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CLOUD ERP ADOPTION-A PROCESS VIEW APPROACH
Siti Aisyah Salim, Information Systems School, Queensland University of Technology, Australia,
Abstract
In spite of a wealth of studies on ERP adoption in recent years, prior studies have presumed ERP
adoption as an immediate action rather than as a process. We also argue that cross-sectional research
design does not adequately represent the complexity and the highly volatile nature of the process of ERP
adoption. Based on a content analysis of one hundred studies on academic and vendor successes, we have
identified 27 transition factors contributing to the adoption of cloud ERP. Building on two process
research studies (Guttman et al. 1998; Klein and Sorra 1996), this research attempts to explore which
transition factors are relevant to the distinct phases of cloud ERP adoption. These transition factors are
classified as “necessary” or “sufficient”; where “necessary” transition factors need to exist in order for
the firm to move to the next stage, while “sufficient” means assisting in the movement. This paper not
only consolidates, but also extends the existing literature on the technology adoption process for complex
organization-wide technologies. For practitioners, this study will assist ERP and cloud vendors in
prioritizing and upgrading their business quality at any point in time during the adoption process, which
would thus increase the likelihood of cloud-based ERP adoption among SMEs.
Keywords: cloud, ERP, SMEs, process
1 INTRODUCTION
Enterprise Resource Planning (ERP) systems have been popular information technology (IT) applications
since the 1990’s (Robey et al. 2002). Prior research has focused predominantly on ERP implementation in
large organisations, while research on ERP implementation in small and medium sized enterprises
(SMEs) is still lacking. This is not surprising, since ERP systems could only be afforded by large
companies in past years. Until recently, due to the realization of the importance of SMEs in global
industry, several ERP providers have started to introduce new cloud-based ERP systems to the
marketplace. These include SAP, Oracle, Microsoft and NetSuite. With more specialised features being
embedded into cloud ERP, such as on-demand access, Project Management and transparency analytics
tools (Pereira 2012), it has been expected the SME adoption of cloud ERPs would increase. However our
expectations have not been correct. The percentage of SMEs that have adopted cloud ERP systems still
remains relatively low (Haddara and Zach 2011).
A number of researchers have attempted to study the factors that encourage firms to adopt cloud ERP
systems. For example, Saeed et al. (2011) and Walther et al. (2012) have identified reduction of
implementation costs, ease of use, extendibility, and ability to concentrate on core business activities, as
the main influencing factors for cloud ERP adoption. However, these studies have only listed all
influencing factors and conceived the adoption of cloud ERP as being a one-off dichotomous decision
(Huizingh and Brand 2009). Exploring these factors without studying how these factors evolve over time
is similar to placing all factors into a single phase, with the comprehensive view of the technology
adoption unable to be achieved. Thus, in response to this research gap, this study attempts to develop a
process framework for cloud ERP adoption. The framework presented (please refer to Figure 1) will show
how the factors that influence cloud ERP adoption (named as transition factors) act as triggers that help
the firm in moving from the initial stage of adoption (entering) until the last stage (commitment). By
understanding how these transition factors work and flow, vendors as well as firms could identify their
main role in completing the adoption process, and thus lead to a successful system implementation.
Considering the fact that content analysis will help the researcher to explore the transition factors, aside
from understanding the phases involved in complex technology adoption and research context (cloud ERP
and SMEs), this research employs a content analysis method as suggested by Hsieh et al. (2005) and
Krippendorff (2004). Studies by Klein et al. (1996) and Gutman et al. (1998) were used as a guidance to
develop the process framework. This paper not only consolidates, but also extends the existing literature
on the technology adoption process for a complex organization-wide technology. For practitioners, this
study will help ERP and cloud vendors in prioritizing and upgrading their business quality at any point in
time during the adoption process and thus will increase the likelihood of cloud-based ERP adoption
among SMEs.
This paper is organized as follows: it commences by explaining the works related to this study. The
discussion then continues with the methods used. Subsequently, the paper continues with a discussion and
introduction of an a priori conceptual framework of the technology adoption process. Finally, the paper
concludes with future studies proposed in this field and recommendations for academics and practitioners.
2 RELATED WORK
This section attempts to provide an overview of existing technology adoption topics in the literature
reviews. It is highlighted that most academic literature focuses on factors that influence technology
adoption and the sub-phases involved in the adoption. A small number of these studies attempt to gauge
how and why these factors flow throughout the technology adoption phases.
