A retrospective data examination of customer loyalty in the e banking technology services industry strategies for new successes

A retrospective data examination of customer loyalty in the e-banking technology services industry Strategies for new successes

A RETROSPECTIVE DATA EXAMINATION OF CUSTOMER LOYALTY IN THE E-BANKING TECHNOLOGY SERVICES INDUSTRY: STRATEGIES FOR

NEW SUCCESSES

by John Reynolds

RICHARD MURPHY, DBA., Faculty Mentor and Chair TONI B GREIF, Ph.D., Committee Member ROBERT A KRAMARCZUK, Ph.D., Committee Member

Kurt Linberg, Ph.D., Dean, School of Business & Technology

A Dissertation Presented in Partial Fulfillment

Of the Requirements for the Degree

Doctor of Philosophy

Capella University

UMI Number: 3288714

3288714 2008

Copyright 2007 by Reynolds, John

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© John Reynolds, 2007

Abstract This study retrospectively examined 2006 e-banking technology services industry customer loyalty survey data results in order to improve marketing resource allocation for corporate e-banking products and services Primary customers were delineated by bank size (i.e., small, medium, and large) and single versus multi product purchases

MANOVA and independent t test statistical measures were applied to 684 survey reports

gathered in 2006 The results indicated that statistically significant and lower ratings of loyalty existed among the small and single product banks Quality ratings were

differentiated between five subcategories (i.e., quality, trust, willingness to renew,

willingness to recommend, and willingness to expand) Trust, willingness to recommend,

and willingness to expand subcategories of quality were also rated significantly lower among the small and single product banks compared with medium and large multi product banks Additional quality categories of general quality and willingness to renew were not statistically significant between the various bank delineations These results provide the basis from which to complete additional research and begin the process of making changes in resource allocation related to optimizing e-banking customer centric business strategies

Dedication This dissertation is dedicated to my family, who gave me the foundation to value learning and the knowledge that learning never stops To my wife and children who have given

me support and understanding over the past seven years To my mother and father who have always been an inspiration

Acknowledgments

I would like to thank my committee for their support and guidance especially Dr Toni Greif, Dr Robert Kramarczuk, and my mentor Dr Richard Murphy

Organizational Structure and Leadership 55

REFERENCES 164

List of Tables

Table 1 Research Design by Variable and Hypothesis 117

Table 8 Average Loyalty Index Ratings by Number of Products 132

Table 9 Quality Dimension Ratings by Number of Products 135

Table 10 Trust Dimension Ratings by Number of Products 135

Table 11 Renew Dimension Ratings by Number of Products 136

Table 12 Recommend Dimension Ratings by Number of Products 136

Table 13 Expand Dimension Ratings by Number of Products 136

Table 14 Small, Medium, Large Bank Loyalty Index Rating Differences 139

Table 15 Small, Medium, Large Bank Quality Dimension Rating Differences 140

Table 16 Small, Medium, Large Bank Trust Dimension Rating Differences 141

Table 17 Small, Medium, Large Bank Renew Dimension Rating Differences 142

Table 18 Small, Medium, Large Bank Recommend Dimension Rating Differences 143

Table 19 Small, Medium, Large Bank Expand Dimension Rating Differences 144

Table 20 Average Loyalty Index Rating Differences by Number of Products 145

Table 21 Single vs Multi product Quality Dimension Rating Differences 146

Table 22 Single vs Multi product Trust Dimension Rating Differences 146

Table 23 Single vs Multi product Renew Dimension Rating Differences 147

Table 24 Single vs Multi product Recommend Dimension Rating Differences 148

Table 25 Single vs Multi product Recommend Expand Rating Differences 148

List of Figures

Figure 7 Average quality dimension ratings by number of products 137

The distinction between perceived service quality and customer satisfaction is blurred in the marketing research literature (Anderson, 1998; Berry, Parasuraman, & Zeithaml, 1994; Berry, Zeithaml, & Parasuraman, 1990; Cooil, Keiningham, Aksoy, Hsu,

2007; Cronin & Taylor, 1992; De Ruyter, Wetzels, Bloemer, 1998; Mueter, Ostrom, Roundtree, & Bitner, 2000; Samuelsen, Gronseth, & Sandvik, 1997) However, customer satisfaction and service quality are defined collectively as the ultimate goal for a firm is customer retention or customer loyalty Customer loyalty is the willingness of customers

to repurchase from a particular firm However, empirical research makes no attempt to distinguish between the concepts of perceived service quality, customer satisfaction, and customer loyalty

