Comparing Traditional and Electronic Business
Models of the Music Industry: A Content Analytical
Steininger, Dennis M., Business School, University of Mannheim, Germany
Hölz, Julian, Business School, University of Mannheim, Germany
Veit, Daniel J., Business School, University of Mannheim, Germany
The aim of this study is to carve out similarities and differences between the value propositions
and associated financial aspects of electronic and traditional business models in the music
industry. The business model concept is particularly suited for the comparison of electronic and
traditional forms of business through shifting the focus from competing firms to competing
networks of capabilities. Using an established business model framework and five human coders,
we apply content analysis to a sample of secondary data on music industry business models. The
investigated sample size is over 150,000 words for our entire project. To our knowledge this is the
first study to empirically elaborate on the topic. Our results underline the role of e-business as an
incubator for change and innovation. Electronic business models focus on reducing search and
acquisition costs and enabling customer co-creation. However, both traditional and electronic
business models stress the importance of realizing economies of scale in order to attain sustainable
E-Business, Business Models, Components, Music, Content Analysis
Corresponding author may be contacted via:
E-Mail: steininger AT bwl.uni-mannheim.de
Phone: +49 (0)621-181-3083
The Internet being one of the most influential technological innovations of the last hundred years
(Battisti, Canepa, & Stoneman, 2009) has dramatically affected the way information can be
produced, shared and diffused over the globe (Afuah & Tucci, 2003; Kotha, 1998). Such changes
are a challenge especially to publishers such as for books, videos or music. They need to counter
the uprising challenges through adapting their business logic. The business model concept is seen
as being a tool for visualizing such adaptations of business logic and business configuration to an
online context in their entirety (Osterwalder, Pigneur, & Tucci, 2005). Now that publishers have
reacted to digitization and adjusted their businesses, it is important to understand how they
approach these challenges and how their configuration differs from traditional business models.
This will enable further evaluation of the ‘improvements’ that have been made by publishers and
their resulting outcomes.
We focus on the case of the music industry since it is largely impacted by the surge of the Internet
and digitization and offers a large variance of traditional and new business models. The emergence
of such new business models triggered by the technological progress (e.g. Apple iTunes) – some in
conflict, others in coexistence with the traditional business models – makes it well-suited for our
research objective (e.g. Bhattacharjee, Gopal, Marsden, & Sankaranarayanan, 2009):
What are the specific characteristics of electronic business models compared to traditional
business models in the music industry?
We apply rigorous procedures of content analysis to secondary data with a sample size of 153,059
words to investigate on these differences in the music industry. Therefore, an established business
model framework is used as the coding scheme and five human coders are employed. The
remainder is structured as follows: We introduce foundations for the study regarding electronic
business and business models in the second part since clear definitions are needed as a basis for
further investigation. The methodology and quality measures are introduced in the next part using
a process model. Results and their discussion follow and we conclude with a summary and hints to
further advance research on the topic.
2 Foundations of Electronic Business and the
Business Model Concept
While early research in this field (e.g. Timmers, 1998) did not yet make the difference between e-
commerce and e-business and used the terms synonymously (Viehland, 2000) subsequent research
has focused on distinguishing them. In many publications this results in a differentiating view on
internal and external transactions which contradicts the initial insight of an increasing integration
of global processes, transactions and networks of companies or even whole economies (Porter,
2001). Thus another and by far the most widespread understanding is considered stating that e-
commerce forms a part of e-business. Hence, we adopt the following definition for this article:
“[E-Business] includes not just the buying and selling of goods and services, but also servicing
customers, collaborating with business partners, and conducting electronic transactions within an
organization” (Turban, McKay, Marshall, Lee, & Viehland, 2008).
Looking at what differentiates e-business from traditional business Laudon and Traver (2011)
identified eight unique features of e-business such as ubiquity because it abolishes geographical or
temporal constraints for doing business or universal standards facilitating the exchange of
information around the world. This shows that e-business is more than just the electronic version
of selling and buying goods and services. It also includes new sources of value creation such as
collaborative content as well as the formation of new participants and networks thanks to lower
interaction costs. The possibilities of modern Information and Communication Technology (ICT)
create virtual markets that are larger than traditional markets and promise great profits but might
also play by different rules. Amit and Zott (2001) review traditional theories for value creation.