2.1 Technology Adoption
New technology adoption (also known as innovation) is defined as an idea, practice, or object that is
perceived as new by an individual or other unit of adoption (Rogers 1995). Technology adoption has been
studied at two levels, namely: the individual (e.g., Brown and Venkatesh 2005) and the firm (e.g., Bajwa
et al. 2004). The majority of technology adoption studies has typically focused on one dimension of
research, namely: discovering the determinants (factors that influence) of technology adoption
(Frambach and Schillewaert 2002) stages involved in technology adoption (e.g., Cooper and Zmud 1990;
Wang et al. 2012) and the characteristics of technology adoption (e.g., Wang et al. 2010). Separating
these dimensions will lead to several assumptions, for instance, treating technology adoption as a single
phase decision (Thong 1999), simplifying the process of new technology adoption, picking and choosing
constructs from multiple theories to develop new theories (Jeyaraj et al. 2006), and citing and adopting
constructs from both domains regardless of whether they are studying an individual or organizational
level of adoption (Plouffe et al. 2001). Based on the issues brought up, we believe that technology
adoption at the firm level should be able to answer “how” and “why” questions (Chia and Langley 2004).
Further, technology adoption should be treated as a process embracing movement, activity, event, change,
and temporal evolution (Langley 2007). In the next section, typical phases used in technology adoption
studies will be discussed.
2.2 Technology Adoption Phases in Organizations
It is generally believed that organizations go through several phases of innovation. The innovation stages
could consist of three to six phases and have similarities in terms of highlighting pre-implementation,
implementation and post-implementation (Yu 2005). The pre-implementation or the adoption phase has
proven to be a critical stage (Markus and Tanis 2000) in achieving a successful project. Therefore, this
research focuses on the pre-implementation stage, focusing on what phases are involved in triggering
SMEs to adopt cloud ERP. To select the most appropriate phases in relation to our research context, three
research streams were reviewed: technology adoption, ERP lifecycle, and marketing lifecycle. Our search
has found seven relevant studies1 (refer to Table 1 for the details of the stages). We also acknowledge
that the use of different terms might provide different interpretations of activities, events, and players
involved in each phase. However, it is not the main objective of this research to determine the best term to
be employed for explaining the process of complex technology adoption, but rather, to understand and to
explore how these phases evolve and interconnect with each other. Based on Table 1 summary, Guttman
et al. (1998) and Klein et al. (1996) provide the nearest similarity to our stages. Therefore, these two
studies were used to build up our research framework. The five stages used are: entering, inquiry,
inquisitive, short listing and commitment.
Table 1. Studies on Lifecycle and Phases References
Our research Entering Inquiry Inquis i tive Short l i s ting Commitment
(Rogers 1995) Restructuring Clari fying Routinis ing
(Kl ien and Sorra
1996)
Adoption Implementation Routinisation
(Shoham 1992) Awareness Evaluation Tria l Adoption
(Guttman et a l
1998)
Need
identi fication
Merchant
brokering
Negotiation Purchase and
del ivery
(Vervi l le and
Hal ingten 2003)
Planning Information
Search
Selection Evaluations Choice (s ) Negotiations
Technology Adoption/Buying Phases
Awareness Selection
Agenda setting Matching
Interest
Product brokering
1 There are many more studies on process and lifecycle. However, we selected only eight studies that were relevant to our
research context. Please refer Table 1 for details of studies selected.
3 METHODS – EXPLORING AND MAPPING
Two steps were carried out to produce the final framework. This entails two main phases: (1) content
analysis phase – to explore the transition factors for technology adoption, and (2) mapping phase – to
understand how transition factors could influence the movement of the overall technology adoption
process.
3.1 Exploring Transition Factors
To ensure validity, a research study requires certain standards and processes. The selection of prior
studies for analysis is based on the approach of Webster and Watson (2002), as well as prior exploratory
studies (e.g., Gable 2010). To ascertain the relevant literature on cloud ERP adoption, a search was
performed using the ScienceDirect database and top IS journals and conference proceedings. The
inclusion of the ScienceDirect database ensured that the search results included complex technology
adoption articles from multiple disciplines. The main keywords employed in the academic search were
restricted to a title and body text search of, namely, (1) cloud ERP and (2) SaaS ERP2. Furthermore, the
results were constrained between 2005 and 2012, with theoretical and conceptual studies excluded. The
practitioner material was scanned using the vendor-stated “customer testimonials”. The search identified
86 academic studies and 14 customer testimonials (the reference list can be requested by emailing the
authors).
All 100 “sources of evidence” were then scanned for the stated adoption factors (reason for adoption).
This process yielded a total of 142 adoption factors. We also noted that approximately 80% of the stated
adoption factors were benefits of cloud ERP (e.g., provision of consistent and accurate information,
reduction of infrastructure and administrative costs, and standardization of reporting). As the intention of
this study is not only to look at the benefits of cloud ERP adoption, we then synthesized the adoption
factors benefits. The synthesis procedure attempts to reduce the identified adoption factors by removing
overlapping measures so as to attain unique factors. The synthesis process was conducted with another
two experts on Innovation and ERP systems, following two simple guidelines. The guidelines include: (1)
when two technology adoption factors are identical, they were merged into a single statement, and (2)
when two technology adoption factors use different keywords, but have a similar meaning, a list of
synonyms were considered, using a thesaurus. The guidelines mentioned allowed us to follow the same
logic when synthesizing the 142 citations. The synthesis process identified 27 unique technology adoption
factors of cloud ERP systems.
