority of Grid Mobile

E-commerce process. This paper is used to provide a new way of thinking in the research of Mobile E-

commerce, for the purpose of integrating theory with practice and making for society.

1 INTRODUCTION

With the development of Mobile E-commerce

industry and Grid Management Theory in recent

years, Mobile E-commerce has developed to the

specific facts and the application stage. Foundation

Joint has got more and more attention. On the

research of Mobile E-commerce, the process

research is always the focus.

Both building new process and optimizing old

process, determining the reasonability and reliability

of the process by a scientific means is needed.

However, the building of traditional process relies

mainly on the experience and the appraisal focuses

on qualitative aspects. For a complex process, the

main points can not be seized. So a scientific means

to reflect and evaluate the process is needed.

System simulation as a product of this demand

came into being. With its unique approach to process

design and optimization and reliable quantitative

data, system simulation shortens the cycle and

improves the scientific decision-making during the

process optimization. As a simulation tool used in

discrete systems, continuous systems and hybrid

systems, Arena is widely used in different situations

at all levels of the simulation. This paper takes it as a

simulation tool to apply to the evaluation of Mobile

E-commerce process.

Arena is one of the representative simulation

software, developed by Rockwell Software. It can

create many kinds of simulation models, such as

production system model, service system model and

so on. Arena can use parameters to simulate one

dynamical system as true as possible, while it can

keep itself easy to use and flexible depend on its

hierarchical structure. Arena can even be integrated

with some program language, just like Microsoft

Visual Basic and C language, which makes itself

more suitable for simulation optimization.

Simulation process is divided into four steps. Firstly,

create simulation model. Secondly, set the

parameters of simulation model. Thirdly, run the

simulation model. Lastly, verify the simulation

model, analyze the result and choose the best

solution. In addition,

Arena uses event scheduling

method, which uses events to analyze the system and

determines logical relationship by delimit events and

the change of system state.

Meanwhile, the formulation of mobile grid

theory provides an integrated, open and dynamic

486

Chang D., Liang Y. and Zeng S..

SIMULATION RESEARCH ON THE MOBILE E-COMMERCE PROCESS OF NON-GRID AND GRID BASED ON ARENA.

DOI: 10.5220/0003584804860494

In Proceedings of the 13th International Conference on Enterprise Information Systems (SSE-2011), pages 486-494

ISBN: 978-989-8425-53-9

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

environment for the building of Mobile E-commerce

process. It integrates sellers’ data to provide

customers an access to resources with a unified

interface. Customers and sellers communicate timely

and smartly, greatly improving the sharing of

information and resources.

Therefore, applying the mobile grid theory and

simulation technology to building and optimizing

Mobile E-commerce process and building the

Mobile E-commerce process based on grid provide a

new way of thinking in the research of Mobile E-

commerce.

This paper builds the appraisal system of Mobile

E-commerce process based on the research at home

and abroad. Then put in order non-grid Mobile E-

commerce process and simulate the model of

process in Arena. Thirdly, build grid Mobile E-

commerce process based on the application of

mobile grid theory and simulate the model. Finally,

appraise and compare the out comings based on the

appraisal system and point out the superiority of the

grid model.

2 LITERATURE REVIEW

At the first International Conference of Mobile

Commerce Mylonopoulos proposed a broad

definition of Mobile E-commerce: “Personal

participants and business groups use wireless and

mobile technology to create a new learning process

of social interactive experience in specific historical

and social environment.” (N.A.Mylonopoulos, 2003)

Therefore, Mobile E-commerce refers to the

business activities through the combination of cell

phones, PDA, notebook computers and other mobile

communication terminals with the Internet.

In the late 1990s, since the advent of Mobile E-

commerce application, scholars began to study the

theory. But it is still in the early stage because the

practice time is short.

The researches which have a certain influence

are P-graph model (Heijden and Valiente, 2002) for

Mobile E-commerce process by Heijden and

Valiente and the Process Landscaping method

(Volker Gruhn, 2003) by Gruhn.

