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Australian Journal ofBUSINESS & MANAGEMENT RESEARCH

Vol. 2 No. 7 2012

Listing & Indexing


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E D I T O R I A L B O A R D

DR GAVRIEL AYI AYAYIUniversit du Qubec, Canada

DR MADAN LAL BHASINCollege of Business Fiji National University, Fiji Islands

DR KEOY KAY HOOICentre of Excellence for Research, Value Innovation and Entepreneurship (CERVIE) UCSIUniversity, Kuala Lumpur Campus

DR JIN-LI HUNational Chiao Tung University, Taiwan

DR SULEYMAN DEGIRMENMersin University Ciftlik Koy Campus, Turkey

DR JUAN-ANTONIO MONDEJAR JIMENEZVice-Dean of the Faculty of Social Sciences of Cuenca,Spain

DR HUNG HSU-FENGNational ChengChi University, Taiwan

DR TEH PEI LEEMultimedia University, Malaysia

DR. HUSAM-ALDIN ALMALKAWIALHOSN University, Abu Dhabi, UAE

DR IMBARINE BUJANGUniversiti Teknologi MARA, Kota Kinabalu,Sabah Malaysia

DR HSEIH TZUNG-YUANDepartment of Finance, MingDao University, Taiwan

DR RUDRA PRAKASH PRADHAN

Indian Institute of Technology, KharagpurKharagpur- 721 302, West Bengal, INDIA


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E D I T O R I A L B O A R D

DR MLADEN PECUJLIJAUniversity of Novi Sad, 21000, Serbia

DR BADAR ALAM IQBALAligarh Muslim University, 202002 (UP) India

DR YUSLIZA MOHD.YUSOFFSchool of Management, Universti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia

DR CHIH-YUNG TSAINational Penghu University of Science and Technology

DR YUNG-HO CHIUSoochow University, Taipei, Taiwan, ROC

DR ZULNAIDI YAACOBSchool of Distance Education, Universiti Sains Malaysia

DR MUHAMMAD ALI EL-HAJJIUniversity of Azteca, Mexico

DR SENOL OKAYPamukkale University Technical Education Faculty Kinikli/DENIZLI-TURKEY.

DR HSIN-HUNG WUNational Changhua University of Education, Taiwan

DR ABDUS SATTAR ABBASI

COMSATS University, Pakistan

I-SHUO CHEN (STEVEN)Institute of Business & Management, National Chiao Tung University, Taiwan

LEE CHEW GINGNottingham University Business School Malaysia Campus

GARRY TAN WEI HANUniversiti Tunku Abdul Rahman, Malaysia


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T a b l e o f C o n t e n t s

EXAMINING THE CORRELATION WEBSITE STATUS AND THE E-COMMERCE SYSTEM

SUCCESS: An Australian StudyJahjah Hallal and Jun Xu

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IS CUSTOMER SATISFACTION AN INDICATOR OF CUSTOMER LOYALTY?Rahim Ajao Ganiyu, Ignatius Ikechukwu Uche and Adeoti Olusola Elizabeth

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Design E-SCM Information Security FrameworkMaryam Mahdikhani, Asadolah Khahande Karnama and Milad Beirami

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Australian Journal of Business and Management Research Vol.2 No.07 [01-13] | October-2012

ISSN:1839 - 0846

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Examining the correlation website status and the e-commerce system success:

An Australian Study

Jahjah Hallal (Corresponding Author)Southern Cross University- Australia

[email protected]

Jun Xu

Southern Cross University- Australia

[email protected]

ABSTRACT

Acknowledging that, by using e-commerce systems, firms can deliver information about their products and

services, their vision, policy and many others related issues to their existence and potential customers.

Typically, the applications that underlie e-commerce systems determine the nature of the product or serviceoffering, the reaction of the customers and the revenue flux accrue to businesses. This designates that the value

added by a firms website system is a critical concern to both existence and potential customers. Based on the

DeLone and McLeans (1992, 2002, 2003) theory of information system success model, a dichotomous

dimensional model for classifying e-commerce website applications/status was developed. The proposed model

was tested via surveying small businesses in Australia. The results of this study indicate that the proposed

dichotomous classifications of the e-commerce website are meaningful, and unveil that e-commerce success

and benefits accrue to firms are determined by the environmental context of the website system applications.

Keywords: E-commerce System Success, Website Status, Small Enterprises, Static Website, Active Website,

Quantitative Approach, Structural Equation Model.

1. INTRODUCTIONA plethora of studies assures that lots of remuneration is expected to be obtained by firms from adopting and

implementing e-commerce. The benefits range from expanding the firm reach (Evans & Wurster, 2000),

improving business productivity and efficiency of gathering information (Watson, 2002), enhancing

communication (Iacovou, Benbasat & Dexter, 1995; Scupola, 2001) and gaining competitive advantage

(Schuete, 2000; Warrington, Abgrab & Caldwell, 2000). Even so, attainment of these benefits is depending on

the efficiency of the e-commerce system applications. The benefits will be accruing to organisations because ofextended applications of the e-commerce system. Review of prior studies findings show a mix of indications

regards the claimed of a connection between the stages of Internet usage and the outcome. In this course,

Raymond (2001), Rosenzweig, Roth, and Dean (2003), affirmed that a strong association has been identified

between the stages of Internet usage and performance. In contrast, Raymond (2001) remarked that the

codification of an association between the stages of Internet usage and the revenue is not supported by strongweight of real evidence. Cunliffe (2000), and Marshall, Sor, and Mckay (2000) stated that some groundwork

studies revealed a wide gap between anticipated and actual achievements from the implementation of the e-commerce system. Apparently, the literature claims of an association between the stages of Internet and the

performance/revenue suffers from the lack of a solid valid verification, because, such claims is not widely

supported by empirical data. Besides, scrutinising of the literature reveals a lack of the existence of a model or

models that address the topic of e-commerce success. Literature on e-commerce success reveals that someresearchers used Delone and Maclean's model (1992) of information system success; others used the

communication and ecological theories (Molla & Licker, 2001). This has pushed Molla and Licker (2001) to

come into a conclusion that there is a common shortage of models and frameworks for assessing e-commerce

success. Considering these facts, this study is allocated to investigate the influence of the implemented

websites on e-commerce system success. It aspires to clarify the fundamental role of website status as a

facilitator of the success of the e-commerce in organisations business practice. The focus will only beconcerned with small enterprises (SEs) that have more than 5 and less than 20 employees, as defined by the

Australian bureau of statistics (ABS 2001, cat. 1321.0). The study endeavours to address various issues in

regards to the applications of the e-commerce websites implemented by SEs. Particularly, examine thepotential influence of the SEs' website status (applications/functions) on e-commerce system efficiency, usage,
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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and subsequently the overall net benefits accrued to SEs. Produce a model that reflects the characteristics of the

e-commerce system in small businesses milieu. Bridge the gap that currently exists in the literature by

investigating the implications of e-commerce system in Australian SEs, and providing SEs the framework, they

must follow, when they decide to embrace the online activities or enhance existent e-commerce systems.