3.2 Mapping the Transition Factors into Technology Adoption Phases
The main objectives of the mapping exercise are two-fold: (1) to provide a clear understanding how the
transition factors flow throughout the adoption process; and (2) to differentiate between sufficient and
necessary transition factors. The twenty-seven (27) transition factors found from the content analysis are
then mapped into the adoption process framework. Each transition factor has a different level of
importance. Two different types of transition factors were used in this paper. The first was transition
factors with sufficient condition – meaning, the existence of these factors can help the movement of the
adoption process (Hakansson et al. 1982). In this context, sufficient transition factors mean that these
factors will be the gateway to move from one phase to another, and the desired output can still be
obtained even though these transition factors do not exist. The second is transition factors with necessary
2 The main concern of the paper is to discuss the process of pooling and synthesizing the factors, therefore details of this method
will only be provided upon request to the authors.
condition – meaning, transition factors that are categorized under this category need to exist (Hakansson
et al. 1982) and be placed in the correct phase, in order to obtain the required output, or allow the firm to
evolve to the next phase. Output here refers to the movement of the firm from the prior stage to the next
stage of the cloud ERP adoption process. By differentiating between these two (sufficient and necessary)
terms, firms or vendors could prioritize and aim for the best action to expedite the adoption process. In
general, a necessary condition is more significant than merely a sufficient condition. Sufficient and
necessary concepts are widely used in the fuzzy set QCA method to see the importance of certain
conditions in relation to their experiments (e.g., Chaiken and Trope 1999; Ragin 2000; Sen and Pattanaik
2012). All the transition factors mapped into the technology adoption phases (entering, inquiry,
inquisitive, short listing or commitment) are guided by academic literature studies and industry success
stories. More than twenty studies were reviewed in order to understand the process of complex
technology adoption (please refer to Table 1 for example of studies). Since our study is based on SMEs
and cloud ERP technology, the stages used are more relevant to this research context. The combination
and merging of several studies into a single adoption framework will assist us in understanding how this
process was performed. Findings from the mapping exercise can be viewed in Table 2.
Table 2: Transition Factors Description, Phase Mapping and References
Factor Description with Reference Phase Authors (Phase)
Business benefits
New technology is observed as being an
improvement on its predecessor
(Ramdani et al. 2009)
Entering
(Campbell 2011)
Internal
awareness
Ability to perceive of events or sensory patterns
(Dwyer et al. 1987) Entering
(Dwyer et al. 1987)
External
awareness
Pressure, external sources preaching (Dwyer et
al. 1987)
Business
characteristics
Senses a difference between actual state and
desired state of firm performance (Comegys et
al. 2006)
Entering
(Comegys et al. 2006)
Strategic
planning
Planning strategies and step-by-step instructions
for carrying out those strategies (Mintzberg
1994)
Entering,
Inquiry
(Mergel and
Bretschneider 2013)
Financial
incentives
Form of material reward, in exchange for acting
in a particular way (Zhu and Kraemer 2005)
Inquiry
(Yap et al. 1994)
Financial
availability
The need to have available financial resources
(Blackwell et al. 2006)
Inquiry
(Blackwell et al. 2006)
Urgency need Perceived need from employees to facilitate the
business operation (Thong and Yap 1995)
Inquiry
(Buchowicz 1991)
Regulation Government intervention either to give pressure
or support (Oh et al. 2007)
Inquiry
(Paul and Kumbhojkar
2012)
Project champion The individual who throws support behind the
new technology adoption (Basoglu et al. 2007)
Inquiry,
Inquisitive,
Short listing,
Commitment
(Abramovitch 2012)
Demonstration Consultant demonstration on the product (Poba-
Nzaou and Raymond 2010)
Inquisitive
(Poba-Nzaou and
Raymond 2010)
Maintaining and
upgrading
Question regarding maintenance and upgrade
support offered from ERP vendors (Ng and
Gable 2009)
Inquisitive (Repschlaeger et al.
2012)
Functions (ease
of use)
New technology is perceived as being difficult
to understand and use (Wind et al. 2012) Inquisitive (Wind et al. 2012)
Cost estimation
Any cost incurred prior to or during the
implementation of innovation (Walther et al.
2012)
Inquisitive,
Short listing
(Repschlaeger et al.
2012)
Table 2: Transition Factors Description, Phase Mapping and References
Support
Support from the vendor in terms of
consultation, expertise, training, responsiveness
and commitment (Chan and Lee 2003)
Inquisitive,
Short listing,
Commitment
(Repschlaeger et al.