In P-graph model there are actors, activities,

locations and other model elements. The business

activities form a structure of relations in space and

time, including decision making, control and

coordination. P-graph model is simple and intuitive

by marking the place of actors and the mobile state

of actors to identify the possible introduction of

wireless information technology. It is easy to

analyse and design business process.

Gruhn proposes a "mobile business process"

concept and the Process Landscaping method.

Operational implementation has a particular

distributed architecture, while the executors have the

mobility. He proposes that mobile business

processes has three different characteristics with

other business processes: the uncertainty of position

and its determinants, the requirement of process

implementation and coordination of external

resources. Process Landscaping method is further

than the P-graph model. It uses the procedure as the

basic element of the process design and decomposes

the business activities into perlsub. Ultimately

determine the location of those actors and identify

interactive information.

Domestic mobile business management scholars

have gradually further study, such as “the analysis

of Mobile E-commerce payment models and safety”

by Deli Yang, “the empirical model and simulation

of Internet content service pricing” by Zhongding

Zhou, “Acceptable model of Mobile E-commerce

and the key success factors in the enterprises

implementation” by Haiqi Feng, “the Study of basic

theory and technical methods in Mobile E-

commerce” by HUST, “Comparative Study of

Mobile E-commerce services between Korean and

China: Government Policy and Corporate Strategy”

by Tsinghua University and so on.

However, the domestic research of Mobile E-

commerce mainly focuses on the basic theory,

information security, industry level analysis,

government policy formulation, technical

application and diffusion. The researches of process

are lacked. Only a few scholars simulate and analyze

Mobile E-commerce process based on Petri or

Flexism.

In summary, the research of Mobile E-commerce

process is still scattered and in the state of

qualitative description. Overall research and

modeling method are needed. There are many kinds

of modeling and simulation software, such as GPSS,

SIMSCRIPT, SLAM, Flexism, and Arena. This

paper uses Arena not only because of its visual

interface, but also because of its unparalleled

advantages for the process of simulation.

SIMULATION RESEARCH ON THE MOBILE E-COMMERCE PROCESS OF NON-GRID AND GRID BASED ON

ARENA

487

3 THE APPRAISAL SYSTEM OF

MOBILE E-COMMERCE

PROCESS

3.1 The Comprehensive Appraisal

System of Mobile E-commerce

Process

In the traditional process of E-commerce and Mobile

E-commerce research, it did not have a set of

appraisal system for Mobile E-commerce process.

However, many researchers did some research on

the website of Mobile E-commerce, customer

satisfaction and sellers’ credit. In addition, some

scholars carried out analyse and research on the

Mobile E-commerce process through the

establishment of the process evaluation model and

simulation methods.

 The Research of Foreign Scholars

LEE (LEE, 2001) believes that customer

satisfaction decides repurchase rate of one online

shop. And he brings forward customer satisfaction

model in E-commerce. Yang and Jun (Yang Zhilin,

Minjoon Jun, 2002) find that reliability is one of the

most important indexes of service quality.

Vijayasarathy and Jones (Vijayasarathy Leo R, 2000)

believe the predilection and attitude of customers

decide the satisfaction, concluding from their

research on Internet customers. Szymanski and Hise

(Szymanski D M, Hise R T, 2000) think that

convenience, website design and safety could affect

customer satisfaction.

 The Research of Domestic Scholars

Jinxiang Zha

(Jinxiang Zha, 2006) studies from

the perspective of the shopping websites and sets up

a structure model among the service quality,

customer expectation and customer satisfaction. The

author divides the service quality into eight

dimensions: web design features, network security,

interactive of the network, product quality

assurance, convenience of the website, price

advantage, and operation difficulty of the website.

The author also did an empirical research on the

sample of college students who are one of the main

participants in current shopping online. And the

empirical research suggests that network security,

price advantage and the product quality assurance

are the main factors of improving customer

satisfaction.