Based on these they identify four primary sources of value creation in e-business. The total value
created in a transaction corresponds to the sum of all participants’ individual values. Unlike
traditional companies, e-business firms profit from higher efficiency, increased information speed
and lower information asymmetry, resulting in lower search, communication and transaction costs.
Extended markets mean extended product ranges and economies of scale for large producers
leading to lower prices or higher margins. The technology also facilitates the offering of horizontal
or vertical complementaries as well as new combinations of online and offline retail channels
(Brandenburger & Nalebuff, 1998). Features for customization and personalization of goods and
services as well as for interactivity and network effects provide opportunities to increase switching
costs and create customer lock-in (Hagel & Armstrong, 1997; Katz & Shapiro, 1985; Katz,
Shapiro, Public, & Affairs, 1983). The Internet and consequently e-business as well represent new
radical technologies and have brought up and enables new business ideas (novelty) (Battisti et al.,
2009; Srinivasan, Lilien, & Rangaswamy, 2002). Companies such as Apple (à-la-carte MP3 store)
or Facebook (social marketing) are vivid examples of innovative business and revenue models that
heavily rely on these new technologies and did not exist before in traditional industries.
In order to create such value, certain success factors for competitive advantage have been found
indispensable such as forming alliances with providers of complementary products or securing
unique and proprietary resources like patents (Porter, 2001; Srinivasan et al., 2002). Benefits of e-
business identified by several researchers are an improved cost-revenues-ratio due to efficiency
gains through streamlined processes, better flow of information, and the possibility to enter new
markets due to lower market entry barriers such as decreased distribution costs and new marketing
channels (Al-Debei & Avison, 2010). Among the consequences are the increased complexity, pace
and mutability of modern e-business compared to traditional forms of business (Al-Debei &
Avison, 2010; Pateli & Giaglis, 2004). Furthermore the Internet is an open system. While e-
business claims to enable a lot of opportunities for the creation of competitive advantages, it is
clear that the technological progress destroys many of the classic competitive advantages (Porter,
2001). This calls for a modification of business models to cope with these challenges. The
business model concept may prove to be a valuable tool in confronting these challenges by shifting
the focus from the traditional view of different competing firms in a certain industry to competing
networks of capabilities or value webs (Amit & Zott, 2001; Hedman & Kalling, 2003; Osterwalder
et al., 2005).
The business model concept can provide valuable information and the ability to react quickly to
changing business environments (Al-Debei & Avison, 2010). Moreover the business model
approach may help to improve communication and a common understanding among the different
stakeholders of a company by outlining their determining elements and relationships (Gordijn &
Akkermans, 2001). The process of conceptualization and visualization can thereby help support
choosing or improving business logic (Osterwalder & Pigneur, 2002).
Osterwalder et al. (2005) identify three differing levels of abstraction in articles on business
models (cf. Figure 1). First, the business model concept is seen as a meta-model on a very abstract
and theoretical level. Second, the business model can be used as a scheme for describing
businesses in a comparable manner highlighting their common characteristics in taxonomies that
are either general or industry-specific. Third, authors take actual companies and decompose their
specific logic of value generation, i.e. their model for doing successful and sustained business
(Osterwalder et al., 2005). In this study, the term business model will be used on the conceptual
level by selecting an existing framework for analyzing the two types of electronic and traditional
business models and comparing their characteristics. We choose the framework of Osterwalder et
al. (2005) over Al-Debei and Avison’s (2010) four elements since it is composed of nine building
blocks that allows a more detailed analysis.
Fig. 1 Business Model Concept Hierarchy (adapted from: Osterwalder et al. (2005))
3 Method and Research Design
This study draws on the existing body of academic literature regarding the differences of
traditional and electronic business models. Thus a technique is needed that enables an objective
and systematic analysis of written documents, i.e. text (Gephart, 1993). Content analysis is one of
several methods that can be used to analyze text (Hsieh & Shannon, 2005). It is “[a] research
technique for the objective, systematic, and quantitative description of the manifest content of
communication or text.” (Berelson, 1952).
