Applications of the REST Framework to Test Technology Activation
in Different ICT Domains
Antonio Ghezzi, Andrea Cavallaro, Andrea Rangone and Raffaello Balocco
Department of Management, Economics and Industrial Engineering, Politecnico di Milano,
Via Lambruschini 4B, 20156 Milan, Italy
Keywords: REST Model, Application, Technology Activation.
Abstract: As innovations based on technology multiply, research on technology diffusion evolves both downstream –
i.e. covering adoption and use – and upstream – i.e. focusing on the antecedents of diffusion. In the latter
domain, the study from Ghezzi et al. (2013) proposed to revisit traditional technology diffusion theory to
include the concept of “technology activation”, which investigates the external determinants influencing the
introduction of technology-based innovations. Such determinants are included in the Regulation,
Environment, Strategy, Technology (REST) framework. This study aims at proposing an application of the
REST framework to the Mobile Video Calls and the MiniDisc industries. This application is meant to
further validate the framework and test the validity of the concept of technology activation in different ICT
domains.
1 INTRODUCTION
Technology diffusion as a process is inherently
multifaceted, and develops both horizontally along
time, and vertically along a number of diffusion
determinants affecting each of its steps (Abernathy
and Utterback. 1978; Antoniou and Ansoff, 2004).
While several studies (e.g. see Lanzolla and
Suarez, 2007) have focused on the analysis and
investigation of what occurs after technology is
adopted, discussing the determinants of technology
use, a literature gap is found with reference to what
comes before diffusion. Indeed, few studies have
focused on the preliminary determinants leading
technology-based innovations’ uptake (Loch and
Huberman, 1999).
The seminal work from Moore (1991) goes in
this direction, by modifying the traditional
technology adoption lifecycle to underscore a “stage
and gate” approach in the process of technology
diffusion: “crossing the chasm” from early adopter
to mass market requires a number of determinants to
be positively met. Recently, the work from Ghezzi et
al. (2013) puts forward the proposal that the
traditional technology diffusion theory should be
revisited, to explicitly include the concept of
“technology activation”, which investigates the
external, non-user determinants influencing the
introduction of technology-based innovations. Such
determinants are included in the Regulation,
Environment, Strategy, Technology (REST)
framework (Ghezzi et al. 2013), which is proposed
as a theoretical tool to integrate the benefits from
both diffusion theory and strategy analysis model
(Okazaki, 2005), and which is later applied to the
Mobile Location Based Services market to assess the
market’s activation status.
This study hence aims at proposing an
application of the REST framework to the Mobile
Video Calls and the MiniDisc industries. This
application is meant to further validate the
framework and test the validity of the concept of
technology activation in different ICT domains.
2 THE REGULATION-
ENVIRONMENT-STRATEGY-
TECHNOLOGY (REST)
MODEL
The REST model proposed in Ghezzi et al. (2013a)
assumes that market activation and technology
activation are influenced by four macro-
determinants: Regulation, Environment, Strategy,
and Technology (Figure 1).
87
Ghezzi A., Cavallaro A., Rangone A. and Balocco R..
Applications of the REST Framework to Test Technology Activation in Different ICT Domains.
DOI: 10.5220/0004889400870091
In Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS-2014), pages 87-91
ISBN: 978-989-758-029-1
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
In the following paragraphs the four building blocks
of the R-E-S-T Model and their set of constitutive
core determinants are described.
Figure 1: The Regulation-Environment-Strategy-
Technology conceptual model.
2.1 Regulations
The Regulation macro-determinant deals with the
overarching framework of laws, policies,
recommendations, licenses (R1) and standards (R2)
(Farrell and Saloner, 1985; West, 2004) governing
the evolution of technology on an industry or
geographical basis. It affects the sphere of influence
and strategic choices regarding technologies made
by players both on the supply side,– i.e. firms
supplying the new technology – and the demand side
– i.e. consumer or business adopters of the new
technology.
2.2 Environment
The Environment macro-determinant consists of the
external, largely exogenous social, political,
economic and financial environment influencing the
new technology’s native business area. It includes
the following determinants.
