A PROCESS FOR DETERMINING USER REQUIREMENTS IN

eCRM DEVELOPMENT

A Strategic Aspect and Empirical Examination

Ing-Long Wu

and Ching-Yi Hung

Department of Information Management, National Chung Cheng University

168 University Road, Ming-Hsiung, Chia-Yi, Taiwan

Chung-Hwa Telecommunication Inc., Taipei, Taiwan

Keywords: Relationship marketing, CRM, eCRM, Consumer behavior, System requirement analysis.

Abstract: Customer relationship management (CRM) has incerasingly become important while business focus has

shifted from product-centric to customer-centric,. However, many organizations fail to achieve the

objectives. One of the important determinants is the deployment of electronic CRM (eCRM) in

organizations. In essence, CRM is complex in comprising product, channel, consumer, delivery, and service

aspects. This requires different approaches in eCRM development. Determining user requirement is the

most important phase and the key to the final success in system use. This research proposes a strategy-based

process for system requirement analysis. Previous research has not discussed the important role of the CRM

strategies in building eCRM. Moreover, the implemenation process was only reported partially in literature.

Basically, the framework contains three steps: (1) define CRM strategies, (2) identify consumer and

marketing characteristics, and (3) determine system requirements. This framework is further examined by

empirical data. The results indicate that CRM strategies have positive impact on system requirement

analysis while developing eCRM.

1 INTRODUCTION

Business over the Internet presents unprecedented

opportunities for building sales and increasing

revenue streams by expanding geographical scope,

enhancing channel coordination, and improving

supply chain efficiency. To be successful at

e-commerce, companies have to rethink their

business focus. Their business model has to evolve

from production-centric to customer-centric. As

products have become more commoditized and

pricing differences more slight, the great

differentiator today is delivering customer value.

Customer value is what leads to increased loyalty,

sales, and retention rates. Customer relationship

management (CRM) is a strategic and management

concept in creating customer value

(Kennedy and

King; 2004; Karakostas, et al., 2005). Here,

electronic CRM (eCRM) is a business and

technology discipline that helps firms acquire and

retain the most profitable customers while meeting

their requirements. With this trend, too many

organizations are rushing to implement a web site

and take a “build it and they will come” attitude.

However, the results were less than what was

expected. Estimates of CRM projects failing to

achieve their objectives range from 60%-80% (Kale,

2004). One of the reasons for unsatisfactory

outcomes are focusing solely on tecchnological

aspect rather than on customer and marketing

aspects for successful use of this system by

marketing personnel (Pavlou, 2003; Wu and Wu;

2005).

Basically, the idea of CRM is basically founded

on relationship marketing. Relationship marketing is

mainly to build a long term association,

characterized by purposeful cooperation and mutual

dependence on social, as well as structural, bonds

(Mowen and Hinor, 1998). CRM context inherently

involves a number of compound components on

product design, customer, marketing characteristics

and customer behavior for relatively complex

processes. The development of eCRM therefore

requires following different approaches from the

traditional system development process (Albert, et

al., 2004). Requirement analysis is the most

Wu I. and Hung C. (2008).

A PROCESS FOR DETERMINING USER REQUIREMENTS IN eCRM DEVELOPMENT - A Strategic Aspect and Empirical Examination.

In Proceedings of the Tenth International Conference on Enterprise Information Systems - ISAS, pages 5-12

DOI: 10.5220/0001668200050012

 SciTePress

important phase in the development process and the

key to the success of system use. Thus, a strategic

view on requirement analysis can provide a clear

picture to define the complex process and further,

simplify the requirement analysis (Maguire, 2001;

Rigby and Ledingham, 2004; Chan, 2005).