Compared to other methods content analysis offers the advantage of being unobtrusive
(Krippendorff, 2004; Morris, 1994). As the focus of study lies on fixed forms of communications
that have already happened neither the sender nor the receiver are being influenced by the
scientist, as would be the case for direct methods such as interviews or questionnaires (Weber,
1990). Its unobtrusiveness makes content analysis especially useful for IS and management
research because direct access to top-managers for scientific observations is usually denied
(Morris, 1994). We take the position of Duriau et al. (2007), Insch et al. (1997) and Weber (1990)
seeing content analysis as a method that should comprise both quantitative and qualitative
elements. This paper’s analysis is of a quantitative nature in a way that it makes use of statistical
tests and methods to evaluate the results. However, we take a qualitative approach and our focus is
not limited solely to single words but tries to capture meanings with regard to context. Rules for
coding are based on existing business model theory and deductively formulated before coding
(Insch et al., 1997). We choose a structured procedure for investigation (cf. Figure 2) to perform
our analysis (cf. Duriau et al., 2007; Insch et al., 1997; Weber, 1990).
Fig. 2 Content Analysis Procedure (adapted from: Insch et al. (1997), Morris (1994) and Weber
The first step of identifying a research question has already been addressed in the introductory
section. The second step of selecting research material is critical to the success of this study. The
safest way to avoid bias on the results is to analyze entire populations. It is evident that this would
be a hopeless endeavor for our topic. Instead, we choose a both manageable and broad sample that
allows for generalization of results (Kassarjian, 1977) since it is not our purpose to derive a
representative sample of the existing body of literature but rather creating a sample that is qualified
answering our specific research question (Krippendorff, 2004). Following these thoughts we create
a theoretical sample (Glaser & Strauss, 1967) with articles on business models in the music
industry. We define the theme as our unit of analysis in the third step since it is the dimension
where issues, characteristics, impacts, values, beliefs and attitudes can be investigated best
In the fourth step the coding categories are developed following the research question. Based on
the four perspectives of the balanced scorecard (Kaplan & Norton, 1992), the coding scheme
features four main pillars and nine building blocks (cf. Table 1), which are deduced from the work
of Osterwalder (2004), Osterwalder and Pigneur (2002), and Osterwalder et al. (2005). Their
components represent the third level categories (L3-categories). We choose these building blocks
over the ones proposed by Al-Debei et al. (2010) since they are on a more detailed level of
abstraction. On the third level (L3-categories), Customer Interface characteristics are adopted from
Osterwalder and Pigneur (2010). We introduce some adjustments since it is more reasonable for
our research purposes to differentiate market types (mass market, niche market, etc.) which are
combinations of socio-demographic and geographical criterions proposed by Osterwalder (2004).
Alike, we consider coding for different types of Distribution Channels (own channel, partner
channel) more feasible. If reasonable the L3-categories are further decomposed (L4-categories)
ending up with 49 final L3/L4 attributes. All categories are provided with anchor examples
(Osterwalder, 2004; Osterwalder & Pigneur, 2010; Osterwalder et al., 2005) for disambiguation
during the coding process. Five coders are trained iteratively in a one-day workshop and the
scheme is further adjusted for clarity until a satisfying level (>0.75) of inter-rater reliability
(Holsti, 1969) is achieved and validity of the coding scheme is verified (Insch et al., 1997; Veit &
Parasie, 2010). We finalize our study by coding every word of the entire sample through at least
two coders for reliability reasons and analyzing the results depicted in the next section.