Ximei Dong (Ximei Dong, 2007) sets up a

customer satisfaction index system based on the

factors of customer satisfaction in the environment

of E-commerce. The article points out five kinds of

factors may have influence on customer satisfaction:

transaction security, product information, the

website design, service integrity and marketing

planning.

Guo and Liang (Yan Guo, Laizhen Liang, Dazhi

Huang, 2007) elaborate the importance of customer

satisfaction in the network economy. They point out

the main factors which affect customer satisfaction:

product quality, safety, service quality and

convenience. And this paper also puts forward some

strategies to improve customer satisfaction.

Jianfeng Hong (Jianfeng Hong, 2007) analyzes

the factors that affect customer satisfaction in the

model of C2C E-commerce, based on the study of

traditional customer satisfaction and the

characteristics of C2C E-commerce. The factors are

C2C web site, online shop, online shop type and

individual customer’s characteristics. On the level of

C2C website, the web technologies and transaction

security are important. On the level of online shop,

the value of products, service and image value are

the main factors. But the online shop type and

individual customer’s characteristics are different

according to the product properties.

Establishing a scientific appraisal system of

Mobile E-commerce should follow the scientific,

comprehensive, feasible and comparable principle.

The selection of indicators should cover all the

requirements and characteristics of Mobile E-

commerce process and avoid the association

between indicators.

According to the research of domestic and

foreign scholars above, build a more comprehensive

and unified appraisal system of Mobile E-commerce

process from the website of Mobile E-commerce and

customer satisfaction as Table 1.

This paper builds a more comprehensive and

unified appraisal system of Mobile E-commerce

process from the website of Mobile E-commerce and

customer satisfaction as Table 1. Most indicators are

applied for qualitative analysis and comprehensive

as far as possible. However, qualitative analysis is

not enough systematic and convincing. The

simulation model only evaluates several specific

aspects. Therefore, this paper evaluates Mobile E-

commerce process as the thread below: Firstly,

establish the appraisal system as comprehensive as

possible through qualitative analysis. Then convert

the indicators that are not easy or inaccurate to

evaluate through qualitative methods into indicators

for quantitative analysis. Lastly, simulate the

simulation model using Arena and analyse the

results.

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

488

Table 1: The comprehensive appraisal indicators of

Mobile E-commerce process.

appraisal indicators

first-level

indicators

secon

-level

indicators

third-level indicators

website

service

T1 communication tools

T2 individuation

T3 BLOG, RSS

T4 help online

technology

T5 website access speed

T6 searching function

T7 design friendly

content

T8 clear navigation

T9 rich information

T10 copywriter quality

T11 update information

in time

process

T12 simple step

T13 clear exit path

T14 accurate statistics

customer

satisfaction

online store

condition

T15 types of goods,

prices and other

information

T16 update goods in time

T17 whether the goods

correspond with the

actual

pre-sale and

after-sale

service

T18 response to

questions

T19 return goods

T20 personalized service

payment

T21 types of transaction

T22 security of

transaction

T23 the protection of

customer privacy

logistics and

distribution

T24 logistics and

distribution methods

T25 logistics and

distribution time

T26 package integrity

3.2 The Simulation Appraisal System

of Mobile E-commerce Process

The quantitative evaluation of the indicators requires

complex process, so the number of indicators can

not be too much. Select quantifiable indicators from

Table 1 and convert the many indicators into a few

composite indicators using principal component

analysis. Then establish the quantitative indicators

table of Mobile E-commerce process. After

classification of the intrinsic link between indicators,

select the principal component indicators and

establish the quantitative indicators table of Mobile

E-commerce process as Table 2.

