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Open Source Software and Open Data Standards as a form of Technology Adoption: a Case Study


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The process of technology adoption has been studied for long time to give instruments to evaluate the best strategies to ease the introduction of technology. While the main research on Open Source Software focuses mainly on the development process, team collaboration and programmers motivations, very few studies consider Open Source Software in this context. In this paper, we provide an overview of literature on technology adoption that can be useful to relate the concepts. We then provide a case study with historical data about file generation and usage across time to evaluate the adoption of Open Source Software and Open Data Standards in the specific case provided. Full Text at Springer, may require registration or fee
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Open Source Software and Open Data
Standards as a form of Technology
Adoption: a Case Study
Bruno Rossi, Barbara Russo, and Giancarlo Succi
CASE (Center for Applied Software Engineering) of the Free University
of Bolzano-Bozen,
Piazza Domenicani, 3, 39100 Bolzano-Bozen
WWW home page:
Abstract. The process of technology adoption has been studied for long time
to give instruments to evaluate the best strategies to ease the introduction of
technology. While the main research on Open Source Software focuses mainly
on the development process, team collaboration and programmers'
motivations, very few studies consider Open Source Software in this context.
In this paper, we provide an overview of literature on technology adoption that
can be useful to relate the concepts. We then provide a case study with
historical data about file generation and usage across time to evaluate the
adoption of Open Source Software and Open Data Standards in the specific
case provided.
1 Introduction
Open Source Software (OSS) has acquired recently a growing popularity in the
software market. The free availability of the source code and the freedom to modify
and redistribute the source code are the main characteristics – among the ones that
characterise OSS - that are at the basis of its growing popularity. Particularly in the
governmental setting, these characteristics have increased the interest towards OSS.
The Interoperable Delivery of European e-Government Services to public
Administrations, Businesses and Citizens organisation (IDABC), identifies five
aspects that can be of interest for organisations willing to adopt OSS [13]:
political aspects, concepts related to governmental tasks, goals and
responsibilities like freedom and equality, digital endurance, digital heritage and
stimulation of innovation;
economical aspects, related to cost reduction and market health;
social aspects, in particular for education and team work support;
managerial and/or technical aspects, in particular quality of the products in
terms of stability and reliability, transparence, support and security;
legal aspects, related to licensing and liability.
All these different point of views make the adoption of OSS inside organisations
as a very appealing option.
2 Bruno Rossi, Barbara Russo, and Giancarlo Succi
Furthermore, a concept sometimes overlooked, but frequently associated to OSS
is the one of Open Data Standards (ODS). ODS are a subcategory of data standards.
Data standards, provide a standardised way to store different typologies of data, and
emerge generally in two different ways, as output of an evolution of the market (so
called de facto standards) or after being recognised by a standardisation committee
(de jure standards). The distinction that is of our interest, is between Open and
Proprietary data standards. In this sense, many different definitions of ODS exist, we
would like to propose the definition given by the Danish Board of Technology in
2002 [5]:
An open standard is accessible to everyone free of charge (i.e. there is no
discrimination between users, and no payment or other considerations are
required as a condition of use of the standard);
An open standard of necessity remains accessible and free of charge (i.e.
owners renounce their options, if indeed such exist, to limit access to the
standard at a later date, for example, by committing themselves to openness
during the remainder of a possible patent's life);
An open standard is accessible free of charge and documented in all its
details (i.e. all aspects of the standard are transparent and documented, and both
access to and use of the documentation is free);
As can be noted the importance of open standards lies, in particular, in the
avoidance of the commitment to a single supplier for the support of the format.
In this paper we review the adoption process of Open Source Software (OSS)
and Open Data Standards (ODS) in an empirical case, by analysing the file
generation and usage process in a single Public Administration. In this early work,
we start to insert the empirical case studied in the context of technology adoption
and lock-in.
We first introduce two main concepts that have been discussed extensively in
literature: technology adoption and lock-in. While the review we provide is not
strictly related to OSS, it is necessary for the overview of the next section about
technology adoption studies related to OSS. In the final part, we provide the details
of the case study and the main results obtained.