Table 1 Category Deduction Process - Level 2 (adapted from: Osterwalder (2004))
& Norton, 1992)
Pillar (Level 1
Create, improve and
offer value to the
A Value Proposition is
an overall view of a
company's bundle of
products and services
that are of value to the
Target, establish and
The Target Customer is a
segment of customers a
company wants to offer
A Distribution Channel
is a means of getting in
touch with the customer.
describes the kind of link
a company establishes
between itself and the
activities and manage
A capability is the ability
to execute a repeatable
pattern of actions that is
necessary in order to
create value for the
The Value Configuration
arrangement of activities
and resources that are
necessary to create value
for the customer.
A Partnership is a
between two or more
companies in order to
create value for the
8. Cost Structure
The Cost Structure is the
representation in money
of all the means
employed in the business
9. Revenue Model
The Revenue Model
describes the way a
company makes money
through a variety of
Drawn from our sample of over 150,000 analyzed words, we find the music industry literature to
comprise 1,238 coded occurrences of business model characteristics for Electronic Business
Models (EBM) or Traditional Business Models (TBM) yielding an overall reliability of 0.76.
Table 2 Codings and Reliabilities by Categories
Coder 1 or 2
Coder 3,4 or 5
Comparing the results, a great imbalance is found between EBM and TBM concerning the number
of codings: Whereas 362 matching codings go on EBM, only 106 are counted for TBM. Table 2
reveals the dominance of ‘Value Proposition’ (VP) over ‘Financial Aspects’ (FA). Similarly, the
numbers of absolute codings prove well distributed, with PL falling behind. Concerning the
‘Financial Aspects’, codings are distributed between ‘Revenue Model’ (RM) and ‘Cost Structure’
(CS) with a ratio of approximately 2 to 1. Among the level-two categories, the most matching
codings by far in EBM were found for the ‘Reasoning’ dimension of the ‘Value Proposition’,
followed by 67 for ‘Revenue Streams’ and 57 for ‘Life Cycle’. TBM draws a similar picture,
though on a smaller scale. 34 matching codings were found for VP, followed by 25 for LC and 20
for RM. In a next step the texts’ thematic priorities were explored. The analysis revealed that the
articles elaborated more on EBM than on TBM.
Fig. 3 Proportions of Coded L1-Categories
Figure 3 demonstrates that for EBM 15% of the text was coded, thereof the majority of 11% as VP
and 4% as FA. VP codings make up 3% and FA only 1%. All datasets generated less codings for
TBM. Arithmetic mean is 52 (median of 51) for EBM and 15 (median of 12) for TBM. The
concentration of EBM codings in proves much higher. For TBM M7 with 13% in VP and M2 with
2% in FA lead the way. Here the arithmetic mean for EBM is 17% (median of 14%) and for TBM
it is 5% (median of 4%).
Fig. 4 Level 3 Occurrences for Value Propositions
In a next step the L1-categories are broken down to the third level. This will show on what aspects
of the value proposition selected data has focused and how value propositions are used to generate
revenues. As this study performs a meta-analysis based on existing research, the more authors talk
about a certain aspect the more important it must be for the business model (Krippendorff, 2004).
Figure 4 features the matching codings per L3-category. Analysis of the reasoning subcategory
reveals that value propositions are assessed differently in EBM and TBM. 32% were classified as
‘Accessibility’ in TBM whereas the same attribute only represents 16% of EBM codings in this
group. Codings for ‘Effort Reduction’ increased the most from TBM and EBM. They now add up
to 39% of EBM codings. ‘Customization’ now accounts for the second largest share with 28 out of
113 matching codings. In EBM 25 matching codings go on the ‘Consumption’ phase. ‘Creation’
and ‘Appropriation’ are closely together with 15 and 14 codings respectively. For TBM, ‘Creation’
was the dominating attribute with 11 out of 25 codings. The value level codings demonstrate an
increasing effort for innovation. ‘Innovation’ accounts for 50% of TBM codings and 71% of EBM
codings. Regarding the pricing part, ‘Free’ amounts for a little more than half of all codings for
EBM. Figure 5 depicts codings for the L3-category on Financial Aspects. Results for EBM consist
mostly of codings for ‘Economies of Scale’ followed by fixed and variable costs. Concerning the
revenue streams subcategory ‘Selling’ accounts for more than two out of three codings for TBM. It
is still among the most often mentioned revenue streams in EBM with 26 out of 67 codings. But
‘Licensing’ is attached even more importance, rising from 2 in TBM to 28 codings in EBM.
