会议论文修改稿

Qun Wang1 Xiaohua Ou2Jun Xue3

Abstract: Through collecting about online stickiness behavior of relate d literatures, this paper mainly studied four aspects i.e.definition, measure, influencing factors and empirical analysis theory ,to summarize the curre nt research online stickiness behavior. The conclusion is abroad online stic kiness behavioral research advance, the domestic research rarely, and most of them involves a few specific areas.

Keywords: Online stickiness, customer loyal, TAM

1 INTRODUCTION

With the penetration of Internet technologies, Internet has been a part of many individuals’social lives.According to 27th statistical reports of CNNIC，By December of 2010 , the number of China's netizensto has arr ived 4.57 billion, increasing 7330 million by the end of 2009, Internet pe netration rate climbed to 34.3%, relatively 2009 improve 5.4%, And Inter net consumption behavior is increasingly becoming the academic research hotspot.Online stickiness behavior has direct impact on network consumpti on patterns and internet development pattern, So this paper mainly collect ed about online stickiness behavior of related literatures, thus summarizes the current research Online stickiness behavior.

2 DEFINITION OF THE ONLINE STICKINESS

In economics, the stickiness including price stickiness, wages stickines s etc., usually refers to commodity prices that the difficulty of changes. I n the network economics, the network stickiness is a new term, which co mbines the network characteristics with visitors behavior.

According to different emphasis from web with visitors，there are two two angles to understand stickness meaning in the existing research.

2.1 Stickiness is ability of website

Such as Boddoe—Stephens Yahoo(1999)、Davenport，T．(2000)、Bus h，E．(1999)、Sheri Rosen(2001)and Judy Chuan—Chuan Lin(2007) ect,fr om the perspective of sticky website or company , they point out that sti ckiness is the ability of websites to draw and retain customers. Haiping Wang(2009) also agree it is based on the visitors to site cognition and e motion, in the face of conversion pressure or other factors affecting witho ut changing the habits, continuous visit and use its preference site of attri bute. according to customer obtaining and retain the behavior characteristi cs and continuous time length，she divided the network stickiness into sho rt-term sticky and long-term stickiness.

2.2 Stickiness is usually described as the user’s dependence o r loyal ty on the website

Dahui Li(2006) defined stickiness from user’s view, considered sticki ness is repetitive visits and use of a preferred website because of a deepl y held commitment to reuse the website consistently in the future, despite situational influences and marketing efforts that have the potential to cau se switching behavior.

According to the definitions mentioned above, two aspects appear to be the most important: the duration and frequency of a user’s visit.

2.3The behavior of internet stickiness

Lin defined stickiness as user’s willingness to return to and prolong his/her duration of stay on the website. Based on relevant literature , thro ugh scientific statistics of customer loyalty in different definitions of conte nt and frequency ,Niwei Li (2006) found that "repeat purchase", "from ot hers," recommended "trust relationship" and "emotional preference" appear frequency is the highest . From understanding to angle of visitors, The meaning of stickiness smiliar to customer loyalty. And in a long time, cu stomer loyalty refer to he/she to target objects retain some degree of supp

ort and preferences, repeat purchase behavior,so two concepts consist in b ehavior.

3 THE MEASUREMENT OF ONLINE STICKINESS BEHAVIOR

In current there is no unified scale of measurment of visitor stickines s behavior .Kim Guenther (2004) pointed out that "stickinesse" is a user f lowers on the web site of the average time and visit the website frequenc y. This is a most usual measure scale ofinternet stickiness behavior. At th e same time,he noted that stickiness refers to the visitor experience about everything in internet, so can use their click stream data to measure stic kiness.

Nemzow (1999) pointed out repeat purchase can describe loyal custo mers in the business .Mohamed Khalifa etc (2002) use repeat purchase qu antity measurement online consumer stickiness substitute duration and freq uency.

4.INFLUENCING FACTORS OF THE ONLINE STICKINESS BEHA VIOR

For definition of the network stickiness is given from two angles--the web site and users, study the factor of the internet stickiness behavior is also from these two aspects:

4.1 View from the web site

Valczuch etc (2001) summed up the drivers of stickiness, divided th em into six types, type of content, dimension of content, sources of infor mation, auxiliary drives and sticky needs. The stickiness here is stressed the extension of stay.