2 Technology adoption and lock-in
Technology adoption, diffusion and acceptance research bases its foundation on
the early work of Everitt Rogers, in the book titled Diffusion of Innovations [17].
Rogers interest lies in studying the diffusion process that characterises technology
adoption. In his seminal work, technology adopters are categorised according to the
phase in which they make the adoption decision. The main distinction is among
innovators, early adopters, early majority, late majority and laggards. In particular,
the author models the diffusion as an S-shaped curve characterised by an initial
Open Source Software and Open Data Standards as a form of Technology Adoption: a case study 3
adoption speed and a later growth rate. The claim is that different technologies will
lead to different adoption patterns.
As a parallel with other fields, one that is frequently reported, is the comparison
with the ecological succession concept delineated by several biologists [4]. In brief,
ecological succession studies the interaction and survival of new biological species
inside an existing ecosystem. The similarity with the success or failure of new
technologies is evident, as reported by Windrum [20].
Fichman & Kemerer [12] report two critical factors that influence the technology
assimilation process: knowledge barriers and increasing returns.
The first effect relates to the effort necessary to acquire the necessary knowledge
and skills to properly adopt a certain technology. This effect leads to what are known
as knowledge barriers [2,12].
The second phenomenon, reports that the adoption of certain technologies is
subject not only to supply-side benefits due to economies of scale [18], but also to a
demand-side effect called increasing returns effect [1]. The effect leads to an
increase of the utility in adoption for each successive adopter, based on the number
of previous adopters. Arthur [1] goes further in this analysis, claiming that economy
can become locked-in to a technological path that is not necessarily efficient, not
possible to predict from usual knowledge of supply and demand functions, and not
easy to change by standard tax or subsidy policies. In this sense, it may not be
possible to easily switch from a certain technology once a certain critical level of
adoption has been reached.
In this context, the lock-in literature emerges. As defined by Shapiro & Varian
[18], a situation of lock-in occurs when consumers are constrained by given past
buying decisions due to the presence of high switching costs. Such situation is
commonly associated to the concept of technology and standard adoption: some
researchers in particular, as already stated, claim that it may lead to the adoption of
an inferior technology [1,6]. Three concepts are highly correlated with the term lock-
in and are very often cited in the literature: increasing returns, network effects and
path dependence. We will discuss all three concepts, while examining the
importance of lock-in.
The study of lock-in has its foundations in the pioneering work on increasing
return theory performed by David [6] and Arthur [1]. The theory evaluates the
behaviour of markets from the demand point of view. In particular, Arthur [1]
classifies three types of markets, depending on the demand side behaviour, as
providing decreasing, constant and increasing return. The interest in the
distinguishing characteristics of increasing return goods, is that they manifest an
increase in utility in adoption for each successive adopter, based on the number of
previous adopters. In this sense, it may not be possible to easily switch from a certain
technology once a certain critical level of adoption has been reached. Two critics in
particular have been made to the model. The first is that the model assumes that all
competing technologies are available at the time of the agent decision [20]. The
second one is that scarce weight is given to large-scale events, such as government
decisions, the focus is mostly on the market impact [14,20].
4 Bruno Rossi, Barbara Russo, and Giancarlo Succi
The problem of lock-in in the IT market has been further investigated by Shapiro
and Varian [18]. They define a lock-in as the situation in which a customer would
incur in high switching costs should s/he decide to move from a brand of technology
to another. They classify lock-in in seven different types, according to the
distinguishing switching cost:
1. Contractual Commitments. Breaking a contract can lead to
compensatory damages.
2. Durable Purchases. Once a durable commitment has been made, a
replacement can be costly.
3. Brand-specific Training. Once training has been performed with a
specific environment, it may be expensive to switch to another provider.
4. Information and Databases. The large number of information stored in
one format, makes the switching costly.
5. Search Costs. The search and evaluation of a new supplied needs a
commitment of resources and time.
6. Specialized Suppliers: relying on a single supplier makes a change
7. Loyalty Programs: By switching to another supplier, all the benefits
gained by the loyalty programs are lost.