Table 2: The quantitative indicators of Mobile E-

commerce process.

principal

component

indicators

comprehensive

indicators

simulation

indicators in

Arena

service response

capabilities

T1、T2、

T6、T8、T14

Wait Time

system

operating time

T12、T13

、T19、T21、

T25

Total Time

service

congestion

T5、T11、

T16、T18

WIP

service intensity

T3、T4、T7、

T9、T10、

T15、T20、

T22、T23、

T24、T26

Instantaneous

Utilization

According to principal component analysis, find

the internal relevance among a number of indicators

and use four new indicators that have poor

correlation to reflect most of the information among

Table 1. Appraise Mobile E-commerce process

through analysing the four new indicators that

reflects in the Arena simulation system as Wait

Time, Total Time, WIP and Instantaneous

Utilization. In summary, by analyzing Wait Time,

Total Time, WIP and Instantaneous Utilization the

operational capabilities and actual results of Mobile

E-commerce process can be reflected

comprehensively and reasonably.

4 THE SIMULATION OF

NON-GRID AND GRID MOBILE

E-COMMERCE PROCESS

4.1 The Simulation of Non-grid Mobile

E-commerce Process

4.1.1 The Process of Non-grid Mobile

E-commerce

The main difference between Mobile E-commerce

process and traditional E-commerce process is that

they use different terminals. Traditional E-

commerce mainly uses the Internet to communicate

with customers. Position is fixed. While Mobile E-

commerce combines Phone, PDA, notebook and

other mobile terminals with the Internet to achieve

mobile and individual service. Therefore, Mobile E-

commerce process and traditional E-commerce

process are similar. The difference lies in the

customer's authentication and access points.

SIMULATION RESEARCH ON THE MOBILE E-COMMERCE PROCESS OF NON-GRID AND GRID BASED ON

ARENA

489

This paper studies the process and sums up the

general non-grid Mobile E-commerce process as

figure 1.

Figure 1: The Non-grid Mobile E-commerce process.

Firstly, the user enters the information platform

through mobile equipment to search target product

or service information. However, due to various

platforms assigned to different users with different

access rights and the lack of a unified interface

between different platforms, the information can not

be shared. If the user can not search satisfied

information from the platform, he needs to enter

other platforms to search information until he gets

useful information.

Secondly, after receiving more than one seller's

product information or service information, users

need to compare them and determine which to buy.

Then submit orders to the appropriate seller.

Thirdly, after confirming the order, users need to

do mobile payment, while the seller organizes to

finish the logistics and distribution.

Finally, the user receives the goods, which

indicates that the transaction is successful.

4.1.2 The Simulation of Non-grid Mobile

E-commerce Process

This paper simulates Mobile E-commerce process

through Arena. The model’s building and

parameters’ setting will be strictly in accordance

with the rules for the implementation of Arena

simulation, using the full hierarchical structure of

the modeling method.

According to the method, convert the process

model into logic model as figure 2. The logic model

is divided into three parts: the incident arrive, the

operation of the main process (MBP) and the

incident left. The incident arrive module gets user

demand and completes access point selection; MBP

module completes the product selection, payment

and distribution; the incident left module is

responsible for follow-up treatment.

Figure 2: The logic model of Mobile E-commerce process

on non-grid.

According to the rules for the implementation of

Arena simulation, convert the logic model into

simulation model as figure 3.

 The user enters the platform according to

certain rules and user demand will be gotten

by the system. Assuming the user's reach is

relatively independent and data fluctuates

strongly, set the parameters to consistent with

the exponential distribution with mean 5 and 1

entity reaches during the average time.

 If the user’s requirements are not met, then log

out the current platform and continue to

submit other platforms.

 If the user's requirements are met, then confirm

the order and complete mobile payment. After

the seller completes logistics and distribution,

transaction is implemented. Transacting of

each module reflects a certain probability

distribution. There is a "most likely” time

among the transacting time for each module,

while other time fluctuates near the "most

likely” time.

4.2 The Simulation of Grid Mobile

E-commerce Process

By analyzing the process of non-grid Mobile E-

commerce, this paper finds that the resources of

Mobile E-commerce domain are not integrated

efficiently.

