A Literature-based Derivation of a Meta-framework for
IT Business Value
Sarah Seufert
a
, Tobias Wulfert
b
, Jan Wernsd
¨
orfer
c
and Reinhard Sch
¨
utte
d
Institute for Computer Science and Business Information Systems, University of Duisburg-Essen,
Universit
¨
atsstraße 2, Essen, Germany
Keywords:
IT Business Value, IT Value Framework, Impact of IT, IT Investments, Literature Review, Meta-framework.
Abstract:
The business value of IT in companies is a highly discussed topic in information systems research. While
the IT business value is an agreed upon term, its decomposition and assessment on a more detailed level is
ambiguous in literature and practice. However, assessing the IT business value is pivotal for goal-oriented IT
management. Therefore, we suggest a hierarchical decomposition of the IT business value along aggregated
impacts and atomic impacts. We introduce a taxonomy to gain a better understanding of what types of atomic
impacts may be caused by IT investments. With the help of the taxonomy, we classify a total of 957 values
from existing value catalogs and derive 29 archetypal IT impacts grouped by a company’s business units.
Bundling this grouping with exemplary impacts for the IT value assessment, we finally propose an IT value
meta-framework for the structured business value assessment.
1 INTRODUCTION
The business value of IT in companies is a highly
disputable topic in information systems (IS) research
(Melville et al., 2004; Brynjolfsson and Hitt, 2003;
Mirani and Lederer, 1998; M
¨
uller et al., 2018; Pathak
et al., 2019). Without an understanding of the busi-
ness value of IT investments within a company, no
goal-oriented IT management is possible (Sch
¨
utte
et al., 2019). The “naive” expectations about only
positive economic effects of IT have been discussed
for a long period in literature as IT productivity para-
dox, focusing on the value contribution of IT and
its contribution to the success of companies in the
1980s and 1990s (Brynjolfsson, 1993; Brynjolfsson
and Hitt, 1998). More recently, the opinion has be-
come accepted that IT in general has a positive influ-
ence on a company’s productivity (Brynjolfsson and
Hitt, 2003). But the problem still exists that the vari-
ance in the return (positive and negative) on IT invest-
ments is still high and the IT business value, defined
as extent of the contribution of IT investments to the
productivity or success of a company (Cao, 2010), is
therefore still difficult to determine. Despite these un-
a
https://orcid.org/0000-0003-3231-2853
b
https://orcid.org/0000-0002-5504-0718
c
https://orcid.org/0000-0002-1152-5043
d
https://orcid.org/0000-0002-1535-9038
certainties in the IT business value, companies extend
their IT budgets for investments in digitalization en-
deavors (Fersht and Snowdon, 2020). Nevertheless,
the assessment of IT business values prior to an IT
investment is especially important in times of crises
such as the American subprime mortgage crisis, the
European debt crisis and currently the coronavirus
disease in which IT budgets are typically reduced.
With reduced IT budgets, decisions demand for more
elaborated business cases and cost-benefit analysis to
approve IT investments (Hajli et al., 2015). Never-
theless, despite the crises, investments in IT are still
necessary, for example to be able to react more flexi-
bly to changes or to adapt the current business model
to changes caused by the crises. However, the IT busi-
ness value of single IT investments is often assessed
by a decision maker’s rule of thumb (Schniederjans
et al., 2010).
To better deal with IT investment decisions, IS
researchers so far have proposed approaches to as-
sess the IT business value of an IT investment in a
company (Mooney et al., 1996; Tallon and Kraemer,
2006) and have introduced a number of value catalogs
including specific impacts and expected business val-
ues of IT (Melville et al., 2004; Samulat, 2015; Porter,
2001a; Farbey et al., 1992; Gregor et al., 2006; Kur-
niawan et al., 2016). A value catalog is a reference
list of positive and negative effects (Schulze, 2009)
that can be attributed to the launch or productive op-
Seufert, S., Wulfert, T., Wernsdörfer, J. and Schütte, R.
A Literature-based Derivation of a Meta-framework for IT Business Value.
DOI: 10.5220/0010447702910302
In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 2, pages 291-302
ISBN: 978-989-758-509-8
Copyright
c
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
291
eration of an IT system (Sch
¨
utte et al., 2019). These
catalogs consist of a set of either specific or abstract
possible impacts for IT systems in general or specific
industry or system constellations with the downside
that these impacts are not always directly quantifi-
able in an arbitrary company (Bartsch, 2015). Nev-
ertheless, value catalogs indicate possible IT business
values and allow decision makers at least for one
catalog - to fully assess the business value of a fu-
ture IT investment and avoiding formally defective
decision models that cannot be solved (Adam, 1996).
The literature already contains a few value catalogs
for the identification of the IT business value that are
intended to serve this purpose. However, the lists
vary in the number, the definitions and the granularity
of categories (Schryen, 2013). Also, many existing
catalogs are prone to problems regarding a compre-
hensive and customizable IT value assessment (exem-
plary IT value catalogs in brackets). Oftentimes, cata-
logs do not sufficiently indicate atomic effects and are
rather abstract (Mirani and Lederer, 1998). Related
to this issue are missing or insufficient hierarchiza-
tions of impacts. While the majority of catalogs aims
to assess the IT business value as a whole (Baum
¨
ol
and Ickler, 2008), those approaches are oftentimes in-
complete due to abstractions from context specific as-
pects. Specific catalogs on the other hand (Schulze,
2009) appear to dismiss important aspects mentioned
in the taxonomy of IT impacts (Figure 2). In general,
IT value catalogs are also not designed to be config-
ured for a specific application context, missing nec-
essary mechanisms and methods for such customiza-
tions (Porter, 2001a).
Conducting a structured literature review (Web-
ster and Watson, 2002), we have identified 32 catalogs
including 957 impacts. These impacts both contain
several duplicates and vary in their scope and mean-
ing. Thus, we aim at providing archetypal IT im-
pacts for the assessment of arbitrary IT investments.
Based on these archetypes we will propose a meta-
framework for the IT business value assessment. Our
research enables practitioners to extend their IT busi-
ness value assessment with our archetypal impacts or
build IT value catalogs themselves. Researchers may
build on our archetypal IT impacts for further quanti-
tative analysis of the IT business value.