2. LITERATURE REVIEW

An e-commerce system can be defined as a computer-based information structure designed to providecustomers purposeful information with a simple and easy way to navigate, search, and inquiry to get sufficient

relevant answers about the enterprises goods and services in an attractive pleasant atmosphere. This kind ofbusiness practice (the internet-based business) has experienced a great expansion since the late of 1990s,

because of the rapid development in innovation of information and communication technology. In this study,

the website status is defined as the extent of use of the e-commerce system for several different business

activities, such as advertising, sales, marketing, information sharing, and other functions (Kraemer, Gibbs, &

Dedrick, 2002). Prior studies indicated that the firms engagement with e-commerce technology is sequential

and progressive (Straub & Klein, 2001; Taylor & Murphy, 2004; Venkatraman, 1994, as cited in Daniel &Wilson, 2002). Moving from a simple structure website, to customer service and personalised models

(Hoffman, Kalsbeek, & Novak, 1996; Karagozoglu & Lindell, 2004; Reynolds, 2000). The portal stage,

transaction stage and integration stage are the main sequential stages of website level of capability that can be

identified. The portal stagebegins with simple Internet access for the purpose of communication and web

presence. In this stage, organisations treat their website operations as a means of directing traffic to theirfundamental business (Evans & Wurster, 1999). The focus of this stage is concerned with attracting newcustomers (OConnor & OKeefe, 1997, as cited in Rao, Metts, & Mora -Monge, 2003), cost cutting, and

increasing productivity. The transaction stagebegins with establishing an active web presence equipped with

the ability to sell and buy, and offering customers a payment facility in a secure environment. The focus here is

shifted to improve customers services, expanding the customers base and managi ng the supply chain.

Integration stagestarts when the organisation implements more sophisticated system that enable it to integrate

activities, such as, supply chain management and managing the relationships with customers. The organisation

aim is to obtain a competitive advantage, by integrating e-commerce into its overall business strategy. During

this stage, the new business model will be created with full immersion into the technology, reflecting greater

complexity and risk (Straub & Klein, 2001). Nonetheless, in this paper a dichotomy model has been proposed

to investigate the interactions between the organisation website capability and the e-commerce success model.

Figure 1 below summarises the main criteria of the dichotomous model of the website status that the analysis

will be based on.

Figure 1: The Website Application

Source: developed for this study based on Martin and Malay (2001); Rao, Metts, and Mora Monge (2003);

Sekhar (2001); Straub and Klein (2001); Taylor and Murphy (2004)

3. THEORETICAL BACKGROUNDIn spite of the fact that the e-commerce system is considered as one of the information systems type. The

applicability of the traditional models of information systems success required from researchers to consider the

additional business functions that can be performed using e-commerce systems in contrast to traditional

Business

benefits

Brochures displaying

Product information

Contact information &Company information

FQA

Static web presence(Portal stage)

Brochures displaying

Product information

Contact information,Company information

FQASelling, buying & orderingfacilitiesSearch capability & product

feedback

Active web presence(Transaction stage)

Applications


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information systems (Cunliffe, 2000). Particularly, with the existence of obvious differences between the

information systems models and the e-commerce success models, in regard of their view for the success in

terms of the system objectives and the system focus. Hence, to examine the potential influence of the website

status on the e-commerce system success among small enterprises, a model that is based on the information

systems success has been proposed. The model outlines the main parts of the theoretical framework that are

involved in manifesting the potential influence of e-commerce system implemented on small organisations

performance. It mainly adopts the basic structure of the Information System Success Model, and modified it tocomply with the common perspective of e-commerce system applied by SEs. It is doing that based on the

Delone and Mclean (1992, 2002, 2003) theory of information system success model and other studies in thisfield, which conducted by Kraemer, Gibbs, and Dedrick (2002), Hoffman, Kalsbeek, and Novak (1996),

Karagozoglu and Lindell (2004), Reynolds (2000), and Taylor and Murphy (2004). The proposed model was

customised by adding two constructs related to the e-commerce website status, which represented in the static

website and the active website (Figure 2). The model combined the first layer of the DeLone and McLean's

model, regarding the system quality, content quality, and service quality, to form one factor called system

efficiency, and combined the second layer of the model (regarding the system use and user satisfaction, to formone factor called system usage. The researcher's objective was to produce a model that reflected the

characteristics of the e-commerce system in small businesses context. Besides achieving the goal that this study

is willing to achieve regarding assessing the influence of the website status on the small enterprise

performance. Figure 2 below summarises the main constructs of the proposed model.

Figure 2: The proposed theoretical framework of the influence

of e-commerce website status

Source: developed for this research

4. HYPOTHESES

The following hypotheses are linked to the website status, system efficiency, system usage, and net benefits.Based on literature, the website status refers to the level of utility of the e-commerce website for several

different business activities (Kraemer, Gibbs, & Dedrick, 2002). This study advocates that two main sequential

stages of website applications can be identified with regard of SEs, which are represented in static website

presence and active website presence. Static or passive website refers to the basic Internet access for the use of

communication and passive web presence. This stage entails the initial steps that organisations take to get

involved in a digital environment, such as: (1) displaying product brochures and services offered (Timmers,

2000); (2) contact information; (3) and other relevant information in a static manner. It also allows

organisations to present information about their businesses and other related frequent questions and answers. In

fact, the portal website offers organisations the opportunity to have a window to the web' (Barry, 2000, as

cited in Rao, Metts, & Mora-Monge, 2003), and provides SEs an opportunity to expand their market base

(Evans & Wurster, 2000). On the other hand, active website refers to more improved website presence, that is,equipped with the capability to sell and buy, by offering customers payment facility in a secure environment.

Active website is accommodating with the facilities to conduct online transactions and services. It allows firms

Net benefits

System usage

System efficiency

Website status

1. Active website 2. Static website


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to offer additional function than the static website, by offering the firms opportunities for: (1) selling, buying,

and ordering facilities; (2) searching capability and product feedback; (3) and linking information with

inventory data. Therefore, based on the prior studies findings (Raymond, 2001; Rosenzweig, Roth, & Dean,

2003), it has been suggested that the active website is more likely to influence e-commerce success than the

static website. This will lead us to state hypothesis H1 of e-commerce website status.