Customer loyalty, measured by intent to continue purchases, increase purchases and recommend the company, is a good indicator of company profits The study is based

on a theoretical basis where by moderating roles of switching cost, customer bonds,

perceived alternatives, and several demographical variables result in customer loyalty ratings, but not necessarily satisfaction Marketers have been interested in using these moderating variables to develop effective marketing strategies to attract and retain the most valuable customers Furthermore, according to Berry, Parasuraman, and Zeithaml (1994), customers perceive some attributes more important than others when determining the overall service quality and satisfaction As such, service quality attributes should be measured routinely to provide actionable managerial guidance regarding which service areas a firm should concentrate on in efforts to build loyalty among current customers and attract profitable prospects (Berry, Zeithaml, & Parasuraman, 1990)

Customer satisfaction is associated with an overall performance of the-banking relationship that customers experience through repeated transactions with the bank As described above, customer satisfaction is determined by two primary indicators: (a) expectations or comparison standards, and (b) performance perception

In order to achieve loyal customers, banks must know how to satisfy the

customers Thus, focus on the customers must be given highest priority in

on-line-banking However, a critical issue follows in regard to how banks can remain in control

of customers' access to the distribution channels In the physical marketplace, banks have dedicated links to their customers through their branch network In electronic markets, services are mediated through a distribution channel with several intermediaries

participating in the value chain: context providers, network operators, Internet access providers, business service providers (i.e., portals) and, to an increasing extent, brokers and (i.e., software) agents From having a dedicated link to their customers through

branches, banks are pushed backwards in the value chain with the danger of losing

control of customer access Disintermediation and loss of customer control mean reduced opportunities for fostering customer satisfaction and building strong brands To achieve this control, it is predicted that cooperation with new actors in the value chain will be needed This may also be supplemented by focused acquisitions and licensing of software products (Gordon, 1996)

To satisfy customers, it is important to listen to the individual and specific needs and desires (Sterne, 1998) Therefore, it is of vital importance to give customers the opportunity to respond to offers Responding can include questions, comments on

services, suggestions for improvements, demands, etc and can be mediated through the e-mail system Another way to satisfy customers is to personalize services Loyal

customers can be obtained by providing them with personal attention (Allen, Kania, & Yaeckel, 1998) Frequently asked questions (FAQ), organized discussion groups and the use of push technology to move personalized messages to customers are other means by which added value for the customers can be created Value-added services are assumed to make customers more satisfied

Branding and brand reputation have been discussed in the marketing literature over the last 10 years (Aaker, 1996; Edlin, & Harkin, 2003; Keating, 2006; Mitchell, 2000; Samuelsen et al., 1997) According to Samuelsen et al (1997) reputation is an important determinant of loyalty when products are difficult to evaluate In markets with many suppliers, complex services and unclear values and preferences, rational choices are difficult to make Mechanisms to simplify buying decisions are needed Brand

reputation is one such mechanism where information gathering and processing are

reduced by substituting attribute evaluation with heuristics (i.e., the brand)

To explain why customer satisfaction seems to be a stronger determinant of loyalty than brand reputation, the research will need to look at the bank services currently available from most of the competing institutional trust/Internet banks Brand reputation

is thought of as being a strong determinant of loyalty in markets with complex products where simplifying buying decisions is needed The bank services available to the

customers in the study may be perceived as standardized services, although with rather complex cost structures (e.g., transaction fees, asset based charges, etc.)

Background of the Study Technology and the Internet have had a profound effect on service marketing (Bitner, Brown, & Mueter, 2000) DeRuyter, Wetzels, and Kleijnen (2001) argued that the next vista for organizations operating in virtual marketplaces will involve e-service, which they defined as "an interactive, content-centered and Internet -based customer service, driven by the customer and integrated with related organizational customer support processes and technologies with the goal of strengthening the customer-service provider relationship" (p 186) Thus, e-service is viewed as an emerging mechanism for achieving customer relationship management strategic outcomes This study supports the objectives of this issue by providing an exploratory test of traditional service/relationship marketing theory and measures within the emerging e-banking industry