4.1.1 Type of website content

4.1.2 Dimension of website content

Dimension of content is the depth, breadth and frequency of updates of the content.

The depth of the content is related to the stickiness of the site. Grea ter the intensity of the feature content’s vertical integration, more sticky the website for users(Hagelet a1．，1997). One way to create stickiness is to provide detailed information, the scope of available resources more wid ely, content more detailed, more informed the users to the information, th e site will become more sticky. The width of the content has positive eff ects on the stickiness(Davenport，2000). Greater range of services availabl e online, longer the users cling to the site. For they have more choices t o stay longer; the frequency of update enhances users’frequency and du ration. If update becomes frequency, the user must visit more often to ke ep informed.

4.1.3 Stickiness sources of information

Stickiness sources of information include the creative content from members, celebrities and experts. Hagel＆Armatrong(1997)pointed that the member- original content is the most stick. It is the information consumer s published in the bulletin board, guest register or chat room. The content is most sticky because the community members consider these informatio n are very reliable.

4.1.4 Sticky auxiliary driving factors

The auxiliary driving factors are the drivers help to increase the stick iness of the site but indirectly link with the content itself. Such as privac y, incentive plans, online special events, brand loyalty, personalization, re minder and navigation, etc. Which Brenner (1998) verified that respect the privacy of the users has a positive effect on the stickiness. Hagel & Ar mstrong (1997) tested that the site should organize special online events, t he purpose of organization events is to make people curious, so that they will constantly return to see if there are new event on the staged. Luedi a (1998)agreed that the Personality website will attract more people to cli ng to site longer, so the website should adjust the content to fit the need

s of individual users. In computer-mediated environment, people can achie ve a state of mind, in this psychological state, they experience the control of their activities, fully aware of these interactions, as the entertainment experience, Hoffman & Novak named this psychological state "flow''(fille d), when people experience filled, the independent thinking is filtered, the y will dedicated to the interaction with the system, resulting in lost the s ense of the passage o f time, then the access time is extended.

4.1.5 Common driving factors

Common drivers Include the virtual identity, social control, offline ev ents, motivation, friendly attitude of the visitor, etc.

4.1.6 The demand of stickiness

Based on the media system dependency theory, the theory thinks that there is interdependence b etween the individual and the media channels. People rely on media channels to meet certain basic needs. For this inter dependence exists is that the media control most of the information sourc es (DeFleur and Ball-Rokeach，1989). If a site can meet the basic needs of the individual, then for him the web site become stickier.

4.2 View from the customer

For the article studied the viscous from the perspective if consumers or users are so little, so the discussion of the factors influent the sticki ness is limited, mainly in the following factors:

4.2.1Site features

Judy Chuan-chuan Lin (2007) Select which the Rayport & Sviokla (1 994) proposed, the site content, context and infrastructure, these three vari ables that reflect the value of site to study the role of adherence intention s. In the study of Bansal etc (2004), compared to interpret the online swi tching behavior, the viscous behavior is seemed as the actual retention. W eb site features not only directly affect the stickiness, but also indirectly affect the stickiness through the overall site satisfaction. In addition to si

te features, such as company size, reputation of your site are also importa nt attribute factors, not yet discussed in the study of viscous.

4.2.2 Positive attitude toward the site

In addition to perceive of the quality of web content, Judy Chuan-ch uan Lin (2007) also showed that the attitude of consumers to the site and the trust to the site are the prerequisite for adhesion sites. In these three factors, the positive attitude toward the site is the most important factor that affect the viscous, and the attitude are also directly affect the trust to the site.

4.2.3 Overall satisfaction

In the research of Mohamed Khalifa(2002) etc, that attributed the fac tors affect the consumer stickiness (to measure re-purchase) to a variable –the overall satisfaction. And online shopping habits are as the factor b etween satisfaction and stickiness to test. Overall satisfaction is the funct ion of product satisfaction, sales process satisfaction and after sales satisfa ction. In Harvie S. Bansal (2004) study also pointed that the satisfaction with the overall site as a marketing results - and the factor of re-purchas e.

