Electronic Business: Concepts, Methodologies, Tools, and Applications (4-Volumes) P152 pdf

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of relationship. Being aware that a plethora of
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communication parties can act on each other, on
the communication medium, and on the messages
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synchronized.” The need for a clear distinction
between relationship and ongoing interaction is
postulated by Zolkiewski (2004), for example.
In summary, it can be ascertained that, while
the importance of customer relationships remains
unquestioned, the problem still persists as how
to adequately describe the online interaction
processes between a customer and a company.
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how the Internet has changed those processes. By
addressing the question as to how the customers
themselves perceive a relationship with an orga-
nization, both scholars and practitioners might
gain some knowledge as to why customers react
as they do, and whether the Internet can be used
for creating social bonds. Furthermore, the issue
of whether online data transfers can substitute for
interpersonal relationships will be examined.
THE IMPORTANCE OF THE
INTERNET FOR BUILDING
CUSTOMER RELATIONSHIPS
Ever since the idea of one-to-one marketing

emerged in the early ’90s (Peppers & Rogers,
1993), the Internet has been regarded as being the
7DEOH6HOHFWHGGH¿QLWLRQVRIrelationship marketing
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1
Relationship marketing (RM) is attracting, maintaining, and—in multiservice organizations—enhancing customer relationships
(Berry, 1983a).
2
marketing oriented toward strong, lasting relationships with individual accounts (Jackson, 1985).
3
marketing can be viewed as the building, maintenance and liquidation of networks and interactive relationships between the
supplier and the customer, often with long-term implications (Gummesson, 1990).
4
relates marketing to the development of long-term relationships with customers and other parties (Grönroos, 1990).
5
RM is not directly aimed at immediate transactions but is based on building, supporting and extending customer relationships
(Matthyssens & Van Den Bulte, 1994).
6
RM is marketing seen as relationships, networks and interaction (Gummesson, 1994).
7
Consumer RM seeks to establish long-term committed, trusting and cooperative relationships with customers (Bennett,
1996).
8
Consumer RM is the organizational development and maintenance of mutually rewarding relationships with customers
achieved via the total integration of information and quality management systems, service support, business strategy and
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9
The core of RM is relations, a maintenance of relations between the company and the actors in its microenvironment The
LGHDLV¿UVWDQGIRUHPRVWWRFUHDWHFXVWRPHUOR\DOW\VRWKDWDVWDEOHPXWXDOO\SUR¿WDEOHDQGORQJWHUPrelationship is enhanced
(Ravald & Grönroos, 1996).

10
RM is to establish, nurture and enhance relationshipsZLWKFXVWRPHUVDQGRWKHUSDUWQHUVDWDSUR¿WVRWKDWWKHREMHFWLYHVRI
the partners involved are met (Grönroos, 1996).
11 RM is an emergent disciplinary framework for creating, developing and sustaining exchanges of value between the parties
involved, whereby exchange relationships evolve to provide continuous and stable links in the supply chain (Ballantyne, 1997).
12 the ongoing process of engaging in cooperative and collaborative activities and programs with immediate and end-user
customers to create or enhance mutual economic value at reduced cost (Parvatiyar & Sheth, 2000).
13
RM is marketing based on interaction within networks of relationships (Gummesson, 2002).
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ideal medium for the individualization of mass
customer communication (Gillenson, Sherrell,
& Chen, 1999; Mulvenna, Anand, & Büchner,
2000; Tan, Yen, & Fang, 2002). With consumers
increasingly gaining access to the Internet, many
companies realized that large customer databases
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to target consumers according to their individual
preferences. Interactive marketing and database
marketing began to challenge the existing para-
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2003).
The Internet supports interaction processes be-
tween customers and organizations by facilitating
the collection of customer-related data, which can
be gathered with or without users being aware of or
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cookies) (Berghel, 2002; Munro, 1997). In addition
during recent years, the methods of data mining