Part of the attractiveness of e-banking for bank marketers is the ability to shift some of the burden of after-sale service and support to end users via the Internet Many marketers hope to eventually replace traditional mechanisms for after-sale service such as large and expensive customer support/service call centers with digital forms of e-service (e.g., e-mail support protocols, online chat, Frequently Asked Questions/FAQs, and online knowledge bases) The mechanism for the transition to digital forms of e-service is e-banking software that directly links an end user with a marketer's human support

resources and knowledge base This orientation helps to make clear the linkages between e-banking and relationship marketing Banks today are increasingly providing customer service in support of relationship marketing strategic objectives, with the help of

technology via e-service (Barnes, Dunne, & Glynn, 2000; Mueter, Ostrom, Roundtree, & Bitner, 2000) E-banking software suites provide the mechanism by which companies hope to begin to more efficiently and efficaciously provide such e-service at a lower cost

It is hypothesized that the aforementioned customer service needs are particularly important for the emerging e-banking industry as this industry must be able to support the efficacy of their products and services in achieving relationship marketing strategic objectives if e-service is to continue to grow as a viable marketing tactic The

organizations within this industry can most effectively achieve this end by demonstrating the ability to be exemplars of relationship marketing efficacy in their own marketing relationships with the purchasers of e-banking software (i.e., products) and service

Loyalty

Customer loyalty is a complex, aggregated concept that cannot be defined nor measured by any single variable From marketing literature, several antecedents of

loyalty have been revealed Among the determinants of loyalty toward a brand is

customers’ satisfaction with the brand (Samuelsen, Gronseth, & Sandvik, 1997; Selnes, 1993), brand reputation (Samuelsen et al., 1997; Selnes, 1993), switching costs (Dick & Basu, 1994), salesperson trust (Macintosh & Lockshin, 1997), salesperson commitment (Macintosh & Lockshin, 1997), and affective antecedents such as emotion, feeling and mood (Dick & Basu, 1994) Furthermore, social norms and situational influences are assumed to affect loyalty (Dick & Basu, 1994) This research focuses on loyalty among bank customers on the Internet Such customers do not meet salespersons Salesperson trust and salesperson commitment are therefore excluded from the analysis Furthermore, the research excludes affective antecedents such as emotion, feeling and mood, assuming that customer relationships are primarily based on cognitive evaluations of the bank due

to the nature of the services bought Search costs are assumed to be reduced when

moving from the traditional marketplace to electronic markets (Bakos, 1991) Search costs are also treated as a part of the switching cost construct (Fornell, 1992) Since search costs are regarded as an important part of the economics of electronic markets, search costs will be treated as an explicit determinant of loyalty

Many definitions of loyalty have been presented in the literature Jacoby and Chesmut (1978) gave a summary of many of them to conclude that the only way to reveal real loyalty is to measure customers’ attitudes and intensions toward the brand in

question Based on this, loyalty is to measure customers' attitudes and intentions toward the brand in question Based on this, Oliver (1997) defined customers’ loyalty as “a deeply held commitment to re-buy or re-patronize a preferred product or service

consistently in the future, despite situational influences and marketing efforts having the potential to cause switching behavior” (p 392) This means that customers must perceive the bank as better than competitors (i.e., affective loyalty) Re-buying or re-patronizing means that customers must have an intention to keep on using the bank in the future (i.e., conative loyalty) In other words, affective loyalty is related to customers' attitudes

toward the bank while conative loyalty is related to customers' behavioral intentions toward the bank in the future Based on this, we see that loyalty is not only re-buying, or

what Dick and Basu (1994) called spurious loyalty, but loyalty toward a brand also

implies a positive attitude toward the brand in addition to intention to re-buy the brand

Moving from the traditional face to face marketplace to an electronic marketplace, changes customer relationships It is therefore assumed that some of the determinants of loyalty will be affected A reduction in search costs has been predicted (Bakos, 1991, 1997; Strader & Shaw, 1997) This reduction is assumed to reduce loyalty and it may also

be argued that it will change the effect of search costs on loyalty relative to other

determinants Brand reputation is often used as a heuristic for the evaluation of a brand If

a brand has a positive reputation, customers are supposed to be loyal to the brand

Furthermore, better opportunities in searching for information about a brand in electronic markets make it easier for customers to evaluate brand attributes before they buy This reduces the importance of brand reputation as a heuristic for brand quality A

consequence of this could be that the relative importance of brand reputation on loyalty is reduced Electronic markets also enable a wide range of new seller and customer

relationships to be set up, for instance increased and customized product information, customer participation in product development and reduction in order fulfillment time (Methlie, 1998) All this may improve customer satisfaction (Strader & Shaw, 1997) By increasing customer satisfaction, this variable may increase its importance as a

determinant of loyalty Based on these possible changes, a fair proposition is that the values of the determinants of loyalty will change when moving bank services from the physical marketplace to an electronic market