Therefore, this research proposes a

strategy-based process for effectively determining

system requirements in eCRM development. The

first defines a well-planned, unique customer

strategy, which conceptually considers customer

needs and marketing objectives, to direct CRM

activities. Next, the fundamentals to determining

customer strategies require further understanding

consumer behavior and marketing stimuli in order to

build effective CRM (Brown, 2000). Accordingly,

requirement analysis in eCRM development can be

effectively determined based on the previous

analyses. In summary, this planning process

comprises three steps: define customer strategies,

identify consumer and marketing characteristics, and

determine system requirements. Little research has

discussed the important role of customer strategies

in e-CRM development. The literature on this

implementation process has only reported partially

rather than integratively. Moreover, the techniques

used for analyzing these steps are also discussed.

Finally, this framework is empirically examined to

understand its practical validity.

2 LITERATURE REVIEW

2.1 IT Planning and User

Requirements

Requirement determination is the process of

gathering and modeling information about required

functionality, data, and interface of a proposed

system by a system analyst, and has been widely

recognized as the most difficult phase in system

development process (Larson and Naumann, 1992;

Guinan, et al., 1998). Difficulties in requirements

determination arise from four major reasons (Davis,

1982): (1) cognitive issues resulting from constraints

on humans as information processors and problem

solvers; (2) problem structuring issues resulting

from the variety and complexity of information

requirements; (3) communication issues resulting

from the complex patterns of interaction among

users and analysts in defining requirements; (4)

political and behavioral issues resulting from

unwillingness of some users to provide requirements.

Problem structuring issues are most apparent to

system analysts for solving requirements

determination problem (Sutcliffe, 1997). In

particular, this study intended to alleviate the impact

of unstructured problem associated with CRM

domain on system requirements analysis.

A number of models have been proposed for

developing the information system plan and

information architecture. The main focus of these

models is on discussing requirements analysis of

system development. The three-stage model by

Bowman et al. (1983) suggests that a strategic

alignment effort as the first stage should precede

organizational information requirements as the

second stage and resource allocation as the third

stage. The stimulus for systems development is

typically an organizational problem. Problems may

be usefully analyzed in terms of four levels in a

pyramid structure with organizational strategies at

the top, business processes at the second, tasks at the

third, and information at the bottom (Leifer et al.,

1994; Browne and Rogich, 2001). The review of

these models would lay a foundation on developing

the research framework in this study. A

strategy-based process initiated with CRM strategis

would define a new type of customer relationship

and in turn, ceate a need for futher understanding

consumer behavior and marketing characteristics.

Accordingly, information requirement analysis

would be effectively followed.

2.2 CRM, eCRM and CRM Strategies

The new Internet Economy presents numerous

challenges to marketers along with the significant

opportunities it offers. Customers are smart,

powerful, and highly informed. Customers are

demanding that every interaction a company has

with them leave them more than satisfied. In fact,

customer satisfaction is considered as the most

important new performance metric, soon to rival

revenue and profit in importance. Today, any

advantage based on product or service is short-lived.

Instead, forging long-term relationships with

customers is the key to stability in an increasingly

dynamic market (Lee-Kelley et al., 2003; Payne and

Frow, 2004). It indicates that traditional marketing

approach no longer fulfills the needs of the Internet

era. The premise is that existing customers are more

profitable than new customers; that it is less

expensive to sell an incremental product to existing

customers; and that customer retention would be

maximized by matching products and levels of

services more closely to customer expectation. The

ICEIS 2008 - International Conference on Enterprise Information Systems

central objective of CRM is thus to maximize the

lifetime value of a customer to the organization

(Peppers et al., 1999; Brown, 2000; Turban et al.,

2004). However, all have remained essentially

theoretical concepts, aspirations rather than a

practical or commercial reality. It has been difficult

to develop eCRM due to the complexity in the CRM

process. The great advancement in Internet and new

information technologies recently has provided

tremendous resources for supporting the

development of eCRM. (Curry and Curry, 2000; van

Nunen and Zuidwijk, 2004).

There are three similar models proposed to

define CRM strategies in e-commerce. The first

model includes three stages: acquisition,

enhancement, and retention (Kalakota and Robinson,

2001). Each has a different impact on the customer

relationship and each can more closely tie the

company to the customer’s life and value.