have been vastly improved and, in combination
w i t h m o r e p o w e r f u l h a r d w a r e , a l l o w t h e e x t r a c t i o n
of information out of large amount of data (Ado-
mavicius & Tuzhilin, 2001). Algorithms, such as
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a customer’s potential interests (Konstan, Miller,
Maltz, Herlocker, Gordon, & Reidl, 1997).
Besides enabling the individualization of
communication, the Internet supports the whole
transaction process. In the case of digital goods,
all phases of the buying process, including the
distribution, are conducted online without a direct
interaction between human beings. Companies
that supply digital goods and use the Internet as
a medium for immediate delivery especially can
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2001). From a transaction-cost perspective, it
can be argued that the ex ante costs of drafting,
negotiating and safeguarding an agreement and
ex post costs, such as maladaption costs, haggling
costs, setup and running costs, and bonding costs
of effecting secure commitments (Williamson,
1985), will decrease by the use of the Internet.
This cost cutting leads, in turn, to a reduction of
interpersonal social interactions, since no contacts
with human beings during the entire buying cycle
are needed. In order to compensate for the loss
of social interactions, personal data, which is
available in a company’s database, may be used
to simulate a close relationship and interest. The

range of individualization strategies varies from
letting users customize Web site features (Lam
& Lim, 2004) to personalized birthday greetings
or electronic recommendation agents (Rowley &
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customizing the content based on characteristics,
behaviors and preferences of users may lead to
an increase in the Web site’s overall performance
(Albert, Goes, & Gupta, 2004).
INTERACTION PATTERNS
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interaction patterns between humans or humans
and organizations have to be taken into account.
As was mentioned before, we perceive interac-
tion as a process of two-way communication and
exchange (Haeckel, 1998; Pavlik, 1998), includ-
ing any kind of online transactions. Information
technology (IT)-enabled interaction between
customers and an enterprise can be differenti-
ated into IT-assisted interaction and automated
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manual process and in the second the complete
control is given to the customer (Wells, Fuerst,
& Choobineh, 1999).
As can be seen in Figure 2, we differentiate
between three types of interaction processes.
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between two human beings (scenario a). During
a sales process, the interaction between a buyer
and a vendor (representing an organization), who

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formalized (scenario b). When transactions are
completed online, the physical contact is lacking
completely (scenario c). Users who are shopping
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personnel, whereas in the case of buying online,
no interpersonal interaction exists at all.
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By using the framework depicted in Figure 2
as a starting point, three major research questions
arise, which will be elaborated upon in more detail
in the following sections.
Research question 1: What are the major at-
tributes that constitute a relationship in general?
By taking into account which features are to be
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in general. This allows us at least to circumscribe
the perceived semantic meaning of a relationship
from a consumer’s point of view. This research
question is equally important for all interaction
processes in Figure 2.
Research question 2: When does a relationship
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a relationship in general, it is essential to know
what the main attributes of a relationship with
an organization are. As was indicated above,
the interaction process with a human being may

differ from the one with an organization as an
abstract entity. This research question explicitly
concentrates on scenario b in Figure 2.
Research question 3: What kinds of aspects are
important to an online relationship with an orga-
nization? By hypothesizing that the online interac-
tion process with an organization may be called a
relationship, we asked users what they perceive to
be the most important attributes to this situation.
Most of the items were derived from the literature
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Internet to foster individualized communication
and, thereby, allow for social interaction with a
multitude of anonymous users. This situation is
depicted as scenario c in Figure 2.
SURVEY DESIGN
We used Austrian Internet users as our universe
to assess the importance of online relationships.
The survey was supported by one of the major
Austrian newspapers, der Standard, which in-
cluded a link to our questionnaire in two weekly
newsletters that were sent to 85,500 registered
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out the questionnaire. The online survey was
conducted between August 25, 2004 (the day
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16, 2004. We used slider bars with a range from
1 (strongly disagree) to 100 (strongly agree). In
total, we gathered 385 usable results. Besides ask-
ing for demographic characteristics, we included