Another concept that is often associated with lock-in, is that of path dependence,
a term that describes the dynamics of the system. Multiple suboptimal paths exist,
and due to successive and connected choices and events, users may reach a position
in which they would not like to be considering the situation ex-post. The concept of
path dependence we are referring here is borrowed from economics; the term has
different meanings in other sciences such as biology or mathematics. Many studies
claim that path dependence may easily lead to the adoption of an inferior technology,
even in presence of users maximising their utility [11].
To present an overall view, we must note that other economists seem to give less
importance to the concept of lock-in, claiming that the lack of empirical evidence
seems to demonstrate that the effect of path dependence is mostly overestimated
[16]. Users will always have the force to move to a better solution without the
intervention of external forces when they get “locked in” to a position. To support
their claims, authors stress that the case studies usually reported in order to support
the lock-in theory seem not to be adequate [15].
3 OSS as technology adoption
There are not many studies that evaluate OSS as a form of technology adoption.
An interesting overview is given in [7], where following the “context for change
methodology” defined in [8], factors that lead adoption process are categorised in
technological, organisational and environmental.
Open Source Software and Open Data Standards as a form of Technology Adoption: a case study 5
Bitzer and Schroder [3], analyse the innovation performance of open source and
proprietary, showing the results of the competition between OSS and proprietary
software. The focus is more on innovation that on the adoption process itself.
Economides [10] studies the incentives that lead to platform innovation. A case
study between Linux and Windows is provided.
4 A case study of OSS migration
To provide some real data about a concrete case of the OSS and ODS adoption
process, we consider the experimentation that took place during an experimental
migration from Microsoft Office to in one medium-size European
Public Administration. The users involved were 100.
The data collection process has been executed by means of two software:
PROM (PRO Metrics), a non-invasive monitoring tool [19], to evaluate in
particular the usage of and Microsoft Office. Metrics of interest
were the number of documents handled and time spent per single document. The
software has been running during all weeks of the experimentation, permitting
to acquire objective data on the experimentation. With a non-invasive impact,
the software gives the opportunity to register for every document the time spent,
the name of the document and the functions used. This last feature is at the
moment still limited, but can give useful insights of the different patterns of
usage between the two solutions.
FLEA (FiLe Extension Analyzer) is a software that permits to collect
information about the data standards available on the target system. It has been
used to perform a scan of the data standards available on the users’ drives. Data
collected are the type of extension, date of creation, date of last access, size of
the file, and for particular extensions also information about the macros
The experimentation has been performed with the following experimental protocol:
Installation of The version of the suite installed was 1.1.3. Various version of the Microsoft Office suite were
present in the target systems.
Installation of the PROM agent to monitor the software adoption level.
Scan of the file servers with the FLEA software.
Training on the suite, mostly performed to show how to perform
the same task in the new office automation environment.
Various questionnaires on the attitude towards Open Source Software submitted
to users.
Support to users through forums and hot-lines.
6 Bruno Rossi, Barbara Russo, and Giancarlo Succi
5Main results
We report the main result from the analysis of data standards and software usage.
In table 1, we show the total number of all the data standards collected at the
beginning of the experimentation, divided per category.
As we can see, some data standards are largely predominant in their category,
like DOC (Microsoft Word) documents, or XLS documents (Microsoft Excel). The
former accounts for 91,21% of the files in the category, while the latter 99,92%. Also
the ZIP format is largely dominant, with a percentage of 98,16%. If we use the
Shapiro & Varian categorisation of switching costs and consider the information &
databases category, we can evaluate that a complete migration and adoption of the
platform can be costly, due to the effort necessary required by the conversion of a
large amount of documents.
We further studied the evolution of file generation across time, in figure 1 we
show the generation of DOC and XLS documents, from the data collected the more
representative for proprietary formats. In figure 2, we show the evolution of file
creation for PNG files, an ODS to store image data.