(1). Acquiring new customer. You acquire new

customers by promoting product and service

leadership that pushes performance

boundaries with respect to convenience and

innovation. The value proposition to the

customer is the offer of a superior product

backed by excellent service.

(2). Enhancing profitability of existing customers.

You enhance the relationship by encouraging

excellence in cross-selling and up-selling.

This deepens the customer relationship. The

value proposition to the customer is an offer

of greater convenience at low cost (one-stop

shopping).

(3). Retaining profitable customers for life.

Retention focuses on service

adaptability–delivering not what the market

wants, but what customers want. The value

proposition to the customer is an offer of a

proactive relationship that works in his or

her best interest.

Next, Organizations all seemed to fall within one

of three distinct stages for customer care: customer

acquisition, customer retention, and strategic customer

care (Brown, 2000). The descriptions of Stage I and

Stage II are similar to Kalakota and Robinson’s model.

Stage III organizations recognize that customer

relationships that are in essence strategic partnerships

allow them to increase own benefits by focusing on

enhancing the customer’s profits. Finally, Gartner

Group discusses a relationship marketing model. It

comprises four categories, customer selection,

customer acquisition, customer retention, and customer

extension, as shown in Figure 1 (Turban et al., 2004).

Figure 1: Relationship marketing model.

2.3 Consumer Behavior

Relationship marketing strategy descrides high-level

concept. Consumer behavior is the basis of the

concept and has a profound impact on the way that

online systems are developed. Market researchers

have been trying for decades to understand

consumer behavior. Schiffman and Kanuk (1994)

briefly discusses six comprehensive models of

consumer behavior: the Nicosia mode (Arsham and

Dianich, 1988), the Howard-Sheth model (Howard

and Sheth, 1969), the Engel-Kollat-Blackwell model

(Engel et al., 1990), the Sheth family

decision-making model (Sheth, 1974), the Bettman

information-processing model (Bettman, 1979), and

the Sheth-Newman-Gross model (Sheth et al., 1991).

For example, the Nicosia model focuses on the

relationship between the firm and its potential

consumers. In the broadest terms, the firm

communicates with consumers through its marketing

messages (advertising), and consumers communicate

with the firm by their purchase responses. This

model involves a four-stage procedure. The first

stage comprises two factors that affect consumer

attitudes, i.e., (1) consumer characteristics, and (2)

target market and competitive environment. The

second stage deals with the search for the relevant

information and evaluation of the firm’s brand in

comparison with alternative brands. The third stage

is that the consumer’s motivation toward the firm’s

brand results in purchase of the brand from a

specific retailer (decision making). The final stage

consists of two types of feedback from the purchase

experience, i.e., one to the firm in the form of sales

data, and the other to the consumer in the form of

experience (Arsham and Dianich, 1988).

Moreover, a model for buyer behavior indicates

a stimulus-response strucure similar to the previous

ones, as indicated in Figure 2 (Kotler, 1997). This

model illustrates marketing and other stimuli

entering the buyer’s “black box” and producing the

buyer’s responses. An exception to this model is

that buyer characteristics are classified as part of

A PROCESS FOR DETERMINING USER REQUIREMENTS IN eCRM DEVELOPMENT - A Strategic Aspect and

Empirical Examination

buyer’s black box, rather than as outside stimuli.

Besides, a consumer behavior model in e-commerce

includes outside stimuli, personal characteristics,

external characteristics and vendors’ controlled

systems entering decision-making process and

eventually producing buyers’ decisions (Turban et

al., 2004). Here, vendors’ controlled systems is

additional input component while compared to

traditional behavior model.

Figure 2: Buyer behavior model (Kotler, 1997).