Affective and Conative Loyalty

Affective loyalty is a component of loyalty that focuses on how much a customer likes the bank or how positive their attitude is toward the bank Conative loyalty focuses

on the customer's intention to keep on using the bank in the future Fishbein and Ajzen (1975) argued that attitude toward a product predicts attitude toward buying the product Attitude toward buying the product is assumed to predict intention to buy the product In marketing literature, attitude toward a product is often used as a direct predictor of

intention to buy the product (Brown & Stayman, 1992; Homer, 1990) Since customer satisfaction and brand reputation are the main determinants of loyalty, banks on the Internet should struggle to satisfy their customers and build strong brands

From research in marketing, there is some knowledge about the determinants of loyalty in the physical marketplace Taking this knowledge as the basis, this research is based on the investigation of whether determinants of loyalty in the marketplace hold in

electronic markets as well The research therefore delineates between various

determinants of loyalty which include customer satisfaction with a brand, brand

reputation, switching costs, and search costs

Satisfaction

Customer satisfaction is a post-choice evaluation of a specific transaction (Selnes, 1993) Early studies conceptualized customer satisfaction as customer perception of product performance (Anderson, 1973; Cardozo, 1965) Later studies showed that

customer satisfaction is a function of customer perception of product performance

compared to a set of standards (e.g., expectations, values and norms) related to the

confirmation/disconfirmation paradigm (Yi, 1990) In addition to the direct effect of confirmation/disconfirmation, both expectation (i.e., the comparison standard) and

perception of brand performance are found to have direct effects on customer satisfaction with a brand (Churchill & Surprenant, 1982; Yi, 1990)

Satisfaction is considered to act as an antecedent of loyalty, arising out of direct prior experience (Dick & Basu, 1994) Several studies have found support for the positive relationship between customer satisfaction with a brand and their loyalty toward that brand (Fornell, 1992; Samuelsen et al., 1997; Sandvik & Duhan, 1996) “Loyal customers are not necessarily satisfied customers, but satisfied customers tend to be loyal

customers” (Fornell, 1992, p 7) A satisfied customer has few incentives to change supplier or brand Therefore, “customer satisfaction makes it costly for a competitor to take away another firm's customer” (Fornell, 1992, p 10) Satisfying customers should therefore be of great importance to vendors in keeping their customers loyal Customers

who are satisfied with their bank probably develop a positive attitude toward the bank As

a result, their intention to stay with the bank in the future is likely to be high

Brand Reputation

A brand is a name, term, symbol, sign or design to identify the goods or services

of one seller and to differentiate them from those of competitors (Keller, 1998) Brand reputation has been defined as a perception of quality associated with the brand's name (Selnes, 1993) A strong brand is a brand with “a set of assets linked to a brand's name or symbol that adds to the value provided by a product or service to that firm's customers” (Aaker, 1996, p 7-8) A strong brand is a signal of quality; it is a risk reducer for

customers and it reduces search costs (Keller, 1998) A brand name, or a brand’s

reputation, is often used as a heuristic for choice when intrinsic cues or attributes are difficult or impossible to employ (Selnes, 1993) Brand reputation and satisfaction may look like the same construct In the literature, however, brand reputation is seen more as a long-term and overall evaluation of the product than customer satisfaction (Selnes, 1993)

A positive relationship is expected between brand reputation and customer loyalty

to the brand (Sandvik & Duhan, 1996) The reason for this is that a brand's reputation might function as a social norm and that customers often rely on the beliefs of their reference groups to a great extent Another reason why brand reputation is important for loyalty is that it may be difficult to evaluate satisfaction with a product directly in some situations In such situations, the brand reputation is used as a heuristic for evaluating the product However, an important point to note is that customer satisfaction with a brand is

a determinant of brand reputation in some situations In the insurance industry, for

instance, customer satisfaction with a brand is found to have a positive relation to brand reputation (Selnes, 1993) This underscores both the direct and indirect effects of

customer satisfaction on customers' loyalty

Switching Costs

Porter (1980) defined switching costs as the costs of switching from one supplier's product to another supplier's product Fornell (1992) included search costs, transaction costs, learning costs, customers' habits, emotional costs and cognitive effort in the

switching costs construct As can be seen, switching costs include both economic and psychological values Switching costs is a common strategy to increase loyalty (Dick & Basu, 1994) Currently, banks are eager to launch loyalty programs where customers obtain substantial benefits by holding most of their banking business within one bank (positive lock-in)