The remainder of this research is structured as
follows: firstly, we will set the foundations for the
meta-framework development involving IT business
value and value catalogs in general and characteris-
tics of atomic IT values in particular. Secondly, we
will sketch our scientific approach followed by a pre-
sentation of our IT value archetypes within the meta
IT value framework. Finally, we discuss our findings
and briefly summarize our main results and provide
an outlook on future research.
2 FOUNDATIONS
2.1 IT Business Value Decomposition
The IT business value can be defined as the impact
of IT on organizational performance (Melville et al.,
2004; Mooney et al., 1996; Devaraj and Kohli, 2003),
which is widely established in the literature (Pathak
et al., 2019). Melville et al. complement this gen-
eral definition with an indication of the level and also
the type of impacts: “at both the intermediate pro-
cess level and the organization-wide level, and com-
prising both efficiency impacts and competitive im-
pacts” (Melville et al., 2004). While efficiency refers
to internal impacts such as productivity enhancement
(Tallon and Kraemer, 2003), product quality (Barua
et al., 1995), profitability improvements (Melville
et al., 2004) or cost reduction (Tallon and Kraemer,
2003), competitive refers to external impacts such as
competitive advantage (Parsons, 1983), product dif-
ferentiation (Belleflamme, 2001) or market expansion
(Tallon and Kraemer, 2003). Although there is a gen-
eral agreement about what an IT business value can
be and the topic has been discussed for many years,
“the relation between IT investments and firm per-
formance remain elusive” (Masli et al., 2011). It is
still not clear what are the returns and the concrete
values generated by IT investments in particular, and
the decomposition of the IT business value in general
(Pathak et al., 2019; Wang et al., 2012).
Some authors have already addressed this gap in
research and decomposed the IT business value to
possibly observable impacts. We propose value cat-
alogs as an important starting point for the identifi-
cation of the IT business value in a specific organi-
zation (Sch
¨
utte et al., 2019). An optimal value cata-
log hierarchically decomposes the IT business value
(level 1) into aggregated values (level 2), observable,
atomic impacts (level 3) and guides the assessment
providing key questions (level 4) for the impact iden-
tification (Figure 1). The hierarchical decomposition
avoids formally defective decision problems (Adam,
1996).
IT Business Value
Aggregated Value n Aggregated Value 1
Atomic Impact n Atomic Impact 1
Question 1 Question 2
Atomic Impact 2
Question n
Decomposition of IT
Business Value
Level 1
Level 2
Level 3
Level 4
Figure 1: Decomposition of IT Business Value.
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
292
2.2 IT Value Dimensions and
Characteristics
The variety of atomic IT impacts can be classified ac-
cording to the following dimensions and characteris-
tics (Nickerson et al., 2013) presented in the taxon-
omy in figure 2. The proposed taxonomy consists
of six dimensions each consisting of several mutu-
ally exclusive and collectively exhaustive characteris-
tics (Nickerson et al., 2013; Bailey, 1994). The Busi-
ness Unit (1) characteristics are based on the value
chain introduced by Porter which dis-aggregates a
firm in strategically relevant primary and supporting
activities (Porter, 2001a). Logistics (Log) activities
are originally divided in inbound and outbound lo-
gistics (Porter, 2001a). Under logistics we comprise
all activities associated with receiving, storing, and
disseminating inputs to the product and with collect-
ing, storing, and physically distributing the product
to buyers. Under Operations (Ops) we subsume all
activities associated with transforming inputs into the
final product. Due to the original focus of (Porter,
2001b) on industrial enterprises with mainly physi-
cal products, we retrospectively also assign the cre-
ation and provision of services to this activity in or-
der represent today’s business environment (Parasur-
aman et al., 2005). Marketing and Sales (M&S) refers
to activities that make the product or service appeal-
ing to customers and also to activities that are nec-
essary for the buyer to purchase the product. Ser-
vices (Ser) includes activities to maintain or increase
the value of the product or service. Thus, this activ-
ity contains the delivery of services created by op-
erations and services accompanying physical goods.
Procurement (Proc) includes all activities that are nec-
essary to purchase resources and necessary material
used in the operations and other business unites of
the company. Technological Development (TD) is
understood to comprise of a variety of activities that
deal with the improvement of a product or service
and in particular with the process associated with it.
Human Resources Management (HR) consists of the
activities related to the recruitment, training, devel-
opment and remuneration of all types of personnel
(Porter, 2001b). For coding impacts that have an in-
fluence on several business units we introduce Cross-
Organizational-Activities (COA) as further character-
istic. It includes activities that involve general man-
agement, planning, finance, accounting, legal, gover-
nance affairs, and quality management which usually
supports the entire chain and not individual activities.
The Tangibility (2) of an IT impact is concerned
with the extent to which it can be measured and eval-
uated in economic terms (Lucas, 2000). The literature
generally distinguishes between tangible and intangi-
ble impacts. Tangible impacts represent impacts that
can be measured and quantified economically (Mi-
rani and Lederer, 1998). Intangible impacts on the
other hand are very hard to quantify, oftentimes not al-
lowing for such economic evaluations (Lucas, 2000).
Thus, a qualitative assessment of the impact is neces-
sary (Kesten et al., 2007).
A widespread distinction in the Level of Exami-
nation (3) is the individual level, the firm level and
the industry level (Bakos, 1987; Chau et al., 2007;
Kauffman and Weill, 1989). We are following this
view, especially since this distinction plays an impor-
tant role in explaining the productivity paradox. The
individual level effects of the IS affecting employ-
ees on an individual level, such as improving skills
or increasing the employee’s satisfaction (Chau et al.,
2007). Firm level is concerned with IT impacts which
have an influence on the whole organization includ-
ing cross-organizational processes. For example, pro-
cess improvements or increased organizational per-
formance (Soh and Markus, 1995). This level of ex-
amination also refers to the value chain of the orga-
nization, thus customer and supplier related activities
or processes. The industry level contains IT impacts
going beyond the organizational boundaries and its
value chain, e.g. on the entire industry or the national
economy (Chau et al., 2007).
Figure 2: Taxonomy of IT Impacts.