2012)
Vendor
reputation
Collective perception and second hand
information of the vendor capabilities (Einwiller
2001)
Short listing
(Repschlaeger et al.
2012)
Committee
A team consisting of the business owner, senior
management and product line manager (Kartam
1996)
Short listing
(Mergel and
Bretschneider 2013)
Compatibility
New technology is perceived as being reliable
for the existing needs of the firm (Olhager and
Selldin 2003)
Short listing
(Repschlaeger et al.
2012)
Infrastructure
pre-requisite
Physical hardware used to interconnect people,
system and technology (Zhu et al. 2003)
Short listing
(Mergel and
Bretschneider 2013)
Install, scoping
and configuring
Creating a logical structure involving one or
many legal-financial entities/ operational entities
(Markus et al. 2000)
Short listing
(Repschlaeger et al.
2012)
Preferred solution
The selection of the ERP system according to
the firm's specific requirements (industry type)
(Tsai et al. 2011)
Short listing
(Repschlaeger et al.
2012)
Proactive service
Proactive behaviour involves acting in advance
of a future situation, rather than just reacting
(Varshney et al. 2000)
Short listing
(Repschlaeger et al.
2012)
Security concern
The technical security aspects that include
potential risks of data loss, data manipulation by
internal employees, external players or the
service provider. (Wind et al. 2012)
Short listing
(Repschlaeger et al.
2012)
Staff involvement
Participation of organizational members for the
success of adoption process (Truman and Raine
2002)
Commitment
(Abramovitch 2012)
Trialability New technology can be experimented with on a
limited basis (Zhu et al. 2006)
Commitment
(Shoham 1992)
Implementation
plan
The complete and precise execution plan
(Basoglu et al. 2007)
Commitment
(Shaul and Tauber 2012)
4 DISCUSSION
For a clearer view, findings from Table 2 are transferred into Figure 1. As presented in Figure 1, the
adoption of cloud ERP can be disseminated into five phases: entering, inquiry, inquisitive, short listing,
and commitment. It is also shown that the transition factors have been classified as sufficient or necessary.
In the entering phase, we found external awareness (information provided by vendors or business
affiliations) and internal awareness (recognition of the firm’s needs) as the necessary transition factors.
These two factors could assist in changing the ignorance of the firm’s owner or manager. Ignorance
occurs when there is a lack of knowledge (Burke and Jarratt 2004) or incapability on the part of the
firm’s members to articulate their long term vision (Mendelssohn 1991). However, only a reliable sense
(information) of awareness could strongly lead the movement from being ignorant to being more curious
about something (Comegys et al. 2006). While discovering business benefits, understanding business
characteristics (the status quo of the firm) and strategic planning are considered as sufficient transition
factors.
At the inquiry phase, the firm’s representative (business, manager or project champion) begins to gather
relevant information (Comegys et al. 2006). The firm’s representative starts become familiar with the
products, pay attention to the advertisements, and find the most appropriate vendor and product so that
they can ask more specific questions. Urgency needs and project champion are identified as necessary
transition factors. Project champion is the one who sets goals and legitimates change by advocating and
promoting the benefits of the new system (Shanks et al. 2000) to board members. Though cloud ERP will
be managed and maintained by the selected ERP vendor, having a project champion will encourage the
adoption process. For a firm in the category of an SME, any kind of investment or expense will be made
only when it is required. Thus, urgency needs will expedite the adoption process. Not seeing the need to
adopt a new system is also a key factor for not continuing on to purchase the system. The other four
transition factors: financial availability, incentives, regulation and strategic planning, are classified as
sufficient conditions.
In the inquisitive stage, more specific and informational questions will be asked (Verville and Halingten
2003). The potential ERP and cloud vendor will be asked to provide the product demonstration
(Repschlaeger et al. 2012). Demonstration is needed to introduce some of the most important functions,
ensure the compatibility of the system with the firm’s business model, andanswer specific questions in
relation to the product (Poba-Nzaou and Raymond 2010). Queries regarding estimation costs, support
and other system functions will also be raised during this phase. However all these are not considered as
the main triggering factor, but rather, as the support for the process to move to the next stage. Therefore,
only demonstration is considered as being a necessary transition factor, while issues such as project
champion, cost estimation, support and functions are considered as sufficient transition factors.
At the short listing stage, the firm’s representative will attempt to screen available product and vendor
choices (Comegys et al. 2006). Sometimes it is difficult to make a choice, especially between products
and vendors that have a good reputation. For certain firms, setting rule cut-offs for the products in their
short listing set will help them to make the decision (Comegys et al. 2006). Other studies suggest that cost
(cost estimation (specific)) would be the major factor for SMEs, whether or not to select the product
offered (Masset and Sekkat 2011; Raihana 2012; Walther et al. 2012). The compatibility of the existing
system with the new technology is also an important aspect (Karahanna et al. 2006) to be considered.