“Switching barriers make it costly for the customer to switch to another supplier” (Fornell, 1992, p 10) The implication of this proposition is a positive relationship

between switching costs and customer loyalty High switching costs retain customers from changing banking relationships Therefore, an increase in switching costs will lead

to an increase in loyalty Since this is a kind of lock-in strategy, it has a positive effect on

the intention to keep on as a customer (i.e., conative loyalty), rather than on customers' affective commitment toward the bank (i.e., affective loyalty) Anecdotal experience suggests that customers will probably perceive high switching costs as something

negative, which reduces their flexibility to switch supplier or product

High search costs are assumed to make it expensive for customers to shop around for the best offer in the market The implication of this is that it is costly for customers to find alternative brands or suppliers Therefore, they keep on using the same brand or the same supplier This implies that high search costs lead to high conative loyalty However, customers are probably not satisfied with a situation where it is difficult to find

alternatives and, thus, having limited flexibility being imposed on them

Statement of the Problem Given the proliferation in the 21st century of the e-banking industry, change is an ongoing process which impacts customer loyalty and satisfaction Currently, the e-

banking technology services industry customer loyalty survey is utilized as a valid and reliable instrument from which to base organizational decisions related to e-banking The problem with current utilization of e-banking technology services industry customer

loyalty survey data for primary clientele of the company are not stratified by bank size or single versus multi product services With additional evaluation of survey results, e-banking resource allocation can be more focused and efficacious in promoting corporate profitability as compared with current utilization which primarily benefits quality

improvement programming

Purpose of the Study The purpose of this study was based on a retrospective examination of 2006 E-banking technology services industry customer loyalty survey data results in order to provide information for better marketing resource allocation and corporate success in the e-banking product and service industry The most significant relationships among service quality dimensions, perceived value, customer satisfaction, and customer loyalty are assessed by primary customer (i.e., bank) size and single versus multi product delineation which is currently not analyzed by corporate executives This study utilized quantitative

ex post facto data examination methods to stratify the primary e-banking clientele survey results to be used for improved resource allocation, particularly marketing MANOVA (i.e., multiple analyses of variance) statistical measures will identify the most significant e-banking clientele loyalty ratings by size stratification (i.e., small, medium, large asset classes) and single versus multi product classification Customer loyalty, measured by intent to continue purchases, increase purchases, and recommend the company is a good indicator of company profits (Gounaris & Stathakopoulos, 2004)

Rationale/Significance The research model developed herein could be expanded to include other important constructs There are numerous model extensions that would merit

consideration For example, the ultimate aim of e-banking and relationship marketing initiatives involves strengthening brand equity Extending this basic model to include constructs such as brand equity would represent a significant contribution to the

literature Adding additional explanatory constructs such as attitude (Bobbitt &

Dabholkar, 2001), e-service adoption characteristics (de Ruyter et al., 2001;

Parasuraman, 2000), trust (Urban et al., 2000), value (Cronin et al., 2000; Sawhney &

Parikh, 2001; Teas & Agarwal, 2000; Ulaga & Chacour, 2001), and equity (Oliver, 1997), would also likely increase the explanatory power of the model Bobbitt and Dabholkar (2000) have specifically called for greater academic research into the theoretical underpinnings of technology-based self-service

With the aforementioned considerations posited, the e-banking technology services industry customer loyalty survey data is analyzed by corporate officials within the company and reported on an annual basis This analysis typically focuses on the relationship between e-service quality and customer loyalty ratings as the basis for quality improvement programming However, certain aspects of the e-banking

technology services industry customer loyalty survey data by section of client response (i.e., Perceptions, Relationship, Experiences, Business Objectives, Integrated Business Solutions, and Overall Assessment) as well as sub-sections within the Overall

Assessment section (i.e., Quality, Trust, Renew, Recommend, and Expand) are not delineated in corporate reporting Furthermore, the primary e-banking client from which the majority of corporate revenues are received (i.e., banks) are not stratified by asset size (i.e., small, medium, large) nor are they delineated by single project versus multi product purchasers in the corporate reports This data is essential for organizations to consider in maximizing resource allocation, particularly marketing resources, from which to recruit new banking business and retain the most valuable-banking businesses Results of this research and data analysis have the potential to expand the utilization of e-banking

technology services industry customer loyalty survey results from quality improvement into resource allocation and marketing strategy based on answering the following

research questions

Research Questions The research questions for this study include:

RQ1 What are the differences in 2006 Loyalty Index Ratings as measured by the e-banking technology services industry customer loyalty survey between small, medium, and large bank customers?