The lack of resources hinders the development of

Mobile E-commerce in some small enterprises,

while other resources are vacant in large enterprises.

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

490

Figure 3: The simulate model of Mobile E-commerce process on non-grid.

The phenomenon not only results in great waste of

resources, but also hinders the development of

Mobile E-commerce. For the customers, there is not

a unified and integrated platform. They need to visit

different sites to browse and compare a lot of

merchandises to meet their own needs.

At the same time, this paper finds that the user

waiting time is the key factor which constraints the

process through the Arena simulation, while nearly

90% of the time customers are waiting for service in

the entire service process. A lot of time waiting in

line reduces order processing speed and web site

accessing speed greatly. Customer satisfaction is

also reduced.

The emergence of grid management provides a

theoretical and technical support and effective

solutions to solve the above problem. The purpose of

the grid is to integrate all physical and logical

resources into a virtual super-computing

environment, which breaks the previous restrictions

on computing resources, such as geographic location,

computing power, sharing and collaboration

restrictions. So people can use computing resources

freely and conveniently.

To solve these problems, based on grid management

theory, this paper constructs grid Mobile E-

commerce process and establishes a comprehensive

resource platform. To provide customers an

integrated, open and dynamic environment with a

unified resource access interface, the platform

integrates business resources to make

communication better between users and sellers.

Therefore, Mobile E-commerce process is that

applying mobile grid theory to traditional Mobile E-

commerce process for resource integration and

better communication.

4.2.1 The Process of Grid Mobile

E-commerce

The idea of constructing Grid Mobile E-commerce

process is to build a mobile business domain, which

is made up of sellers, customers and the integrated

resource platform. The seller has its own

independent business system. The integrated

resource platform is the bridge of communication

between sellers and customers. It is responsible for

information integrated into a unified platform and

presented to the customers. The handling of business

is finished in the integrated resource platform.

Figure 4: The Mobile E-commerce process on grid.

As shown in Figure 4, for the users, they enter

the information platform through mobile equipment

to search target product or service information. After

receiving more than one seller's product information

or service information, users need to compare them

and determine which to buy. Then submit orders to

the appropriate seller. Thirdly, after confirming the

order, users need to do mobile payment, while the

seller organizes to finish the logistics and

distribution. Finally, the user receives the goods,

which indicates that the transaction is successful.

the user's entire operation, users only need to

log an integrated resource platform to complete a

series of operations without entering other platforms.

These operations are done by the integrated resource

SIMULATION RESEARCH ON THE MOBILE E-COMMERCE PROCESS OF NON-GRID AND GRID BASED ON

ARENA

491

platform automatically. Many sellers’ information is

integrated in a unified platform, which allows users

to complete mobile payment through task package

judgment and order distribution.

4.2.2 The Simulation of Mobile E-commerce

Process Based on Grid

According to the Arena simulation method, convert

the process model into logic model as figure 5. The

logic model is divided into three parts: the incident

arrive, the operation of the main process (MBP) and

the incident left. The incident arrive module gets

user demand and completes access point selection;

MBP module completes the product selection,

payment and distribution; the incident left module is

responsible for follow-up treatment.

Figure 5: The logic model of Mobile E-commerce process

on grid.

According to the rules for the implementation of

Arena simulation, convert the logic model into

simulation model as figure 6.

 The user enters the platform according to

certain rules and user demand will be gotten

by the system. Assuming the user's reach is

relatively independent and data fluctuates

strongly, set the parameters to consistent with

the exponential distribution with mean 5 and 1

entity reaches during the average time. The

rules are the same as those in non-grid mode.

 If the user's requirements are met, then confirm

the order and complete mobile payment. After

the seller completes logistics and distribution,

transaction is implemented. Transacting of

each module reflects a certain probability

distribution. There is a "most likely” time

among the transacting time for each module,

while other time fluctuates near the "most

likely” time.

