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Follow APA 7 guidelines See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/220306470 IT innovation adoption in the government sector: Identifying the critical success factors Article  in  Journal of Enterprise Information Management · March 2006 DOI: 10.1108/17410390610645085 · Source: DBLP CITATIONS 228 READS 5,964 1 author: Some of the authors of this publication are also working on these related projects: Using Big Data and Artificial Intelligence in Business to Impact Global Challenges View project Muhammad Mustafa Kamal Coventry University 56 PUBLICATIONS   1,964 CITATIONS    SEE PROFILE All content following this page was uploaded by Muhammad Mustafa Kamal on 23 December 2015. 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Kamal Article information: To cite this document: M.M. Kamal, (2006),"IT innovation adoption in the government sector: identifying the critical success factors", Journal of Enterprise Information Management, Vol. 19 Iss 2 pp. 192 - 222 Permanent link to this document: http://dx.doi.org/10.1108/17410390610645085 Downloaded on: 23 December 2015, At: 02:25 (PT) References: this document contains references to 90 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 4566 times since 2006* Users who downloaded this article also downloaded: Chinyao Low, Yahsueh Chen, Mingchang Wu, (2011),"Understanding the determinants of cloud computing adoption", Industrial Management & Data Systems, Vol. 111 Iss 7 pp. 1006-1023 http:// dx.doi.org/10.1108/02635571111161262 Kirsten M. Rosacker, David L. Olson, (2008),"Public sector information system critical success factors", Transforming Government: People, Process and Policy, Vol. 2 Iss 1 pp. 60-70 http:// dx.doi.org/10.1108/17506160810862955 Yazn Alshamaila, Savvas Papagiannidis, Feng Li, (2013),"Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework", Journal of Enterprise Information Management, Vol. 26 Iss 3 pp. 250-275 http://dx.doi.org/10.1108/17410391311325225 Access to this document was granted through an Emerald subscription provided by emerald-srm:328478 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. 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Kamal Department of Information Systems and Computing, Brunel University, Uxbridge, UK Abstract Purpose – This paper aims to acquire underlying knowledge of how IT is adopted in private sector organisations and further explore what factors impact its adoption (optimistically and pessimistically). Design/methodology/approach – An interpretive and qualitative multiple case study approach was selected to test and validate the conceptual model empirically. The selection of the interpretivism viewpoint in the context of this research is to understand how government organisations adopt new technologies and support their decisions and actions. The interpretive research methodology is related to data gathering and generating solid descriptions and interpretations and further allows theory building. Through a multiple case study strategy, factors influencing EAI adoption in the government sector are investigated. In doing so, various data collection methods such as interviews, documentation, and observation are adopted. Findings – The author identified 42 critical success factors (CSF) for IT innovation adoption. These factors provide sufficient understanding of their importance when adopting an innovation (technology). The author exploits these factors further when developing a conceptual EAI adoption model and also presents a taxonomy of the IT innovation adoption process. This taxonomy is an eight-stage adoption process based on studying 11 IT adoption models. Simply acquiring or adopting a technology is not sufficient – in order to obtain the anticipated benefits, IT must be deployed and used appropriately by the organisation and its intended users. However, this taxonomy would further assist in identifying factors affecting IT innovation adoption at each stage of the adoption process. Originality/value – The proposed conceptual IT innovation adoption model is a contribution to theory. This model presents a detailed list of factors that impact IT adoption in government sector organisations. The author conjectures that each factor within this model signifies its importance and must be considered by organisations while adopting innovation (technology). The taxonomy of the IT innovation adoption process is another contribution. This taxonomy is developed by studying 11 IT adoption models as presented in this paper. This taxonomy identifies the pre-adoption and post-adoption stages of an adoption process. Further in this taxonomy, the author identifies stages where the organisation is impacted, i.e. the pre-adoption stage and post-adoption, where individual adopters are impacted. Keywords Communication technologies, Innovation, Critical success factors, Government Paper type General review Introduction The post-Second World War era has witnessed dramatic expansion in governments’ social and economic responsibilities (Ahmad and Zink, 1998). Citizens have increased their demands for government-sponsored social and economic programs. The need for expeditious responses to those demands has led to rapid expansion in the size and number of government agencies and to an almost continual series of agency reforms and reorganisations. Many reform initiatives have involved governments’ information systems (IS) as organisations