4.2.4 Commitment and trust

Commitment and trust are the core elements of relationship marketin g, is the indicator to study from the point of view of the relationship the quality of relationship between the site and its users. Judy Chuan-chuan Lin (2007) proved that consumers trust the site is a prerequisite for site a dhesion. But Dahui Li etc (2006) adopted the point of relationship to pro ve the role between commitment and trust, make that the user adhere to a Web site through the process of establishment, the adhesion sites reflect s the relationship between the sustained sites and the users.

4.2.5Characteristics of demographic

In Dahui Li etc (2006) stickiness study reveals the complexity of de mographic characteristics on the viscous Intentions. First, women are more likely to express intentions stickiness, this are consistent with the hypot hesis of women are more to show relationship (Cross, S.E. & Madson, L., 1997). Second, the more the age and years of experience with the co mputer, the more likely the user does not continue to use the current site. Finally, there are positive relation between more experience users and th e experience and stickiness of the site being evaluated. Only when Moha med Khalifa etc (2002) point the future direction of the research calls for an investigation of other types of products or industries, the merger of i ndividual characteristics to explain the possibility of customer stickiness.

5.THE THEORETICAL MODEL OF ONLINE STICKINESS OF EM PIRICAL ANALYSIS

Now internet stickiness empirical research has not been formed unifie d theory model.Most researchers improved model according to their resear ch direction or their field ,and then select a specific site type for empiric al research. Based on collection in current related documents,we found tha t This research in the field of roughly based on the following four theore tical model.They are Oliver (1980) proposed expectations confirm theory (ECT); Davis (1989) proposed technology acceptance model (TAM); Roger s (1995) proposed innovation diffusion theory (DOI) and Morgan&Hunt (1 994) proposed commitment - trust theory. Recent researcher by empirical study is based these theories synthetically modeling.

5.1 Research based on ECT theory

Bhattacherjee (2001)was the first who use the ECT theory into intern et stickiness empirical analysis. In order to make ECT theory more suitabl e for network environment, After modification of ECT models , Bhattache rjee obtained the Expectations Confirmation Model(As shown in figure 1). Through to randomly selected citibank online user carried on the question

naire survey to collect data, Bhattacherjee then used structure equation mo del to verify the research hypotheses, the conclusion of the support of all the hypothesis. Bhattacherjee ’s research affirmed of effectiveness and ap plicability of ECM model, and subsequent many studies based on the basi s of the model.

figure 1: ECM model

5.2 Research based on TAM theory

TAM, technology acceptance model, is put forward by Davis in 198

9. The structure of TAM model is simple, as shown below, and a large n umber of empirical studies have confirmed its value. Because that the TA M model describes the initial adoption of information system behavior, an d viscous behavior occurred after the initial adoption, so many scholars e xtend the TAM model, in order to study the viscous behavior.

Gefen (2003) using the TAM model to study the experienced user, in troduced the viscous behavior intention and used variables to verify wheth er the habits accumulated with experience affect the user's intention of vis cous behavior or not.

朗读显示对应的拉丁字符的拼音Chan and other scholars (2004) ver ified the adherence factors of user adoption and online banking in Hong Kong, introduced Subjective Norm, Image, Result Demonstrability, and Per ceived Risk to this model as the variables of perceived usefulness, and co mputer self-efficacy as the variable of perceived ease of user.

When studied the act based on sticky web learning technology of col lege students of Baltic States Estonia of the, Ifinedo (2006) joined the vis cosity intention in the TAM model as the dependent variable, while the te chnology characteristics, including ease of finding and ease of understandi Satisfaction

Confirmation

Perceived

Usefulness

Continuance Intention Perceived

Playfulness

ng, and user characteristics, including self-efficacy and computer anxiety , as exogenous variables.