The definition of IT business value already empha-
sizes that the Performance Focus (4) is a central as-
pect, which should also be considered when identify-
ing impacts. Operation process performance is usu-
ally created by tangible impacts of the IT. They repre-
sent automatizations of activities or processes which
constitute the regular day-to-day business, thus affect-
ing the performance of the organization. However,
they also oftentimes form the basis for intangible im-
pacts that build on them (Mooney et al., 1996). Man-
agement process performance increases the availabil-
ity and quality of information, allowing for better co-
ordination, control and a decision making by the man-
agement.
IT systems produce a (potentially continuous)
stream of net benefits. Thus, this dimension focuses
A Literature-based Derivation of a Meta-framework for IT Business Value
293
on the Time of Occurrence (5) of the impacts. Con-
ducting an a priori assessment of the impact of the IT
at the time of the investment decision, the impacts un-
til and exploitable immediately at the go-live (imme-
diate impacts) of the IT can be determined and proba-
ble future impacts (anticipated impacts), by accessing
the quality of the IS as a proxy measure, can be antic-
ipated (Figure 3) (Gable et al., 2008).
Time
Time of occurence
t
1
Immediate Impacts
Investment Decision
t
2
Go-live
Anticipated Impacts
Figure 3: Time of Occurence.
Investments in IT systems do not only provide posi-
tive impacts to the organization. To assess the overall
benefits of an IT, it is necessary to analyze the Direc-
tion (6) of these impacts (Schumann, 1992). As the
majority of the literature focuses on positive benefits
of IT, our presupposition is to regard IT impacts as
positive, if a negative character of an impact is not ex-
plicitly stated. Positive impacts have contributed to
an overall corporate objective, to justify the IS invest-
ment (Schulze, 2010). The implementation and the
operation of an IT system may also cause direct (one-
time) and indirect (ongoing) negative impacts such as
costs for the organization (Schulze, 2010).
3 RESEARCH APPROACH
To analyze possible IT impacts and derive a profile
of aggregated clusters of impacts, we conduct a struc-
tured literature review and cluster identified IT im-
pacts accordingly. Our analysis begins (1) with the
identification of IT impacts already discussed in the
literature (Figure 4) to build upon existing knowledge
regarding IT-impacts (Webster and Watson, 2002).
The review starts by identifying and selecting qual-
ified sources upon which the relevant data can then
be extracted. This data, primarily the individual IT
impacts, builds the foundation for the subsequent cre-
ation of the IT value framework. By limiting the key-
word search (Urbach et al., 2009) to leading jour-
nals (AIS Senior Scholars’ Basket), the quality of
the results should be ensured (Webster and Watson,
2002). Based on an initial screening of the literature
we formulated the following generic search string that
is customized for EBSCOHost: (Information Tech-
nology OR Information System* OR IT OR IS) AND
(Value Catalog* OR Impact* Catalog* OR Value Cat-
alog*)
To broaden the possible literature pool, German
publications where also recognized by translating the
search string. After an initial screening based on the
criteria according to Fink (2019, p. 53) (e.g., lan-
guage: German/English; research subject: IT sys-
tems; etc.), a total of 57 contributions could be iden-
tified. Due to the lack of a common generic term,
the keyword search yielded rather imprecise results,
putting special importance on the subsequent forward
and backward search (Webster and Watson, 2002).
The identified contributions were subjected to a thor-
ough selection process defined by the following selec-
tion criteria: (a) the content must meet the previously
established definition of IT impacts, (b) the catalog
must be based on some form of categorization, and
(c) the catalog must contain atomic impacts. A to-
tal of 32 sources were deemed suitable for extracting
and analyzing their contents. Key sources for devel-
oping our meta-framework are illustrated with exem-
plary impacts in figure 6.
(1) Literature Review
Search
String
Generation
Keyword
Estab-
lishment
Database
Search
Literature
Screening
Back-/
Forward
Search
(2) Impact Preprocessing
Catalogue
Details
Documentation
(Atomic)
Impacts
Extraction
Dimension
Derivation
Charac-
teristics
Derivation
(3) Impact Clustering and Hierarchisation
Dimension
Update
Test
Coding
Manual
Coding
Intercoder
Calculation
Clustering &
Hierar-
chisation
Figure 4: Research Approach.
We then (2) extracted all impacts from the identified
sources with focus on the atomic impacts. Following
a systematic selection process (Schwarz et al., 2007),
all sources were read to document relevant data in
a structured form. Specifically, atomic impacts and
their respective categories were collected in an Excel
spreadsheet, while additional aspects of each IT value
catalog were documented separately. This selection
process resulted in a collection of 957 IT impacts, of
which 682 can be designated as atomic (level 3). Ag-
gregating the impacts in a concept matrix (Webster
and Watson, 2002) led to the overarching dimensions
and characteristics describing the variety of impacts
identified (Section 2.2).
Using this data-set of 682 atomic IT impacts, we
firstly conducted a qualitative content analysis involv-
ing each (hierarchy of) impacts and their respective
research paper and codified (3) each IT impact re-
garding the presented dimensions and characteristics.
After an initial test coding with a set of 50 impacts,
we updated the dimensions and their respective char-
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
294
acteristics. For example, it appeared that the dimen-
sion Form of Investment investigating the type of IT
and related staff to be invested in could not be coded
reliably and therefore had to be dismissed. Also,
the characteristic All had to be removed from the di-
mension Performance Focus due to its distorting ef-
fect. Having the dimensions and characteristics estab-
lished, five independent coders knowledgeable about
IT business value in general and IT value catalogs in
particular manually assessed the selected IT impacts.
As suggested in the literature (Nili et al., 2017), those
coders where trained in the coding procedure and pro-
vided with a coding guide stating the definitions of
each code. Due to the large number of IT values, the
coding was done in multiple stages in order to pre-
vent coder fatigue (Jourdan et al., 2008; Neuendorf,
2002). We used Microsoft Excel and VBA to sup-
port the coding process. If information for an IT im-
pact is missing, we considered supplementary mate-
rial such as referenced papers. If an IT impact is as-
signed with diverging characteristics during the cod-
ing process, the characteristic used by the majority of
the coders is assigned. Cases in which an unambigu-
ous decision cannot be made as the coders all assigned
different characteristics are discussed among the five
coders via online communication media, referring to
the respective reliability measures (Weber, 1990). To
assess the coding quality, we calculated Fleiss’ Kappa
as suggested indicator (Landis and Koch, 1977) for
the intercoder reliability (Fleiss, 1971) for each di-
mension. This method allows for determining the
agreement between more than two coders while ac-
counting for agreements by chance (Nili et al., 2017).