3 THEORETICAL MODEL

Theoretically, the solution for this problem would be

based on a strategic perspective to pre-define

marketing orientation. Accordingly, system

requirements would be effectively determined from

a high-level perspective. Thus, this research

proposes a strategy-based process for effectively

defining system requirements in eCRM development,

as indicated in Figure 3. The theoretical basis for

building this model is mainly based on the analysis

of a hierarchical structure with firm strategies at the

top, business processes at the second, tasks at the

third, and information at the bottom, as discussed in

Section 2.1. This process basically contains three

steps: (1) define customer strategies, (2) identify

consumer and marketing characteristics, and (3)

determine system requirements. Prior research has

just literally discussed the importance of strategic

role in determining system requirements.

Furthermore, a well-defined process for requirement

analysis has not reported integratively.

Identify

consumer & marketing

characteristics

Identify

consumer & marketing

characteristics

Define

CRM strategies

Define

CRM strategies

Determine

system requirements

Determine

system requirements

Figure 3: Theoretical model.

3.1 Define CRM Strategies

Comparatively, the Brown’s model basically covers

the primary features of the other models, as

discussed previously, adopted to analyze the choice

of CRM strategies in this step, i.e., customer

acquisition, customer retention, and strategic

customer care. The decision is important because it

will dictate the infrastructure strategy of technology

(Brown, 2000).

3.2 Identify Consumer and Marketing

Characteristics

This step analyzes consumer and marketing

characteristics based on the defined CRM strategies

because the strategies are all attempting to discover

and build highly personalized customer service. A

summary of the literature indicates that the driving

forces for making purchase decisions are primarily

from the set of inputs and specifically, there were

three key inputs, i.e., (1) personal characteristics, (2)

external characteristics, and (3) stimuli. This set of

inputs can be concluded with consumer

characterisitcs and marketing stimuli.

3.3 Determine System Requirements

This step mainly bases the analyses of CRM

strategies and consumer and marketing

characteristics, on deriving a series of system

requirements for eCRM. An example could be that if

the customers tend to be more sensitive for the price

toward certain prodcuts, the eCRM will consider

such IT features as price-comparative analysis for

these products to be included. Thus, the the major

focus would be on discussing the performance of

system requirements analysis.

Next, the three-step framework is primarily

derived based on an extensive literature review and

thus, further verification by empirical data is

required for practitical validity. This verification is

primarily to explore the influence of the first step on

the second step, the second step on the third step.

However, there are two sets of variables discussed in

the second step, consumer and marketing

characteristics. Thus, two hypothesess for each

relationship are presented for this.

Hypothesis 1: The choice of CRM strategies is

positively related to consumer

characteristics.

Hypothesis 2: The choice of CRM strategies is

positively related to marketing

stimuli.

ICEIS 2008 - International Conference on Enterprise Information Systems

Hypothesis 3: Consumer characteristics are

positvely related to the performance

of requirements analysis.

Hypothesis 4: Marketing stimuli are positively

realted to the performance of

requirements analysis.

4 RESEARCH DESIGN

4.1 Instrumentation

The instrument contains a four-part questionnaire as

described subsequently. The first part uses nominal

scales, while the rest use 7-point Likert scales.

4.1.1 Basic Information

This part collects organizational characteristics

including industry, annual revenue, number of

employees, and experience of eCRM and

respondent’s characteristics including education, age,

experience, and position.

4.1.2 CRM Strategies

This part is adapted from a self-assessed instrument

for defining CRM strategies (Brown, 2000),

comprising 12 items in all. Example attributes

include Internet applications, differentiated services,

customer segmentation, and customers’ profitability,

in order to discriminate the adoption of CRM

strategies.

4.1.3 Consumer and Marketing

Characteristics

This part is adapted from two constructs in Turban et

al., (2004). It includes 10 subconstructs for

consumer characteristics such as age, gender,

income, education, lifestyle, psychological state,

occupation, values, personality, and marital as well

as 4 subconstructs for marketing stimuli such as

price, promotion, quality and product.