RQ2 What are the differences in the 2006 Overall Quality Ratings (i.e., Quality, Trust, Renew, Recommend, Expand) as measured by the e-banking technology services industry customer loyalty survey between small, medium, and large bank customers?

RQ3 What are the differences in the 2006 Loyalty Index Ratings as measured by the e-banking technology services industry customer loyalty survey between single and multi product bank customers?

RQ4 What are the differences in the 2006 Overall Quality Ratings (i.e., Quality, Trust, Renew, Recommend, and Expand) as measured by the e-banking technology services industry customer loyalty survey between single and multi product bank

customers?

Hypotheses The alternate hypotheses for this study include:

HA1: There are statistically significant differences in the 2006 Loyalty Index Ratings as measured by the e-banking technology services industry customer loyalty survey between small, medium, and large bank customers

HA2: There are statistically significant differences in the 2006 Overall Quality Ratings (i.e., Quality, Trust, Renew, Recommend, Expand) as measured by the e-banking technology services industry customer loyalty survey between small, medium, and large bank customers

HA3: There are statistically significant differences in the 2006 Loyalty Index Ratings as measured by the e-banking technology services industry customer loyalty survey between single and multi product bank customers

HA4: There are statistically significant differences in the 2006 Overall Quality Ratings (i.e., Quality, Trust, Renew, Recommend, and Expand) as measured by the e-

banking technology services industry customer loyalty survey between single and multi product bank customers

Definition of Terms The following terms are defined for the purpose of this study:

Affective Loyalty The component of loyalty that focuses on how much a customer

likes the firm or how positive their attitude is toward the firm (Chandrashekaran et al., 2007)

Brand Reputation The perception of quality associated with the brand’s name

(Selnes, 1993)

Cognitive Loyalty The component of loyalty that focuses on the customer’s

intention to keep using the firm in the future (Chandrashekaran et al., 2007)

Large bank asset classification Banks with assets over $10 billion (Stiroh &

Metli, 2003)

Loyalty A positive attitude toward a brand in addition to intention to re-buy the

brand (Chandrashekaran et al., 2007)

6 Search Costs are the costs incurred by the buyer to locate an appropriate seller

and purchase a product (Bakos, 1997)

Medium bank asset classification Banks with assets between $500 million and

$10 billion (Stiroh & Metli, 2003)

Small bank asset classification Banks with assets less than $500 million (Stiroh

& Metli, 2003)

Switching Costs The costs of switching from one supplier’s product to another

supplier’s product (Porter, 1980)

Assumptions and Limitations This study makes the following assumptions:

1 It is assumed the 2006 e-banking technology services industry customer loyalty survey participants answered honestly and without bias

2 It is assumed the 2006 e-banking technology services industry customer loyalty survey participants are representative of the e-banking customers that did not complete the 2006 survey

3 It is assumed that the 2006 e-banking technology services industry customer loyalty survey has adequate measures of content and criterion related validity from which to reach valid research conclusions in this study

4 It is assumed that 2006 e-banking technology services industry customer loyalty survey subsection questions for each category are equivalently

weighted and contributory in the loyalty index scores

5 It is assumed that e-banking client stratification by asset size (small, medium, large) and single versus multi product lines is useful in proposing marketing strategy and resource allocation resulting in increased corporate profitability This study has the following limitations:

1 The study is limited to e-banking clients and the results cannot be generalized beyond this population

2 The study is limited to the analysis of 2006 e-banking technology services industry customer loyalty survey data which may or may not be representative

of previous or future year results

3 Affective responses by 2006 e-banking clients to survey questions may have been affected by daily events beyond the control of the researcher

4 Biases and other mental processing capabilities by 2006 e-banking survey clients are unknown factors that cannot be directly assessed by the survey questionnaire instrument

5 There was the possibility of human data entry errors by the survey compiler to the electronic database which are not controllable

The e-banking technology services industry customer loyalty survey was custom designed in 2000 by an outside research firm to meet the needs the Client Loyalty

Program (CLP) The survey was revised in 2005 and again in 2006 to reflect changes in the CLP and to eliminate statistically redundant items Approximately 1,100 customers are invited to complete the survey each year The overall response rate in 2006 was 68%

The survey was intended to measure three factors: (a) customer perceptions (4 items); (b) customer-provider relationships (10 items); and (c) achievement of strategic objectives (5 items) In addition, the survey employs three industry-standard outcome items and one specific item to assess customer satisfaction and loyalty:

1 Overall Satisfaction In general, how satisfied are you with the products and

services you have purchased?