The calculated kappa values are benchmarked against
a set of fixed agreement measures in order to access
the reliability of our coding (Landis and Koch, 1977).
The intercoder reliability for the dimension Direction
is almost perfect (0.98) and substantial for Business
Unit (0.61). The dimensions Tangibility (0.47) and
Level of Examination (0.54) both constitute a mod-
erate level of agreement between the coders. For
Performance Focus (0.35) and Time of occurrence
(0.40) a fair strength of agreement could be measured.
The coding processes leads to a codified table of 682
IT impacts. After qualitatively assessing the IT im-
pacts, the clusters are established by statistical meth-
ods (Denscombe, 2008). We cluster the hand-coded
IT impacts to derive archetypal IT impacts general-
izable for arbitrary IT investments. The clustering is
used to abstract from the diverging connotations of
the IT impacts used by the authors of the value cata-
logs under consideration. The meta-framework pro-
vides an overview on the existing IT impacts as previ-
ously described in literature. We applied hierarchical
clustering on the set of 682 IT impacts with their re-
spective coding. For deriving the number of clusters,
we visually examined the dendrogram resulting in a
number of 29 clusters (Ketchen and Shook, 1996).
Aiming at maximizing the homogeneity within each
cluster, we apply the Ward method with squared Eu-
clidean distances (T
¨
auscher and Laudien, 2018). The
clusters as archetypal IT impacts form level 3 in our
decomposition of the IT business value (Figure 1). In
order to aggregate the impacts we used the business
unit dimension as it includes the highest number of
characteristics, thus allowing for the highest degree
of differentiation. This dimension also seemed to be
a key differentiator among the derived clusters. Ad-
ditionally, the business unit dimension is perceived to
be the most relevant for the internal organization of
a company, regarding a practical application of the
framework. This aggregation follows Porter et al.,
taking the perspective of key organizational activities
(Porter, 2001b), also building upon previous classifi-
cations of IT impacts (Anselstetter, 1984). The result-
ing meta IT value framework is presented in the fol-
lowing chapter indicating the number of IT impacts
summarized in each cluster following the cluster ID
in brackets (cluster ID - number of impacts).
4 IT VALUE FRAMEWORK
By applying the hierarchical cluster analysis to the IT
impacts, we identify 29 distinct archetypal IT impacts
for the third level of the IT business value decomposi-
tion. These impacts can be aggregated (level 2) to the
business units (section 2.2). For exemplary archety-
pal IT impacts, we propose exemplary IT impacts and
leading references allowing practitioners to better as-
sess the IT business value of their respective IT in-
vestment. Further guiding questions can be derived
based on the following descriptions of the archety-
pal IT impacts and mentioned literature. This also al-
lows for a customization of the framework to the spe-
cific IT investment decision regarding organization,
IT system, and other environmental factors (Brynjolf-
sson and Hitt, 2003). An extract of the developed IT
value framework is depicted in figure 5 illustrating the
structure and design of the framework (level 1-3). The
extract is detailed in figure 6 presenting the clustered
archetypal IT impacts as level 3 impacts and exem-
plary impacts for level 4. We used the characteristics
of the business unit dimension (level 2) for aggregat-
ing the clusters of IT impacts (level 3) and developing
a hierarchical IT value framework.
The Log aggregated value consists of two impacts.
Better inventory management (Log 1 - 32) which
A Literature-based Derivation of a Meta-framework for IT Business Value
295
leads to cost reductions in this domain. This can be
achieved by impacts reducing the inventory (O’Leary,
2004), e.g. delivering products electronically (Schu-
mann, 1992), increasing the turnover (Vanlommel and
De Brabander, 1975), or reducing the storage require-
ments (Andresen et al., 2002). IT systems can also
improve the incoming goods inspection (Log 2 - 9)
e.g. by impacts decreasing reclamation and spoilage
risks (Anselstetter, 1984).
By clustering the Ops aggregated values two dis-
tinct, archetypal impacts can be identified. The
first cluster involves improvements to production pro-
cesses (Ops 1 - 27). Those production related effi-
ciency and effectivity benefits can materialize in var-
ious immediate impacts. Some examples are an IT-
based increased throughput (Mooney et al., 1996),
optimized capacity utilization (Schulze, 2009), re-
duced operational costs, or higher production relia-
bility (Anselstetter, 1984). Another cluster is consti-
tuted by impacts which improve the product quality
(Ops 2 - 8). This can be achieved by providing lean
production (Shang and Seddon, 2002) or a higher de-
gree of standardization (Vanlommel and De Braban-
der, 1975).
Six archetypal clusters are identified for the M&S
aggregated value. Impacts of the IT system can
improve the M&S capabilities (M&S 1 - 8) of
the organization. Examples are the ability to pro-
vide instant price quotations to clients (Andresen
et al., 2002), analyzing ordering behaviors (Schu-
mann, 1992), or adding multi-currency capabilities in
IT systems (Shang and Seddon, 2002). Another as-
pect of the M&S business unit is represented by the
cluster which improved customer retention (M&S 2
- 12). Those impacts can improve the overall cus-
tomer relations (Gammelg
˚
ard et al., 2006; Mirani and
Lederer, 1998) or by saving customer requests and
utilizing such data in order to provide personalized
offers (Schumann, 1992). Some impacts are specif-
ically directed towards increasing sales (M&S 3 - 7)
and the respective business unit. Possible approaches
are to implement ordering systems in order to develop
new sales areas (Schumann, 1992) and to increase
responsiveness to customers (O’Leary, 2004). The
sales management (M&S 4 - 6) cluster contains im-
pacts that support decision makers in this domain, e.g.
by providing faster and cheaper information about the
success of marketing measures (Schumann, 1992) or
more elaborated product range analysis (Anselstet-
ter, 1984). Besides increasing and managing sales,
IT systems can also provide time savings in market-
ing, sales, and product delivery (M&S 5 - 23). By
introducing sales automation (O’Leary, 2004), faster
billing (Gable et al., 2008), or immediate price and
availability information (Schumann, 1992) can, for
example, result in decreased capital commitment or
less delayed deliveries (Anselstetter, 1984). By De-
veloping competitive sales capabilities (M&S 6 - 10)
consist of impacts which improve the company image
and public relations (Andresen et al., 2002). Addi-
tionally, through superior marketing (Vanlommel and
De Brabander, 1975), market (Anselstetter, 1984) and
sales analyses (Schumann, 1992) , the company can
improve its competitive position (Anselstetter, 1984).
