International Journal of Business and Management Vol. III, No.

4 / 2015

DOI: 10.20472/BM.2015.3.4.001

THE TECHNOLOGICAL, ORGANIZATIONAL AND

ENVIRONMENTAL FRAMEWORK OF IS INNOVATION
ADAPTION IN SMALL AND MEDIUM ENTERPRISES.
EVIDENCE FROM RESEARCH OVER THE LAST 10 YEARS

ERIND HOTI
Abstract:
This paper relies on the technological innovation adoption literature and uses the
technological-organizational-environmental (TOE) framework to analyze the factors influencing new
information systems (IS) adoption in small and medium-sized enterprises (SMEs). Even though the
TOE framework has not seen much development in the last years, research on the TOE framework
can take a number of directions in the future, because novel contexts of adoption and new
technologies are persistently being developed. This paper undertakes a review of the literature on IS
adoption in SMEs during the last decade (2004 to 2015) and identifies the main variables influencing
the adoption process. In doing so, we try to see if any changes in the patterns of IS adoption from
SMEs are present and look for emerging research topics and gaps in the field of SME and IS
innovation adoption in the last decade.

Keywords:
SME, technology innovation, information systems adoption, technology–organization–environment
framework

JEL Classification: L21, O32, M15

Authors:
ERIND HOTI, European University of Tirana, Albania, Email: erind_hoti@yahoo.com

Citation:
ERIND HOTI (2015). The technological, organizational and environmental framework of IS innovation
adaption in small and medium enterprises. Evidence from research over the last 10 years.
International Journal of Business and Management, Vol. III(4), pp. 1-14., 10.20472/BM.2015.3.4.001

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International Journal of Business and Management Vol. III, No. 4 / 2015

1 Introduction
Small and Medium-sized Enterprises (SMEs) cannot ignore the technological advancements taking
place rapidly. In the knowledge society, firms need to develop competitive advantages based on
adequate and intensive use of information systems (IS), which are essential sources of innovation
and success in today’s market. The innovation orientation of enterprises is an important aspect that
encourages the IS adoption process. SMEs face tremendous challenges in their efforts to pursue
technological innovations and their survival depends often on the use they make of information
systems to develop new organizational models, compete in new markets or enhance their internal
and external communication relationships. IS are considered to be an important and fast growing
technological innovation providing to businesses the opportunity to improve their efficiency and
effectiveness and even gain competitive advantage (Porter and Millar, 1985), (Ives and Learmonth,
1984). Comparing to large businesses, small business have been slow in adopting technological
innovations. Large firms can take greater risks associated with innovation adoption, because they
have more resources and greater economies of scale (Thong, 1999), (Kuan and Chau, 2001), (Zhu
et. al., 2003). It is critical for small businesses to benefit from new IS, because small businesses
constitute the large majority of all business in many economies (Thong Y.L., 1999). The large
number of SMEs reveals their importance as an essential source of jobs. According to Ritchie and
Brindley (2005), SMEs are significant because of their entrepreneurial spirit and adaptive
capabilities and as drivers of economic growth and innovation by fostering competitiveness (Levy
and Powell, 2005). Through their knowledge SMEs are able to innovate on products or processes
that help them create a competitive advantage and generate more profits (Loh and Koh, 2004).
Information systems provide mechanisms for getting access to new market opportunities and
specialized information (Fulantelli and Allegra, 2003). Benefits of SMEs that adopt IS are increased
productivity, increased efficiency of internal business operations and more easily and cheap
connection to external contacts. Other benefits are increased business competitiveness, vertical
integration with other related business, stakeholder and institutions, improved networking with other
parties etc. (Levy and Powell, 2005). According to Stockdale and Standing (2004), the benefits of
participating in e-marketplaces are the product differentiation and supply chain entry. Besides the
positive aspects of IS adaption, employees often refuse to adopt a new technologies because of
the perceived danger of job loss or unwillingness to change their working practices. As a
consequence, SME owners are often reluctant to bring their business through a learning curve
which proves to be difficult, disruptive and costly (Love et al., 2001). One of the major criticisms of
technology adoption research is that adoption is mainly viewed as a dichotomous outcome (either
the innovation is adopted or not adopted). However, the adoption versus non-adoption approach
does not fully address the issue of technology adoption (Hovav et. al., 2004), (Daniel et. al., 2002).
This paper helps to increase understanding why some SMEs choose to innovate their information
systems, while seemingly similar ones facing similar conditions do not.
We investigate the impact of a number of factors, extracted from the technological innovation
literature that influence IS adoption in SMEs. Based on the theoretical background of technological

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innovation, we provide a review and analysis of different articles. These articles are then compiled
in a summary table and sorted according to the methodology, type of research (qualitative or
quantitative) and the context and factors that influence IS adoption in SMEs. An additional
classification is undertaken based on the variables identified from the technology-organization-
environment (TOE). Finally we discuss the observations and include recommendations for future
research.