have tried to maintain reliable, high-quality, and The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm JEIM 19,2 192 Journal of Enterprise Information Management Vol. 19 No. 2, 2006 pp. 192-222 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410390610645085 D ow nl oa de d by B ru ne l U ni ve rs it y L on do n A t 02 :2 5 23 D ec em be r 20 15 ( P T ) up-to-date information. To meet these challenges, government sector organisations in some countries (such as Singapore) have frequently been the early adopters of a wide variety of information technologies. Indeed, one of the most visible phenomena of the information age is a direct result of private organisations and government-developed innovations and applications of information technology. Increased response to the citizenry has often been the avowed goal of government sector organisations in the adoption of information technology. The reality is that without the use of information technology and computing, the mere administration of today’s large and complex social and economic programs would simply not be possible. A considerable gap is seen between IT adoption in private sector and government sector organisations, in provisions of early and successful IT adoption, and in identifying its impact. Themistocleous et al. (2004) report in this regard that government sector organisations introduce information and communication technology (ICT) reactively as compared to private sector organisations. The author supports that this may be attributed to the bureaucracy and the culture that exists in many government sector organisations. Conversely, Cardozo et al. (1993) report that innovation is generally considered to be one of the key drivers of corporate success. However, the author states that apart from being reactive rather than proactive, one of the other main issues several government organisations face in this perspective is how to successfully adopt and implement their innovations. In the past three decades, extensive research has been conducted to identify various factors for the success and failure of innovative technologies (see, for example, Montoya-Weiss and Calantone, 1994). The focal point of this research relevant to the government sector is that many new technologies are unsuccessful, and this may be attributed to the lack of realisation of citizenry’s requirements, the absence of a project champion, relative superiority over the existing alternatives, or lack of ample acquaintance with the innovation. Thus, for government authorities to be successful in introducing innovations, they need to have a thorough understanding of their IT capacity, relative advantage, existing organisational operations, managerial capabilities and other processes and factors influencing the government authority’s decision to either adopt the innovation or not. In this respect, the research on the adoption of innovation offers a significant contribution to government sector organisations. The objective of this paper is to identify various factors that influence organisational decisions on IT innovation adoption. In essence, two types of adoption streams can be identified within this perspective: (1) the decision made by the government sector organisation as a whole to adopt innovation; and (2) the impact of innovation on the individual adopter of the innovation within the organisation. The author attempts to incorporate research findings and present a model that encompasses factors from both streams. The model of innovation adoption derived within this paper can serve as a framework of references and that the decision makers within the government sector may use it for a specific information technology adoption (e.g. adopting integration technology – or technologies – to incorporate their disparate legacy information systems within their departments and with external entities for a IT innovation adoption 193 D ow nl oa de d by B ru ne l U ni ve rs it y L on do n A t 02 :2 5 23 D ec em be r 20 15 ( P T ) seamless flow of information and interaction with their stakeholders). However, to explore the aforementioned research area in depth, the author commences by describing innovation adoption process in the organisations. Furthermore, the author investigates and analyses diverse IT adoption models and presents a classification of IT adoption models. Besides this, based on the research findings, a taxonomy of the IT innovation adoption process is presented. Moreover, the author discusses IT innovation adoption in government organisations. Thereafter, the author illustrates the impact of IT innovation adoption. Subsequently, the author attempts to describe a comprehensive understanding of the factors that influence the organisational IT innovation adoption decision. This is by integrating findings from diverse theories in the normative literature. The author conjectures that coalescing different perspectives on IT innovation adoption in the organisational context contributes to other studies that have reviewed more specific areas within this domain. Following this discussion, the author proposes an IT innovation adoption model for government sector organisations and summarises the factors identified. The factors reported in this model will support the author’s prime research objective, i.e. to identify key factors influencing the adoption of integration technology such as enterprise application integration (EAI) in integrating customer relationship