Entire sample articles, coding scheme and codings can be attained through the first author of the
We explore the co-occurrences between the respective attributes in a final step. Results show that
several co-occurrences are found between the attributes for level 3. Strongest co-occurrences for
EBM are found between ‘Advertising’ and ‘Free’ (c-index of 0.52), between ‘Customization’ and
‘Creation’ (c-index of 0.43), ‘Consumption’ and ‘Innovation’ (c-index of 0.3) and ‘Consumption’
and ‘Accessibility’ (c-index of 0.26). In TBM the strongest relationship exists between ‘Economy’
and ‘Me-too Value’ (c-index of 0.5) followed by ‘Customization’ and ‘Innovation’ (c-index of
0.43), ‘Creation’ and ‘Accessibility’ (c-index of 0.38), and ‘Creation’ and ‘Customization’ (c-
index of 0.36). These relations must be treated with care as absolute numbers of co-occurrences
Fig. 5 Level 3 Occurrences for Financial Aspects
Our results reveal remarkable differences in the business model components “Value Proposition”
and “Financial Aspects”. Value Propositions seem to have been of higher importance than
assessing financial aspects of business models. This is interesting all the more because an analysis
over time reveals the rapidly decreasing amount of codings for “Value Proposition” and the
increasing amount for the “Financial Aspects” category, especially for EBM. Apparently research
initially focused on the opportunities for new value propositions enabled by the electronic channel
but now shifts attention towards the financial foundations and consequences. In EBM even more
importance is placed on effort reduction, i.e. the reduction of search, evaluation and acquisition
costs. In contrast to TBM the literature stresses the performance aspect meaning that EBM offers a
lot of possibilities to improve product or service performance. With regard to the value level the
research, attention has shifted from excellence to innovation. Innovative imitations must also be
regarded. They are defined as new combinations of already existing business practices or
offerings. This importance is backed by the fact that ‘Innovation’ tended to co-occur with
‘Accessibility’ and ‘Innovative Imitation’ with ‘Customization’. Obviously the Internet and the
opportunities of electronic business have fueled the drive for innovation in this respect. Great
importance is also placed on innovative offerings. It is well established that the Internet and
especially peer-to-peer networks have exerted great pressure on the music industry which has
apparently boosted the urge for innovative business models and value propositions. However a
sustainable value proposition is yet to come. Following the current stream of research it may
incorporate free music offerings. Research suggests numerous models where a combination of free
music with advertising and merchandising offers new revenue streams. ‘Advertising’ and ‘Free’
also co-occur heavily.
Regarding the reasoning attribute a change of power is witnessed. So far the aspect of making
music accessible for people has been the key to the music industry. This aspect still plays an
important role and is definitely facilitated through the global reach of the Internet. Two other
essential ideas of EBM seem to be effort reduction and customization. Electronic business models
concentrate on reducing search and acquisition costs and open the chance of customizing music.
This means compiling individual albums, playlists or albums for streaming and download. This
matches the findings for the value life cycle. A fourth of the EBM codings fall on the creation
stage where customization or customer co-creation takes place. This explanation is supported by
the strong co-occurrence of ‘Customization’ and ‘Creation’. Still the dominating stage in the value
life cycle is consumption when the value proposition is actually used. Following the co-occurrence
between ‘Consumption’ and ‘Accessibility’ the distribution of music to the consumers might still
play an important role here.
Regarding the price level the music industry yields very interesting findings as two thirds of the
codings in this subcategory address offerings without direct financial compensation by the
customer. Record labels and artists are apparently trying to find innovative business models where
the music itself is still at the heart of the value proposition, but no longer the determining revenue
stream. Again the pressure by illegal file-sharing networks or streaming websites seems to be a
driver for this radical change.