2 Likely to Renew If you had to renew your contract today, how likely is it that

you would do so?

3 Likely to Recommend How likely are you to recommend current e-banking

services to a business associate?

4 Company to do business with Considering all of your organization's

interactions with us in the past 12 months, how would you rate the service provider as a company to do business with?

The e-banking technology services industry customer loyalty survey also uses an index constructed of two items from the perceptions factor and three outcome variables (i.e., renew, recommend, and company to do business with) to track changes in customer perceptions and loyalty

Annual reviews of the e-banking technology services industry customer loyalty survey’s statistical properties consistently support the validity of the survey Factor analysis is used to confirm the existence and relative independence of the three factors Reliability of scales based on these three factors is typically well above 80 Further evidence of the validity of the survey derives from its usefulness at the corporate level in identifying strengths and areas for improvement, and at the individual customer level, identifying and rejuvenating at-risk customer relationships

Theoretical/Conceptual Framework The ultimate purpose of e-banking services is to help firms better manage

investment accounting information, increase efficiency and improve decision making

For the service provider (i.e., financial service firm) the goal is to improve customer relationships, loyalty and maximize a customer's lifetime value In fact, Kalakota and Robinson (2001) stated that within the context of e-banking, "the timely delivery of excellent service is customer relationship management" (p 171) The growing focus on e-banking underscores the relationship marketing foundations of e-service practices, an important area of recent academic inquiry Parvatiyar and Sheth (2000) reviewed the literature to date and conclude with an overall definition of relationship marketing as "the ongoing process of engaging in cooperative and collaborative activities and programs with immediate end-user customers to create or enhance mutual economic value at a reduced cost" (p 9) The conceptual model (see Figure 1) represents the

theoretical/conceptual framework with the e-banking industry in an integrated fashion similar to Oliver's (1997) more general and comprehensive model of consumption

processing

Figure 1 Conceptual e-banking model

The first three model constructs (i.e., subjective disconfirmation, quality, and satisfaction) share a long history of being considered relative to one another in the

marketing literature based on Oliver’s (1997) interpretation of the appropriate

constitutive and operational definitions of these constructs, as well as the hypotheses related to their relative causal orderings Subjective disconfirmation can be defined as a comparative process by customers between performance evaluations and some pre performance standards While many standards can be applied, this study uses three of the most widely used including expectations, predictions, and relative to competitive

offerings Subjective disconfirmation has been related in the literature to both quality

perceptions and satisfaction judgments (Parasuraman, Berry, & Zeithaml, 1991;

Zeithaml, Berry, & Parasuraman, 1993)

Quality can be defined as excellence Dabholkar (2000) posited that within service

contexts, the evidence supports an assertion that customers who view technology-based service as easy-to-use, reliable, and enjoyable also perceive higher service quality in such technology-mediated service offerings (i.e., e-service) Perceived service quality is

believed to contribute to positive business outcomes such as greater levels of customer satisfaction and, by extension, favorable marketing behaviors such as repurchase and positive word-of-mouth behaviors

Satisfaction, on the other hand, is the consumer's fulfillment response (Oliver, 1997) Szymanski and Hise (2000) argued for the importance of e-satisfaction in

technology-mediated relationships These authors suggested that the conceptual domain

of e-satisfaction appears similar to that understood from the general marketing literature This assertion further supports our reliance on Oliver's (1997) constitutive definitions for purposes of this research study In addition, satisfaction judgments are generally believed

to be superior to quality perceptions (Cronin & Taylor, 1992; Oliver, 1997)

Loyalty to business partners who use the Internet in electronic exchanges

similarly seems an important contributor to Internet use and e-commerce Griffin (1996) reported that customer loyalty is one of the most significant contributors to the bottom line in a technology-mediated environment Reichfeld and Schefter (2000) argued that loyalty is a more important customer consideration than even price In fact, the research

will determine whether or note there is a high cost associated with low levels of loyalty in e-commerce

Loyalty is a sophisticated construct Oliver (1999) asserted "it is time to begin the determined study of loyalty with the same fervor that researchers have devoted to a better understanding of customer satisfaction" (p 33) Oliver (1999) distinguished satisfaction (i.e., pleasurable fulfillment) from loyalty, which he defines as "a deeply held

commitment to re-buy or re-patronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or same-brand set purchasing, despite situational influences and marketing efforts having the potential to cause switching

behaviors" (p 34) Morgan (2000) suggested that the term loyal can be interpreted in

different ways, ranging from affective loyalty (i.e., what I feel) to behavioral loyalty (i.e., what I do) This research study operationalized loyalty at the global level of analysis to accommodate these perspectives