management (CRM) applications with legacy back office systems in an electronic government (e-government) environment. The IT innovation adoption process in organisations The IT innovation adoption process concerns a sequence of stages that an organisation passes through before initiating a new technology within the organisation. In this respect, Rogers (1995) defines adoption as: . . . the process through which an individual or other decision making association passes from first knowledge of innovation, to forming an attitude towards innovation, to a decision to adopt or reject, to implementation of new idea, and to confirmation of this decision. With respect to organisational adoption, Gopalakrishnan and Damanpour (1997) state two main distinguishable stages, i.e. the initiation and the implementation of the innovation. Gopalakrishnan and Damanpour (1997) report that the actual adoption decision occurs between the initiation and implementation phases. In the initiation stage, the organisation becomes aware of the innovation, forms an attitude towards it acceptance, and further evaluates the new technology or idea (Gopalakrishnan and Damanpour, 1994); the initiation stage encompasses the awareness, consideration and intention stages. In the implementation stage, the organisation decides to purchase and make use of the innovation technology. However, this organisational adoption decision merely marks the beginning of the actual implementation of an innovation. From this point onwards in the adoption process, acceptance or assimilation within the organisation becomes important. The innovation process can only be considered a success to the extent that innovation is accepted and integrated into the organisation (Rogers, 1995; Gopalakrishnan and Damanpour, 1997) and the target individual adopters demonstrate commitment by continuing to use the technology over a period of time (Bhattacherjee, 1998). Thus the full and actual adoption of (many) innovations in an organisational context implies that adoption also occurs within the organisation, at the individual adopter level. Bhattacherjee (1998) reports that this can be termed JEIM 19,2 194 D ow nl oa de d by B ru ne l U ni ve rs it y L on do n A t 02 :2 5 23 D ec em be r 20 15 ( P T ) intra-organisational acceptance of innovation. Rogers (1995) and Ram and Jung (1991) report a pessimistic viewpoint, where an instance where the utilisation of innovation at an individual level within an organisation becomes tentative and contingent upon a former organisational adoption decision is referred to as a “contingent innovation decision” or “forced adoption”. The different phases of innovation adoption are shown in Figure 1. Identifying and analysing IT adoption models Research on IT innovation adoption and diffusion has long converged on a core set of theoretical models that seek to explain target adopter attitudes and their innovation-related behavior (Gallivan, 2001). The author identified manifold information technology adoption models from the research conducted in the past. These core models are diffusion of innovations (Rogers, 1983), the theory of reasoned action (Ajzen and Fishbein, 1975), the technology acceptance model (Davis, 1989), the theory of planned behavior (Ajzen, 1985), the IT innovation adoption research model (Agarwal and Prasad, 1998), stages of innovation adoption (Becker and Whisler, 1967), and innovation adoption and implementation (Gallivan, 2001). Others reported in the normative literature have received widespread validation for many technological innovations and also where individual autonomy is permitted to adopt or reject an innovation. Increasing evidence suggests that most of the traditional models neglect the realities of implementing technology innovations within organisations, especially when individual adoption decisions are made at the organisational, division, or workgroup levels, rather than at the individual level (Fichman and Kemerer, 1997; Orlikowski, 1993). Under these conditions, which Zaltman et al. (1973) and Gallivan (2001) also denoted “contingent authority innovation decisions”, organisations make the initial decision to adopt and the targeted users have few alternatives but to adopt the innovation and make the necessary adjustments for using it to perform their jobs. Thus, rather than fitting the conditions under which traditional models of innovation adoption and diffusion (Rogers, 1983) or technology acceptance (Davis, 1989) were created, the reality of innovation adoption and implementation within organisational settings may require modifications to these models. Joshi (1991) reports in this context that successful implementation of modern innovative technologies and management science is critical for enhancing the productivity and the competitive position of an organisation. Karahanna et al. (1999) support this assertion and state that the process Figure 1. Innovation adoption process IT innovation adoption 195 D ow nl oa de d by B ru ne l U ni ve rs it y L on do n A t 02 :2 5 23 D ec em be r 20 15 ( P T ) http://www.emeraldinsight.com/action/showImage?doi=10.1108/17410390610645085&iName=master.img-001.jpg&w=181&h=112 of information technology adoption and use is critical to deriving the benefits of information technology. Karahanna et al. (1999) state that integration of innovation with diverse aspects of the organisation including legacy systems in different departments is a major concern for