three major sections in our questionnaire, where
we assessed the importance of online relation-
ships and which will be discussed subsequently.
Figure 2. Interaction patterns
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Basically, in all sections, a general question was
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associate with the term ‘relationship’?”), and the
respondents were asked to assess individually the
relevance of the respective items (e.g., friendship).
The original questionnaire was in German. Since
we did not use scales from existing literature, no
translation-retranslation process was necessary.
Instead, the results were translated by the authors
and double-checked by a native speaker.
RESULTS
The respondents are 30.4% male and 69.6% fe-
male, with 71.1% between 21 and 35 years old and
84.6% possess at least a high school degree. The
largest group, as far as the current employment
situation is concerned, works as administrative
or technical employees (45.2%), while the second
largest group consists of students (20.7%). Most
of the users possess considerable experience with
the Internet, with only 9.1% indicating that they
have been online for fewer than four years. The
weekly frequency of Internet usage shows a wide
range of answers with approximately one-fourth of
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a week. About the same number of respondents
(22.6%) state that they use the Internet for 6 to
10 hours a week. Included in the sample is also
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30 hours of weekly usage (12.7%).
For the following analyses the items, which
were gained by literature research in IS and
marketing publications dealing with relationships
and e-CRM and related topics, are clustered into
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attributes that could be used to describe a rela-
tionship in general, while the second category
focuses on the interaction between an individual
Table 2. Characteristics of respondents (n = 385)
Sex Occupation Experience on the Internet
Male 30.4% Management, civil servant 13% less than 4 years 9.1%
Female 69.6% Administrative/technical employee 45.2% 4-5 years 29.9%
Self-employed 4.9% 6-7 years 24.4%
Housewife or -husband 2.6% 8-9 years 17.9%
Retired more than 9 years 17.1%
Student 20.7% n/a 1,6%
Other 11.9%
Age Education Frequency of Internet use
- 20 years 2.4% Secondary school 2.9% less than 5h/week 25.9%
21 – 25 years 24.9% Vocational school 10.1% 6-10 h/week 22.6%
26 – 30 years 27% High school graduation 57.5% 11-15 h/week 11.2%
31 – 35 years 19.2% Technical college 5.5% 16-20 h/week 14%
36 – 40 years 10% University 21.6% 21-25 h/week 4.2%
41 – 45 years 6% Other 2.6% 26-30 h/week 7.8%
46 – 50 years 6% 30+ h/week 12.7%

50+ 4.5% n/a 1.6%
Note: Figures may not add up to 100% due to rounding differences.
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and an organization. The third pool of items con-
centrates on those activities that a company can
conduct only online, such as individualizing mass
communication and production (Dewan, Jing, &
Seidmann, 2000), or at least can be considerably
supported by the use of the Internet, as is the
case when offering customized pricing, such as
discounts or rebates based on former purchases
(Simon & Dolan, 1998).
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cussed individually and then be integrated into
a more comprehensive framework. For all three
cases we used a principal axis factoring with
Promax as the method of rotation. In contrast to
the most commonly used principal component
analysis, the results from principal axis factoring
more accurately represent the population load-
ings (Widaman, 1993). Furthermore, we strive
to understand the latent structure of a set of
variables instead of simply reducing them with-
out interpreting the resulting variables in terms
of constructs (cf., Conway & Huffcutt, 2003, p.
150f.). An oblique rotation is chosen instead of an
orthogonal rotation, since we expect a correlation
between the constructs. The Promax procedure
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DQG DWWHPSWV WR LPSURYH WKH ¿W WR WKH GDWD E\
allowing correlations (Russell, 2002). Fabrigar,
Wegener, MacCallum, and Strahan (1999) write
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rotation would also forfeit any knowledge of the
existing correlations among factors” (p. 287). In
all cases the number of factors is determined by
using the scree test instead of retaining all factors
with eigenvalues greater than 1.0, since the latter,
albeit commonly used, is perceived as being less
accurate and leading to overextraction (Velicer
& Jackson, 1990).
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relationship in general, the respondents were asked
to assess the perceived importance of several
items for constituting a relationship (see Table 3).
All items were scrambled within the respective
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relationship with a company) and an exploratory
factor analysis was used to detect underlying
structures. The results of all three analyses will
be discussed in the next section. The respondents
were asked to assess separately the importance of
a number of attributes in regard to the research
questions elaborated above.
It is essential to mention that this chapter
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tionships.” With the exception of the existence of