H1: Active websites are more likely to positively influence the efficiency of the e-commerce system than its

counterpart the static website.

Hypothesis linked to e-commerce system efficiencyThe hypothesis related to the e-commerce system efficiency is based on the conceptual foundation provided by

DeLone and McLean (2002) reformulated model. According to that model, e-commerce system efficiency is

conceptualised at three different issues related to system quality, content or information quality and service

quality. System quality is related to the system operational effectiveness. It is concerned with the function

provided by the website, such as accessibility, ease of navigation, access to information and ability to load

quickly, appearance attractiveness, secure and privacy policy, system design and accessibility (Han & Noh,1999; Turban & Gherke, 2000). Content or information quality refers to the characteristics and manifestation of

information of the system (Cunliffe, 2000; Dedhia, 2001; Savin & Silberg, 2000; Von Dran, Zhang, & Small,

1999). It is concerned with the information logical organisation, easy to comprehend, accurate, comprehensive

and reliability and clarity, relevance and currency. Service quality refers to the system use in delivering the

adequate performance to enhance the business operation. It is particularly concerned with responsiveness,prompt assistance when needed, follow-up services, quality of responses to frequently asked questions andtracking orders. Hence, based on the prior studies findings (Evans & Wurster, 2000; Iacovou, Benbasat, &

Dexter, 1995; Raymond, 2001; Rosenzweig, Roth, & Dean, 2003; Schuete, 2000; Scupola, 2001; Warrington,

Abgrab, & Caldwell, 2000; Watson, 2002) and the theoretical framework model proposed for this study. It has

been suggested that a better efficiency of the e -commerce system quality is more likely to lead to a better e-

commerce system usage. This will guide us to state hypothesis H2 of e-commerce system competency, which

is devoted to assess the correlation between the e-commerce website efficiency and the usage of the e-

commerce system applied.

H2: The more efficient the e-commerce system, the more likely it will positively influence the e-commerce

system usage.

Hypothesis linked to usage of the e-commerce system

Usage of the e-commerce system in this research includes two key variables related to the system actual useand customer's satisfaction due to the use. The use terminology in this study is related to customers' behaviour

regarding the number of website visits, the length of stay at a particular site, the number of purchases

completed, and retrieval and execution of a transaction. It is mainly, concerned with the use of the output of the

e-commerce website by customers. Use represents one of the most critical factors employed to evaluate the

success of information and e-commerce systems (Young & Benamati, 2000). Meanwhile, user/customersatisfaction refers to the valuation of the reaction or feeling of a customer. It related to his/her experience with

all aspects of an e-commerce system put in place by an organisation to market its products and services

(Seddon, 1997; Spreng & Mackoy, 1996). User satisfaction is completely connected to improve the wealth of

the organisation (Meuter, Ostrom, Roundtree, & Bitner, 2000; McColl, Kennedy, & Schneider, 2000;

Naumann, Jackson, & Rosenbaum, 2001), as use and user satisfaction are influencing the organisation's net

benefits. Net benefits refer to positive or negative effects of the implemented system on the organisation

efficiency and operational productivity, from the perception of the system adopter (DeLone & McLean, 1992;

Jarvenpaa & Ives, 1991). This construct is measured through various variables related to the organisationscontext, which directed toward assessing the actual achievement or net benefits. Hence, based on the prior

studies findings (e.g. Evans & Wurster, 2000; Raymond, 2001; Rosenzweig, Roth, & Dean, 2003; Schuete,

2000; Scupola, 2001; Warrington, Abgrab, & Caldwell, 2000; Watson, 2002), and the theoretical frameworkmodel proposed for this study, it has been suggested that, the more usage of the e-commerce system is more

likely to affect positively the net benefits. This will guide us to state hypothesis H3 of e-commerce system

usage, which is devoted to assess the correlation between the usage, and the net benefits.

H3: The more the usage of the e-commerce system the more likely it will positively influence the e-commerce

system success and subsequently the organisation's net benefits.

Figure 3 outlines the hypotheses that are postulated to influence the SEs' net benefits due to the status of the e-

commerce website applied.


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Figure 3: The proposed research model of e-commerce

website net benefitsand its related hypotheses

Source: developed for this research

5. RESEARCH METHODOLOGYRecognising that, the appropriateness of a research approach is driven by the nature of the social phenomena to

be explored (Easterby-Smith, Thorpe, & Lowe, 2002). The aim of this study to obtain a broad perspective of

the SEs managers' beliefs and attitude towards e-commerce website application, will be explored by testing

existing theories, such as the social cognitive theory self-efficacy beliefs (Bandura, 1991, 2001) and the

information system success model (DeLone & McLean, 1992, 2002, 2003). It achieves that, with a quantitative

approach, relying entirely on primary data, and utilises the questionnaire survey, as the most appropriate tool

that can offer an explanation of the research methods. The questionnaire was designed to gather information of

attitudes and perceptions of the participants organisations about various statements related to e-commercesystem impact. All items were measured with a seven-point Likert scale. A convenience sampling method was

employed in this research, participants SEs were randomly selected from the Australian Yellow P ages. The

mail survey was selected as being the most suitable method for collecting original data describing a largepopulation (Babbie, 1990). This method is considered a practical tool in gathering information related to the

beliefs, values, attitudes and perceptions of the respondents (Hair, Bush, & Ortinau, 2003). It also has an

efficient mechanism for data collection when the researcher knows exactly what is required and how to

measure the variability of interest (Sekaran, 2000). The questionnaires were distributed to managers of the

selected small enterprises. Data collected from the questionnaires was then edited, coded, entered into the

statistical program Statistical Package for Social Sciences' (SPSS), and then cleared. To ensure that the dataobtained is complete, accurately entered and arranged to facilitate analysis operation. Inferential analysis was

conducted to find out the relationship between e-commerce website status as two separated dependent variables

and the predictors independent variables. The main inferential statistical technique employed to test the

hypotheses is structural equation modeling.