organisations, and also report an issue of integration in the traditional proposed innovation adoption models. These models provide extensive discussions on the process of innovation adoption, but no one model discusses comprehensively the need for integration of these innovations in their innovation adoption process. As mentioned perviously, this issue of integration in government sector organisations is addressed as a prime objective in the author’s research. Additional literature streams of organisational process research and further stage research (Prescott and Conger, 1995) must be considered to develop suitable models to understand the processes and outcomes relevant to individual, workgroup, and company-wide innovation adoption and integration. In the following, the author presents a framework of 11 IT adoption models, but given the constrains on time and other resources, the author briefly describes four IT adoption models. This section is further organised according to the models shown in Figure 2. The author commences with Lewin’s model (Lewin, 1952). The technologically based organisational innovation and adoption literature is based on the early social change model presented by Lewin (1952). According to Lewin’s model, the process of change is a sequence of three steps: (1) unfreezing; (2) moving (or change); and (3) refreezing. Dasgupta (1997) explains that these steps remain in dynamic social equilibrium changing from one stage to another. Unfreezing prepares the system for change; in moving the group or unit or system learns new behavior patterns and assimilates the ramification of change. Refreezing refers to making these patterns of behavior a permanent part of the system. According to Pierce and Delbecq (1977) and Cooper and Zmud (1990) the organisational innovation process consists of three stages: (1) initiation; (2) adoption; and (3) implementation. These authors define these stages as follows. Initiation is the pressure to change, and gathering and evaluating the information regarding innovation; adoption involves the decision to commit resources to it; and implementation refers to development of and installation activities to ensure that expected benefits of innovation are realised. The initiation stage of the innovation adoption process (see Figure 2) corresponds to the unfreezing stage of Lewin’s change model, while adoption is only a part of the change step of Lewin’s model. Adoption only involves the decision to commit resources to innovation. Learning behavior patterns and assimilation of the ramification of change, which are a part of the moving step and the whole refreezing step, are included in the implementation stage of the organisational innovational model. JEIM 19,2 196 D ow nl oa de d by B ru ne l U ni ve rs it y L on do n A t 02 :2 5 23 D ec em be r 20 15 ( P T ) The stages of innovation adoption presented by Becker and Whisler (1967) are based on four stages of the innovation process. These four stages are: (1) stimulus; (2) conception; (3) proposal; and (4) adoption. Becker and Whisler (1967) report that the stimulus to the organisation to take the lead in the use of new idea is mediated through individual action. In the second stage, they conceive a plan of action that the organisation should pursue. Again this is an individual act and in highly innovative organisations is presumably exhibited by a number of members simultaneously, each pursuing their own particular conception of what is good for the organisation. In the third stage, a formal proposal is made for the Figure 2. IT innovation adoption models and processes IT innovation adoption 197 D ow nl oa de d by B ru ne l U ni ve rs it y L on do n A t 02 :2 5 23 D ec em be r 20 15 ( P T ) http://www.emeraldinsight.com/action/showImage?doi=10.1108/17410390610645085&iName=master.img-002.jpg&w=335&h=350 approval of others in the organisation. The final stage is that of adoption (or rejection). This fourth stage is group process. Becker and Whisler (1967) noted that the factors that may enhance the level of activity in the first three stages might discourage the rate of adoption. The conceptual model adopted for research by Darmawan (2001) is based on a variety of factors that may influence the outcome of adopting and implementing IT in local governments. These factors range from technological and institutional to personal, social and economic factors. Past research in innovation highlights the importance of human factors, organisational factors, technological factors, and the environmental factors for successful adoption and implementation of an innovation (Tornatzky and Klein, 1990; and Zaltman et al., 1973). By synthesizing various stages of innovation adoption process proposed by previous authors, Darmawan (2001) presented a four phase conceptual model of innovation adoption and implementation process. These four-phase innovation adoption processes consist of initiation phase, adoption phase, implementation phase, and evaluation phase. This four-phase innovation adoption process can also be observed at several levels. Possible adopters of the technology are organisations, organisational units, organisational sub units, and individuals. In Darmawan’s (2001) study, two levels of adoption are considered. The first level of adoption – organisational level adoption – starts when an organisation begins to realise the need for strategic change and decides to incorporate IT. It ends with acquisition of the