4.1.4 Performance of Requirement Analysis

This part is adapted from the instrument for

assessing requirements analysis (Teng and Sethi,

1990). This measure includes five items, accuracy

and free bias, completeness, decrease of user

requirements determination time, usefulness of

output information, and ease of use.

4.2 Sample Organizations and

Respondents

Service industries would have more expeience on

CRM activities. Moreover, the activities usually

need massive IT investment and also involve

strategic planning. It is assumed that larger firms

would be more likely to have this experience. A

study sample including 645 service firms and 200

finance and banking firms was thus selected from

the year 2004 listing of commonwealth 1155

manufacturing firms, 645 service firms, and 200

finance and banking firms. Based on this sample,

CIOs or IS top managers were selected as the

respondents. This is because this study focuses on

the understanding of IT applications development

and also involves the analysis of CRM strategies,

and therefore CIOs are likely to be the managerial

personnel most familiar with this topic. 159 replied,

with 4 incomplete responses deleted, resulting in a

total sample of 155 respondents for an 18% response

rate. The seemingly low response rate raises the

concern about non-response bias. A test for

non-response bias was conducted using two

responding subsamples: early and late respondents.

They were correlated on their annual revenue and

working experience. There is no significant

systematic non-response bias in the responding

sample.

4.3 Scale Validation

Confirmatory factor analysis (CFA) is used to analyze

scale validation. There are three measurement models

for the instrument. The results are reported in Table 1.

All indices are above the criteria.

Table 1: Scale reliability and validity.

Scale Item loading

Construct

reliability

AVE

Define CRM strategies

0.85-0.88 0.92 0.82

Identify consumer and

marketing

characteristics

0.76-0.83/0.82-0.8

0.83/0.87 0.69/0.75

Performance of

Requirement analysis

0.88-0.96 0.95 0.85

5 ANALYSIS AND FINDINGS

5.1 Define CRM Strategies

Cluster analysis is used to analyze the strategic types.

The results finally suggests that three-cluster

A PROCESS FOR DETERMINING USER REQUIREMENTS IN eCRM DEVELOPMENT - A Strategic Aspect and

Empirical Examination

solution is the appropriate choice, with cluster sizes

of 20, 70, 65 firms for clusters 1, 2, and 3

respectively. Scheffe’s multiple comparisons is used

to define the three clusters. Corresponding to the

Brown’s model, clusters 2, 3, and 1 can be

reasinabely defined as the strategies of customer

acquisition (45.2%), customer retention (41.9%),

and strategic customer care (12.9%), respectively.

From the percentage distribution, some facts can be

discussed for practice. There are almost half of the

responding firms considering customer acquisition

as the major CRM strategy. Obviously, traditional

marketing approach is still playing the important

role while CRM approach is currently in the early

stage for most firms in Taiwan.

Nevertheless, the adoption of the other two

CRM strategies adds up to occupy a high percentage

(54.8%). This implies that a trend of moving toward

CRM-based marketing strategies is developing as

Internet-based technology plays an important role in

supporting the features of customer retention and

strategic customer care. Finally, only 12.9 % of the

responding firms are in the stage of strategic

customer care. They have built the relationship of

strategic partnership with customers. However,

customers, in essence, are associated with

uncertainty and complexity in many aspects and

require extended time and effort to achieve.

5.2 Identify Consumer and Marketing

Attributes

MANOVA is used to examine the relationship of

CRM strategies with metric attributes and consumer

characteristics with non-metric attributes. The test is

significant at 0.01 level. Therefore, Hypothesis 1 is

accepted. In particular, univariate F statistics are

further examined to understand the ten consumer

characteristics varying across the three CRM

strategies. The results are reported in Table 2. Eight of

them report significant differences across the three

CRM strategies. This explains some facts.

The range

of user requirement may be approximately defined

based on these aspects and the determination process

should proceed with priorities on these aspects.

Specifically, while examining group mean

differences of the consumer characteristics, it

indicates a pattern that acquisition strategy indicates

the least significant role in identifying the consumer

characteristics for building customer relationship.