2 The theoretical background and characteristics of technological innovation

adaption
In this paper we use the technological innovation literature as a theoretical reference. Research
indicates that technologically innovative companies may outperform their competitors (Geroski et.
al., 1993). Technological innovation has been subject of extensive theoretical and empirical studies
and is now widely acknowledged as an important determinant of sustained superior performance
(Blundell et. al, 1999). An innovation is an idea, practice, or object that is perceived as new by an
individual or other unit of adaption (Rogers, 2003, p.12). An innovation in ICT, does not refer only
to a technology renewal, but it refers also to renewal in terms of thought and action (Thong 1999,
p.190). Technological innovation consists of two related but distinct factors:

(1) Finding innovation in existing ICT,

(2) If unsuccessful, deciding to adopt more advanced (ICT) innovations.
On the other hand, the adoption of technological innovations per itself may be described as
consisting of a sequence of 3 stages: initiation, adoption and implementation (Pierce and Delbecq,
1977), (Thompson, 1965). In the initiation stage the information about the technological innovation
is gathered and evaluated. During the adoption stage a decision regarding the adoption of the
technological innovation is made and in the third stage, if the decision goes in favor of the adoption,
the implementation of the technological innovation in the enterprise takes place.
Researchers suggest that there are also some functional parallels between IS adoption and
technological innovation adoption (Thong Y. L., 1999). Four are the dimensions along which the
characteristics of an innovation differ (Poutsma et. al., 1987). We distinguish between product
innovations, process innovations, as well as radical and incremental innovations. Product
innovations involve the development, production and dissemination of new consumer and capital
goods and services. Process innovations improve the production process by introducing new
methods, machines and production systems which apply not only to the traditional definition of
production but also to distribution, data processing and services. IS adoption falls under the
category of process innovation (Poutsma et. al., 1987). Incremental innovations encompass minor
improvements or simple changes in current technology. Contrary to that, radical innovations
represent fundamental and revolutionary changes in technology (Dewar and Dutton, 1986). IS
innovations represents radical innovations. Moreover, innovations may occur because of
technology-push or market-pull. Technology-push implies developing and offering an innovation in

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a matured form in the capital-goods market. The market absorbs the innovation because of the
superiority of the new innovation as well as the pressure and the competing suppliers. In a market-
pull the new technology is developed because of an acknowledged social need. Both, technology-
push as well as market-pull are also influencers of IS adoption (King et. al., 1994). Another
differentiation can be made based on the way in which an innovation takes place. Hereby we
distinguish between planned and incidental innovations. Planned innovations are carried out
according to plan from the business side that aims to control the market through the innovation,
while incidental innovations occur as a specific reaction of a business to a new market demand.
Both approaches apply in the adoption of IS.

Figure 1: Dimensions and characteristics of technological innovations

Dimension Characteristics

Nature of Innovations Process vs. Product

Complexity of Innovations Radical vs. Incremental

Motivation of Innovations Technology-push vs. Market pull

Timing of Innovation Planned vs. Incidental

Source: Own adjustment based on (Rogers E. M., 2010), (Thong, 1999) and (Kuan and Chao, 2001).

3 Literature review
To identify the focus and influencing factors of the adoption of new IS in SMEs, we have performed
a literature review that covers articles published from 2004 to 2014. Literature reviews represent a
well-established method for accumulating existing knowledge within a domain of interest. Abstracts
and contents of 87 articles were carefully read to check for their relevance. The selected articles
were published in scientific journals and conference proceedings. An initial search of the articles
was performed in Google Scholar and ProQuest using the keywords: SME, information systems,
innovation adoption, technology-organization-environment (TOE) framework. The keywords for the
search are used in different combinations. After identifying the relevant literature, only articles
directly addressing IS adoption in SMEs were selected. The selection process was based on the
author, year of publishing, type of study (qualitative or quantitative), type of IS being adopted,
methodology, data, context of the study, focus and influencing factors. We have used a review
approach with explicit procedures and conditions that minimize bias. The analyzed articles are
illustrated in a summary table as illustrated below.