technology. The second level of adoption – individual level adoption – commences with the acquisition of the technology, and finishes when the technology is utilised. However, given the constraints on time and other resources, this research study does not seek to examine all possible models. The author concluded from the models shown in Figure 2 that most innovation theorists have terminated their innovation analysis at the adoption stage. What must be done thereafter in terms of actually changing the organisation is the integration of innovative technology with other legacy systems in the organisation. All these models discuss the process of innovation adoption and or diffusion in a broad spectrum and in diverse perspectives, but the author asserts that these models fall short in explaining the post-adoption (technology stance after adoption) viewpoint of the innovative technologies. The author suggests further research from perspective. In the following section, the author presents a taxonomy of the IT innovation adoption process. A taxonomy of the IT innovation adoption process IT is viewed as innovation when it is felt by potential adopters to be relatively new (Rogers, 1995). Knol and Stroeken (2001) state that IT at a high aggregation level is a new technology paradigm affecting the management and control of production and service systems throughout the economy, based on an inter-connected set of radical innovations in electronic computers, software engineering, control systems, integrated circuits and telecommunications, which have drastically reduced the cost of storing, processing, communication and disseminating information. Similarly, according to Huff and Munro (1985), information technology refers to the broad range of technologies involved in information processing and handling, such as computer hardware, software, telecommunications and office automation, and includes such technologies as new systems development methodologies. From a more pragmatic and JEIM 19,2 198 D ow nl oa de d by B ru ne l U ni ve rs it y L on do n A t 02 :2 5 23 D ec em be r 20 15 ( P T ) technological perspective IT is related to all technologies used to collect, store, process, graphically display and transport data, and therefore encompasses computer equipment and system programs, application programs and communication facilities. The characteristic of IT is that it is a generic technology that can be applied in many ways in diverse environments (Knol and Stroeken, 2001). In this section, the author provides a detailed overview of the IT innovation adoption process. The innovation adoption decision process leading to institutionalisation of usage may be conceptualised as a temporal sequence of steps through which an individual organisation passes from initial knowledge of an innovation, to forming a favourable or unfavourable attitude towards it, to a decision to adopt or reject it, to putting the innovation to use, and to finally seeking reinforcement of the adoption decision made (Rogers, 1983). Rogers (1995) reports that innovation is an idea, practice or object that is perceived as new by individual or other unit of adoption. The author reports here that simply acquiring or adopting a technology is not sufficient; in order to obtain the anticipated benefits, it must be deployed and used appropriately by the organisation and its intended users. In the following model, … SYSTEM ANALYSIS AND DESIGN 5 Introduction System Analysis and Design (SAD) refers to a broad term which is used to describe methodologies and frameworks that develop top quality information systems that combine people, Information Technology (IT), and data to help in supporting the business requirements. There are various components which complement and support SAD. Cloud computing refers to the process of delivering computing services such as servers, analytics, software and networking over the internet to help increase the speed of innovation, enhance flexibility of resources, and create economies of scale in a business. The purpose of this research paper is to take a look into three concepts IaaS, PaaS, and SaaS. These concepts help in complementing the system analysis and design. IaaS refers to a cloud computing offering where the vendor gives users access to the computing resources such as the servers and networks. PaaS on the other hand provides users with a cloud environment where they can develop, manage and also deliver applications. SaaS gives the users access to the vendors cloud based software. Literature Review Infrastructure as a service (IaaS) Although the issue of data security is present in all service models the IaaS is very vulnerable because it is the location where the entire data is stored and where a network connection begins. Saed et al., 2018 is about the checklists and the guidelines to help in securing the IaaS layer in organizations. In ensuring data governance and security of IaaS layer a business should first identify the specific threats of the IaaS model layer. Businesses can also come up with security controls to help in protecting the infrastructures. Some of the threats that IaaS is exposed to includes the abuse of cloud, data loss, data theft, data leakages and account hijacking among others. IaaS is considered as one of the most important elements of the cloud computing because it is where the information and data is stored and hence it needs to be secure so that third parties cannot gain access to