Measuring the Success of Social CRM
First Approach and Future Research
Torben Küpper
Institute of Information Management, University of St. Gallen, St. Gallen, Switzerland
Keywords: Social CRM Measurement Model, Social CRM Measurement, Social CRM, Social CRM Measures.
Abstract: Web 2.0 and Social Media provide new opportunities for collaboration and value co-creation. Social
Customer Relationship Management (CRM) addresses the opportunities and deals with the integration of
Web 2.0 and Social Media within CRM. Social CRM has the potential to enable the, e.g., customer-to-
customer support, which results in reducing companies’ service costs. In order to measure the success (e.g.,
cost-savings) of Social CRM activities (e.g., customer-to-customer support) a Social CRM measurement
model is indispensable and a prerequisite step for future research. At present, scholars conduct research on
Social CRM measures and attempt to develop a Social CRM measurement model. This paper presents a
systematic and rigorous literature review for the research topic – Social CRM measurement model. The
major result reveals the lack of extant literature regarding the research topic. The findings disclose the need
for a Social CRM measurement model on an evaluation based foundation.
1 INTRODUCTION
Social Media is a group of internet-based
applications and technology foundations of Web 2.0,
which change the approach of online communication
towards a dialog among web users (Cheung, Chiu,
and Lee 2011; Lehmkuhl and Jung, 2013). In this
context, Social Media enables collaboration between
companies and their customers. The customers
content on the companies’ Social Media platforms
(e.g., Facebook, Twitter, Blogs, etc.) provide a two-
sided value co-creation (Vargo, Maglio, and Akaka,
2008). The value co-creation becomes apparent, for
example, when customers articulate requirements
(value for the company) or authentic feedbacks on
products (value for other customers). Social
Customer Relationship Management (CRM)
addresses, among others, this opportunity and deals
with the integration of Web 2.0 and Social Media
within CRM (Lehmkuhl and Jung, 2013).
The challenge for companies to implement a
Social CRM approach documents the following
facts: first, service demand on Social Media
platforms increased by 26 % over the past 4 years
(MCKensey, Chui, and Westergren, 2012). Second,
an increasing number of companies apply a service
oriented Social CRM approach (Band and Petouhoff
2010; Bernet PR, 2013). Social CRM fosters
customer engagement which in turn enables
customer-to-customer support, thus reducing
companies’ service costs. When customers share
positive user experiences, customer engagement can
also lead to additional sales because indecisive
potential customers may be encouraged to purchase.
Measuring Social CRM is essential to assess and
monitor the success of Social CRM activities (Sarner
and Sussin 2012; Sarner et al., 2011) and the first
step to implement a Social CRM management
cockpit. In practice, measuring Social CRM is
perceived as one of the biggest challenges in the
upcoming years (Bernet PR, 2013). This view can be
confirmed from a scholarly perspective: Reinhold et
al. (2012) argue that Social CRM activities have to
be analyzed and measured in order to capture the
Social CRM success (Reinhold et al., 2012). This
demands innovative approaches and measurement
models.
According to Moore and Benbasat (1991), a
prerequisite for measurement models are well-
defined constructs (i.e. measures) with high degrees
of validity and reliability. Therefore, the
contribution of this article is to discover extant
Social CRM measures and based on them to identify
current Social CRM measurement models.
Despite this necessity Social CRM measurement
models are sparsely addressed in extant literature.
573
Küpper T..
Measuring the Success of Social CRM - First Approach and Future Research.
DOI: 10.5220/0004867105730582
In Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS-2014), pages 573-582
ISBN: 978-989-758-028-4
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
Authors focus on CRM measurement models (e.g.,
Chen et al. 2009; Reinartz et al. 2004; Wang and
Sedera 2009; Sedera et al. 2009) and illustrate single
Social CRM performance measures (Behravan and
Sabbirrahman 2012; Farb 2011; Li et al. 2012; Vulic
et al. 2012) without proving their applicability (i.e.,
without an evaluation based foundation). Literature
reviews aim “to uncover the sources relevant to a
topic under study,” (vom Brocke et al. 2009) and
make a contribution to the relevance and rigor of
research (vom Brocke et al. 2009). This article
provides a literature review regarding the research
topic - Social CRM measurement model. Therefore,
the research question (RQ) is stated as:
RQ: “What is the current state of knowledge on a
Social CRM measurement model?