Therefore, cost estimation (specific) and compatibility are considered as necessary transition factors. At
the same time, other transition factors listed in the phase are classified as sufficient transition factors.
At the commitment stage, the firm members will express their agreement to buy and adopt the system. As
the decision will be made at this stage, each of the transition factors will have the same condition (e.g.,
sufficient). Cloud and ERP vendor loyalty is achieved (Dwyer et al. 1987) as soon as the customer (firm)
signs the contract. The pre-adoption process will end at this point. The new cloud ERP deployment
concept is not the same as the traditional ERP system where firms are locked-in with a specific vendor for
a certain period (Acumatica 2012). With new cloud technology concept, firms can decouple the system at
anytime they want. This situation compels vendor to actively seek to maintain their relationship with
customers (firms) so that they will not run away or terminate the service with them.
The classification of the transition factors into several phases shows that the process of cloud ERP
adoption is affected either directly or indirectly by individuals, units or departments from both inside and
outside the organisation. Consistent with Kimberly and Evanisko (1981) statement, firms’ decision-
making process is perhaps being made by different individuals or groups of individuals. Therefore, even
if this research tries to examine transition factors in technology adoption from firm level perspectives, the
involvement from external parties or individuals cannot be avoided. As the technology adoption process
moves into a more critical stage (from entering to commitment), the level of influence and involvement
becomes more specific. For example, when the firm starts thinking of or realizing the need to have such a
system, the factors that influence them to move can come from several sources. These usually include:
external vendors, competitors and industry alliances. However, as the process moves towards making the
final decision, only certain individuals or groups can actually make the decision. The findings from Table
1 have demonstrated that collaboration from several parties is needed in order to align business goals
(Luftman 2000).
ENTERING COMMITMENTINQUIRY SHORT LISTINGINQUISITIVE
1. Externalawareness
2. Internalawareness
3. Business benefits4. Business
characteristics5. External Strategic
planning
1. Urgency need2. Project champion3. Financial
availability4. Incentives5. Regulation6. Strategic Planning
1. Demonstration2. Project champion3. Cost estimation4. Support5. Functions (ease of
use)6. Maintaining and
upgrading support
1. Compatibility2. Cost estimation
(specific)3. Support4. Project champion5. Committee6. Infrastructure pre-
requisite7. Install, scoping and
configuring8. Preferred solution9. Proactive service10. Security concern11. Vendor reputation
1. Project champion2. Support3. Implementation
plan4. Trialability5. Staff involvement
Key: Underlined andbolded terms arenecessary conditiontransition factors
Figure 1. A Priori Cloud ERP Adoption Framework
Conclusion and Future Works
This paper explores the transition factors that lead to the adoption of cloud ERPs in SMEs, and discusses
the preliminary findings of research, with the objective of identifying and categorizing each of the factors
into one of the five phases of the cloud ERP adoption framework (refer to Figure 1). The mapping of the
factors could potentially be different in other scenarios; however, our goal is to derive a robust, valid,
simple, yet applicable model of cloud ERP adoption for the SME market. The term “transition factors”
was introduced after identifying the need to understand the factors that influence complex technology
throughout the entire process stages, as opposed to being lumped into a single stage. These transition
factors were also classified as being sufficient or necessary, depending on the condition of a particular
phase.
The purpose of this paper is to extends the understanding of technology adoption process for complex
organization-wide technologies. By understanding the evolving process, it could help vendors prioritizing
and upgrading their business quality at any point in time during the adoption process. While for cloud
ERP clients (firms), this study not only provides buying strategies, but could also help the firm in
understanding how the collaboration between several components (individual, group, departments, firms
and global) could influence and accelerate the adoption process.
As this is a preliminary finding, there are several plans that have been developed. First, the a-priori
framework presented in this paper is conceptual. Hence, we will validate these preliminary findings by
using a q-sorting procedure as suggested by Moore et al. (1991) in order to produce inter-rater reliabilities.
Second, we will conduct a series of case studies with IT decision makers from two different types of
SMEs, to assess the general relevance of each factor in each phase. We also believe that the
management’s maturity level and firm’s technology infrastructures have an effect on the readiness and
speed with which to adopt new technology. For us, this will be an interesting research area to be studied,
as it will help us in understanding how the management pattern will actually influence the speeding-up of
the adoption process. Therefore, understanding the level of firm maturity will become another agenda for
our future research.
REFERENCES
Abramovitch, D. 2012. "EntryPoint." Retrieved April 25,2013, from
http://www.entrypointblog.com/byd/
Acumatica. 2012. "Freedom from SaaS Lock-in." ERP Cloud News Retrieved March 16,
2013, from http://erpcloudnews.com/2012/05/freedom-from-saas-lock-in/
Bajwa, D.S., Garcia, J.E., and Mooney, T. 2004. "An Integrative Framework for the
Assimilation of Enterprise Resource Planning Systems: Phases, Antecedents, and
Outcomes," Journal of Computer Information Systems (44:3), pp. 81-90.