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Figure 2: Review and categorization of articles

Author and
Type of study IS/IT adaption Focus and influencing factors Methods Data and context
Year
relationship between ICT adoption in SMEs and perceived cross sectional survey addressed
(Alam & Noor, Qualitative and IT adoption and usage
benefits & cost, ICT knowledge, external pressure and to the owner and/or manager of 180 SMEs in Malaysia
2009) Quantitative
government support SME
identification of business and organizational factors (such
(Buonanno et. al., questionnaires and interviews 366 companies of any
Quantitative ERP adoption as: business complexity and organizational change)
2005) adressed to top managers size (SMEs & large)
influencing ERP adoption
examiniation of determinant factors of adoption such as:
(Grandon and
Quantitative E-commerce adoption operational support, managerial productivity, and strategic Internet survey of top managers 100 surveys in USA
Pearson, 2004)
decision
B2B E-commerce Literature review, questionnaire
proposing a TOE model of E-commerce adoption and 4 Danish and 4
(Scupola, 2009) Qualitative adaption and and face to face interviews with
implementation Australian SMEs
implementation CEOs
(Ramdani & ERP, CRM, SCM and e- develop a model that can be used to predict which (SMEs) Direct interviews, logistic 102 SMEs in
Quantitative
Kawealek, 2009) procurement adaption are more likely to become adopters of enterprise systems regression Northwest England
Questionnaires, regression, factor
Qualitative and examine what factors are associated with the adoption of E- 193 SMEs in South
(Oh et. al., 2009) E-trade adoptin analysis, cronbach alpha,
Quantitative trade by Korean SMEs Korea
discriminant analysis
survey data were analysed by
(Shiau et. al., development of measures to assess the ERP adoption of
Quantitative ERP adoption structural equation modelling 126 SMEs in Taiwan
2009) SMEs
(SEM)
IT readiness/IT 3 longitudinal case studies,
(Haug et. al. 2011) Qualitative presenting a framework for analyzing 'IT readiness' 3 SMEs
adoption Literature review

ex postevaluation of an ERP system adoption. Collection of

Qualitative and Direct interviews with SMEs’
(Federici, 2009) ERP adoption actual 50 SMEs in Italy
Quantitative managers
achievement, advantages and context/project characteristics

5 attributes are ranked for each of the following alignment 104 surveys from
(Gutierrez et. al. IT and business Online and telephone survey,
Quantitative factors: communication, competency/value measurement, organisations all over
,2009) alignment ANOVA
governance, partnership, architecture and scope and skills. the globe

217 small
impact of owner’s knowledge of IT on business, IT strategic
(Chao and IT adoption and email survey to the owner of the manufacturers and
Quantitative alignment and use in the small firm context.
Chandra, 2012) strategic alignment small business financial services
Resource-based view as a theoretical foundation
firms in the USA
analyze the adoption, implementation, motivation of team
adaption of social
(Zeiller and members, in-depth analysis of multiple case 6 case studies of
Qualitative media initiatives for
Schauer, 2011) benefits and success factors of social media utilization for studies european SMEs
team collaboration
team collaboration.
48 MBA students and
develop a benefits realisation road-map for ERP usage in
(Esteves, 2009) Qualitative ERP usage direct interviews 87 business
SMEs
managers
e-business and e-business and business strategy alignment in SMEs in
(Raymond and Qualitative and contingency theory perspective, 107 Canadian
business strategy terms of Miles and Snow’s strategic typology, including
Bergeron, 2008) Quantitative correlation analysis manufacturers
alignment prospectors, analyzers, and defenders
(Loh and Koh, examine critical elements of successful ERP
Qualitative ERP implementation literature review and interviews 8 SMEs in the UK
2004) implementation in SMEs
(Aguila-Obra and explore factors affecting the implementation of Internet
Qualitative and innovation adaption theory,
Padilla-Melendez, Internet adoption technologies and the extent to which company size, as an 280 companies
Quantitative questionnaire
2006) organizational factors, influences the process.
composite index of the usage 237
(Kaynak et. al., factors affecting the willingness of SMEs to adopt E-
Quantitative E-commerce adoption frequency of 14 EC application manufacturing SMEs
2005) commerce usage
tools (managers were asked) in Turkey
examine the critical success factors of ERP
(Doom et. al., ERP survey + multiple case study.
Qualitative implementations in Belgian SMEs and to identify those 4 SMEs in Belgium
2010) implementation Structured interview technique
success factors that are specific to a SME environment
principal component analysis,
Qualitative and empirical analyses (t-tests), linear survey of 1200 Korean
(Jeon et. al., 2006) adoption of E-business Determining factors for the adoption of E-business in Korea
Quantitative probability SMEs
model, logit model
477 small
develop a basic model of E-commerce adoption barriers to empirical survey, data analysed by
(MacGregor and Qualitative and E-commerce adoption businesses in
small businesses located inregional areas of developed correlation
Vrazalic, 2005) Quantitative and implementation Sweden and
countries matrices and factor analysis
Australia