With regard to the required infrastructure, economies of scale are mentioned very often. Scale and
market power have traditionally been very important in the oligopolistic music industry where a
few large record companies effectively dominated the market. The Internet may change this but
still scale economies are crucial in order to realize lasting profits in an increasingly fragmented and
competitive market where music is becoming a commodity. On the income side licensing and
advertising have appeared as new streams of revenues. This is due to the move from selling
predefined albums and physical CDs towards customized playlists and free streaming offers.
Selling is still important as well but has lost its exclusivity. Yet findings for this subcategory are
sparse and must be interpreted with care.
We conducted an extensive content analysis of scholarly articles about the music industry to find
differences of electronic and traditional business models regarding their value propositions and
associated financial aspects. The investigated sample of the project comprised over 150,000
analyzed words which were coded by five human coders. Our analysis yields a satisfactory overall
reliability of 0.76. Comparison of results showed considerably more codings for electronic
business models (EBM) than for traditional business models (TBM). Evaluation and interpretation
of data revealed that articles of the industry focused clearly on the value proposition category. The
business models are deeply influenced by the opportunities of electronic business and a bulk of
innovative offerings is witnessed with the potential for significant improvement if not revolution
of existing practices. The main concern of TBM was to make music accessible to consumers. In
EBM it is being replaced by reducing search and acquisition costs and enabling customer co-
creation. Often this goes along with free distribution of music financed by advertising. However,
certain similarities between EBM and TBM were observed as well such as the importance of lean
cost structures and especially the realization of economies of scale. Interestingly enough no high-
end pricing strategies at all were described in the literature. Quite the opposite, business models
stressed providing lower prices than the competition. Despite the high degree of innovation in e-
business, apparently very few businesses are able to offer truly unique value to customers and
capitalize on this competitive advantage. Obviously the Gordian knot of innovation and
profitability in e-business has not yet been cut through. This means that research on electronic
business models has to advance as well. Given the scope of this work focusing the music industry,
it may be of interest to other researchers to apply the developed coding scheme to other industries.
Furthermore, an increase in coder capacities may allow incorporating all four pillars of the
Business Model Framework into the analysis. Incorporation of the Customer Interface and the
Infrastructure Management would certainly provide valuable insights into the relations between all
four business model segments.
Afuah, A., & Tucci, C. L. (2003). A Model of the Internet as Creative Destroyer. IEEE
Transactions on Engineering Management, 50(4), 395–402.
Al-Debei, M. M., & Avison, D. (2010). Developing a Unified Framework of the Business Model
Concept. European Journal of Information Systems, 19(3), 359–376.
Amit, R., & Zott, C. (2001). Value Creation in E-Business. Strategic Management Journal, 22(6-
7), 493–520. doi:10.1002/smj.187
Battisti, G., Canepa, A., & Stoneman, P. (2009). E-Business Usage Across and Within Firms in the
UK: Profitability, Externalities and Policy. Research Policy, 38(1), 133–143.
Berelson, B. (1952). Content Analysis in Communication Research. New York: Free Press.
Bhattacharjee, S., Gopal, R. D. M., Marsden, J. R., & Sankaranarayanan, R. (2009). Re-tuning the
Music Industry – Can They Re-Attain Business Resonance? Communications of the
ACM, 52(6), 136–140.
Brandenburger, A., & Nalebuff, B. (1998). Co-Opetition: 1. A Revolutionray Mindset That
Combines Competition and Cooperation ; 2. The Game Theory Strategy That’s Changing
the Game of Business. New York: Doubleday.
Duriau, V. J., Reger, R. K., & Pfarrer, M. D. (2007). A Content Analysis of the Content Analysis
Literature in Organization Studies: Research Themes, Data Sources, and Methodological
Refinements. Organizational Research Methods, 10(1), 5–34.
Gephart, R. P. J. (1993). The Textual Approach: Risk and Blame in Disaster Sensemaking. The
Academy of Management Journal, 36(6), 1465–1514.
Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for
Qualitative Research. Transaction Publishers.