The relationship between satisfaction and loyalty has also enjoyed a measure of attention in the recent literature This research study envisions loyalty as super ordinate to satisfaction in that loyalty can capture long-term relationship elements that lie outside the domain of satisfaction in a Business-to-Business (B2B) context (Barnes et al., 2000) This B2B perspective appears consistent with Heskett, Sasser, and Schlesinger (1997) and Hunter (1997) who asserted that the three primary measurements of customer loyalty commonly known as the three R’s included:

1 Revenues and profits from retention of loyal customers

2 Repeat sales

3 Referrals

From a practitioner perspective, Pastore (2001) suggested that customer loyalty and satisfaction will continue to play key roles as companies evaluate spending budgets based on a study by NFO Prognostics (proprietary) In fact while the study suggested that satisfaction scores and reference ratings are generally strong, many professional service

buyers are shopping around with each new IT project Such shopping around behavior is

an indicant of a weak marketing relationship This finding strengthens the basic premise

of this research study calling for relationship-marketing-based models specific to the banking industry In summary, the weight of the evidence to date suggests that e-

e-satisfaction should be subordinate to loyalty in the formation of customer behaviors Assuming a base level of satisfaction, the research expects loyal customers to engage in activities that support and strengthen their relationship with the sponsoring e-banking company, as well as engage in positive word-of-mouth activities within the professional community (Taylor, 1997)

Organization of the Remainder of the Study

In summary, the purpose of this study is to retrospectively examine 2006 banking technology services industry customer loyalty survey data results in order to provide information for better marketing resource allocation and corporate success The most significant relationships among service quality dimensions, perceived value,

E-customer satisfaction, and E-customer loyalty will be assessed by primary E-customer (i.e., bank) size and single versus multi product delineation which is currently not analyzed by

corporate executives Chapter 2 presents the literature review in support of the conceptual framework, including the study constructs, concepts and variables Chapter 3 reviews the design of the study, population, instrumentation, data collection, and data analysis

Chapter 4 provides the data analysis And, chapter 5 discusses the results of the study with provisions for future research recommendations

CHAPTER 2 LITERATURE REVIEW

Introduction The purpose of this study is to retrospectively examine 2006 E-banking

technology services industry customer loyalty survey data results in order to provide information for better marketing resource allocation and corporate success The most significant relationships among service quality dimensions, perceived value, customer satisfaction, and customer loyalty will be assessed by primary customer (i.e., bank) size and single versus multi product delineation which is currently not analyzed by corporate executives This study utilized quantitative ex post facto data examination methods to stratify the primary e-banking clientele survey results to be used for improved resource allocation, particularly marketing MANOVA (i.e., multiple analyses of variance)

statistical measures will identify the most significant e-banking clientele by stratification (i.e., small, medium, large asset classes) and single versus multi product classification by survey loyalty component stratification Customer loyalty, measured by intent to continue purchases, increase purchases and recommend the company, is a good indicator of

company profits (Gounaris & Stathakopoulos, 2004)

This chapter presents a review of the literature in support of the conceptual

framework for the study in seven sections Section 1 presents an overview of the new economy in the 21st century that is largely driven by electronic related advances in

technology Section 2 presents an overview of e-business followed by section 3 which

discusses business models and theoretical paradigms Section 4 presents summary

information related to organizational structure and leadership while section 5 is based on concepts of organizational change and trust Section 6 is related to customer centric business strategies while section 7 provides a comprehensive overview of customer loyalty to include sub topics of relationships, total quality management, customer

intimacy, customer satisfaction, brand reputation, switching costs, search costs, and other related variables of interest in this study

Technology Advances and the New Economy

In an increasingly networked world, information of varying quality is being aggregated for business use Senior management's course of action is clear: (a) view; (b) manage, and (c) deliver information as a competitive weapon Information technology (IT) change is all-pervasive, or ubiquitous Consequently, it is important that employers engage in change process in thoughtful ways–respecting and holding to ideas and

practices of the past that have enduring value while also attending to emerging ideas and necessary changes in practice The changes now experienced are no one-time affair All business organizations must expect accelerating change and continuing efforts for

renewal Gullivan (2001) explained that it is not getting people to learn C++, but trying to figure out how to do things, all the time, and differently

The capabilities and potential of technology is increasing more rapidly than ever before During the past three decades, consumers have received about 30% more

computer power each year for the same price Competition among microprocessor