Net benefits

Status of the e-commerce website applied

Static website presence Active website presence

System efficiency

System usage

H3

H1

H2


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The overall level of e-commerce website efficiency, usage and e-commerce system success are measured

against various criteria based on prior studies by Bellman (2001), Deeter-Schmelz and Kennedy (2004),

Fellenstein and Wood (2000), Hassan and Li (2005), Joseph, Cook, and Javalgi (2001), Kalakota and Robinson

(2001), Kambil (1995), Karagozoglu and Lindell (2004), Karayanni and Baltas (2003), Korper and Ellis

(2001), Pavlou (2003), Riquelme (2002), Schneider and Perry (2000), Schuete (2000), Sekhar (2001), Straub

and Klein (2001), Straub, Limayem, and Karahanna-Evaristo (1995), and Warrington, Abgrab, and Caldwell

(2000). Evaluation of e-commerce system quality was based on: (1) accessibility, ease of navigation, access toinformation, ability to load quickly; (2) appearance attractive; (3) secure; (4) privacy policy. Evaluation of e-

commerce information quality was based on: (1) appropriate information logically organised; (2) easy tounderstand; (3) accurate, adequate, comprehensive, reliable, concise, and clear; (4) relevant; (5)

current/currency. Evaluation of e-commerce service quality was based on: (1) responsiveness, receive

assistance and follow-up services promptly; (2) answer frequently asked questions; (3) track orders. Evaluation

of e-commerce system use was based on: (1) number of customer purchases completed; (2) number of

customer navigations. Evaluation of e-customers satisfaction was based on: (1) customers satisfaction with

information provided by the companys website: (2) customers satisfaction with services offered by thecompanys website; (3) customers overall satisfaction with companys website. Evaluation of e -commerce

system net benefits was based on criteria of: (1) increase customers base; (2) decrease transactions cycle time;

(3) cost reductions (search cost, communication, time saving); (4) improve trading relationships; (5) increase

sales; (6) increase businesss competitive position; (7) increase businesss profits; (8) increase businesss staff

productivity, change in working hours, change in number of workers; (9) decrease inventory investment; (10)and improve customers service. Evaluation of the passive or portal website was based on: (1) display companyinformation; (2) display brochure and product information; (3) display contact information and feedback.

Evaluation of the active or transaction integration website was based in addition to having all portal stage

characteristics on the ability to: (1) sell and buy online, utilise ordering, and payment facilities; (2) receive

product feedback; (3) utilise search capabilities; (4) and provide after-sales customer service and support.

6. TESTING OF HYPOTHESES

A structural equation model (SEM) method is used to analyse the potential interrelationship of proposed model

constructs. This method is considered a good tool to examine models containing complex relationships when a

set of structural linear equations exist, irrespective of whether the variables in the equations are observed or

latent (Garson, 1998, 2008, 2009). SEM is a theory-based approach that is governed by hypothesis rather than

experiment (Hair, Black, Babin, Anderson, & Tatham, 2006). The tested model contained four independent

factors (static website, active website, system efficiency, and system usage), and one dependent factor (netbenefits). Each of these factors was represented in a cluster of predictors.

Collected data have passed various tests to make sure that they are suitable and ready for inferential analysis.

The assumption of multivariate normality and linearity were evaluated through SPSS using the techniques

described by Tabachnick and Fidell (2007). This was completed by calculating z-scores or standard scores foreach item on those variables, and calculating mahalanobis distance for each factor using data from variables of

each set of the four factors. The issue of missing data was addressed and a replacement of the missing data was

applied using series mean method. Ultimately, using data from 201 respondents, a confirmatory factor analysis,

was performed using AMOS (Analysis of Moment Structures) on the twenty one sub-tests of the website

function. The hypothesised model (model 1) is shown in Figure 4, where circles represent latent variables and

rectangles represent measured variables. The measurement errors are enclosed by smaller circles and indicate

that some portion of each observed variable is measuring something other than the hypothesised factor. The

following abbreviation sub-tests serves as indicators of: (1) the static website factor (statc1_f, statc2_f andstatc3_f); (2) the active website factor (statc1_f, statc2_f, statc3_f, activ1_f, activ2_f, activ3_f, and activ4_f);

(3) the system efficiency factor (syst1, info1 and srv1); (4) the system usage factor (sat1_sqf, sat2_sqf, sat3_f,

q13_a_1, q13_b_1, q13_c_1 and q13_d_1); (5) the net benefits factor (be1_lnf, be2_srqf, be3f, be4f). The fourfactors hypothesised to be connected with single head arrows imply a hypothesised direct effect.

Model estimation (model 1)

Maximum likelihood estimation was employed to estimate all models. The independence model that tests the

hypothesis that all variables are uncorrelated was easily rejectable, X2(210, N = 201) = 3104.56, p < .001. The

hypothesised model was tested next and support was found for the hypothesised model. Goodness of fit relatedto this five factors model,X

2(182, N = 201) = 374.63, p < .001, comparative fix index (CFI) = .85; and the root

mean square error of approximation (RMSEA) = .07. A chi-square difference test indicated a significant

improvement in fit between the independence and the hypothesised model. The model p value is less than .05,

so the test agrees in rejecting the null hypothesis at the .05. Nonetheless, since the RMSEA for this model is
http://80-docserver.emeraldinsight.com.ezproxy.scu.edu.au/deliver/cw/mcb/14626004/v11n3/s2/p290.htm?fmt=html&tt=4373&cl=54&ini=emerald&bini=emerald&wis=emerald&ac=11073344&acs=35009407,11073344&kn=1&expires=1107248853&checksum=D429A3D47E98EDEABB128699C7F1DA2A&cookie=586256512#b2http://80-docserver.emeraldinsight.com.ezproxy.scu.edu.au/deliver/cw/mcb/14626004/v11n3/s2/p290.htm?fmt=html&tt=4373&cl=54&ini=emerald&bini=emerald&wis=emerald&ac=11073344&acs=35009407,11073344&kn=1&expires=1107248853&checksum=D429A3D47E98EDEABB128699C7F1DA2A&cookie=586256512#b2


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.07 > .06, the tucker-Lewis index is .92 < .95 and the comparative fix index = .85 < 90, the model does not fit

well according to the accepted measures of fit recommended by Hu and Bentler (1995, 1999).

The next task was to identify any area of misfit in the model as recommended by Joreskog (1993). In this

regard, two types of the model output information, the standardised residuals covariance and the modification

indices were examined, to detect any possible misspecification. Consequently, post hoc model modifications

(model 1a) were preformed in an attempt to develop a better fitting and possibly more parsimonious model(Figure 5). The model 1a,X

2(172, N = 201) = 228.40, p = .001, with a ratio of 1.31 < 2 represent an adequate

fit (Byrne, 1989). The root mean square residual (RMR) = .03 < .05, indicates a good fitting model, whichmeans that the model explained the correlations within an average error of .03 (Hu & Bentler, 1995). The

goodness of fit index (GFI) = .91, which is close to 1 indicate a good fit (Hu & Bentler, 1995). The

comparative fit appendix CFI = .98 .95, is considered representative of a well-fitting model (Hu & Bentler,

1999).