Basoglu, N., Daim, T., and Kerimoglu, O. 2007. "Organizational Adoption of Enterprise
Resource Planning Systems: A Conceptual Framework," The Journal of High
Technology Management Research (18:1), pp. 73-97.
Blackwell, P., Shehab, E.M., and Kay, J.M. 2006. "An Effective Decision-Support
Framework for Implementing Enterprise Information Systems within SMEs,"
International Journal of Production Research (44:17), pp. 3533-3552.
Brown, S.A., and Venkatesh, V. 2005. "Model of Adoption of Technology in
Households: A Baseline Model Test and Extension Incorporating Household Life
Cycle," MIS Quarterly (29:3), pp. 399-426.
Buchowicz, B. 1991. "A Process Model of Make-vs.-Buy Decision-Making. The Case of
Manufacturing Software," IEEE Transactions on Engineering Management (38:1),
pp. 24-32.
Burke, G.I., and Jarratt, D.G. 2004. "The Influence of Information and Advice on
Competitive Strategy Definition in Small-and Medium-sized Enterprises,"
Qualitative Market Research: An International Journal (7:2), pp. 126-138.
Campbell, P. 2011. "Mimecast’s NetSuite Implementation." Retrieved April 10,2013,
from http://www.jd-od.com/2011/06/27/mimecasts-netsuite-implementation/
Chaiken, S., and Trope, Y. 1999. Dual-Process Theories in Social Psychology. New
York: : Guilford Press.
Chan, J.K., and Lee, M.K. 2003. "SME E-Procurement Adoption in Hong Kong-The
Roles of Power, Trust and Value," Proceedings of the 36th Hawaii International
Conference on System Sciences Waikoloa, Hawaii IEEE Computer Society, p. 10.
Chia, R., and Langley, A. 2004. "The First Organization Studies Summer Workshop:
Theorizing Process in Organizational Research " Organization Studies (25:8), p.
1486.
Comegys, C., Hannula, M., and Vaisanen, J. 2006. "Longitudinal Comparison of Finnish
and US Online Shopping Behaviour among University Students: The Five-Stage
Buying Decision Process," Journal of Targeting, Measurement and Analysis for
Marketing (14:4), pp. 336-356.
Cooper, R.B., and Zmud, R.W. 1990. "Information Technology Implementation
Research: A Technological Diffusion Approach," Management Science (36:2), pp.
123-139.
Dwyer, F.R., Schurr, P.H., and Oh, S. 1987. "Developing Buyer-Seller Relationships,"
The Journal of Marketing (51:2), pp. 11-27.
Einwiller, S. 2001. "The Significance of Reputation and Brand for Creating Trust in the
Different Stages of a Relationship Between an Online Vendor and Its Customers,"
Proceedings of the 8th Research Symposium on Emerging Electronic Markets
Maastricht,Netherlands, p. 18.
Frambach, R.T., and Schillewaert, N. 2002. "Organizational Innovation Adoption: A
Multi-Level Framework of Determinants and Opportunities for Future Research,"
Journal of Business Research (55:2), pp. 163-176.
Gable, G. 2010. "Strategic Information Systems Research: An Archival Analysis," The
Journal of Strategic Information Systems (19:1), pp. 3-16.
Guttman, R.H., Moukas, A.G., and Maes, P. 1998. "Agent-Mediated Electronic
Commerce: A Survey," Knowledge Engineering Review (13:2), pp. 147-159.
Haddara, M., and Zach, O. 2011. "ERP Systems in SMEs : A Literature Review,"
Proceedings of the 44th Hawaii International Conference on System Sciences
Kauai, Hawaii IEEE Computer Society, pp. 1-10.
Hakansson, N.H., Kunkel, J.G., and Ohlson, J.A. 1982. "Sufficient and Necessary
Conditions for Information to Have Social Value in Pure Exchange," The Journal
of Finance (37:5), pp. 1169-1181.
Hsieh, H.F., and Shannon, S.E. 2005. "Three Approaches to Qualitative Content
Analysis," Qualitative Health Research (15:9), pp. 1277-1288.
Huizingh, E.K.R.E., and Brand, M.J. 2009. "Stepwise Innovation Adoption: A Neglected
Concept in Innovation Research," International Journal of Technology
Management (45:3), pp. 267-281.
Jeyaraj, A., Rottman, J.W., and Lacity, M.C. 2006. "A Review of the Predictors,
Linkages, and Biases in IT Innovation Adoption Research," Journal of
Information Technology (21:1), pp. 1-23.
Karahanna, E., Agarwal, R., and Angst, C.M. 2006. "Reconceptualizing Compatibility
Beliefs in Technology Acceptance Research," MIS Quarterly (30:4), pp. 781-804.