The conclusion of path analysis showed that, technical characteristics and user characteristics had a positive impact on perceived usefulness and ease of use, perceived ease of use significantly affected the perceived us efulness, only perceived ease of use affected the use of the system, but p erceived usefulness and system using both had the positive impact on the sticky intention.

Naidoo and Leonard (2007) incorporated service quality variable and loyalty incentives variable in the improved TAM model, constructed an E-Service viscous model, assuming that the service quality and loyalty incen tives have significant effects on viscosity intention as perceived usefulness. After the research hypotheses were verified, they found that the service quality, loyalty incentives and perceived usefulness were significantly affec ted viscosity intentions, and perceived usefulness was the adjustment varia ble between service quality and viscosity intention.

Kim and Malhotra (2005) had a longitudinal study based on the TA

M model, constructed a two-stage model to explain the user perception an d evaluation of the network how to evolve with the accumulation of netw ork using experience. At every stage of constructing this model, four vari ables: system use, perceived usefulness, perceived ease of use and use int ention were included. The results showed that the perceived ease of use s ignificantly affected the the perceived usefulness and intention use at each stage; system use, perceived ease of use and perceived usefulness in first stage had significant effects on the same corresponding variables in seco nd stage; except the perceived usefulness variable in the first stage, other variables were significantly affected the use intention in the same stage.

5.3 Research based on the DOI theory

Diffusion of innovation theory is put forward by Rogers in 1995, ha d repeatedly been used in the network sticky research area. For users, the innovation is a new thinking, new practices or new things (Everett M. R ogers, 1995), when DOI theory was applied in the field of information sy stems, the specific information system was considered innovation. Innovati ve decision-making process includes five stages, namely the knowledge sta ge, persuasion stage, decision stage, implementation stage and confirmation stage. In persuasion stage, five characteristics of innovation will affect us ers’perception of innovative Online stickiness or deny, which are: relativ e advantage, compatibility, complexity, trialability and observability.

Back in 1998, Parthasarathy & Bhattacherjee put DOI as a theoretical framework to study the users’Online stickiness behavior to online servi ce, distinguished potential sticky and potential of non-sticky by personal c haracteristics and perceptual belief. By multiple discriminate analysis, the sticky who perceived usefulness and compatibility were stronger than non-sticky; in addition, the external influence, interpersonal influence, utilizatio n and network externality which the sticky perceived were also stronger t han non-sticky.

5.4 Commitment - trust theory

Dauhui Li(2002) integrated the theory of The Investment Model ”“C ommitment-Trust theory”and “Multidimensional Commitment,then set up the model as bellow:

Dahui Li demonstrates the commitment and trust hypothesis by the n et continuous use relationship theory, stated that users would show stickin ess to a web through establishing a relationship with the web site. So sti ckiness reflects the relationship between continuous web use and the user s. From the customers' perspective, by referring to the social psychology t heory and relationship sales theory,he set up a website stickiness module which considers the relationship between user and websites , commitment

and trust as critical inter variables,then demonstrated the obvious connecti on of continuous use intention commitment and trust.But Dahui Li(2007) i n another article,tested the differentiations on the relation orientation betwe

en stayers and

swichers by useing the relationship theory.figure 3: A Conceptual model of stickiness based on commitment-trus t theory

（note: means direct positive relation ；means direct negat ive relationship ；means indirect positive relationship ）

5.5 The other comprehensive theory

5.5.1The integration of TAM,TRA ,TPB and commitment –trust the ory

Based on the main factors of reasoning action theory (TRA),Haiping

Wang （2009）built concept model reference technology acceptance model (T

AM). According to TRA theory,faith attitude directly influence the attitud e, and attitude influence on purchase intention.From online consumer's poi nt of view, based on the cognition,her research combined the emotional fa ctors and constructed a "" as the main path of short-term viscosity formin g model.