2,139 establishments
(Gibbs and Quantitative and telephone survey, stratified random
E-commerce use determinants of scope of use among E-commerce adopters from three industries
Kraemer, 2004) qualitative sample
across 10 countries

empirical investigation,
(Evangelista et. al, Qualitative and Adoption of Knowledge 18 SMEs located in
shed light on the KM practices in small firms. questionnaire survey through
2010) Quantitative Management Systems Naples City (Italy)
interviews with managers
contribute to a growing body of research on cloud 15 SMEs and service
Cloud computing
(Alshamaila, 2013) Qualitative computing, by studying the small to medium ‐sized semi ‐structured interviews providers in the north
adoption
enterprise (SME) adoption process east of England
assess the impact of organizational, manager and
(Wamba S.F. and
Quantitative Social Media adoption environmental characteristics on hierarchical logistic regression survey of 453 SME
Carter L, 2014)
SME utilization of the Facebook Events Page

Source: Own adjustment

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4 Models of technological innovation adaption and the TOE framework

There is a growing amount of theories and studies on technological innovation and technology
adoption. The most common theories are the Technology Acceptance Model (TAM) (Davis 1986)
(Davis et al. 1989), Theory of Planned Behavior (TPB) (Ajzen, 1985) (Ajzen, 1991), Unified Theory
of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), Diffusion of Innovation
(DOI) (Rogers, 1995) and the Technology-Organization-Environment (TOE) framework (Tornatzky
and Fleischer, 1990).
The review of the literature on technological innovation confirms that the majority of empirical
studies refer to the “Diffusion of Innovation” or the DOI theory of Rogers as well as to the TOE
framework. DOI is recognized by many researchers as being able to identify “perceived” critical
characteristics of technological innovations (such as relative advantage, compatibility, complexity,
observability and trialability) that may influence the attitude of potential adaptors or rejecters of IS.
It was however argued that Rogers model should also be blended with other contexts or factors for
a more holistic adoption approach. In line with this argument we found that the TOE framework
includes the environment context (not included in the DOI theory), thus becoming better able to
explain intra-firm innovation adoption and therefore more complete. The TOE framework has a solid
theoretical basis and the potential for application in the IS adoption (Oliveira and Martins, 2011). It
is developed by Tornatzky and Fleischer (1990) and it specifies 3 types of factors that influence the
adoption and organizational usage of technological innovation. The technological context which
includes both internal and external technologies that might be useful in improving organizational
productivity. The organizational context, defined in terms of firm size and scope, complexity of the
managerial structure, quality, characteristics and availability of firms technology and financial
resources), as well as environmental (or institutional) context, which refers to the firm’s industry
and dealings with business partners, competitors and government (Tornatzky and Fleischer, 1990).
The TOE framework has found regular empirical support for factors of IS adoption such as “external
pressure”, “organizational readiness” (in terms of technology and financial resources), and
“perceived benefits” (Iacovou et al., 1995) (Chau and Tam, 1997) (Kuan and Chau, 2001). Zhu et
al. (2003) studied data from 3,100 firms to understand how technological competence,
organizational factors such as “firm scope” and “size” and the environmental context influence
“consumer readiness”. Zhu et al. (2003) identified “trading partner readiness” as well as
“competitive pressure” as influencing factors and antecedents in e-business adoption. The TOE
framework is also used to empirically validate the antecedent factors that influence EDI adoption
(e.g., Iacovou et al., 1995) (Kuan and Chau, 2001) (Lippert and Govindarajulu, 2006). The identified
variables are defined and summarized in the below given table:

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Figure 2: Identified elements of the TOE framework

Technological
Degree to which an innovation is perceived as being better than the
1. Relative advantage
idea it supersedes
Degree to which an innovation is perceived as consistent with
2. Compatibility
existing values, past experiences and adopter needs
Degree to which an innovation is perceived as relatively difficult to
3. Complexity
understand and use
Organizational

1. Top management support Support of the top management (CEO) to the IS adoption initiative
Comparing to large businesses small businesses face ressource
2. Organizational readiness (size) poverty and thus difficulties in innovation adaption. Ressource
cost/financial and technical resources) poverty manifests itself also in financial constraints and lack of
professional expertise.
Degree to which information is present in the product or service of
3. Information intensity and product
a business, reflects the level of information intensity of that product
characteristics
or service
4. Managerial time Time required to plan and implement the new IS.
Environmental

Competition and high rivalry increases the likelihood of innovation

1. Industry pressure (competition)
adaption for the purpose of gaining competitive advantage

Government strategies or initiatives that encourage SMEs to adopt

2. Government pressure/support
new IS.
Lack of customer readiness Influences the adoption process and
3. Consumer readiness
is an inhibitor towards IS use

Source: Own adjustment

A lot of authors used the TOE framework to understand the adoption of different IS such as:
Electronic Data Interchange (EDI) (Kuan and Chau, 2001), Open Systems (Chau and Tam, 1997);
Website (Oliveira and Martins 2008); E-Commerce (Liu, 2008, Martins and Oliveira, 2009),
Enterprise Resource Planning (ERP), (Pan and Jang, 2008), Business to Business (B2B),
E-Business (Zhu et al. 2003) (Zhu and Kraemer, 2005) (Zhu et al., 2006) (Lin and Lin, 2008)
(Oliveira and Martins, 2010), Knowledge Management Systems (KMS) (Lee et al., 2009).
In the last 10 years (2004 to 2014), we encountered a growing body of research, focusing on SME
adaption of new technologies such as social media, cloud computing and other Web 2.0 tools which
are enjoying growing popularity. Although reports suggest that social media tools really enhance
the development of SMEs, there is still little empirical evidence on their adoption and usage from
this category of firms (Dixon, 2010). A TOE based framework for assessing the readiness of
organizations prior to the adoption of social media has already been proposed and validated for
usage in large organizations (Abeysinghe, 2013). It would be of research interest to identify critical
success factors and specify alternative frameworks which would serve as guidelines for the
adaption of social media in SMEs. Also a technology with great potential benefits is cloud
computing. The term started to appear in Google searches in the third quarter of 2007, then

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searches increased rapidly. Through the adoption of cloud computing, SMEs can lower their entry
cost for powerful IT capabilities by reducing the cost of ownership for hardware and software and
by reducing the IT staff. Startup expenses for SMEs may be particularly minimized through the idea
of metered services. Cloud computing has also the potential to provide competitive advantage,
because on-demand elasticity enables rapid scaling of resources as the SME grows (Kourik, J. L.,
2011). These qualities make cloud computing another important technological innovation. Based
on the reviewed literature we classified the articles according to the above specified variables of
the TOE framework. The different variables were considered to be significant or insignificant to the
IS adoption from various authors.

Table 3:
Determinig factors Found significant Found insignificant
Technological
(Alam & Noor, 2009), (Grandon & Pearson, 2004),
(Ramdani & Kawealek, 2009), (Oh et. al., 2009),
(Shiau et. al., 2009), (Esteves, 2009), (Raymond &
1. Relative advantage Bergeron 2008), (Kaynak et. al., 2005),
(Stockdale & Standing, 2004), (Jeon et. al., 2006),
(MacGregor & Vrazalic, 2005), (Gibbs & Kraemer,
2004), (Alshamaila, 2013)
(Grandon & Pearson, 2004), (Doom et. al., 2010),
2. Compatibility
(Alshamaila, 2013)
(Grandon & Pearson, 2004), (MacGregor & Vrazalic,
3. Complexity (Buonanno et. al., 2005)
2005)
Organizational
(Ghobakhloo et. al., 2011), (Parker & Castleman
2009),(Scupola, 2009), (Ramdani & Kawealek, 2009),
1. Top management support
(Shiau et. al., 2009), (Haug et. al. 2011), (Chao &
Chandra, 2012), (Alshamaila, 2013)