Kartam, N.A. 1996. "Making Effective Use of Construction Lessons Learned in Project
Life Cycle," Journal of Construction Engineering and Management (122:1), pp.
14-21.
Kimberly, J.R., and Evanisko, M.J. 1981. "Organizational Innovation: The Influence of
Individual, Organizational, and Contextual Factors on Hospital Adoption of
Technological and Administrative Innovations," Academy of Management Journal
(24:4), pp. 689-713.
Klein, K.J., and Sorra, J.S. 1996. "The Challenge of Innovation Implementation,"
Academy of Management Review (21:4), pp. 1055-1080.
Krippendorff, K. 2004. Content Analysis: An Introduction to its Methodology. Beverly
Hills, CA: SAGE PublicationsNewbury Park.
Langley, A. 2007. "Process Thinking in Strategic Organization," Strategic Organization
(5:3), p. 271.
Luftman, J. 2000. "Assessing Business-IT alignment Maturity," Communications of the
Association for Information Systems (4:14), pp. 1-51.
Markus, M.L., and Tanis, C. 2000. "The Enterprise Systems Experience-from Adoption
to Success," in Zmud, R.W. (Ed.), Framing the Domains of IT Management:
Projecting the Future Through the Past. Cincinnati, OH: Pinnaflex Educational
Resources, Inc., pp. 173-207.
Markus, M.L., Tanis, C., and Van Fenema, P.C. 2000. "Enterprise Resource Planning:
Multisite ERP Implementations," Communications of the ACM (43:4), pp. 42-46.
Masset, B., and Sekkat, I. 2011. "Implementation of Customer Relationship Management
in the Cloud," in: School of Business and Engineering. University of Halmstad.
Mendelssohn, J. 1991. "Small Firms and the Marketing Mission," Accountancy
(107:1169), pp. 96-97.
Mergel, I., and Bretschneider, S.I. 2013. "A Three‐ Stage Adoption Process for Social
Media Use in Government," Public Administration Review (73:3), pp. 390–400.
Moore, G.C., and Benbasat, I. 1991. "Development of an Instrument to Measure the
Perceptions of Adopting an Information Technology Innovation," Information
Systems Research (2:3), pp. 192-222.
Ng, C.S.P., and Gable, G.G. 2009. "Maintaining ERP Packaged Software–A Revelatory
Case Study," Journal of Information Technology (25:1), pp. 65-90.
Oh, L.-B., Phua, T.-W., and Teo, H.-H. 2007. "A Conceptual Model for IT-Enabled
Enterprise Risk Management in Financial Organisations," Proceedings of the 15th
European Conference on Information Systems, St Gallen, Switzerland:
Association of Information Systems, p. 191.
Olhager, J., and Selldin, E. 2003. "Enterprise Resource Planning Survey of Swedish
Manufacturing Firms," European Journal of Operational Research (146:2), pp.
365-373.
Paul, A., and Kumbhojkar, N. 2012. "Counter-Intuitive Models to Accelerate Cloud
Computing Adoption by SMEs." Retrieved April 24, 2013, from
http://www.techmahindra.com/Documents/WhitePaper/2012/Cloud_computing_
White%20Paper_120512.pdf
Pereira, B. 2012. "How SAP Business ByDesign will Change the Way SMEs Do
Business." Retrieved June 25, 2012, from
http://www.insidesap.com.au/_blog/SME_Focus/post/How_SAP_Business_ByDe
sign_will_change_the_way_SMEs_do_business/
Plouffe, C.R., Hulland, J.S., and Vandenbosch, M. 2001. "Research Report: Richness
versus Parsimony in Modeling Technology Adoption Decisions—Understanding
Merchant Adoption of a Smart Card-Based Payment System," Information
Systems Research (12:2), pp. 208-222.
Poba-Nzaou, P., and Raymond, L. 2010. "Managing ERP System Risk in SMEs: A
Multiple Case Study," Journal of Information Technology (26:3), pp. 170-192.
Ragin, C.C. 2000. Fuzzy-set social science. USA: The University of Chicago Press.
Raihana, G.F.H. 2012. "Cloud ERP - A Solution Model," International Journal of
Computer Science and Information Technology & Security (2:1).
Ramdani, B., Kawalek, P., and Lorenzo, O. 2009. "Predicting SMEs' Adoption of
Enterprise Systems," Journal of Enterprise Information Management (22:1/2), pp.
10-24.
Repschlaeger, J., Wind, S., Zarnekow, R., and Turowski, K. 2012. "Selection Criteria for
Software as a Service: An Explorative Analysis of Provider Requirements,"
Proceedings of the 19th European Conference on Information Systems, Esade,
Barcelona: Association of Information Systems.