Table 1: Total number of data standards detected by the data collection
Text Documents Graphic Format Database
310648 BMP 6908 DB 3361
36259 DB
PDF 12518 JPEG 83143 MDA 10
PS 656 PNG 2173 MDB 2170
RTF 6185 SVG 0 Music
SXW 160 TGA 0 MP3 967
11061 RA/RM/RAM 4
10422 Draw ing Movie
Spreads heets DWG 36051 AV
47 DX
411 MOV 227
XLS 60267 SXD 9 MPEG 77
Presentations Web SW
2541 CSS 1370
27 HTML 16057
Comp r es s io n XHTML 0
ACE 1 Data Exchange
ARJ 37 CSV 64
GZ 19 DTD 6
43 SDX
0 XML 483
ZIP 5338
Open Source Software and Open Data Standards as a form of Technology Adoption: a case study 7
While the figures are given for representational purposes, we may note an
interesting phenomena that emerges by analysing data of many data standards, that is
the creation process of documents is very consistent once a critical level of adoption
has been reached. Once a large set of base documents is constituted, the creation
process somehow fades, as the activity of users will be constituted in small part also
by the modification of already available documents.
Figure 2: Evolution of PNG files created by users during years, on x-axis time in days,
on y-axis number of files generated
Figure 1: Evolution of DOC and XLS files created by users during years, on x-axis
time in days, on y-axis number of files generated
8 Bruno Rossi, Barbara Russo, and Giancarlo Succi
While OSS research community list mostly in studying the team and collaboration
dynamics of the development process, OSS and ODS have still to be well studied as
a form technological innovation. We overviewed some of the lock-in and technology
adoption literature that may be useful in this sense and some recent works that
manage to insert OSS in this context. We further considered ODS as an important
and often overlooked instrument that has to be associated to OSS when considering
its adoption. We studied as a case study, the evolution of a migration to OSS in the
office automation field, considering data standards as a sign of the presence of
possible lock-in phenomena. The data analysed show the commitment of the
organisation under study to proprietary data formats, in particular in the office
automation category.
Future work will consist in putting in a more rigorous framework the evaluation of
lock-ins situations by means of the study of ODS evolution. In particular, we are
planning to put the data collected in the lock-in model proposed by Brian Arthur [1].
7 Limitations
The study is still preliminary As a major limitation of the work, we must cite that the
modification and creation dates reported on the Microsoft Windows system are not
always precise and can sometimes be misleading. An example of this behaviour has
been reported also in [9], where authors were interested in collecting various
statistics about file usage of different file systems.
This work has been partially supported by COSPA (Consortium for Open Source
Software in the Public Administration), EU IST FP6 project nr. 2002-2164. We
would like to acknowledge in particular all the Public Administrations that took part
to the project. Acknowledgments also go to all the users involved, participants to the
experimentation, technical personnel, and supervisors: without their constant effort
and their availability this study would not have been possible.
9 References
[1] Arthur, W.B. (1989). Competing Technologies, Increasing returns, and lock-in by
historical events. Economic Journal, 99, 116-131.
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[2] Attewell, P. (1992). Technology Diffusion and Organizational Learning: The
Case of Business Computing. Organization Science. 3(1), 1-19.
[3] Bitzer, J. and P. J. H. Schroder, (2003). Competition and Innovation in a
Technology Setting Software Duopoly. DIW Discussion Paper No. 363.
[4] Clements, F.E., (1936). Nature and the structure of the climax, Journal of
Ecology, 24, pp.252-284.
[5] Danish Board of Technology. (2002). Definition of open standards. Retrieved,
14th January 2007, from
[6] David, P., A. (1985). Clio and the economics of QWERTY, American Economic
Review, 75 (2), May.
[7] Dedrick, J., West, J., (2004). An Exploratory Study into Open Source Platform
Adoption, HICSS, p. 80265b, Proceedings of the 37th Annual Hawaii International
Conference on System Sciences (HICSS'04) - Track 8, 2004.
[8] Depietro, Rocco, Edith Wiarda and Mitschell Fleischer, (1990). The Context for
Change: Organization, Technology and Environment, in Tornatzky, Louis G. and
Mitchell Fleischer, The processes of technological innovation. Lexington, Mass.:
Lexington Books, 1990, pp. 151-175.
[9] Douceur J. and Bolosky W. (1999). A Large-Scale Study of File-System
Contents, Proceedings of the 1999 ACM Sigmetrics Conference, pp. 59–70, June
[10] Economides, N., Katsamakas, E. (2006). Linux vs. Windows: A comparison of
application and platform innovation incentives for open source and proprietary
software platforms, in Juergen Bitzer and Philipp J.H. Schroeder (eds.) The
Economics of Open Source Software Development, Elsevier Publishers, 2006
[11] Farrell, J. and Saloner, G, (1985). Standardisation, compatibility and innovation,
Rand Journal of Economics, 16, pp.70-83.