Figure 4: Hypothesised CFA model (model 1)

Source: created for this research

Root mean square error of approximation RMSEA of .04 .06, indicate a good fit (Hu & Bentler, 1999), the

Tucker-Lewis Index TLI = .98 .95, indicates of good fit (Hu & Bentler, 1999). The noncentrality parameterNCP = 54.40 with a confidence interval of 19.29 and 97.62 indicates that we can be 90% confident that the

population value of the noncentrality parameter lies between 19.29 and 97.62. The default model (1a) expected

cross-validation index (ECVI) of 1.71, the saturated model (ECVI) of 2.31 and the independence model of(ECVI) of 15.73. Given the lower ECVI value for the default model (1a) compared with the saturated model

and the independence model, we conclude that it represents the best fit to the data. The expected cross-

validation index (ECVI) is considered as a means of assessing in a single sample the likelihood that the models

cross-validates across similar-sized samples from the same population (Brwone & Cudeck, 1989, 1993 as cited

in Schumacker & Lomax, 2004, p. 240- 254; Byrne, 2001, p. 86). A Chi square difference test indicated that

the model1a was significantly improved by addition of those paths, X2diff (8, N =201) = 146.23, p =.001.

Because post hoc model modifications were performed, the squared multiple correlation among the model (1a)

factors and the hypothesised model factors were inspected, where parameter estimates were hardly changed

despite modification of the model. The size of the correlated error associated with items is considered

substantially large. In addition, testing the standardised and unstandardised values of the factor loading

Static

website

statc1_fe11

statc2_fe21

System

usage

r3

System

efficiency

syst1

e8

info1

e9

1

srv1

e10

sat1_sqfe111

sat2_sqfe12 1

sat3_fe131

r2

1

Active

website

activ4_fe71

activ3_fe61

activ2_fe51

activ1_fe41

Net

benefits

be3f

e20

1be2_srqf

e19

1be1_lnf

e18

1

r4

1

statc3_fe31

q13_a_1e141

q13_b_1e151

q13_c_1e161

q13_d_1e171

1

1

1 r1

1

be4f

e21

1

1

1

1

1

1

Chi-square = 374.63

Degrees of freedom = 182

Probability level = .00

GFI = .85

Model 1


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on the system efficiency than its counterpart the static website (refer to Figures 5); (2) H2 was found that the

system efficiency has a significant impact on the system usage (refer to Figures 5); (3) and H3 was found that

the system usage has a significant impact on the net benefits (refer to Figures 5).

8. DISCUSSIONS

The findings of this study revealed that system efficiency was significantly influenced by the status of the

implemented website (whether it is static or active) and its various applications. System efficiency in terms ofsystem quality, information quality and services quality was found to be a significant predictor in influencing

the system usage. System usage was found to be a significant predictor in influencing the organisational netbenefits (Figure 5). These finding is correspondent with prior studies, which suggested that: (a) a strong

association had been identified between the stages of Internet use and the organisation performance and

subsequently the input the Internet adds to organisation bottom line (e.g. Raymond, 2001; Rosenzweig, Roth,

& Dean, 2003); (b) system efficiency contributes to achieve higher visibility, better advertising and promotion

activities, and enhances customers services (Fellenstein & Wood, 2000); (c) a strong association had been

identified between the stages of the Internet usage and its performance (e.g. Raymond 2001; Rosenzweig,Roth, & Dean, 2003). This result verified the literature claims that sale growth and profitability can be

adversely affected by websites that do not function properly, that is, businesses can lose as much as 40 percent

of repeat end-user traffic' (Fellenstein & Wood, 2000). As long as, potential customers will judge the

organisation's e-commerce website they visit, by the ability of the website to offer the most convenient

functions that satisfy their needs (Savin & Silberg, 2000). As the table (5) shows the results of theunstandardised regression coefficient analysis of the active website is 4.29, the static website is 0.23. Theseresults clearly showed that the active website has a considerably higher positive significance influence on

system efficiency than its counterpart the static website. The system efficiency has a significant influence on

the system usage, and in turn, the system usage has a significant influence on the net benefits that the

organisation can achieve.

The findings of this study affirm that the e-commerce website status is playing the key role as a determinant for

the success of the e-commerce system in small enterprises. The research's findings have offered an empirical

support on a national level among Australia for the influence of the website status on the system efficiency, the

system efficiency on the system usage, and the system usage on the net benefits. The findings of this study

unearth that the better the level of improvement of the website status of the e-commerce system, the better

results regarding usage and net benefits, and subsequently a better opportunity of success for the e-commerce

system. This study as well, offered a practical support for the creation of model that clarifies the impact of thewebsite status on the system success. The model tested in this study can serve up as a reference source for

practitioners and academics alike in better understanding of impact of the e-commerce system applications, and

grant them the appropriate recommendations based on the empirical findings. It clarifies the overall picture of

how the status of website can affect the expected outcomes of the implemented e-commerce system, and

presents small enterprises useful information for enhancing their understanding of e-commerce and itsanticipated results. It also provides insightful information about the pathway that small enterprises must be

followed to yield the desirable benefits, with respect of the sales and net revenue.

The findings of this study has outlined the path that policy makers, and business practitioners must be observed

when developing future strategy/ies to promote e-commerce within SEs. The findings show clearly that

implementing the appropriate website system by means of: (1) a clear developed online strategy; (2) a relevant

website that reflects the business's strategy; (3) the website should be frequently updated and present current

information about the SE's products and services. Would offer SEs the opportunity to achieve their desires,which is to survive in increasing tough competitive marketplace. The findings of this study can be used as a

basic background that offers ongoing advice and support to developing future strategy/ies to establish,

promote, and enhance e-commerce adoption and implementation.

9. CONCLUSION AND SUGGESTIONS

This study might experience diverse limitations that could affect the overall validity and reliability of its

findings. Those limitations could arise from the theoretical, procedural, and methodological approaches applied

in the research. The principal limitation of this study being a cross-sectional is related to the nature of the mail

survey used to collect the data. This limitation is attributed to the likelihood that respondents answers may notreflect precisely the outcome figure of actual benefits they attained. The probability of response bias, which

could exist because of the participants' tendency to respond to questions in a certain way, might misrepresent or

misconstrue facts (Zikmund, 2003). This problem would attribute to the characters of the SEs' decision makers

being busy people, and so they have limited time to answer the survey questions accurately. Likewise, because


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we are unable to determine the person who completed the survey is? This also adds problems to the accuracy of

the researchs findings. Besides, SEs mainly owned and operated by family members who might possess high

professional skills with little or no formal education might make them unable to interpret the actual outcome of

e-commerce system. Also, the sample method utilised to identify the SEs who participated in this research was

not based on a strictly random sample, due to the absence of complete list accounting for all Australian SEs.