To answer the question, the article is structured
as follows: first, a rigorous and systematic literature
review (section 2) is described. Second, a literature
analysis and synthesis (section 3) is done in order
to identify the research gap. Third, a research
agenda (section 4) is derived. Finally, a short
conclusion (section 5) is given.
2 LITERATURE REVIEW
A thorough and rigorous literature review is a
prerequisite step for a research project and provides
a solid theoretical foundation (Levy and Ellis, 2006).
This literature review is based on vom Brocke’s
framework for reviewing scholarly literature (vom
Brocke et al., 2009). It comprises five steps being
definition of review scope (section 2.1),
conceptualization of topic (section 2.2), literature
search, literature analysis and synthesis (section 3),
and the derivation of a research agenda (section 4).
2.1 Definition of the Review Scope
The scope of a literature review can be characterized
by a taxonomy (vom Brocke et al. 2009). Table 1
describes the scope of the literature review at hand
using the taxonomy of Cooper (1988) which
differentiates six categories, each having a different
number of characteristics. The grey shades indicate
the literature review’s characteristics. The focus is
on the identification of the research outcomes and
the different research methods. The goals are
integration and central issues. The organization of
this literature review is related to the same abstract
ideas (conceptual) and employing similar methods
(methodological). The perspective can be
categorized by the characteristic neutral
representation. Due to the specific research topic,
the audience is specialized scholars. Finally, the
representative coverage is applied in the literature
search (cf. Table 3) reducing the number of articles
(hits) to a smaller number of net hits.
2.2 Conceptualization of the Topic
A literature review has to “provide a working
definition of key variable” (Webster and Watson
2002). Table 2 presents an overview of the research
topic’s key variables and their definitions: Web 2.0,
Social Media, CRM, Social CRM and Measurement.
Web 2.0 has to be considered, because it is
frequently used as a synonym for Social Media
(Lehmkuhl and Jung 2013). To conclude, a Social
CRM measurement model is defined as follows: a
model that measures Social CRM activities in order
to assess and monitor the Social CRM success (e.g.,
sales, cost-savings, etc.) (Faase, Helms, and Spruit
2011; Greenberg 2010; Soeini, Jafari, and
Abdollahzadeh, 2011).
2.3 Literature Search
A systematic literature search was conducted in
order to identify articles relevant to the research
topic. Hence, this section follows the search sub-
process proposed by vom Brocke et al. (2009) (cf.
Figure 1) including (1) a journal search, followed by
(2) a database search, and (3) a keyword search, and
finally (4) a forward and backward search. The
application of the search sub-process assures a
rigorous, comprehensive and traceable literature
search (vom Brocke et al., 2009).
Table 1: Taxonomy of literature reviews based on Cooper (1988).
Categories Characteristics
Focus research outcomes research methods theories applications
Goal integration criticism central issues
Organization historical conceptual methodological
Perspective neutral representation espousal position
Audience specialized scholars general scholars practitioners general public
Coverage exhaustive exhaustive and selective representative central / pivotal
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Table 2: Overview of Social CRM measurement model definitions.
Key
Variables
Definition Author(s)
Web 2.0
”Web 2.0 is a set of economic, social, and technology trends that collectively form the
basis for the next generation of the Internet - a more mature, distinctive medium
characterized by user participation, openness, and network effects.”
Musser and
O’Reilly,
2006
”[…] Web 2.0 is a set of dynamic principles and practices such as participation and
engagement, collaboration and cooperation or transparency and openness.”
Lehmkuhl and
Jung, 2013
Social
Media
”…a group of Internet-based applications that build on the ideological and
technological foundations of Web 2.0, and that allow the creation and exchange of
user generated content.”
Kaplan and
Haenlein,
2010
CRM
It is supported by both technology and process that is directed by strategy and is
designed to improve business performance in an area of customer management.
Richards and
Jones, 2008
”CRM is a strategic approach that is concerned with creating improved shareholder
value […] with customers and customer segments. CRM unites the potential of
relationship marketing strategies and IT to create profitable, long-term relationships
with customers and other stakeholders.”
Payne and
Frow 2005
Social
CRM
”[…] a philosophy and a business strategy, supported by a technology platform,
business rules, processes and social characteristics, designed to engage the customer
in a collaborative conversation in order to provide mutually beneficial value in a
trusted and transparent business environment.”