a monopoly where no choice between suppliers
exists, consumers will tend to change suppliers
rather than maintain an unsatisfactory relation-
ship.
The Kaiser-Meyer-Olkin measure of sam-
pling adequacy (MSA) provides a measure of
the extent to which the variables belong together
and, therefore, are appropriate for factor analy-
sis (Kaiser & Rice, 1974). A MSA value of 0.89
(meritorious) for the items used to measure the
attributes that constitute a relationship indicates
a good eligibility of the data for factor analysis.
The three-factor solution shown in Table 3, with
the items being grouped by their highest primary
factor loading, turned out to be the best one,
according to their interpretability. Based on the
analysis and conceptual congruence, we labeled
the three components as emotion, communica-
tion/transparency and ties to indicate that the
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feelings, such as solidarity, familiarity, friendship
and partnership, whereas the second one focuses
on the exchange of information and communica-
tion. The third component describes the existence
of invisible ties, as can be seen from items such
as dependence and bondage.
In order to estimate the absolute valuation of the
items, the means are shown in the second column
of Table 3. Generally speaking, the emotional and
communicational components are considered to be

of greater importance than the perceived existence
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contact” achieved the highest level of agreement
(84.29), which indicates the high importance of
social interaction in a relationship. On the other
hand, items such as trust (83.78) or satisfaction
(73.60), which are also valued quite highly, do not
necessarily call for human contact.
In the next step we look at the most important
attributes of a relationship between an individual
and an organization (see Table 4). The MSA
YDOXHLVDQGFDQEHLQWHUSUHWHGDV³PHUL-
torious.”
As can be seen from the high level of agree-
ment, indicated by the value of the means, ser-
vice-related activities, such as the handling of
personal requests (84.82) or complaints (81.15)
and the provision of competent advice (82.70),
are regarded as being highly important for a rela-
tionship with an organization. In addition to that,
customers show a high level of agreement that
regular (83.96) or frequent (76.87) purchases from
a company may be called a relationship. Given
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for example the differentiation into transaction
marketing and relationship marketing (including
database marketing, interaction marketing and
network marketing) (Zineldin, 2000), it seems

remarkable that many customers perceive exist-
ing transactions as being de facto relationships,
thereby blurring those distinctions. The other
components that resulted from the factor analysis
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offer of high-quality products (59.82) and low
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general, these items are valued less important
than service or existing transactions.
Table 3. Constitutive attributes of a relationship
Mean Item F1 F2 F3
In general, which meaning do you associate with the
term “relationship”?
Emotion
72.66 Friendship 0.909
76.73 Solidarity 0.891
80.57 Familiarity 0.830
76.57 Partnership 0.802
62.78 Intensity 0.682
70.22 Emotion 0.660
83.78 Trust 0.540
71.52 Long-term orientation 0.482
84.29 Interpersonal contact 0.476
Communication/
68.03 Exchange of information 0.696
transparency
61.34 Transparency 0.580
80.96 Communication 0.578
77.78 Concern 0.443
Ties