IT Business Value
Ser 1
LogisticService
Cross Organizational Activities
COA 1Log 1 Log 2 COA 2
Figure 5: Extract from the IT Value Framework.
All impacts assigned to Ser can be represented by the
archetype improved customer services (Ser 1 - 18)
that contains operational, cross organizational activ-
ities which improve the quality and delivery of cus-
tomer services (Gammelg
˚
ard et al., 2006). Improve-
ments can be achieved, for example, by impacts accel-
erating responses to such enquiries and a faster, bet-
ter delivery of the requested service (Andresen et al.,
2002), or by reducing the overall need for services
(e.g. maintenance) (O’Leary, 2004). The customer
interaction can also be impacted by interactive and
customizable services (Shang and Seddon, 2002) or
24/7 service availability (Riggins, 1999).
The Proc cluster analysis resulted in two archety-
pal impacts. On an operational level, IT can con-
tribute to a more efficient procurement of resources
(Proc 1 - 15). This refers to faster (Anselstetter, 1984)
and cheaper (Vanlommel and De Brabander, 1975)
procurement by e.g. improving the order manage-
ment (O’Leary, 2004) or faster responses to supplier
quotations (Andresen et al., 2002). Improved bar-
gaining against suppliers (Proc 2 - 6) involves IT im-
pacts improving the supplier selection resulting in im-
proved supplier identifications and assessments (An-
dresen et al., 2002) as well as improvements to the
order planning, control, and monitoring (Anselstetter,
1984).
The aggregation of the TD impacts can be decom-
posed in to two IT value archetypes. Improved IT
infrastructure support (TD 1 - 18) constitutes impacts
which provide immediate benefits by improving upon
the IT infrastructure of the company. Those can ma-
terialize in improvements to the data security (Kesten
et al., 2007), quicker, easier, and cheaper incorpora-
tion of product features (Porter and Millar, 1985), or
reduced communication costs (Mirani and Lederer,
1998). Impacts assigned to the improved R&D (TD
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
296
2 - 16) cluster allow a company to make product,
service and business process innovations and to alter
their product life cycles (Mooney et al., 1996), thus
possibly utilizing IT as an competitive weapon (Par-
sons, 1983). Exemplary impacts consist in an faster
application development (Mirani and Lederer, 1998)
and the ability to apply previously unfeasible business
technology (Porter and Millar, 1985).
The clustering revealed two impacts for the aggre-
gated HR values. Staff reductions (HR 1 - 22) consti-
tutes e.g. impacts to increase employee productivity
(Gable et al., 2008) in order to avoid the need to in-
crease the work force (Anselstetter, 1984) or decrease
the current number of employees (Petrovic, 1994).
Another approach is to reduce the staff requirements
(Andresen et al., 2002). Impacts which improve the
employee’s skills (HR 2 - 17) focus on learning us-
ing IT. Those skills can materialize in a broadened
skill level (Shang and Seddon, 2002) and enhanced
recall of job-related information (Gable et al., 2008)
as well as social skills such as the ability to work au-
tonomously (Shang and Seddon, 2002) and improved
human relations (Anselstetter, 1984).
The aggregated COA values can be decomposed
into twelve archetypal impacts. Operational time and
cost savings (COA 1 - 109) at firm level constitutes
the largest cluster. Those impacts represent clas-
sic effectiveness and efficiency benefits which can
be achieved through investment in IT. Examples are
various forms of cost reductions (e.g. staff, transac-
tions, etc.) (Andresen et al., 2002; Shang and Seddon,
2002) and process improvements (Riggins, 1999).
Those impacts are mostly tangible and occur imme-
diately after the implementation of the IT system.
The improvements in management process (COA 2
- 62) cluster is primarily concerned with immediate
information-related impacts of the IT investment and
how they affect the management. For example, IT
investments can increase the availability and accu-
racy (Gregor et al., 2006) of information, enabling
faster, and more efficient decision making (Parker
et al., 1988). Impacts enabling the development of
new business areas (COA 3 - 6) constitute a relatively
small cluster. This can be done by new products and
applications (Bartsch, 2015) or amendments to the
workforce, policies, and procedures (Shang and Sed-
don, 2002). Impacts clustered in the improve market
position (COA 4 - 63) group are cross-organizational,
mostly anticipated and directed towards management
processes. To name a few, IT systems may support
strategic goals of the company (Baum
¨
ol and Ickler,
2008), constitute a competitive advantage (Weill and
Broadbent, 1998), or enable changes to the business
model (Schulze, 2009). The cluster improved corpo-
rate growth (COA 5 - 11) contains impacts which en-
able the company to grow or ones that minimize re-
lated risks. IT can create such growth by increasing
the operational readiness (Anselstetter, 1984), allow-
ing for new services (Shang and Seddon, 2002), or
minimizing the risk of new business ventures (An-
dresen et al., 2002). IT systems can also increase
the company flexibility (COA 6 - 53) allowing the
company to adapt to future changes. Exemplary im-
pacts for this cluster are an increase level of stan-
dardization (O’Leary, 2004) and an improved change
management (Gammelg
˚
ard et al., 2006). The growth
management (COA 7 - 11) cluster contains impacts
IT can have on the highest company level to gen-
erate growth. Examples are building a cost leader-
ship (Shang and Seddon, 2002), leveraging the com-
panies size (O’Leary, 2004) and to increase the mar-
ket share (Andresen et al., 2002). Impacts of IT
systems can also create and defend competitive ad-
vantages (COA 8 - 16) by developing new markets
and influencing the relationship to competitors. For
example, impacts creating or removing barriers for
market entry (Schulze, 2009), allowing expanding to
e-markets (Shang and Seddon, 2002), and improv-
ing relations to external parties (Gammelg
˚
ard et al.,
2006). By improving the integration and information
flow (COA 9 - 66) across the company, IT impacts
can provide various positive, but oftentimes intangi-
ble benefits. This allows to perform tasks separated
in time and space or to increase idea and information
sharing among project teams (Andresen et al., 2002).