Greenberg,
2010
“Social CRM is about creating a two-way interaction between the customer and the
firm. It is a CRM strategy that uses Web 2.0 services to encourage active customer
engagement and involvement.”
Faase et al.,
2011
Measure-
ment
A CRM measurement is ”[…] a subset of strategic research, following a research
performed on categorizing researchers […] and therefore a mechanism that is
supposed to measure CRM performance should notice to various perspective towards
effective factors on CRM performance.”
Soeini et al.,
2011
The (1) journal search is the first step in the
literature search and it may include conference
articles. “The major contributions are likely to be in
the leading journals,” (Webster and Watson, 2002)
as well as in high ranked, renowned conference
proceedings (Rowley and Slack, 2004).
Consequently, the scholarly databases, which
allow a search of the leading journals and
conference proceedings, are primarily queried and
investigated (Webster and Watson, 2002).
According to vom Brocke et al. (2009) and the
research topic at hand the relevant journals for the
(1) journal search are derived from the disciplines
Information Systems (IS) and Marketing. Within IS
the top-tier journals are: Information Systems
Research, MISQ and Journal of Information
Technology. High quality Marketing journals
are: Journal of Marketing, Journal of Marketing
Figure 1: Literature search process.
Research, Journal of the Academy of Marketing
Science, as well as the Journal of Interactive
Marketing. The selection of relevant IS conferences
includes the International Conference on
Information Systems (ICIS), the European
Conference on Information Systems (ECIS), the
Pacific Asia Conference on Information Systems
(PACIS), as well as the American Conference on
Information Systems (AMCIS). The selected high
quality Marketing conferences are the American
Marketing Association (AMA) and the European
Marketing Academy (EMAC).
The (2) database search has to make sure that
the previously identified journals (journal search)
are covered. Therefore, the following databases have
been queried: EBSCOhost, ProQuest, Emerald,
ScienceDirect, Web of Science and the AIS World
database (AISeL).
The third sub-process step, the (3) keyword
search, is the core of the literature search. The
applied keywords are precisely documented and
sufficiently traceable for a repeatable investigation
(vom Brocke et al. 2009). The keywords are derived
from the key variables in Table 2 and, consequently,
all abbreviations and similar terms are included. The
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databases have been queried using the following
search phrases: (a) (“CRM” or “Customer
Relationship Management”) and ("Web 2.0" or
"Social Media") and ("Measure" or "Measurement"
or "Measuring"); (b) ("Social CRM" or "Social
Customer Relationship Management") and
("Measure" or "Measurement" or "Measuring"); (c)
("CRM" or "Customer Relationship Management")
and ("Measure" or "Measurement" or "Measuring").
An overview of the results for the (3) keyword
search is given in Table 3 which illustrates the
mentioned databases, the corresponding, completed
search phrases, and presents the number of hits for
the period 2003-2013.
Table 3: Result of the keyword search.
Database
Search phrases
Net
hits
(a) (b) (c)
EBSCOhost 0 (7) 0 (2) 10 (46) 10
Emerald 0 (2) 0 (0) 0 (2) 0
ProQuest 1 (23) 0 (18) 5 (48) 6
Science Direct 0 (0) 0 (0) 0 (2) 0
Web of Science 1 (4) 1 (2) 1 (21) 3
AISeL 0 (0) 0 (0) 4 (20) 4
Total Net hits 23
The number in brackets (hits) represents the number
of articles found in the respective database using the
specific search phrase. The queried attributes have
been title, keywords, and abstract. The search has
been extended to all fields if the first query produced
no hits (e.g., the database Emerald produced no hits
for the attributes title, keywords and abstract for the
(a) search phrase; consequently the search was
extended to all fields and two hits were found).
Furthermore, the initial search for search phrase (c)
in EBSCOhost produced 974 hits. In order to reduce
this result to a manageable number of articles we
restricted the search to title and keywords, thus
reducing the number to 46 hits. The inherent risk of
omitting articles is later on mitigated by applying a
backward reference search. The articles have been
further evaluated by manually analyzing (reading)
title, abstract and introduction and eliminating
duplets. The number in bold represents the number
of articles considered relevant in the latter step. The
total net hits have been calculated as the sum of
articles considering all search phrases. The (3)
keyword search yields 23 articles in total.