The selected sample of participants SEs was based on a convenience sample method, where the selection here

is purely subjective and arbitrary. This non-probability sampling method suffers from problems of extremebias, which raised the question concerning its appropriateness, and how equitable the results would be in

representing the entire SE population. Nonetheless, various procedures have been applied to ease and/ordiminish the effect of these limitations. Those procedures are reflected in selection of the most appropriate

paradigm for this study, selection of the quantitative research approach, sampling process, questionnaire

design, determination the data needed and construct operationalisation, determination of measurement scale

applied, and the judgment of the quality of the survey research method by constructing validity and reliability.

Consequently, we believes that the research has projected and examined a number of significant factors that

affect e-commerce system success.

The findings of this study shows how the functions that the website can provide will determine the success of

the implemented e-commerce system in bringing small enterprises the benefits they desire. SEs must be aware

that: (1) the website system quality must be accessible, ease of navigation, attractive and secure; (2) the website

information quality must be accurate, comprehensive, reliable and clear, relevance and current; (3) the websiteservice quality must be responsiveness, prompt, offering follow-up services and excellence of responses tofrequently asked questions. Accordingly, SEs who have adopted e-commerce or on the brink to adopt e-

commerce should be fully understood that the website status of the e-commerce system adopted will contribute

significantly to the net benefits they expected from adopting e-commerce. Thereby, SEs should have the

precise answers on the following questions:

What system quality might make their websites effective and attractive? What information quality is ideal to be presented for their websites? What services quality the website should provide to satisfy customers needs?

Still, this study demonstrated that the website of e-commerce system is an inevitable phenomenon that the

businesses of all types should be aware about its impact. For that reason, to be able to gain the most benefits of

e-commerce, businesses in general and SEs in specific should think through the following suggestions:

Implement the e-commerce system that suits your business activities. Constantly update your website capability. Monitor the development in e-commerce innovation and how it can be leveraged, if

possible to improve the current business practice.

Nonetheless, further research efforts are required to shed more light on the influence of website status on the e -commerce system efficiency, usage and subsequently the overall success of the e-commerce system. Likewise,

this study has illuminated the effect of the website status of the e-commerce system on a limited extent, by

investigating two categories of the website status (active and static). Extending the examination of any future

research on website status to include other categories, such as the integration stage would help to clarify the

influence of the website status on the e-commerce success. This research has assessed the influence of the

website of e-commerce system in Australian SEs based on the perception of SEs manages/owners. Future

studies that look into the influence of the website of e-commerce system in Australian SEs based on customers

perception, would be of great benefits in supporting the result of this research. Besides, various opportunitiesare exist for future studies to address the above mentioned limitations, by trying to avoid them or as many as

possible are emerging. Additional empirical investigates that illuminate further the impact of the website status

on the e-commerce system success are required for validating the findings of this study. Whether, the results ofsuch studies are support or refute the claims of this research, they will provide further theoretical and practical

contributions to the knowledge of e-commerce and website applications.

.

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Is Customer Satisfaction an Indicator of Customer Loyalty?

Rahim Ajao Ganiyu (Corresponding author)

Department of Business AdministrationUniversity of Lagos, Nigeria.

[email protected]

Ignatius Ikechukwu Uche

Department of Business Administration

University of Lagos, Nigeria.

[email protected]

Adeoti Olusola ElizabethDepartment of Business Administration

University of Lagos, Nigeria.

[email protected]

ABSTRACT

Customer satisfaction and loyalty is a well known and established concept in several areas like marketing,

consumer research, economic psychology, welfare-economics, and economics. And has long been a topic of

high interest in both academia and practice. The aim of the study was to investigate whether customer

satisfaction is an indicator of customer loyalty. The findings of the study supported the contention that strongrelationship exist between customer satisfaction and loyalty. However, customer satisfaction alone cannot

achieve the objective of creating a loyal customer base. Some researchers also argued, that customer

satisfaction and loyalty are not directly correlated, particularly in competitive business environments because

there is a big difference between satisfaction, which is a passive customer condition, and loyalty, which is an

active or proactive relationship with the organization.

Keywords: Customer satisfaction, customer loyalty, switching cost, loyalty programme, consumption

experience, word-of-mouth, customer value

1. INTRODUCTIONCustomer loyalty has long been a topic of high interest in both academia and practice, and a loyal customer base

has been found to be beneficial to the firm. Most companies strive for customer loyalty as the competition in

most sectors grows tighter, both the importance of, and the challenge in, keeping customer loyalty increases.Indeed, customer satisfaction has for many years been considered as key factor in determining why customers

leave or stay with an organization. Therefore, organizations need to know how to keep their customers, even if

they appear satisfied. Every organization has come to realize that in order for it to survive, let alone grow, it has

to acquire and then retain profitable customers. And it is loyal customers that generate increasing profits for

each additional year they are retained. Customer satisfaction is not a guarantee of repeat patronage. Satisfied

customers jump ship every day, and the reasons are not always due to customer dissatisfaction, some customers

are lost due to indifference which arises from pure neglect (Michael et al., 2008).

Customer satisfaction is the heart of marketing. The ability of an organization to satisfy customers is vital for a

number of reasons. For example, it has been shown that dissatisfied customers tend to complain to the company

and in some cases seek redress from them more often to relieve cognitive dissonance and bad consumptionexperiences (Oliver, 1987; Nyer, 1999). If service providers fail to properly address such behavior, it can have

serious adverse effect. In extreme cases of dissatisfaction, customers may resort to negative word-of-mouth as a

means of getting back to the company. Reichheld (1996) posits that unsatisfied customers may choose not to

defect, because they do not expect to receive better service elsewhere or if the switching cost is high.

Additionally, satisfied customers may seek for competitors because they believe they might receive better

service elsewhere.
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Customer retention is a function of other factors other than customer satisfaction. These include a wider variety

of product choices, greater convenience, better prices, and enhanced income (Storbacka et al., 1994).

Therefore, many researchers consider customer satisfaction to be the best indicator of a companys fu ture profit

and competitiveness. The outcomes of customer satisfaction include customer loyalty (Bei and Chiao, 2001). In

the consumer marketing community, customer loyalty has long been regarded as an important goal of any

corporate entity (Reichheld and Schefter, 2000). And as such both marketing academics and professionals have

attempted to uncover the most prominent antecedents of customer loyalty.

Researchers have found a strong relationship between customer satisfaction and loyalty. For instance,Szymanski and Henard (2001), in their meta-analysis study, indicate 15 positive and significant correlations

between the two constructs. Bearden and Teel (1983) have also shown a relationship between satisfaction and

loyalty. In fact Jones et al., (1995) argued that this relationship is not a simple linear one; the resulting behaviors

may depend on consumer attributions, (i.e. their belief in the causes of the customer satisfaction and

dissatisfaction assessment).