figure 4: A Conceptual model of short-term stickiness of Wang Haipi ng ’s research Based on the TAM, TRA, TPB, commitment - trust model, investme

nt model and so on the related theory, Haiping Wang ’s research formed

a long-term stickiness conceptual model.investment

Size communicati

on quality opportunistic behavior

normativ e

trust

use intention

stickness Perceived useness

Perceived ease Initial trus t flows Perceived risk

attitude Short-term stickiness

intention Perceived

information quality & Perceived system qualitye Perceived

reputation flows

Continuous trust Overall satisfaction

Perceived conversion cost commitment

Long-term stickiness

intention Practical transactions Perceived information qualitye Perceived information quality Perceived reputation

figure 5: A Conceptual model of long-term stickiness of Wang Haipi ng’s research

5.5.2 The integration of ECT , TRA&TPB theory

Based on the Triandis model and integrated of theory ECT,TRA and TPB theory, Hong&Lee (2005) constructed stickiness model including habi ts, Perceived Switching cost,Dual standards of Quality), satisfaction and B ehavioral Attitude variables, and Dual standards of Quality include desire-congruency & expectation-congruency.

5.5.3 The integration of Interaction theory&Cultural Lens Model

Based on Interaction Theory and Cultural Lens Model, Lee(2007) pro posed a new model that study the role of the cultural factors in mobile n etwork service stickiness. The research hypotheses satisfaction directly affe cts stickiness intention, four kinds of network stickiness post- adoption pe rception that is perception usefulness, perception of interest, perceived eas e of use and perceived monetary value. These four kind of network sticki ness post-adoption perception directly influence the satisfaction,and respecti vely by four cultural factors that is uncertainty avoidance, individualism, c ontext and time perception. Through large-scale web survey respectively K orea, Hong Kong and Taiwan several big Mobile network services compa nies’users, this study obtained the data of different cultures. Research re sults show that all the hypothesis model is verified, namely these four ki nd of network stickiness post-adoption perception directly influence the sat isfaction,and respectively by four cultural factors.

6 CONCLUSIONS

The conclusion is abroad online stickiness behavioral research be adv anced in theoretical research and empirical research, the domestic research rarely concentrated in the theoretical research, especially measurment of online stickiness behaivor. Furthmore, most of the domestic empirical rese arch stickiness of online consumer behavior based on the website or the e

nterprise, few paid attention to the consumer & socility. So furture researc h in these respect should be strengthen.

ACKNOWLEDGEMEN

This research was supported by the National Social Science Foundati on of China under Grant 10BGL099.

REFERENCES

[1] Haiping Wang (2009) The Research of Online Customer Stickines s,Jinan : 43-48;

[2] Dahui Li，Glenn J．Browne，Patrick Y.K．Chau．(2006)An Empi rical Investigation of WebSite Use Using a Commitment-Based Model．De cision Sciences，37(3)：427-444．

[3] Dahui Li (2002) Why do intetnet users stick in website,.MI:22-24

[4]Yao Chen,Peiji Shao(2010), reviewed of Empirical research in Infor mation system continuous use. Management experts，04：62-69

[5] Albert Hayashi,Charlie Chen,Terry Ryan,Jiinpo Wu(2004).TheRole of Social Presence and Moderating Role of Computer Self Efficacy in Pre dicting the Continuance Usage of E-Learning Systems[J].Journal of Inform ation Systems

Education, 15(2):139-154.

[6] Anol Bhattacherjee,(2001).Understanding I nformation SystemsConti nuance:An Expectation-Confirmation Model[J].MIS

Quarterly, 25(3):351-370.

[7] Anol Bhattacherjee,Johan P erols,Clive Sanford. (2008),Information Technology Continuance:A Theoretic Extension andEmpirical Test[J].The Jo urnal of Computer InformationSystems, 49(1):17-26.

[8] Inseong Lee,Boreum Choi,Jinwoo Kim,Se-Joon Hong (2007).Cultur e-Technology Fit:Effects of Cultural Characteristics

on the Post-Adoption Beliefs of Mobile Internet Users[J].International Journal of Electronic Commerce, 11(4): 11-51

.[9] Moez Limayem,Sabine Gabriele Hirt,Christy M.K.Cheung.(2007) How Habit Limits the Predictive Power of Intention:

The Case of Information Systems Continuance[J].MIS,31(4):305-317

[10] the 27th Statistical Reports of CNNIC(2011)，Beijing：1-2