The last sub-process step is the (4) forward and
backward search and aligns on the approach by
Levy and Ellis (2006) backward references search
and forward references search. A first-level
backward references search focuses solely on the
references of the net hit’s articles from the keyword
search (Levy and Ellis, 2006). In sum, this search
yields 2 additional articles. This small number is
due to the fact that the most identified articles were
already found in (3) keyword search. The forward
references search focuses on the articles that have
been referenced in the net hit’s articles. Therefore,
each of the 23 net hits was analyzed using Google
Scholar and the six databases from sub-process step
(2) database search (X. Chen, 2010). The forward
references search yielded 14 additional articles (cf.
Table 4). This leads to a total of 39 relevant articles
that are used for further analysis.
Table 4: Forward reference search.
Database Net hits
Goo
g
le Schola
r
3 (1376)
EBSCOhost 0 (11)
Emerald 0 (4)
ProQuest 0 (5)
Science Direct 4 (66)
Web of Science 7 (289)
AISeL 0 (10)
Total Net hits 14
3 LITERATURE ANALYSIS AND
SYNTHESIS
The core of a literature review is to analyze and
synthesize the relevant articles based on selected
informative characteristics and to categorize them
within a framework (Webster and Watson, 2002).
3.1 General Findings
A first content analysis of the 39 relevant articles
reveals five different categories of Social CRM
measurement models, which partly cover the
research question (RQ: “What is the current state of
knowledge on a Social CRM measurement model?”).
Table 5 depicts the categories found and presents
the corresponding characteristics. The number in
brackets represents the number of articles that use
the respective characteristic as a descriptive means.
All of the mentioned characteristics are mutually
exclusive.
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Table 5: Categories of Social CRM measurement models.
Categories Characteristics
Measurement perspective company-perspective (25) customer-facing (14)
Measurement object company (27) customer (6) company & customer (2) none (4)
Measurement type indirect (9) direct (30)
Measurement scope holistic (13) partial (26)
Measurement
framework
business-to-
business (1)
business-to-
customer (34)
business-to-business & business-to-
customer (4)
Measurement perspective comprises two
characteristics. The customer-facing perspective
includes the building of a single view of a customer
across all contact channels and the distribution of
customer intelligence to all customer-facing
functions (Reinartz, Krafft, and Hoyer, 2004). The
company-perspective covers all company functions
involved in CRM or Social CRM. The
measurement object defines which unit of analysis
(company and / or customer) is analyzed (Markus
and Robey, 1988). The indirect and direct measures
are the characteristics of the category measurement
type. A direct measure “focuses on the achievement
level of CRM related processes and tries to find an
answer for the question: how good are we doing in
CRM process?” (Öztaysi et al., 2011b), while
indirect measurement models do not consider direct
impact. The measurement scope comprises two
characteristics (J. Chen et al., 2009). According to
Öztaysi et al. (2011b), the “partial measurement
models do not mention the area,” i.e. they do not
cover the whole Social CRM processes. (Öztaysi et
al., 2011b). While “the holistic models cover CRM
process to some degree“ (Öztaysi et al., 2011b). The
category measurement framework defines the
context of analysis. A business-to-business (B2B)
framework (e.g., Zablah et al., 2012) differs from a
business-to-customer (B2C) framework (e.g.,
Reinartz et al. 2004), has different assumptions and
initial positions (e.g., volumes of B2B transactions
are much higher than the volume of B2C
transactions; B2B focused companies have a lower
number of sellers than B2C companies). The number
of relevant articles (39) within the categories and
corresponding characteristics distributes as follows:
25 articles cover the company-perspective and 27
articles measure the company as the measurement
object. The direct measurement type is mentioned in
30 articles and the partial approach is the most
common measurement scope with a count of 26. In
addition, 34 articles engage with an underlying B2C
framework. To conclude, the current state of Social
CRM literature focuses on a company-perspective,
which measures a direct impact on performance by
companies within a partial scope and an underlying
B2C framework.
3.2 Findings on a Framework
A second content analysis focuses on categorization
within a framework in order to identify a research
gap. Therefore, a primarily holistic framework was
sought, which had a sufficient and diverse quantity
of process dimensions to categorize all of the 39
relevant articles. Regarding these restrictions, the
Payne and Frow (2005) framework which was
identified during the backward reference search,
was chosen for four reasons. First, the existing
Social CRM literature mainly bases on a partial
approach (cf. Table 5) and misses a quantitatively
evaluated foundation (Lehmkuhl and Jung, 2013).