Environmental phenomena (E1): the exogenous
phenomena and trends that impact market conditions
– e.g. the convergence of the IT,
Telecommunications and Media industries (Peppard
and Rylander, 2006). This factor can influence the
market structure, the players involved, and the
“technology pool” of products, services and
solutions that can be bundled, transformed or
developed to bring about a technology innovation.
Economic situation (E2): the overall economic
climate related to the new technology market. It
affects suppliers’ ability and intention to innovate
and launch a new technology, influencing cash flow,
R&D spending, advertising spending, etc., as well as
affecting users’ purchasing resources.
Influence of neighbouring markets (E3): the
impact of neighbouring – complementary or
substitutive – market trends on the new
technology’s market. A business area is influenced
and cross-fertilized by the conditions that
characterise related markets, which in turn can affect
technology activation status.
2.3 Strategy
Based on the widely-held assumption that strategy
design is intimately related to technology and
technological innovation (Brandenburger and
Nalebeuf, 1996), the Strategy macro-determinant
implies the Strategic landscape and structure that
characterise the market in which the technology-
based innovation is offered, and the Strategic
choices made by providers of the new technology’s
products or services. It is further divided into four
determinants.
Value Network structure (S1): the structure of
the industry, assessed in terms of a set of “static”
variables (i.e. network focal firm; critical network
influences; structural equivalence; structural holes;
revenue streams) and “dynamic” phenomena (lock-
in and lock-out effects; and learning races) (Gulati et
al., 2000; Dell’Era et al., 2013). It affects the way
value-creating activities related to technology
activation are allocated to different providers ,
responsible for organising and linking them in an
efficient and effective configuration.
Nature of competition (S2): the technology
innovation providers’ strategic attitude towards other
parties operating in the business area, which ranges
from aggressive contrast (Porter, 1980) to a hybrid
interaction process combining competition and
cooperation – or “co-opetition” (Shapiro and Varian,
1999). It influences the overall approach towards
technology innovation, whether it is consortium-led
or single entity-driven, and whether it enables or
inhibits technology activation.
Strategic Commitment (S3): the interest of
incumbent or challenger technology innovation
providers towards investing in the new technology’s
development and building a market – i.e. whether or
not innovation is perceived as a strategic priority. It
is a supply-side determinant that affects the pace of
technology evolution and commercialization.
Business Model and offer (S4): the way the
business configured around the new technology is
organised to create value for customers, and to
capture a share of such value, in terms of: the
ICEIS2014-16thInternationalConferenceonEnterpriseInformationSystems
88
efficiency and appeal of the technology and its
related services, and both direct and indirect
associated costs (Timmers, 1998; Teece, 2010;
Ghezzi, 2013). It is a further supply-side activation
determinant that in turn affects several modifiers of
technology diffusion as identified by TAM-derived
models (e.g. new technology’s price/performance
ratio, user and firm expected benefits, and user
experience).
2.4 Technology
The Technology macro-determinant addresses the
technology landscape in which the innovative
technology is embedded and derived, consisting of
the past and present technological choices made by
the players involved, and represented in the
following determinants.
Infrastructure (T1): the underlying enabling
technology infrastructure – e.g. traffic networks in
ICTs, Energy or Transport industries – and its core
functionalities and characteristics – e.g. capacity or
bandwidth, availability, reliability, localization
(Ghezzi et al., 2010).
Device (T2): the tools and instruments employed
by individual or business users to exploit the new
technology, and their key features – e.g. cost,
compatibility, interoperability, performance, user
experience.
Enabling services and applications (T3): the
constellation of systems, services and applications –
e.g. creation, integration and publishing tools,
management and delivery platforms, storage systems
– built on the infrastructure and enabling the new
technology’s stages of development, translation into
a set of services, and commercialization.
3 EMPIRICAL ASSESSMENT
The empirical assessment method chosen for this
study is historical analysis, i.e. the process of
assembling, critically examining, and summarizing
the records of the past (Gottschalk, 1969).