This may be because this strategy mainly focuses on

expanding new customers rather than exploring

existing customers. As the firms move to customer

retention, the focus shifts to customer-centered and

customers are initially considered as the important

asset of the firms. Differentiated services for

customers are critical to sustaining their profits. For the

firms evolving to strategic customer care, the focus is

on determining the most profitable customers and

further developing differentiated services for the

customers. The specific findings, while different

customer strategies place different focuses on

consumer characteristics, would provide insight for

clearly defining the particular scope of user

requirement.

For instance, one, six, and eight consumer

characteristics, as indicated in Table 2, are the focus on

requirement analysis for the adoption of acquisition,

retention, and strategic customer care respectively.

Table 2: Univariate tests for consumer attributes across

CRM strategies.

Customer

strategies

Consumer

characterist

ics

P-val

1 2 3

Group

mean

differences

Age 7.83 0.012* 3.58

5.01 5.93

3>1*, 2>1*

Gender 6.43 0.031* 2.84

5.16

5.26

3>1*, 2>1*

Income

13.2

0.000*

4.98

5.69

6.43

3>1*

Education

10.1

0.001* 3.21

4.82

6.25

3>1,2*, 2>1*

Lifestyle 5.12 0.041* 2.31 3.84

4.51

3>1*

Psychological 7.34 0.071 3.03 3.31 4.01 -

Occupation 6.64 0.029* 2.96

5.39

6.23

3>1*, 2>1*

Values 6.38 0.033* 3.01 3.68

5.23

3>1,2*

Personality 9.23 0.009* 3.18

5.23

5.41

3>1*, 2>1*

Marital 5.89 0.064 3.11 3.70 4.01 -

*:P<0.05; 1:Customer acquisition, 2:Customer retention, 3:Strategic

customer care

The second part discusses the effect of CRM

strategies on marketing stimuli. The same procedure

is used. The test is significant at 0.01 level.

Therefore, Hypothesis 2 is accepted. The same

univariate F statistics are further examined across

the three CRM strategies. The results are reported in

Table 3 and all the four marketing stimuli are

significant differences across the three CRM

strategies. Specifically, while examining group mean

differences of the marketing stimuli, acquisition

strategy influences the four marketing stimuli. This

is because this strategy aims mainly at expanding

new customers and thus, focuses on product

attributes rather than consumer attributes for

attracting new custoemrs. While customer strategies

evolving to latter stages, the correlation with the four

product attributes becomes weaker and weaker. For

example, four, two, and one marketing attributes as

indicated in Table 3, are the focus on requirement

analysis for the adoption of acquisition, retention,

and strategic customer care respectively.

5.3 Determine System Requirements

This step discusses the performance of requirement

analysis after the analysis of the previous steps. First,

multiple regression analysis is used to examine

Hypotheses 3 and 4. Hypothesis 3 and Hypothesis 4

ICEIS 2008 - International Conference on Enterprise Information Systems

Table 3: Univariate tests for marketing stimuli across

CRM Strategies.

Customer strategies

Marketing

attributes

P-val

1 2 3

Group

mean

difference

Price 5.33 0.028*

6.31 5.25 4.83

1>3*

Promotion 4.43 0.031*

6.01

3.31 3.16 1>2,3*

Quality 4.23 0.039*

5.75

4.29 4.23 1>2,3*

Product 4.12 0.041*

5.83

4.82

4.16 1>3*

*:P<0.05; 1:Customer acquisition, 2:Customer retention, 3:Strategic

customer care

are accepted. Next, the performance of requirement

analysis is assessed using the five items in the

questionnaire for the three groups of responding

firms with different strategies. Their average

performances are 5.71, 6.16, and 6.42 respectively,

with 7-point Likert scale, as indicated in Table 4.

This indicates that the performance of requirement

analysis is good while following the strategy-based

determining process. In particualr, different

strategies has different impacts on consumer

behavior and marketing attributes and further,

provides insight to requirement analysis in eCRM

development.