30.67 Dependence 0.708
47.28 Bondage 0.535
36.71 6HOÀHVVQHVV 0.431
Eigenvalue
6.10 1.95 0.97
Variance explained
0.32 0.10 0.5
Note: Factor loadings <0.4 are omitted for better readability.
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The third factor analysis is intended to include
the Internet as an important communication and
transaction channel. Again, a MSA value of 0.855
(meritorious) indicates a good eligibility of the
data for factor analysis.
Service is the most important factor in the
relationship with an organization. In addition to
that, in the online world, transparency becomes a
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no clear distinction between items pertaining to
service and those belonging to transparency, all
items were combined and the factor label contains
both constructs. The second most important fac-
tor, as indicated by the absolute means, includes
the offering of presents or discounts (69.66)
or aggregated rebates (75.16) and, therefore, is
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the Internet and were subsumed into the factors
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tend to get lower levels of agreement. Personal-
ized communication, such as congratulations on
important dates (38.01) or welcome greetings
(44.40), receive below-average acceptance. The
VDPHKROGVWUXHIRUPRVWLWHPVLQFOXGHGLQ³2QOLQH
entertainment,” such as the valuation of online
games (17.40), the download of software (37.08)
or the participation in sweepstakes (38.54).
In a last step, the combined results are visu-
alized in Figure 3. The ordinate represents the
unweighted mean of all items loading on a single
Table 4. Relationship with a company
Mean Item F1 F2 F3
A relationship with an organization
exists, if
Service and
84.82 personal requests are treated individually. 0.712
transactions
81.15 my complaints are handled satisfactorily. 0.637
82.70 I get competent advice. 0.560
82.50 I already have positive experiences with the company. 0.712
83.96 I buy regularly from this company. 0.816
76.87 I buy frequently from this company. 0.725
66.57 I am already a customer of this company. 0.431
77.49 I am so committed to this company that I won’t buy anywhere
else. 0.404
Value for money

59.82 the company offers high-quality products. 0.766
42.65 the company offers brand products I know. 0.632
42.79 prices are low. 0.609
51.87 friends and acquaintances recommended this company to me. 0.511
65.52 additional services exist. 0.478
63.29 the corporate philosophy appeals to me. 0.409
Information exchange
46.35 I inform myself actively about the company. 0.761
48.28 I already have provided a lot of personal information. .549
Eigenvalue
4.79 1.59 1.38
Variance explained
0.24 0.80 0.70
Note: Factor loadings <0.4 are omitted for better readability.
1451
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factor, while on the abscissa the different types
of relationships are depicted.
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general, it can be seen that involuntary interactions
usually are not perceived as being a relationship,
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in the lower left corner of the framework. On the
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DQG³&RPPXQLFDWLRQWUDQVSDUHQF\´DUHIURPD
consumer’s point of view, much better suited to
characterizing the essence of a relationship. By
having a look at the relationship with an organiza-
tion, one can see that especially good service and
existing transactions are associated with a rela-

WLRQVKLS,QFRQWUDVW³,QIRUPDWLRQH[FKDQJH´RU
³9DOXHIRUPRQH\´DUHUDWHGPXFKORZHU7KHODVW
section describes the relationship with an online
organization and again good service is seen as
being essential. In addition to that, transparency
is considered being quite important. Measures
of individualization or online entertainment are
regarded as being of comparatively less impor-
tance for building relationships online. While in
interpersonal interactions hedonic or social mo-
tives (e.g., familiarity or emotion) are seen as being
very important for constituting a relationship, the
Table 5. Online relationship with a company
Mean Item F1 F2 F3 F4
In an online relationship, it is important for me that
Service and
90.91 I receive the ordered products and services on time. 0.825
transparency
85.74 I can inspect my personal data at any time. 0.778
82.84 the Web site is clearly arranged. 0.764
88.82 I get answers for my requests quickly. 0.719
80.18 data can be encoded transmitted. 0.676
84.58 ,FDQ¿QGDFRQWDFWSHUVRQDWDQ\WLPH 0.619
73.34 WKHJHQHUDOWHUPVDQGFRQGLWLRQVDUHFOHDUO\GH¿QHG 0.557
78.82 I can check my delivery status at anytime. 0.545
71.56 I have the opportunity to give feedback. 0.477 0.448
Individualization
55.64 I regularly receive individualized newsletters. 0.788
62.30 I receive individualized offers. 0.607
38.01 I receive congratulations on important dates (e.g., birthday). 0.569