Information gathered from published sources about
the commercialization of the technological
innovations related to Mobile Video Calls was
analyzed and employed to test the importance of a
technology activation and market activation analysis
through the REST model.
In the first years of the 21
st
century, Mobile
Network Operators were looking for new revenue
generating value added services to make up for
market saturation and shrinking margins. Mobile
video calls soon became a paramount innovative
service among those tentatively launched by
Operators: some players, like H3G Italy, even made
this the core of their offer and market penetration
strategy. However, as the customer base and
revenues never took off, it became apparent that
such service and the related innovation had inherent
criticalities. Such criticalities could not have been
spotted by traditional models on technology
adoption, as they did not only refer to user
characteristics: they largely depended on the supply-
side surrounding ecosystem.
At the strategic level, the mobile value network
was neither structured not ready to support the
service, since the key players (e.g. device
manufacturers and content providers) lacked the
necessary commitment, as Operators provided them
with no incentive to craft a surrounding offer that
could have boosted the service demand; in addition
to this, the business model and revenue model built
around the service was too expensive or simply
unappealing. At the same time, technology
determinants were not activated: the network
infrastructure would have needed an expansion to
support the increased data traffic, but no player was
willing to overinvest in an innovation whose uptake
was far from being certain; the share of customers
owning a smartphone was too little at that time, and
even such devices of devices enabling video calls
had neither the characteristics nor the performance
to ensure a satisfactory customer experience. In
addition, no complementary application or service
were bundled to video-calls.
This report clearly shows that the market for
video calls was not activated when Operators first
launched their services: a lack of technology
activation hence determined the resounding market
failure they experienced.
A technology activation analysis employing the
REST model would have probably highlighted the
supply-side hurdles and pitfalls, thus sparing
Operators expensive investments.
Similar considerations and conclusions could be
drawn for other failed innovation such as MiniDisc
format, where a lack of market activation at multiple
sides covered by and unified in the REST model
(including: strategic agreements; value network;
business model; network of complementary
technology and products; ancillary services and
applications) prevented the rise of this potentially
interesting technology. At the strategic level, in fact,
there was no strategic agreement between two of the
main competitors (Sony and Philips). While Sony
introduced the MiniDisc technology, Philips focused
ApplicationsoftheRESTFrameworktoTestTechnologyActivationinDifferentICTDomains
89
on the digital compact cassette. Such choice created
marketing confusion. Moreover, MiniDisc had to
face the competition from substitutive products.
Initially when recordable compact disc (CD-R)
became more affordable to consumers, but later the
biggest competition for MiniDisc came from the
emergence of MP3 players.
Figure 2: Application of the REST framework to the
Mobile Video Calls industry.
Figure 3: Application of the REST framework to the
Minidisc industry.
Table 1 summarizes the distribution of
determinants. As can be easily seen, more than a half
of determinants in both industries caused a lack of
market activation.
Table 1: The distribution of determinants in the two
industries.
Enabling
Half-
way
Limiting
Mobile
Video
Calls
5 2 4
Minidisc 4 3 4
4 CONCLUSIONS
Innovation diffusion theory may significantly benefit
from an extension which explicitly considers uphill
determinants acting as a prerequisite or trigger of
adoption. Indeed, this extension would underscore
the inherent relationship existing between the
technological domain and the strategic, regulatory
and environmental ecosystems, where the latter may
severely influence the former’s performance.
Research on technology diffusion should hence be
more tightly connected to that on strategy: in turn,
this would create mutual opportunities for both
literature streams.
In parallel, revisiting the technology diffusion
process to include the activation phase has insightful
implications for entrepreneurs or managers dealing
with technology-based innovations.
Managers could employ the REST framework to
assess a number of issues possibly affecting the
successful launch of their innovation, ranging from
regulation, to external environment, external and
internal strategy analysis, and technological
infrastructure and applications. Thanks to the
analysis of resounding market failures like that of
Mobile Video Calls and the MiniDisc format, this
study shows how a detailed analysis of those
market’s activation status would have spared
significant amounts of resources to the companies
involved. Their poorly planned and short-sighted
eagerness to rush towards a fascinating innovation
led several managers and their companies to
commercial disasters.