(Buonanno et. al., 2005), (Ghobakhloo et. al., 2011),

(Parker & Castleman 2009), (Scupola, 2009),
(Ramdani & Kawealek, 2009), (Oh et. al., 2009) , (Haug
2. Organizational readiness (size) (cost/financial and (Alam & Noor, 2009), (Grandon & Pearson, 2004),
et. al. 2011),(Aguila-Obra & Padilla-Melendez, 2006),
technical resources) (Shiau et. al., 2009), (Jeon et. al., 2006)
(Kaynak et. al., 2005), (MacGregor & Vrazalic, 2005),
(Gibbs & Kraemer, 2004), (Evangelista et. al, 2010),
(Alshamaila, 2013)

(MacGregor & Vrazalic, 2005), (Evangelista et. al,

3. Information intensity and product characteristics
2010)
(MacGregor & Vrazalic, 2005), (Evangelista et. al,
4. Managerial time
2010)
Environmental
(Ghobakhloo et. al., 2011), (Parker & Castleman 2009),
1. Industry pressure (competition) (Scupola, 2009), (Haug et. al. 2011), (Stockdale & (Jeon et. al., 2006), (Alshamaila, 2013)
Standing, 2004), (Doom et. al., 2010)
(Alam & Noor, 2009), (Grandon & Pearson, 2004),
(Ghobakhloo et. al., 2011), (Parker & Castleman 2009),
2. Government pressure/support
(Scupola, 2009), (Jeon et. al., 2006), (Gibbs &
Kraemer, 2004)
3. Consumer readiness (MacGregor & Vrazalic, 2005) (Oh et. al., 2009)
(Ghobakhloo et. al., 2011), (Parker & Castleman 2009),
(Scupola, 2009), (Aguila-Obra & Padilla-Melendez,
4. Support from technology vendors
2006), (Doom et. al., 2010), (Evangelista et. al, 2010),
(Alshamaila, 2013)

Source: Own adjustment

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Variables which could not be categorized (or didn’t fit) in the TOE framework, but found significant
for the adaption from the respective authors are not depicted in the table. As such we identify the
“CEOs/Employee knowledge of IS and innovativeness” which was found significant from several
authors (Alam and Noor, 2009), (Scupola, 2009), (Shiau et. al., 2009), (Haug et. al., 2011), (Chao
and Chandra, 2012), (Jeon et. al., 2006), (MacGregor and Vrazalic, 2005), (Alshamaila, 2013).

Conclusions
With new technologies and means of technology adaption that evolve constantly, there is a
permanent need in understanding the organizational adoption of technological innovation, its
dimensions and characteristics. The TOE framework of Tornatzky and Fleischer (1990) has proved
that it is able to provide insights for researchers and practitioners interested in this topic. The
adoption of IS innovations is clearly affected by the technological, organizational, and
environmental contexts of the enterprise. The TOE framework has been useful in investigating a
wide range of innovations and contexts. The major part of the research in the domain of IS
innovation adoption in small and medium sized enterprises is concentrated on the adaption of
technologies such as E-commerce, E-business, ERP, estimating the IT readiness of SMEs etc.
However, for the period under investigation (2004 to 2014), we encountered a growing body of
research, focusing on SME adaption of new technologies such as social media, cloud computing
and other Web 2.0 tools which are enjoying growing popularity.
During the literature review, different factors that influence technological innovation adaption in
SMEs could be identified and illustrated in a summary table. Among the most stated factors in the
analyzed articles are the expected relative advantage, top management support, organizational
readiness, IS knowledge and innovativeness. Because of the limited human resources, critical
decisions in SMEs are taken from the CEO. Thong (1999) points out the importance of
“characteristics of the organizational decision makers” (including CEO’s IS knowledge and CEO’s
innovativeness) as a fourth element of context in the technological innovation literature beside
“characteristics of the technological innovation”, “characteristics of the organization” and
“characteristics of the environment”.
Concluding, for the period under investigation, we identify as a research gap the missing studies
on the SME adoption of the new Web 2.0 technologies and how well their patterns of adoption do
fit in the currently available frameworks of technological innovation adaption, such as the TOE
framework. The ongoing technological innovation demand for permanent validation of existing
frameworks and continued empirical research work. Findings presented in this study may have
implications for the research community, SME managers and information and communication
technology providers in terms of illustrating the status of research in this area as well as formulating
better strategies and frameworks for the adaption of new IS in SMEs.

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