The cluster improved employee satisfaction and per-
formance (COA 10 - 12) shows how IT impacts can
directly affect the workforce. Those impacts usually
apply to all business units and are difficult to quantify
in monetary terms. For example, a better perform-
ing system can increase the moral or the interpersonal
communication (Shang and Seddon, 2002), some im-
pacts may also boost employee’s creativity (Mooney
et al., 1996). Besides those primarily positive impacts
of IT, such investments also cause considerable costs.
The IT investment costs (COA 11 12) represent di-
rect and indirect costs associated with the IT invest-
ment. For example, acquisition and personnel costs
as well as an increased dependence on the IT (Ansel-
stetter, 1984). In the cluster time savings in daily busi-
ness operations (COA 12 - 5) IT systems contribute to
such savings by reducing calls and mails (Anselstet-
ter, 1984) as well as changes to the individual work-
place (Schumann, 1992).
A Literature-based Derivation of a Meta-framework for IT Business Value
297
ID
Aggregated Values Examples of Impacts of the Aggregated Values
COA 1
Operational time and
cost savings at firm-
level
Labor cost reduction (Shang und Sheddon, 2002; Mooney et al., 1996), Cost reductions (Porter and Millar, 1985; Parsons, 1983; O'Leary, 2004;
Gammelgard et al., 2006; Gable et al., 2008), Productivity Improvements (O'Leary, 2004; Gable et al., 2008; Andresen et al., 2002; Parson, 1983), Overall
operation efficiency and effectiveness (Shang und Sheddon, 2002; Mooney et al., 1996; Bamöl und Ickler, 2008), Speed up transactions or shorten product
cycles (Mirani und Lederer, 1998), Reduced planning times (Andresen et al., 2002), Enabling faster access to information (Gregor et al., 2006), ...
COA 2
Immediate
improvements in
management process
Improving information accuracy (Gregor et al., 2006), Availability of new, better or more information providing opportunity to compete morc effectively
(Parker et al., 1988), New Reports/Reporting Capability (O'Leary, 2004), Improved ability to coordinate and integrate (Gammelgard et al., 2006), Increase
the flexibility of information requests (Mirani und Lederer, 1998), Better asset management (Shang und Sheddon, 2002), ...
COA 3
Development of new
business fields
Business growth with increased employees, new policies and procedures (Shang und Sheddon, 2002), Improved capture of design and construction
decisions (Andresen et al., 2002), Development of new business fields (Baumöl and Ickler, 2008; Bartsch, 2015), Better research/development planning
(Anselstetter, 1984), ...
COA 4
Improved market
positioning of the
company
Enable new market strategy (Shang und Sheddon, 2002), Help establish useful linkages with other organizations (Mirani und Lederer, 1988; Andresen et
al., 2002; Gregor et al., 2006), Improved strategy formulation and planning (Gammelgard et al., 2006), Strategic competitive advantage (Andresen et al.,
2002; Weill and Boradbent, 1998), ...
COA 5
Improved corporate
growth (and
reporting)
Business growth in transaction volume, processing capacity and capability (Shang und Sheddon, 2002), Reporting (Mooney et al., 1996), Business growth
in new markets (Shang and Sheddon, 2002), …
COA 6
Increased flexibility
to addapt to future
changes
Global resource management (Shang und Sheddon, 2002), Expandable to a range of applications (Shang und Sheddon, 2002), Improved organizational
culture (Gammelgard et al., 2006), Improved change management (Gammelgard et al., 2006), Increased business flexibility (Andresen et al., 2002; O'Leary,
2004), Reduced technology risks (Andresen et al., 2002), ...
COA 7
Growth management
Build cost leadership (Shang und Sheddon, 2002), Increased market share (Andresen et al., 2002), Leverage Size (O'Leary, 2004), Revenue increases
through product differentiation (Schumann, 1992), ...
COA 8
Creating/defending
competitive
advantages
Enable the organization to catch up with competitors (Mirani and Lederer, 1998), Improved relations with external parties that are neither customers,
competitors nor suppliers (Gammelgard et al., 2006), Negating existing entry barriers (Parsons, 1983; Schulze, 2009), Creating new entry barriers (Parsons,
1983; Schulze, 2009), ...
COA 9
Improved integration
and information flow
Improved communication (Gammelgard et al., 2006), Make use of extensive user feedback (Riggins, 1999), Fewer information bottlenecks (Andresen et al.,
2002), Enabling easier access to information (Gregor et al., 2006), Smoother work flow (Vanlommel and Brabander, 1975), Business integration (Weill and
Broadbent, 1998), Information processing efficiency (Parker et al., 1988), ...
COA 10
Impoved employee
satisfaction and
performance
Greater employee involvement in business management (Shang and Seddon, 2002), Increased employee satisfaction with better decision making tools
(Shang and Sheddon, 2002), Satisfied employees for better employee service (Shang and Sheddon, 2002), Creativity (Mooney et al., 1996), ...
COA 11
IT-Investment costs
Acquisition and implementation costs (Anselstetter, 1985), Personnel costs for training and instruction (Anselstetter, 1985), indirect investment costs
(Schulze, 2010), …
COA 12
Time savings in
daily business
operations
Labour time saving (Kesten et al., 2007), Fewer phone calls (Anselstetter, 1985), Fewer letters (Anselstetter, 1985), …
HR 1
Staff reductions
Save money by avoiding the need to increase the work force (Mirani and Lederer, 1998; Gregor et al., 2006), enhances effectiveness in the job (Gable et al.,
2008), Reduced staff requirement (Andresen et al., 2002), Personnel Reduction (O'Leary, 2004; Petrovic, 1994; Anselstetter, 1984), …
HR 2
Improving employee
skills
Shorten learning time (Shang and Sheddon, 2002), Improved learning and/or increased knowledge of persons in the organization (Gammelgard et al., 2006;
Gregor et al., 2006), learning throug the presence of IS (Gable et al., 2008), Enabling of cross-functional teams (Andresen et al., 2002), ...