Robey, D., Ross, J.W., and Boudreau, M.-C. 2002. "Learning to Implement Enterprise
Systems: An Exploratory Study of the Dialectics of Change," Journal of
Management Information Systems (19:1), pp. 17-46.
Rogers, E.M. 1995. Diffusion of Innovations. Free Press.
Saeed, I., Juell-Skielse, G., and Uppström, E. 2011. "Cloud Enterprise Resource Planning
Adoption: Motives & Barriers," Proceedings of the 5th International Conference
on Research and Practical Issues of Enterprise Information Systems Aalborg,
Denmark.
Sen, A., and Pattanaik, P.K. 2012. "Necessary and Sufficient Conditions for Rational
Choice Under Majority Decision," Journal of Economic Theory (1:2), pp. 178-202.
Shanks, G., Parr, A., Hu, B., Corbitt, B., Thanasankit, T., and Seddon, P. 2000.
"Differences in Critical Success Factors in ERP Systems Implementation in
Australia and China: A Cultural Analysis," Proceedings of the 8th European
Conference on Information Systems, Vienna, Austria: Association of Information
Systems, pp. 537-544.
Shaul, L., and Tauber, D. 2012. "CSFs Along ERP Life-Cycle in SMEs: A Field Study,"
Industrial Management & Data Systems (112:3), pp. 2-2.
Shoham, A. 1992. "Selecting and Evaluating Trade Shows," Industrial Marketing
Management (21:4), pp. 335-341.
Thong, J. 1999. "An Integrated Model of Information Systems Adoption in Small
Businesses," Journal of Management Information Systems (15:4), pp. 187-214.
Thong, J.Y.L., and Yap, C.S. 1995. "CEO Characteristics, Organizational Characteristics
and Information Technology Adoption in Small Businesses," Omega (23:4), pp.
429-442.
Truman, C., and Raine, P. 2002. "Experience and Meaning of User Involvement: Some
Explorations from a Community Mental Health Project," Health & Social Care in
the Community (10:3), pp. 136-143.
Tsai, W.H., Lee, P.L., Shen, Y.S., and Lin, H.L. 2011. "A Comprehensive Study of the
Relationship between Enterprise Resource Planning Selection Criteria and
Enterprise Resource Planning System Success," Information & Management
(49:1), pp. 36–46.
Varshney, U., Vetter, R.J., and Kalakota, R. 2000. "Mobile Commerce: A New Frontier,"
Computer (33:10), pp. 32-38.
Verville, J., and Halingten, A. 2003. "A Six-Stage Model of the Buying Process for ERP
Software," Industrial Marketing Management (32:7), pp. 585-594.
Walther, S., Plank, A., Eymann, T., Singh, N., and Phadke, G. 2012. "Success Factors
and Value Propositions of Software as a Service Providers–A Literature Review
and Classification," Proceedings of the 18th Americas Conference on Information
Systems, Seattle, Washington.
Wang, X., Conboy, K., and Pikkarainen, M. 2012. "Assimilation of Agile Practices in
Use," Information Systems Journal (22:6), pp. 435-455.
Wang, Y.-M., Wang, Y.-S., and Yang, Y.-F. 2010. "Understanding the Determinants of
RFID Adoption in the Manufacturing Industry," Technological Forecasting and
Social Change (77:5), pp. 803-815.
Webster, J., and Watson, R.T. 2002. "Analyzing the Past to Prepare for the Future:
Writing a Literature Review," MIS Quarterly (26:2), pp. xiii-xxiii.
Wind, S., Repschlaeger, J., and Zarnekow, R. 2012. "Towards a Cloud Computing
Selection and Evaluation Environment for Very Large Business Applications,"
Proceedings of the 18th Americas Conference on Information Systems, Seattle,
Washington: Association of Information Systems.
Yap, C.-S., Thong, J.Y., and Raman, K. 1994. "Effect of government incentives on
computerisation in small business," European Journal of Information Systems
(3:3), pp. 191-206.
Yu, C.-S. 2005. "Causes Influencing the Effectiveness of the Post-Implementation ERP
System," Industrial Management & Data Systems (105:1), pp. 115-132.
Zhu, K., Dong, S., Xu, S.X., and Kraemer, K.L. 2006. "Innovation Diffusion in Global
Contexts: Determinants of Post-Adoption Digital Transformation of European
Companies," European Journal of Information Systems (15:6), pp. 601-616.
Zhu, K., Kraemer, K., and Xu, S. 2003. "Electronic Business Adoption by European
Firms: A Cross-Country Assessment of the Facilitators and Inhibitors," European
Journal of Information Systems (12:4), pp. 251-268.
Zhu, K., and Kraemer, K.L. 2005. "Post-Adoption Variations in Usage and Value of E-
Business by Organizations: Cross-Country Evidence from the Retail Industry,"
Information Systems Research (16:1), pp. 61-84.