5 THE COMPARISON OF

SIMULATION RESULTS

BETWEEN NON-GRID AND

GRID

5.1 Setting a Simulation Example

This paper studies Mobile E-commerce process.

Unlike the typical production business system,

reliable data can not be obtained. So Arena refers it

as "special data ". For this type of data, if it is

relatively independent and fluctuates strongly, set

the parameters to consistent with the exponential

distribution. If time data represents activity and there

is a "most likely” time among the transacting time

for each module, while other time fluctuates near the

"most likely” time, set the parameters to consistent

with the triangular distribution. Thus, each module's

parameter setting are used to reflect the probability

distribution, monitoring and decision-making

aspects are omitted, and assuming that system is in

normal operation; system stakeholders are skilled in

operation, and no conflict or acts are carried out;

resource status is always good.

Figure 6: The simulate model of Mobile E-commerce process on grid.

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

492

The simulation parameter setting assigns the non-

grid mode as the benchmark, which makes the non-

grid mode is at a higher busy status and the resource

allocation of each node process is also more

balanced. In order to make the simulation also has

certain practical reference value, the parameter

setting of the grid mode references to the non-grid

model and reality.

A simulation example sets a period of 8 hours;

the user demand can be submitted at any time; the

basic statistical unit is minute. Since the existence of

random factors, any two simulation results are

probably not the same. Therefore, this simulation

adopts the results of statistical with 10 times.

5.2 The Analysis of the Simulation

Results

As Table 2, the four principal component indicators:

service response capabilities, system operating time,

service congestion and service intensity, are

corresponded to the four Arena simulation indicators:

Wait Time, Total Time, WIP and Instantaneous

Utilization. Therefore, this paper analyses the results

from Wait Time, Total Time, WIP and Instantaneous

Utilization as figure 7 to 10.

Wait Time

non-grid grid

minutes

Figure 7: The comparison of Wait Time between non-grid

and grid.

Total Time

non-grid grid

minutes

Figure 8: The comparison of Total Time between non-grid

and grid.

WIP

non-grid grid

number

Figure 9: The comparison of WIP between non-grid and

grid.

Instantaneous Utilization

37%

70%

81%

94%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

resource 1 resource 2

non-grid

grid

Figure 10: The comparison of Instantaneous Utilization

between non-grid and grid.

 The Comparison of Wait Time;

Wait Time is the period from customer’s arrival

time to start time that he receives service. This

indicator evaluates service response capabilities.

Shown in Figure 7, by adding the grid management

theory to Mobile E-commerce process, the user's

average waiting time is reduced to 30% of the

original and the system processing speed is greatly

improved. Therefore, the grid mode has an

advantage in service response capabilities than the

non-grid mode.

 The Comparison of Total Time;

Total Time is the period from customer’s arrival

time to end time that he receives service. This

indicator evaluates system operating time. Shown

in Figure 8, by adding the grid management theory

to Mobile E-commerce process, the system

operating time is about 40% of the original and the

time required is greatly improved. Therefore, the

grid mode has an advantage in system operating

time than the non-grid mode.

 The Comparison of WIP;

WIP is the number of customers in the system, the

sum of the number of customers waiting in line

and the number of customers in service. This

indicator evaluates service congestion. Shown in

Figure 9, by adding the grid management theory to

SIMULATION RESEARCH ON THE MOBILE E-COMMERCE PROCESS OF NON-GRID AND GRID BASED ON

ARENA

493

Mobile E-commerce process, the WIP is reduced

to 61% of the original. Therefore, the grid mode

has an advantage in service congestion than the

non-grid mode.

 The Comparison of Instantaneous Utilization;

Instantaneous Utilization is the utilization of

resources during the entire service. This indicator

evaluates service intensity. Shown in Figure 10,

the resource utilization improves greatly on grid

mode. Therefore, the grid mode has an advantage

in service intensity than the non-grid mode.