Gordijn, J., & Akkermans, H. (2001). Designing and Evaluating E-Business Models. Intelligent
Systems, IEEE, 16(4), 11–17. doi:10.1109/5254.941353
Hagel, J., & Armstrong, A. (1997). Net Gain: Expanding Markets Through Virtual Communities.
Boston: Harvard Business School Press.
Hedman, J., & Kalling, T. (2003). The Business Model Concept: Theoretical Underpinnings and
Empicical Illustrations. European Journal of Information Systems, 12(1), 49–59.
Holsti, O. R. (1969). Content Analysis for the Social Sciences and Humanities. Reading: Addison-
Hsieh, H.-F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis.
Qualitative Health Research, 15(9), 1277–1288.
Insch, G. S., Moore, J. E., & Murphy, L. D. (1997). Content Analysis in Leadership Research:
Examples, Procedures, and Suggestions for Future Use. Leadership Quarterly, 8(1), 1–
Kaplan, R. S., & Norton, D. P. (1992). The Balanced Scorecard - Measures That Drive
Performance. Harvard Business Review, 70(1), 70–79.
Kassarjian, H. (1977). Content Analysis in Consumer Research. Journal of Consumer Research,
Katz, M. L., & Shapiro, C. (1985). Network Externalities, Competition, and Compatibility.
American Economic Review, 75(3), 424–440. doi:http://www.aeaweb.org/aer/
Katz, M. L., Shapiro, C., Public, W. W. S. of, & Affairs, I. (1983). Network Externalities,
Competition, and Compatibility. Princeton: Woodrow Wilson School, Princeton
Kotha, S. (1998). Competing on the Internet: The Case of Amazon.com. European Management
Journal, 16(2), 212–222.
Krippendorff, K. (2004). Content Analysis: An Introduction to its Methodology (2nd ed.).
Thousand Oaks: Sage Publications.
Laudon, K. C., & Traver, C. G. (2011). E-Commerce 2011: Business. Technology. Society (7th
revised ed.). Prentice Hall International.
Morris, R. (1994). Computerized Content Analysis in Management Research: A Demonstration of
Advantages and Limitations. Journal of Management, 20(4), 903–931.
Osterwalder, A. (2004). The Business Model Ontology - A Proposition in a Design Science
Approach. University of Lausanne, Lausanne. Retrieved from
Osterwalder, A., & Pigneur, Y. (2002). An E-Business Model Ontology for Modeling E-Business.
BLED 2002 Proceedings (pp. 17–19).
Osterwalder, A., & Pigneur, Y. (2010). Business Model Generation: A Handbook for Visionaries,
Game Changers, and Challengers.
Osterwalder, A., Pigneur, Y., & Tucci, C. L. (2005). Clarifying Business Models: Origins, Present,
and Future of the Concept. Communications of the Association for Information Systems,
Pateli, A. G., & Giaglis, G. M. (2004). A Research Framework for Analysing eBusiness Models.
European Journal of Information Systems, 13(4), 302–314.
Porter, M. E. (2001). Strategy and the Internet. Harvard business review, 79(3), 62–79.
Srinivasan, R., Lilien, G. L., & Rangaswamy, A. (2002). Technological Opportunism and Radical
Technology Adoption: An Application to E-Business. Journal of Marketing, 66(3), 47–
Timmers, P. (1998). Business Models for Electronic Markets. Electronic Markets, 8(2), 3–8.
Turban, E., McKay, J., Marshall, P., Lee, J., & Viehland, D. (2008). Electronic Commerce: A
Managerial Perspective. Upper Saddle River: Prentice Hall.
Veit, D. J., & Parasie, N. (2010). Common Data Exchange Standards: Determinants for Adoption
at the Municipal Level. Proceedings of the 16th Americas Conference of Information
Systems (AMCIS), August 12-15 (pp. 1 – 10). Presented at the 16th Americas Conference
of Information Systems (AMCIS), Lima, Peru.
Viehland, D. W. (2000). Critical Success Factors for Developing an E-Business Strategy. AMCIS
2000 Proceedings (pp. 911–915).
Weber, R. P. (1990). Basic Content Analysis (2nd ed.). Newbury Park: Sage Publications.
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