Second, the framework from Payne and Frow (2005)
is a widely used success framework (e.g., on 20
th
April, 2013, a total amount of more than 700
citations were archived on Google Scholar) and
therefore provides a high degree of external validity.
Third, the holistic approach covers a wide range of
CRM process dimensions, wherein each of the 38
articles (the 39 relevant articles include Payne and
Frow (2005)) can be exclusively assigned. Finally,
five out of seven A and A+ journal articles as well as
66% of the investigated 39 articles refer to this
framework.
The corresponding framework includes five
process dimensions: (1) strategy development
process, (2) value creation process, (3) multichannel
integration process, (4) information management
process, and (5) performance assessment process.
The (1) strategy development process has two
different focus areas. On the one hand it describes an
organization’s business strategy and on the other
hand a customer strategy. The (2) value creation
process “transforms the outputs of the strategy
development process into programs that both extract
and deliver value” (Payne and Frow, 2005).
Furthermore, it involves a process of co-creation and
segments the customers to maximize the lifetime
value. The (3) multichannel integration process
describes the most common appropriate
combinations of channels, which has a highly
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Table 6: Content analysis based on the framework by Payne and Frow.
Articles
Strategy
development
process
Value creation
process
Multichannel
integration
process
Information
management
process
Performance
assessment
process
N.
Ap.
Tr.
Ap.
N.
Ap.
Tr.
Ap.
N.
Ap.
Tr.
Ap.
N. Ap.
Tr.
Ap.
N.
Ap.
Tr. Ap.
Keyword search
Padmavathy et al., 2012 x x x x
Reinartz et al., 2004 x x x x
Öztaysi et al., 2011b x x
Llamas-Alonso et al., 2009 x x x x x
Jain et al., 2003 x x x
Chen et al., 2009 x
Ahearne et al., 2007 x x
Lindgreen et al., 2006 x x x x
Saccani et al., 2006 x x
Borle et al., 2008 x
Farb, 2011
x x
Kim and Kim, 2009 x x x x
Shaw, 1999 x x
Zinnbauer and Eberl, 2005 x x
Jafari, 2012
x x x
Ryals et al., 2005 x
Vulic et al., 2012 x
Li et al., 2012 x x
Wang and Feng, 2012 x x x
Sedera et al., 2009 x x x x x
O’Reilly and Dunne, 2004 x x x
Wang and Sedera, 2009 x x x x
Shang and Lin, 2005 x x
Forward search
Chang et al., 2010 x x x
Öztayşi et al., 2011a x x x x
Rapp et al., 2010 x x x x
Becker et al., 2009 x x x
Zablah et al., 2012 x x
Kim et al., 2012 x x
Coltman et al., 2011 x x x
Hillebrand et al., 2011 x x x
Gharibpoor et al., 2012 x x x x x
Soeini et al., 2011 x x x x
Peltier et al., 2013 x x
Shafia et al., 2011 x x x x
Ernst et al., 2010 x x x x x
Behravan and Sabb., 2012 x
* Kim et al., 2003
x x x
Hits 0 20 3 26 0 8 0 22 3 28
* Backward search
positive interaction with customers. The (4)
information management process “is concerned with
the collection, collation, and the use of customer
data the collection, collation, and the use of
customer […] to generate customer insight […]”
(Payne and Frow, 2005). The (5) performance
assessment process ensures that the organization’s
strategic aims are effected in an acceptable standard
and that future improvements are derived from this
process.
In order to answer the research question
completely Table 6 reveals an overview of the
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investigated literature. The 38 relevant articles are
described in the rows and the five process
dimensions are shown in the columns, which are
separated in a new Social CRM approach (N. Ap.)
and a traditional CRM approach (Tr. Ap.). The x
marks the articles’ classification within the process
dimensions of Payne and Frow (2005). According to
the classification, no article was categorized in the
(1) strategy development process, (3) multichannel
integration process and (4) information management
process for the N. Ap. Regarding these results only a
few articles classify the N. Ap. for the (2) value
creation process and (5) performance assessment
process. The appropriate articles (Behravan and
Sabbirrahman, 2012; Farb, 2011; Li et al., 2012;
Vulic et al., 2012) use conceptual, as well as
illustrative research methods (Alavi and Carlson
1992) without an evaluation based foundation.