[12] Fichman, R. G., & Kemerer, C. F. (1997). The Assimilation of Software Process
Innovations: An Organizational Learning Perspective. Management Science. 43(10),
[13] IDABC, The Many Aspects of Open Source. Retrieved, 14th January 2007, from
10 Bruno Rossi, Barbara Russo, and Giancarlo Succi
[14] Islas, J., (1997). Getting around a lock-in in electricity generating systems: the
example of the gas turbine, Research Policy, pp.49-66.
[15] Liebowitz, S. J. and Margolis, S. E. (1990). The fable of the keys. Journal of
Law and Economics 33: 1-26.
[16] Liebowitz, S. J. and Margolis, S. E. (1995a). Path dependence, lock-in and
history. Journal of Law, Economics and Organization 11: 205-226.
[17] Rogers, E. (1995). Diffusion of Innovations. N.Y.: The Free Press.
[18] Shapiro, C., & Varian H.R. (1999). Information Rules: A Strategic Guide to the
Network Economy. Harvard Business School Press.
[19] Sillitti A., Janes A., Succi G., Vernazza T. (2003). Collecting, Integrating and
Analyzing Software Metrics and Personal Software Process Data, in proceedings of
EUROMICRO 2003, Belek-Antalya, Turkey, 1 – 6 September 2003
[20] Windrum, P., (2003). Unlocking a lock-in: towards a model of technological
succession, in Applied Evolutionary Economics: New Empirical Methods and
Simulation Techniques, P.P. Saviotti (ed.), Cheltenham: Edward Elgar.
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The chapter analyzes and compares the investment incentives of platform and application developers for Linux and Windows. It finds that the level of investment in applications is larger when the operating system is open source rather than proprietary. The comparison of the levels of investment in the operating systems depends on reputation effects and the number of developers. It also develops a short case study comparing Windows and Linux and identifying new directions for open source software research. The chapter analyzes the incentives to invest in application software and an operating system under two different software ecosystems: one based on an open source operating system, such as Linux, and the other based on a proprietary operating system, such as Microsoft Windows.
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The burden of organizational learning surrounding software process innovations (SPIs)---and complex organizational technologies in general---creates a "knowledge barrier" that inhibits diffusion. Attewell (Attewell, P. 1992. Technology diffusion and organizational learning the case of business computing. Organ. Sci. 3(1) 1--19.) has suggested that many organizations will defer adoption until knowledge barriers have been sufficiently lowered; however, this leaves open the question of which organizations should be more likely to innovate, even in face of high knowledge barriers. It is proposed here that organizations will innovate in the presence of knowledge barriers when the burden of organizational learning is effectively lower, either because much of the required know-how already exists within the organization, or because such knowledge can be acquired more easily or more economically. Specifically, it is hypothesized that organizations will have a greater propensity to initiate and sustain the assimilation of SPIs when they have a greater scale of activities over which learning costs can be spread (learning-related scale), more extensive existing knowledge related to the focal innovation (related knowledge), and a greater diversity of technical knowledge and activities (diversity). An empirical study using data on the assimilation of object-oriented programming languages (OOPLs) by 608 information technology organizations strongly confirmed the importance of the three hypothesized factors in explaining the assimilation of OOPLs.
'. . . this book aims at a double objective: contributing to the specific issues dealt with in the chapters, and proposing an agenda for the development of an evolutionary economics methodology, which the chapters support but as examples and as tests. On both these respects the book can be considered a success. The individual contributions constitute a good sample of the very frontier of their respective fields.'- JASSS Review of Applied Evolutionary Economics. The expert contributors to this book examine recent developments in empirical methods and applied simulation in evolutionary economics. Using examples of innovation and technology in industry, it is the first book to address the following questions in a systematic manner: Can evolutionary economics use the same empirical methods as other research traditions in economics? Is there a need for empirical methods appropriate to the subject matter chosen? What is the relationship between appreciative theorising, case studies and more structured empirical methods? What is the relationship of modelling and simulation to empirical analysis?