Log 1
Reduced inventory
and better inventory
management
Inventory Reduction (O'Leary, 2004; Schumann, 1992), Higher turnover inventory (Vanlommel and Brabander, 1975; Anselstetter, 1984), Íncreasing the
speed of distribution (Parsons, 1983), Improved delivery scheduling (Andresen et al., 2002), …
Log 2
Improved inventory
control
Better inventory management (Shang and Sheddon, 2002), More precise production planning, control and monitoring (Anselstetter, 1984), Improved
operational decisions (Shang and Sheddon, 2002), …
M&S 1
Improved Marketing
& Sales capabilities
Multi-currency capability (Shang and Sheddon, 2002), Improving external access to stock levels and price information (Andresen et al., 2002), Ability to
provide instant price quotations to clients (Andresen et al., 2002), …
M&S 2
Improved customer
retention
Improve customer relations (Gammelgard et al., 2006; Gregor et al., 2006), Customer loyalty (Schulze, 2009; Kesten et al., 2007), ...
M&S 3
Increased Sales
Provide new products or services to customers (Mirani and Lederer, 1998), Increased Sales (Andresen et al., 2002, Weill and Broadbent, 1989), Customer
Responsiveness (O'Leary, 2004), …
M&S 4
Time savings in
Marketing & Sales
and product delivery
Sales Automation (O'Leary, 2004), Faster invoicing (Andresen et al., 2002), Easily find the best offer (Schumann, 1992), Faster and more secure checkout
processing (Anselstetter, 1984), …
M&S 5
Leveraging
marketing and sales
capabilities as
competitive
advantages
Improved company image (Andresen et al., 2002), Easier decision making for buyers due to improved evaluation of sources of materials (Porter and Millar,
1985), Better marketing information (Vanlommel and Brabander, 1975), More detailed market analyses (Anselstetter, 1984), …
M&S 6
Improved sales
management
More precise sales planning, control and monitoring (Anselstetter, 1984), More precise assortment analysis (Anselstetter, 1984), Faster and more cost-
effective information on the success of marketing measures (Schumann, 1992), ...
Ops 1
Improved production
processes
Reduced construction time (Andresen et al., 2002), Manufacturing performance (Shang and Sheddon, 2002), improved outcomes or outputs (Gable et al.,
2008), Reducing operating costs (Gregor et al., 2006), Throughput (Mooney et al., 1996), …
Ops 2
Improved product
and production
quality
Quality improvement (Shang and Sheddon, 2002; Kesten et al., 2007), Higher degree of standardization of operations (Vanlommel and Brabander, 1975),
Contribute to high quality (Parsons, 1983), …
Proc 1
More efficient
procurement of
materials
Improved supplier relations (Gammelgard et al., 2006), Procurement Cost Reduction (O'Leary, 2004), Faster response to supplier quotations (Andresen et
al., 2002), Cost reduction in the area of raw materials (Vanlommel and Brabander, 1975; Anselstetter, 1984), …
Proc 2
Strengthening the
companies position
towards suppliers
Better supplier selection (Anselstetter, 1984), Strengthening negotiating power with suppliers (Bartsch, 2015), …
Ser 1
Improved quality
and delivery of
customer services
(Gammelgard et al., 2006), Better customer service (Anselstetter, 1984), Providing customized product or services (Shang and Sheddon, 2002), Improved
focus on client requirements (Andresen et al., 2002), Better service to customers (Vanlommel and Brabander, 1975; Anselstetter, 1984), Establish 24 × 7
customer service (Riggins, 1999), Contribute to superior customer service (Parsons, 1983; Shang and Sheddon, 2002; Schumann, 1992)
TD 1
Improved IT-
Infrastrucutre
support
Save money by reducing system modification or enhancement costs (Mirani and Lederer, 1998), Mainframe or hardware replacing (Shang and Sheddon,
2002), Provide the ability to perform maintenance faster (Mirani and Lederer, 1998), Integration of new functions (Baumöl and Ickler, 2008), Increasing
system stability (Kesten et al., 2007), ...
TD 2
Imporved R&D and
Life Cycles
Continuous improvement in system process and technology (Shang and Sheddon, 2002),
Allow other applications to be developed faster (Mirani and
Lederer, 1998), Speeded up by product life cycle by shortening the development process (Parsons, 1983; Mooney et al., 1996), Making new businesses
technologically feasible (Porter and Millar, 1985), ...
Figure 6: IT Value Framework.
ICEIS 2021 - 23rd International Conference on Enterprise Information Systems
298
5 DISCUSSION AND
IMPLICATIONS
Although, the meaning of the IT business value is
agreed upon in literature (Melville et al., 2004; De-
varaj and Kohli, 2003; Mooney et al., 1996), its de-
composition to detailed and measurable atomic im-
pacts of the IT system remains either undescribed or
varies strongly across existing literature. Hence, we
provide decision makers with an IT value framework
with possible IT system related impacts and exem-
plary references for the structured assessment of IT
impacts. The framework is customizable to a specific
IT investment situation. A proper IT business value
assessment requires for IT- and company-specific im-
pacts (Brynjolfsson and Hitt, 2003). However, the IT
value framework is neither IT- nor company-specific
so that it requires further customization. Neverthe-
less, the IT value framework allows for a more com-
prehensive IT business value assessment as it contains
more information in a (more) structured form as de-
cision makers usually attempt when applying rules
of thumb (Schniederjans et al., 2010). While exist-
ing IT value catalogs only incorporate impacts from a
single existing catalog (Samulat, 2015; Gregor et al.,
2006; Riggins, 1999; Bartsch, 2015), we draw on 32
value catalogs with a total of 957 impacts and pro-
pose a hierarchy to aggregate the impacts to a single
root value (level 1). With our IT value framework
we aim at aligning the different connotations of the
IT impacts in existing value catalogs (Melville et al.,
2004). During the coding we deviate from the au-
thor’s classification of impacts. O’Leary for example,
categorizes some impacts as intangible (e.g. customer
responsiveness, cost reduction) (O’Leary, 2004) that
we coded as tangible as KPIs exist to economically
measure them. There exist further alternatives for the
aggregated values besides the business units. Below
the business unit level, several clusters are concerned
with the competitive positioning (e.g. Proc 2, COA
4, COA 8) or the organizational capabilities to ex-
ploit future potentials (M&S 1, COA 6). These aggre-
gations may also serve as aggregated values in cus-
tomized versions of the framework. We provide an
overview of the existing literature on IT impacts and
provide decision makers with additional exemplary IT
impacts and references. The framework can be used
both for the identification of impacts a priori to an
IT investment decision and during the project imple-
mentation for the controlling of impact achievement
(Sch
¨
utte et al., 2019).
