CLOUD ERP ADOPTION-A PROCESS VIEW APPROACH

Siti Aisyah Salim, Information Systems School, Queensland University of Technology, Australia,

sitiaisyah.salim@student.qut.edu.au

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.

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