Quite understandably, marketing practitioners have often lay claim with customer satisfaction, using slogans

such as Our focus is customer satisfaction, or The customer is a king Customer is our reason for being in

business. etc. The importance of customer satisfaction inform the study carried out by the University of

Michigan which tracks customers across 200 firms representing all major economic sectors to produce the

American Customer Satisfaction Index (ACSI). Each company receives an ACSI score computed from itscustomers perceptions ofquality, value, satisfaction, expectations, complaints, and future loyalty (Fornell et al.,1996). According to Boselie, et al., (2002) satisfaction is a positive, affective state that results from the appraisal

of a working relationship between parties. Customer satisfaction is defined by Olivers (1997) as the

consumers fulfillment response. It is a judgment/assessment that a product or service feature, or the product or

service itself, provides a pleasurable level of consumption related fulfillment. In other words, it is the overall

level of contentment with a service/product experience. Bitner and Zeithaml (2003) opined that satisfaction is

the customers evaluation of a product or service in terms of whether that product or service has met their need s

and expectations.

Customer loyalty can seem elusive and magical to those trying to obtain it. However, there are a lot of good

reasons for businesses to pursue customer loyalty as a strategic objective. Customers are expensive to acquire;

keeping them loyal allows you to amortize acquisition costs. Loyal customers are often willing to pay premium

prices. For example, some of the important attitudes and behaviors expected of a loyal customer include: Likelihood to recommend company products and services to others.

Likelihood to continue purchasing the company products and services, at minimum, at the same level.

Likelihood of purchasing other products and services the company offer.

Believing company products and services are superior to competitors.

Not actively seeking alternative service providers.

Providing the company with opportunities to correct problems and not using these as a basis for

compromising the relationship.

Numerous studies have pointed out that two of the most effective means of generating customer loyalty are to

delight customers (Oliver, 1999; Lee, et al., 2001) and to deliver superior customer value derived from excellent

services and quality products (Parasuraman and Grewal, 2000). In addition, some scholars argue that switching

costs, is a key moderating variable, and can significantly influence customer loyalty through such determinants

as customer satisfaction (Fornell, 1992; Oliver, 1999; Lee et al., 2001) and perceived value (Woodruff, 1997;

Neal, 1999).

Customer loyalty can be defined as the adherence of customers to a company. Even if businesses make

mistakes, loyal customers will not leave. Kincaid (2003, p.10) defines customer loyalty as a consumer

behavior, built on positive experience and value, which leads to buying products, even when that may not

appear to be the most rational decision . Furthermore, the concept was later divided in to behaviouristic and

non-behaviouristic dimensions where the latter is more focused on the underlying causes of customer loyalty


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and attitudes of consumers (Peppers and Rogers, 2004). So, in the investigation of customer loyalty, it is valid to

explore two fields: the behavior of consumers and their intentions (Schweizer, 2008).

Stone et al., (2000) posits that customer loyalty is also dependent on a number of customer related factors, i.e.

how customers perceive the business rather than what the business really does. Given all these benefits, its only

natural that businesses should turn to a diverse range of tools to develop customer loyalty. And every company

seems to have a different formula for making that loyalty happen. Such initiatives include creation of valuablecustomer experiences, creation of resonant brand, proactive marketing initiatives, quality control processes, and

customer relationship management.The common thread here is that the experience the customer ultimately has with the business, if it is positive

creates the emotional bond that leads to customer loyalty. But something is missing from this assertion. What

about the product itself? What role does it play in creating customer loyalty? Of all the touch points customers

have with the company, companys product is the one touch point with which they are likely to spend the most

time. The product is also the touch point likely to create the strongest emotional reaction, because it is the

customer experience with product that customers use to portray the company brand and image.

Although, it is widely acknowledged that customer satisfaction is a driver of customer loyalty. However, a

number of contributions to the services marketing literatures over the past decade have called this into question

and empirical studies have begun to demonstrate service contexts in which customer satisfaction and loyalty do

not always correlate positively (Silvestro and Cross, 2000, Kamakura, 2002, Pritchard and Silvestro, 2005).However, most of these empirical studies have been based on business to consumer (B2C) contexts, and onlatitudinal rather than longitudinal data.

The term customer loyalty was widely researched in 1990s but considerably fewer investigations were

conducted in later periods (see for example, Heskett et al., 1994, Rucci and Kirn, 1998, Reichheld and Markey,

2000; Vandermerwe, 2000; Fredericks, 2001, Reichheld, 2004). Also, moderate amount of empirical research

has been conducted to examine the relationships among customer loyalty, satisfaction, switching costs, and

customer value. And to date very few empirical studies has investigated these constructs in a single framework.

And the complicated interrelationships among these constructs have not been fully uncovered and understood

(Reichheld and Sasser, 1990; Jones and Sasser, 1995).

Therefore, the current study seeks to address some of these gaps and offers further theoretical insight and

contribution into the contention that customer satisfaction is an indicator of customer loyalty.

2. CONCEPTUAL BACKGROUND

Customer loyalty has been studied since the 1950s (see Jacoby and Chestnut 1978 for a review). Customer

satisfaction remains a worthy pursuit among the consumer marketing community (Oliver, 1999). Certainly,customer satisfaction is a critical focus for effective marketing programs. According to Yi (1991) customer

satisfaction is a collective outcome of perception, evaluation and psychological reactions to the consumption

experience with a product or service. Customer satisfaction is regarded as how customers can get more benefits

than their cost (Liu and Yen, 2010). Customer satisfaction plays the most important role in total quality

management. And in comparison with other traditional performance measures, customer satisfaction is probably

less sensitive to seasonal fluctuations, changes in costs, or changes in accounting principles and practices

(Kotler, 2006).

Some researchers (Parasuraman, et al., 1988; Cronin and Taylor, 1992) consider overall satisfaction to be the

primary function of perceived service quality. Among the more popular measures of customer satisfaction, two

widely employed approaches are transaction-specific and cumulative or overall satisfaction. The transaction-specific approach defines customer satisfaction as an emotional response by the consumer to the most recent

transactional experience with an organization (Oliver, 1993). The associated response occurs within the time

frame of consumption, after the choice process has been completed. The affective response on the other hand

varies in intensity depending upon the situational variables that are present. Compared to transactional-specific

satisfaction, overall satisfaction reflects customers cumulative impression of a firms service performance

On the other hand, the overall satisfaction perspective views customer satisfaction in a cumulative evaluation

fashion that requires summing the satisfaction associated with specific products and various facets of the firm.