This study’s contribution is to provide further
evidence of the REST framework’s validity in
additional ICT industries, thus confirming the REST
framework’s descriptive and normative power.
The study’s limitations mostly lead back to the
methodological approach taken to perform the
empirical analysis, where historical analysis might
show shortcomings in both the recollection and in
the gathering and interpretation of past events.
Future research opportunities lies in the
validation of the framework under scrutiny with
quantitative methodologies, by means of a proper
operationalization of each of its constituting
variables.
REFERENCES
Abernathy, W. J., J. M. Utterback. 1978. Patterns of
industrial innovation. Technology Review 80: 97–107.
Antoniou, P. H., H. B. Ansoff. 2004. Strategic
ICEIS2014-16thInternationalConferenceonEnterpriseInformationSystems
90
Management of Technology. Technology Analysis and
Strategic Management 16, no. 2: 275-291.
Lanzolla, G., F. F., Suarez. 2007. The Role of User
Bandwagon in Information Technology Use, Paper
presented at Università di Bologna, in Bologna, Italy,
April 30th, 2007.
Loch, C. H., B. A., Huberman. 1999. A punctuated
equilibrium model of technology diffusion.
Management Science 45, no. 2: 160 – 177.
Moore, G. A. 1991. Crossing the Chasm: Marketing and
Selling High-Tech Products to Mainstream
Customers. Harper Business Essentials, HarperCollins.
New York, NY.
Ghezzi, A., A. Rangone, R. Balocco. 2013. Technology
diffusion theory revisited: a regulation, environment,
strategy, technology model for technology activation
analysis of mobile ICT. Technology Analysis &
Strategic Management, 25, no. 10: 1223-1249.
Okazaki, S. 2005. New Perspectives on M-Commerce
Research. Journal of Electronic Commerce Research
6, no. 3: 160 – 165.
Farrell, J., G., Saloner. 1985. Standardization,
compatibility, and innovation. Rand Journal of
Economics 16: 70-83.
West, J. 2004. The Role of Standards in the Creation and
Use of Information Systems. Paper presented at the
Workshop on Standard Making: A Critical Research
Frontier for Information Systems, Seattle, WA, 2004,
pp. 314-326.
Peppard, J. R., Rylander. 2006. From Value Chain to
Value Network: an Insight for Mobile Operators.
European Management Journal 24, no. 2: 57–68.
Brandenburger A. M., and B. J., Nalebeuf. 1996. Co-
opetition. New York, NY: Currency.
Gulati R., N., Nohria, A., Zaheer. 2000. Strategic
Networks. Strategic Management Journal 21: 203-
215.
Dell’Era C., Frattini F., Ghezzi A., 2013. The Role of the
Adoption Network in the Early market survival of
Innovations: the Italian Mobile VAS Industry.
European Journal of Innovation Management, Vol. 13,
Issue 1, pp. 118-140.
Porter ME. 1980. Competitive Strategy: Techniques for
Analyzing Industries and Competitors. Free Press:
New York.
Shapiro, C., and H. R., Varian. 1999. Information rules. A
strategic guide to the network economy. Harvard
Business School Press. Boston, MA.
Timmers P. 1998. Business models for electronic
commerce. Electronic Markets 8, no.2: 3-8.
Teece J. 2010. Business Models, Business Strategy and
Innovation. Long Range Planning. 43, no.2-3:172-
194.
Ghezzi A. 2013. Revisiting Business Strategy Under
Discontinuity. Management Decision, Vol. 51, Issue 7,
1326-1358.
Ghezzi A., Balocco R., Renga F., Pescetto P. 2010.
Mobile Payment Applications: offer state of the art in
the Italian market. Info. 12(5): 3-22.
Gottschalk, L. R. 1969. Understanding history: a primer
of historical method. Knopf, New York.
ApplicationsoftheRESTFrameworktoTestTechnologyActivationinDifferentICTDomains
91