Table 4: Impact of CRM strategies on requirement analysis.

CRM strategy Emphases on consumer/marketing characteristics

Performance

Customer acquisition Income

Price, Promotion, Quality, Product

5.71

Customer retention Age, Gender, Income, Education*, Occupation, Personality

Price, Quality, Product

6.16

Strategic customer care

Age, Gender, Income, Education, Occupation, Values

, Lifestyle, Personality

Price, Quality*, Product*

6.42

: P<0.05, The others: P<0.01

6 CONCLUSIONS AND

SUGGESTIONS

As the growth of customer base has become more

saturated and the price premium of products less

differentiated, this justifies the need for better CRM.

While the Internet offers a tremendous amount of

communication resources to support eCRM

implementation, most organizations are rushing to

move to web-based CRM systems. However, a high

percentage of firms fail to achieve their CRM goals.

While CRM domain involves a number of

compound components on product design, market

characteristics, and consumer behavior, a

strategy-based process for requirement analysis can

initially provide a clear picture to define the

complex process and further, facilitate the

requirement analysis. Therefore, this study proposes

a three-step process for requirement analysis, i.e.,

define customer strategies, identify consumer and

marketing characteristics, and determine system

requirements. Important findings have been

concluded. In general, while firms adopt different

customer strategies in market competition, i.e.,

acquisition, retention, and strategic customer care,

the determinants in building CRM, i.e., consumer

and marketing characteristics, are greatly different.

As a result, complex domain on CRM can be

defined in terms of the particular customer segments

or marketing approaches and further, base them on

effectively eliciting user requirements.

The implications for practitioners are noted as

below. While eCRM is complex and dynamic in

nature, it is difficult to manage the requirement

determination process. System analysts can base the

adopted customer strategies and further, emphases

on consumer and marketing characteristics on

clearly defining the scope or the boundary of eCRM.

The findings are summarized in Table 4.

Accordingly, user requirements can be effectively

defined and stabilize under the particular boundary.

Besides, this will also facilitate the effective

allocation of organizational resources and reduce the

development cost. The implications for researchers

are discussed as below. A strategy-based approach

for requirement analysis is critical for eCRM

development since it intends to overcome system

analysts’ and users’ inabilities in recognizing

problem unstructuring issues. This is a common

problem for system analysts in developing complex

information systems. Traditional method is

operation-based and often difficult to converge in

requirement determination process. Prior research

has not discussed the important role of customer

strategies in eCRM development and has only

reported partially for the implementation process.

This research provides a new thinking for emerging

research on this research issue.

Furthermore, subsequent research could be based

on this foundation. First, this study is primarily at

developing a theoretical framework to effectively

determine requirements and further, empirically

validates it by survey data. Future research could

specifically conduct case studies longitudinally to

understand the usefulness of this framework in building

eCRM in practice. Second, the empirical survey is

sampled from a combination of industries, so the

conclusions are more general and comprehensive.

Future research could be targeted toward the particular

industries, for instance, the banking industry, to

understand their differences and similarities. Third, IS

managers or CIOs (from developer perspectives) are

chosen as participants in this survey since this study

mainly involves the planning work of system

development. However, a complementary study from

the perspective of marketing personnel (from user

A PROCESS FOR DETERMINING USER REQUIREMENTS IN eCRM DEVELOPMENT - A Strategic Aspect and

Empirical Examination

perspectives) would provide further insight to

understand requirement analysis.

Finally, although this research has produced

some useful results, a number of limitations may be

inherent in it. First, the response rate is lower than

desirable, despite the various efforts to improve it.

This may be due to lack of strategy-based planning

experience in eCRM development. However, the

sample data indicates no systematic non-response

bias in the responding sample and is well

representative of the sample frame. Next, CIOs from

larger firms are primarily chosen for the participants

in the survey; however, some of the questionnaires

may have been completed by subordinates, and as a

result the data may be some biases.

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