Due to the changing role of IT and the progress
(DeLone and McLean, 2003) from the early 1970s
until today, existing catalogs must be viewed criti-
cally. While (Anselstetter, 1984) for example high-
lights the reduction of paperwork as a main IT busi-
ness value, more recent catalogs focus on capabilities
enabled by introducing future IT systems (Melville
et al., 2004; Kurniawan et al., 2016). IT systems have
developed from the support of human actors to a high
level of automation in many industries. This develop-
ment needs to be considered when dealing with gen-
eral impacts extracted from IT value catalogs. Ap-
plying our IT value framework or IT value catalogs
in general, decision makers must pay attention that
specific atomic impact are only included in one im-
pact category. Otherwise, a possible double account-
ing would distort the IT business value assessment
(Bartsch, 2015). Although our sample of 32 IT value
catalogs results in a total of 957 impacts, we do not
raise a claim for completeness, as our systematic liter-
ature review was rather narrow compared to vague ter-
minology on value catalogs. Thus, we started our lit-
erature research on major IT business value (and Ger-
man equivalent) literature and focused on forward and
backward search (Webster and Watson, 2002). Be-
cause of our focus on scientific literature, we excluded
practitioner contributions on IT value catalogs and did
not include additional impacts not mentioned in prior
research. As indicated in the scientific approach sec-
tion (Section 3), we reached substantial results for the
coding of the business unit and direction dimension
but only achieved fair results for the performance fo-
cus and time of occurrence. The coders disagreed on
the performance focus of impacts such as “Creating
competitive advantage” (Gregor et al., 2006), “Create
service excellence” (Gregor et al., 2006), or Alter-
ing the product lifecycle” (Parsons, 1983). It seems
that these dimensions require for further characteris-
tics as a differentiation between operational and man-
agement level is difficult. For the dimension time of
occurrence an additional characteristic indicating the
quality of the IT system as enabler for future impacts
may be more comprehensive (Gable et al., 2008).
Nevertheless, we argue that the independent coding
of five experts with a Fleiss’ Kappa of 0.35 is still a
valid result (Landis and Koch, 1977). While recent
research generally suggest Krippendorffs alpha (Nili
et al., 2017), Fleiss’ Kappa is expected to provide sim-
ilar results for the specifications of our coding (Landis
and Koch, 1977) while being much more adaptable to
the tools for the statistic evaluation (VBA) (Nili et al.,
2017). Kappa statistics may also be subject to a para-
dox in which a strong agreement between the coders
is reflected by a disproportionately low index, which
has to be taken into account during the analysis. The
rather complex coding scheme and the large amount
of codes increases the probability for coding errors
A Literature-based Derivation of a Meta-framework for IT Business Value
299
(Campbell et al., 2013). We tried to minimize the cog-
nitive difficulty for the coders by training, providing
a coding manual (Nili et al., 2017), and conducting
the coding in multiple stages (Jourdan et al., 2008;
Neuendorf, 2002). However, this circumstance must
also be considered during our analysis. Once the in-
tercoder reliability has been calculated, the question
arises as to what constitutes an acceptable reliabil-
ity level. While most reliability measures, e.g. per-
center agreement, require a high level of agreement,
Kappa values can be accessed by more liberal criteria
due to their relatively conservative indices (Lombard
et al., 2002). Thus, we adopted the agreement mea-
sures by Landis and Koch, which of cause represent
an arbitrary division (Landis and Koch, 1977). How-
ever, they provide fixed measures against which we
can benchmark our Kappa values to access the reli-
ability of our coding. Even more importantly those
agreement measures allow us to better identify deviat-
ing understandings of the IT impacts and analyze such
coding variation (Olson et al., 2016). Those findings
could then be integrated into our IT value framework
to account for different perspectives on IT impacts.
6 CONCLUSION
The IT business value on the highest level of abstrac-
tion is an agreed upon term in literature. However, its
decomposition and assessment on a detailed level of
atomic impacts is often not described. We propose to
hierarchically decompose the IT business value to an
assessable and atomic level via aggregated impacts,
atomic impacts and questions. For assessing the ex-
pected IT business value of an IT investment there al-
ready exist 32 IT value catalogs including 957 possi-
ble impacts for IT that partially differ in denomina-
tion and definition. The classification of 682 atomic
IT impacts results in 29 clusters of atomic impacts
that can be aggregated to a company’s business units
as aggregated values. The meta IT value framework
further provides exemplary impacts and further liter-
ature for assessing each of the atomic impacts more
specifically. The contribution of this paper is to pro-
vide a comprehensive meta-framework of IT impacts
that takes into account all the key aspects identified
earlier. This allows a holistic IT impact assessment to
be performed in any practical context, which was not
possible with previous frameworks. We have deliber-
ately chosen the perspective of key business functions
to guide practitioners, but other perspectives may be
considered in future papers.
Another important avenue for future research is
the further operationalization of atomic and exem-
plary impacts with guiding questions, making them
configurable for specific IT investments decisions and
industries. As this research focuses on the atomic
impacts within existing values catalogs ignoring the
specifics and peculiarities of the catalogs itself, fu-
ture research may investigate the IT system- and
company-specifics of these catalogs. Additionally, as
we solely rely on impacts from existing IT value cat-
alogs taken from the literature, future research should
also integrate practitioner sources and may also in-
corporate additional impacts derived from IT projects.
These additional impacts can reflect current trends in
IT system development and incorporate state of the art
processes. In addition, the IT value framework should
be applied in practice to get insights into, for exam-
ple, whether the abstraction of IT business values is
sufficient. This evaluation will be the next step in our
research.
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