This article discusses the model of the diffusion of innovations and describes this model’s key variables. Diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system. An innovation is an idea, practice, or object that is perceived as new by an individual or other unit of adoption.
The dominant explanation for the spread of technological innovations emphasizes processes of influence and information flow. Firms which are closely connected to pre-existing users of an innovation learn about it and adopt it early on. Firms at the periphery of communication networks are slower to adopt. This paper develops an alternative model which emphasizes the role of know-how and organizational learning as potential barriers to adoption of innovations. Firms delay in-house adoption of complex technology until they obtain sufficient technical know-how to implement and operate it successfully. In response to knowledge barriers, new institutions come into existence which progressively lower those barriers, and make it easier for firms to adopt and use the technology without extensive in-house expertise. Service bureaus, consultants, and simplification of the technology are examples. As knowledge barriers are lowered, diffusion speeds up, and one observes a transition from an early pattern in which the new technology is typically obtained as a service to a later pattern of in-house provision of the technology. Thus the diffusion of technology is reconceptualized in terms of organizational learning, skill development, and knowledge barriers. The utility of this approach is shown through an empirical study of the diffusion of business computing in the United States, reporting survey and ethnographic data on the spread of business computing, on the learning processes and skills required, and on the changing institutional practices that facilitated diffusion.
Getting an innovation adopted is difficult; a common problem is increasing the rate of its diffusion. Diffusion is the communication of an innovation through certain channels over time among members of a social system. It is a communication whose messages are concerned with new ideas; it is a process where participants create and share information to achieve a mutual understanding. Initial chapters of the book discuss the history of diffusion research, some major criticisms of diffusion research, and the meta-research procedures used in the book. This text is the third edition of this well-respected work. The first edition was published in 1962, and the fifth edition in 2003. The book's theoretical framework relies on the concepts of information and uncertainty. Uncertainty is the degree to which alternatives are perceived with respect to an event and the relative probabilities of these alternatives; uncertainty implies a lack of predictability and motivates an individual to seek information. A technological innovation embodies information, thus reducing uncertainty. Information affects uncertainty in a situation where a choice exists among alternatives; information about a technological innovation can be software information or innovation-evaluation information. An innovation is an idea, practice, or object that is perceived as new by an individual or an other unit of adoption; innovation presents an individual or organization with a new alternative(s) or new means of solving problems. Whether new alternatives are superior is not precisely known by problem solvers. Thus people seek new information. Information about new ideas is exchanged through a process of convergence involving interpersonal networks. Thus, diffusion of innovations is a social process that communicates perceived information about a new idea; it produces an alteration in the structure and function of a social system, producing social consequences. Diffusion has four elements: (1) an innovation that is perceived as new, (2) communication channels, (3) time, and (4) a social system (members jointly solving to accomplish a common goal). Diffusion systems can be centralized or decentralized. The innovation-development process has five steps passing from recognition of a need, through R&D, commercialization, diffusions and adoption, to consequences. Time enters the diffusion process in three ways: (1) innovation-decision process, (2) innovativeness, and (3) rate of the innovation's adoption. The innovation-decision process is an information-seeking and information-processing activity that motivates an individual to reduce uncertainty about the (dis)advantages of the innovation. There are five steps in the process: (1) knowledge for an adoption/rejection/implementation decision; (2) persuasion to form an attitude, (3) decision, (4) implementation, and (5) confirmation (reinforcement or rejection). Innovations can also be re-invented (changed or modified) by the user. The innovation-decision period is the time required to pass through the innovation-decision process. Rates of adoption of an innovation depend on (and can be predicted by) how its characteristics are perceived in terms of relative advantage, compatibility, complexity, trialability, and observability. The diffusion effect is the increasing, cumulative pressure from interpersonal networks to adopt (or reject) an innovation. Overadoption is an innovation's adoption when experts suggest its rejection. Diffusion networks convey innovation-evaluation information to decrease uncertainty about an idea's use. The heart of the diffusion process is the modeling and imitation by potential adopters of their network partners who have adopted already. Change agents influence innovation decisions in a direction deemed desirable. Opinion leadership is the degree individuals influence others' attitudes