From the above analysis, the Wait Time, Total

Time and WIP on non-grid mode are longer

compared with the grid model. Because on the non-

grid mode, the business services are separately

controlled by computer and the user needs to search

for resources on different platforms. While on grid

mode the user needs to submit only once demand,

then he can get all of the corresponding information.

This advantage on grid mode will reflect more

obvious when the order involves a number of

companies.

6 CONCLUSIONS

With the development of information technology,

Mobile E-commerce has entered the stage of service

as the theme and process optimization as the main

line. The main difficulty is how to share information,

collaborate and reengineer business process. This

paper, combining qualitative analysis method with

quantitative analysis method and using Arena, forms

the appraisal system and simulates the model of

Mobile E-commerce process based on Grid and

Non-grid. Finally, point out the superiority of the

model based on Grid and provide a new way of

thinking in the research of Mobile E-commerce.

However, many aspects of this paper are needed

to be strengthened, especially setting the parameters

according to Arena simulation rules. This paper will

further the research and collect more reliable data to

evaluate the models more reasonably.

ACKNOWLEDGEMENTS

Firstly, thank my teacher and classmates, who

provide me with a lot of support during the research.

Here I appreciate them a lot. Secondly, I thank my

family and friends, whose support is the guarantee of

my success.

REFERENCES

Wenjin Zhao, Zhaoxiang Shi, Shuguang Huang,

2006.32(5). Survey of mobile grid computing.,

Application of Electronic Technique.

Lijuan Du, Zhenwei Yu, 2010.31(6). Development of

Mobile Grid., Computer Engineering and Design.

Jian Li, Lijuan Liu, 2007.7(510):138. The Impact of 3G on

Mobile E-commerce, Market modernization.

Wei Huang, Runxiao Wang, Nan Shi, Dongbo Wang,

2006(10). Review Study on Mobile E-commerce.,

Application Research of Computers.

Weidong Li, 2008. Applied Multivariate Statistical

Analysis, Peking University Press. Beijing, 1st edition.

Mu Yang, Runtong Zhang, Hailou Yang, 2009.4. C2C E-

commerce Transaction Process Analysis and

Improvement of the Advantages and Disadvantages.,

Commercial Times.

N. A. Mylonopoulos, G. I. Doukidis. 2003.8(l):5-22.

International Journal of Electronic Commerce, Mobile

Business: Technological Pluralism, social assimilation

and growth.

Valiente P, H. Van Der Heijden. 2002. SSE/EFI Working

Paper Series in Business Administration, Stockholm

School of Economies, A method to identify

opportunities for mobile business processes.

Volker Gruhn, 2003. Mobile Business Processes.

IICS2003LNCS2877.

Lee, 2001. Comprehensive Model of Internet Consumer

Satisfaction, Hong Kong: City University of Hong

Kong.

Yang Zhilin, Minjoon Jun, 2002.19(1):19－41. Consumer

Perception of E － service Quality: From Internet

Purchaser and Nonpurchaser Perspectives. Journal of

Business Strategy.

Vijayasarathy Leo R, Jones Joseph, 2000. M Intentions to

Shop Using Internet Catalogues: Exploring the Effects

of Product Types, Shopping Orientations, and

Attitudes towards Computers, Electronic Markets.

Szymanski D. M, Hise R. T, 2000. E-satisfaction: An

Initial Examination, Journal of Retailing.

Jinxiang Cha, Lisheng Wang, 2006.19(1):50-58. Empirical

Study of Influential Elements of E-satisfaction.,

Management Sciences In China.

Ximei Dong, 2007. Index System and Evaluation Model of

the E-Commerce customer satisfaction., Sci-Tech

Information Development & Economy.

Yan Guo, Laizhen Liang, Dazhi Huang, 2007. Research

about customer satisfaction online shopping.,

Enterprise Vitality.

Jianfeng Hong, 2007. Research on factors of Customer

satisfaction in the model of C2C., New Western.

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

494