Satisfied customers tend to have a higher usage level of a service than those who are not satisfied (Ram and

Jung, 1991; Bolton and Lemon, 1999). They are more likely to possess a stronger repurchase intention and to


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recommend the product/service to their acquaintances (Zeithaml et al., 1996). Numerous studies have also

revealed that customer satisfaction positively affects loyalty (Zeithaml et al., 1996; Bloemer, et al., 1999; Oliver,

1999).

As identified by the researchers that customer loyalty as a construct is comprised of both customers attitudes

and behaviors. Customers attitudinal component represents notions like: repurchase intention or purchasing

additional products or services from the same company, willingness of recommending the company to others,demonstration of such commitment to the company by exhibiting a resistance to switching to another competitor

(Cronin and Taylor, 1992; Prus and Brandt, 1995; Narayandas, 1996), and willingness to pay a price premium(Zeithaml, et al., 1996). On the other hand, the behavioral aspect of customer loyalty represents- actual repeat

purchase of products or services that includes purchasing more and different products or services from the same

company, recommending the company to others, and reflecting a long-term choice probability for the brand

(Feick, et al., 2001).

The behavioral typology to customer loyalty is primarily concerned with measures of repeat purchase,proportion of purchases etc. Although, this is considered to be a relevant measure, the main criticism of this

typology is that it does not include the customers motives for their behavior. Therefore attitudinal approaches to

loyalty have been developed. While a behavioral approach to loyalty is still valid as a component of loyalty, it is

argued that attitudinal approaches to loyalty should supplement the behavioral approach (Samuelson and

Sandvik, 1997). The attitudinal typology includes, for example, measures of commitment and trust.

3. METHODOLOGY AND METHOD

3.1 Corelational Research Method

To achieve the study objective, the researchers adopted co relational research method, using qualitative research

approach. The study explored and established the existence of relationship/interdependence between customer

satisfaction and customer loyalty. Previous published studies, articles, books etc on the subject matter wasthoroughly reviewed to gain a deeper understanding and insight in what earlier researchers have said, done and

come up with. The major advantage of using secondary information is that much of the background work

needed has already been carried out and have been already used and established by other researchers for a

similar or different researcher purposes (Harris, 2001).

4. DISCUSSIONS AND CONCLUSION

Customer satisfaction is a popular concept in several areas like marketing, consumer research, economic

psychology, welfare-economics, and economics. The most common interpretations obtained from various

authors reflect the notion that satisfaction is a feeling which results from evaluation process of what has been

received against what was expected, including the purchase decision itself and the needs and wants associated

with the purchase (Armstrong and Kotler, 1996).

Many empirical studies have shown that customer satisfaction secures future revenues (Fornell, 1992; Bolton,

1998), reduces future transactions costs (Reichheld and Sasser, 1990), decreases price elasticity (Anderson,

1996), and minimizes the likelihood of customers defecting if quality falters (Anderson and Sullivan, 1993).

Customer loyalty is winning the confidence of the customer in favor of an organization such that the relationshipbecomes a win-win situation for both the organization as well as the customer. Customer loyalty is not a process

that finishes with the customer joining the loyalty program but actually a process that starts with the customer

joining the same. Customer loyalty is something more of what an enterprise must get from the customer. As

opposed to what the name suggests, it is not just something that the customer has to build towards the enterprise.

Customer loyalty will be hard to get in times of a recession. At least harder than it was when the consumer had

enough to spend. Small reasons will be enough for customers to turn away from putting money into a business.

Customers will not put loyalty first but the price will be a major driving force. For now - the consumer

confidence is so lowand will be influenced by immediate benefits. As such customer loyalty programs will

need to adapt to quicker and possibly immediate awards to the customer. Lower prices as part of the loyalty

program will definitely boost membership to the loyalty programs but this must be carefully communicated to

the customer, to avoid perceiving companys product as inferior compare to competitors offering. Therefore,

discounts to customers must be treated separate from the benefits of lower price to loyal customers. Loyal


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customers must be given a feeling that they are being treated specially, particularly with the ongoing economic

recession. That is the key to keeping the customers with the business in these hard times. Customers need to be

better informed now of the benefits that they are getting by belonging to loyalty program.

The power of customer loyalty is clear and compelling: It leads to more profitable growth. Loyal customers stay

longer with companies that treat them well. They buy more of their products, and they cost less to serve. They

recommend the companies to their friends and colleagues, becoming, in effect, a highly credible volunteer salesforce. Investing in loyalty can generate more attractive returns than rolling out an ambitious new marketing plan

or expanding line of companys business. Loyalty can be of substantial value to both customers and the firm.Customers are willing to invest their loyalty in business that can deliver superior value relative to competitors

(Reichheld, 1996). When they are loyal to a firm, consumers may minimize time expended in searching and in

locating and evaluating purchase alternatives. Also, customers can avoid the learning process that may consume

the time and effort needed to become accustomed to a new vendor. Customer loyalty is one major driver of

success in e-commerce (Reichheld and Schefter, 2000).

It is a fallacy to assume that a customer is loyal just because he/she continue to buy from the companys. There

are many reasons why a customer repeats purchasing which have little to do with being really loyal. Moreover,

loyalty means hanging in there even when there may be a problem because the organization has been good to

customers in the past and addresses issues when they arise. It means that they do not seek out competitors and,

when approached by competitors, are not interested. It also means being willing to spend the time and effort tocommunicate with the organization so as to build on past successes and overcome any weaknesses.

Customer satisfaction alone cannot achieve the objective of creating a loyal customer base. In theory and

practice trust has come out to be an important antecedent of customer loyalty. While determining the

imperatives of how to win customers trust the service provider(s) must focus on both present and future time

frame. The construct of trust contains belief in the brand or company, which provides the customers an

assurance of positive outcomes not only for the present but also for the future.

It had been thought and research has found that by increasing loyalty as it is apparent that satisfied customer are

likely to remain loyal to the service provider (Eriksson and Vaghult, 2000). However, research by Jones and

Sasser (1995) has found that satisfaction and loyalty are not directly correlated, particularly in competitive

environments. The findings shows that to achieve loyalty in competitive environments organizations need to

completely satisfy their customers (Jones and Sasser, 1995). Fredericks (20 01) also points out that there is abig difference between satisfaction, which is a passive customer condition, and loyalty, which is an active or

proactive relationship with the organization.

Furthermore, Coyles and Gokey (2002) found from their research that satisfaction alone does not make a

customer loyal and that merely measuring satisfaction does not tell a company how susceptible its customersare to changing their spending patterns or jump ship to competitors with a better offering. They identify three

basic customer attitudes, emotive, inertia and deliberative that underlies loyalty profiles. They have found that

the emotive customers are the most loyal. Thus, it would seem that while satisfaction is an important component

of loyalty the loyalty definition needs to incorporate more attitudinal and emotive components.

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