Furthermore, three out of the four N. Ap. articles,
which are categorized to (5) performance
assessment process focus especially on a partial
measurement scope and measure through a
company-perspective (Farb, 2011; Li et al., 2012;
Vulic et al., 2012). The remaining fourth paper
(Behravan and Sabbirrahman 2012) provides a
customer-facing measurement scope and describes
an indirect measurement type.
All articles related to N. Ap. (4 articles) lack a
direct holistic measurement approach with an
evaluation based foundation. Regarding this finding
a Social CRM measurement model is sparsely
addressed in extant literature and thus a research gap
is identified.
4 RESEARCH AGENDA
The results from the current literature review and the
identified research gap confirm the need for
extensive research regarding the research topic. The
research agenda describes the process steps,
according to (Peffers et al. 2007) for a Social CRM
measurement model in order to develop and
implement a Social CRM management cockpit.
Figure 2 depicts the research agenda over time
(axis of abscissae) and shows the six design science
research process phases (marked in grey boxes),
namely (1) identify problem & motivate, (2) define
objectives of a solution, (3) design & development,
(4) demonstration, (5) evaluation and (6)
communication. The first process phase (identify
problem & motivate) was done in 2013.
Practitioners’ needs were recorded, processed
and analysed, which were summarized in working
Figure 2: Research Agenda.
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reports. The current and future cooperation with
Swiss and German companies (listed in “Deutscher
Aktien Index” (DAX) and “Swiss Market Index”
(SMI)) confirms the motivation and practical need
for further research. This article is part of the second
process phase (define objectives of a solution) and
sheds light the scientific research gap. A practical
solution was detained in a working package, which
results from a focus group with the cooperative
companies. The resulting Social CRM measurement
model is determined by the end of 2015. Within the
third phase (design & development) an explorative
case study identifies new Social CRM measures.
The new measures will be analyzed, categorized and
results in a new Social CRM approach. Their
measurement follows the three step approach (as
mentioned in the introduction) according to Moore
and Benbasat (1991): (1) item creation, (2) scale
development, and (3) instrument testing. It is an
iterative process with the phases four
(demonstration) and five (evaluation). In the first
step (item creation), new items will be developed for
the new Social CRM measures. Secondly (scale
development), a content validation confirms the
reliability of the items. For example, the
demonstration of the scale development will be
conducted through a Q-Sorting approach with
practitioners and PhD-students (Petter, Straub, and
Rai, 2007). In the final step (instrument testing) the
designed scale development will be demonstrated
with different practitioner pilots and evaluated with
a company and customer survey. The survey data
will be analyzed with SmartPLS (a software
program for structured equation models) according
to Hair et al. (2013). The overall result of the third
process phases will be a Social CRM measurement
model, which is demonstrated on a prototype web
application (a Social CRM management cockpit).
The results will also be evaluated with additional
explanatory case studies to falsify the practical need.
The last process phase (communication) includes
several working reports, conference papers, a journal
article, and the implementation of a management
cockpit with one of the cooperative companies.
5 CONCLUSIONS
The goal of this paper is to analyze the current
literature for the research topic Social CRM
measurement model. A systematic and rigorous
literature review, according to vom Brocke et al.
(2009), is conducted to derive a research gap and
depicts further research project steps. Consequently,
39 relevant articles were analyzed, structured in five
different categories (cf. Table 5) and synthesized
within the framework of Payne and Frow (2005).
The major finding reveals the lack of extant
literature regarding the research topic and discloses
the need for a Social CRM measurement model
based on a direct holistic measurement approach.
Three apparent limitations restrict the results of
the paper. First, the journals and conferences
proceedings as well as the search phrases from the
literature search process provide no sufficient
guarantee that all relevant articles were taken into
account. Secondly, the key variables are certainly
not all-encompassing, even though they are derived
from extant literature. Other and additional key
variables lead to different articles and could
influence the result. Finally, the mentioned
framework (Payne and Frow, 2005) is based on
CRM literature and constitutes a possibly
inappropriate framework for the research topic. The
development of a new Social CRM framework
covers the limitations for a thoroughly rigorous
literature analysis and synthesis.
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