it. Platform as a service (PaaS) Olokunde et al., 2017 is an article that proposes a model to be used in evaluation of PaaS. There are various quality criteria that the authors propose for the evaluation model. One software developers should ensure that they create a platform that can be used easily. A good PaaS should be portable and that means that it should be easy to move it from one location to another. To ensure portability the software developers need to be easily installed and uninstalled from a location. Yasrab talks about the portability of the next generation of PaaS addressing the improvements which are expected in PaaS in cloud computing. The article also talks about the reason as to why the PaaS has been hyped so much. The demand for the software applications is currently going up and this gives IT managers and IT teams so much pressure. Hence the IT teams are seeking platforms to help them shift from the manual systems to faster and automated procedures in their businesses. Software as a service (SaaS) Loukis et al 2019 talks about the factors that determine the benefits and impacts of SaaS on the performance of organizations. From the research the authors discovered that the ability of an organization to adapt to the SaaS model has a positive impact on both the operational and innovation benefits gained from using SaaS. Some of the operational benefits of the use of SaaS include the reduction of the operating costs and the achievement of high quality levels of production. Additionally the use of SaaS in business helps in the improvement of the agility of an organization and also adaptation to the business challenges and environmental factors. Hyysalo, 2019 in the article talks about the influence of the customer success on the sustainable performance of the SaaS Company. According to this research article for organizations to achieve customer success they are needed to develop the capabilities which will help a business sense and seize opportunities as and at when they present themselves. The article proposes some of the ways in which businesses can build these capabilities. For instance in the sensing capabilities organizations can segment data to help identify the customer needs and wants faster. Analysis of Literature (evidence) Infrastructure as a service (IaaS) As seen in the literature review section the IaaS is exposed to a wide range of risks and challenges. One of the challenges in IaaS is the different points of vulnerability. When organizations shift to cloud, they tend to do a lift and shift where they move all the existing apps and solutions as if they were on-premise server and the reason for doing this is that it is cheaper compared to coming up with new ones. However this is not safe as it ignores that there are different points of vulnerability in the cloud environment when compared to an on-premise environment. Another source of risk in IaaS could be different locations since the locations will necessitate for additional firewall or routing rules to assist in the handling of traffic accordingly. The complexity of the IaaS is one of the sources of risk as well especially because of the different points of vulnerability. Platform as a service (PaaS) PaaS allows the software developers to develop applications with the in-built software components. There are various factors that ensure the effectiveness of PaaS and one of the factors proposed according to the literature review is portability. Portability is important since most people opt for cloud computing because of convenience and portability is one of the ways to offer convenience. The PaaS should also have an unlimited database customization and a customizable user interface. Additionally PaaS needs to ensure that the coding that is needed to be done is minimal and this will help lower the complexity of PaaS. Software as a service (SaaS) From the literature review there are various benefits of using Software as a service (SaaS) and this benefits include cost minimization. Since SaaS exists in a multi-tenant model it lowers the costs since the costs of the hardware and the software are low when compared to the costs in the traditional model. The maintenance costs are also low since the SaaS provider owns the environment which is split among customers. SaaS solutions exist in cloud environments which are scalable, in SaaS as opposed to the traditional model one does not have to buy a server. As a client, the SaaS allows for the flexibility to scale up or scale down. Conclusion Through system analysis and design processes organizations are able to analyze a situation in a business with an aim of improving it and creating better procedures and methods. Organizations can use cloud computing to help achieve operational efficiency and attain its set objectives. The research looks at the IaaS, PaaS and SaaS components of cloud computing and the application of the concepts in business. One of the benefits for the concepts in business is that they help in minimizing the costs of a business and automation of the organizational process and procedures. References Hyysalo, J. (2019). How can a Software as a Service (SaaS) company develop customer success processes to be a source of sustained performance?. Loukis, E., Janssen, M., & Mintchev, I. (2019). Determinants of software-as-a-service benefits and impact on firm performance. Decision Support Systems, 117, 38-47. 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