44.40 I am personally welcomed. 0.536
56.27 I can express my opinions in forums. 0.441
Online
17.40 the Web site offers online games. .650
entertainment
37.08 I can download software. .587
43.89 ,¿QGWKH:HEVLWHHQWHUWDLQLQJ .559
41.08 I can send SMS free of charge. .546
38.54 I can participate in sweepstakes. .501
63.14 I like the Web site. .422
Extended
69.66 I get presents or discounts. 0.805
%HQH¿WV
75.16 I get aggregated rebates. 0.753
Eigenvalue
6.39 2.68 1.16 1.06
Variance explained
0.26 0.11 0.50 0.40
Note: Factor loadings <0.4 are omitted for better readability.
1452
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opposite holds true for online organizations. For
the majority of users of an entertaining Web site,
the ability to customize it or the participation in
sweepstakes are not adequate instruments for
producing a perceived relationship, as indicated
by the below average grading for the latter.
CONCLUSION AND FURTHER
RESEARCH
When RM emerged, the Internet was seen by

many researchers as the ideal medium for creating
and maintaining long-lasting relationships with
customers. Due to the increased capacity to gather,
store and process vast amounts of information
about customers’ attributes, behaviors, needs and
wishes, companies hoped to be able to mimic so-
cial relationships. In this chapter, we took a closer
ORRNDWKRZFXVWRPHUVWKHPVHOYHVZRXOGGH¿QH
DUHODWLRQVKLSHLWKHURIIRURQOLQH7KH¿QGLQJV
suggest that the term relationship (in the sense of
a social relationship) might be misleading, since
customers tend to emphasize different focuses,
depending on the situation and their interaction
partner (human vs. organization and online vs.
RIÀLQH:KLOHLQDQRQFRPPHUFLDOLQWHUSHUVRQDO
interaction, emotional values are still of preemi-
nent importance; in a selling situation, the level
of service determines the perceived existence of a
relationship. In addition, transparency is consid-
ered to be important when conducting business
online. Our results indicate that in a business con-
text, especially when conducting business online,
FXVWRPHUVSUHIHUVHUYLFHDQG³WDQJLEOH´EHQH¿WV
such as discounts and rebates, to individualiza-
tion measures. Therefore it comes as no surprise
WKDWLWHPVVXFKDV³,QDQRQOLQHUHODWLRQVKLSLWLV
important for me that I receive congratulations
RQLPSRUWDQWGDWHV´HJELUWKGD\RU³LWLVLP-
portant for me that I am personally welcomed,”
were considered to be of minor importance for

most respondents. Simply mimicking human
behavior with technological means does not
seem to be enough to create emotional bonds.
However, this emotional component seems to be
quite important for characterizing relationships,
as indicated by the prevalent importance of items
like trust or interpersonal contact for describing
general relationships.
Figure 3. A framework for categorizing the constituents of relationships
1453
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However, certain limitations must be taken
into account when interpreting the results of this
survey. First and foremost, it should be mentioned
that some factors include a multitude of items,
ZKLFK PDNHV LW KDUG WR ¿QG D FRPPRQ QDPH
Further research has to concentrate on the valida-
tion of the factors. The low response rate, which
is typical for e-mail surveys, requires further
research in order to ensure the generalizability of
the results. Nonetheless, even imperfect samples
allow for important insights (Blair & Zinkhan,
 HVSHFLDOO\ ZKHQ WKH\ DUH FRQ¿UPHG E\
replication studies.
Furthermore, the factor loadings of some
items fall below the commonly accepted thresh-
old of 0.5 (Kaiser & Rice, 1974). For the sake of
completeness, we included them in this explor-
atory study but recommend follow-up studies to
improve the validity. While we did not explicitly

concentrate on the development of scales for mea-
suring antecedents of relationships, this chapter
could nonetheless be used as a starting point for
the development of a measurement instrument.
3UDFWLWLRQHUV HVSHFLDOO\ PLJKW ¿QG LW XVHIXO WR
see how customers perceive ongoing interaction
processes with a company.
ACKNOWLEDGMENTS
The author wishes to thank Martina Lausmann
for her support in collecting the empirical data.
An earlier version of this research was presented
at the Fourth Annual Workshop on Human Com-
puter Interaction Research in MIS, December 10,
2005, Las Vegas, USA.
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