Stage Theory

Relating to rationalistic assumptions on technology adoption, the stage theory proposed by Nolan (1973), has also attracted the attention of several IS researchers. Stage theory is premised on the idea that organizations pass through various stages in assimilating technology (Gibson & Nolan, 1974). This progression is in successive and identifiable stages, and is described as an “evolutionary journey” for most firms (Earl, 2000, p.33).

Various stage models have been proposed to gauge the degree of maturity or evolution of an information system over time. According to King and Toe (1997), the models describe a wide variety of phenomena; organizational life cycle, product life cycle, biological life cycle, and so forth. Since stage theory was first introduced by Nolan (1973), the stage hypothesis has continued to draw attention from both practitioners and members of the academic community (Benbasat, Dexter, Drury, & Goldstein, 1984), and has been very influential in business and IS academic communities (A. Friedman, 1994; Galliers & Sutherland, 1994; J. L. King & Kraemer, 1984). Although the stage hypothesis is widely acknowledged, the stage model has also been criticised throughout this period for its simplicity (Benbasat, et al., 1984; J. L. King & Kraemer, 1984), its lack of empirical validation (J. L. King & Kraemer, 1984), and for having a lack of detail in different stages of growth (A. Friedman, 1994; J. L. King & Kraemer, 1984).

However, the model continues to be used by organizations, enabling IS managers to manage ICT effectively (Benbasat & Zmud, 1999) and it is important to note that those authors who criticise the model have not totally rejected it. With the emergence of the Internet and e-business, the stage hypothesis has attracted even more attention, and several “stages of growth models” have appeared to describe and explain the phases of development in the use and management of ICT in the e-commerce arena (Prananto, Marshall, & McKay, 2003; Prananto, McKay, & Marshall, 2001). These stage models (also termed “adoption ladders”) postulate that organizations move step-by-step from basic uses of the Internet, such as e-mail, to a higher level of sophistication, integrating business systems and redesigning business processes through the use of ICT (Martin &

Matlay, 2001). Each stage reflects a particular level of maturity in terms of the use and

58 management of ICT in an organization’s business activities (Damsgaard & Scheepers, 2000; Mendo & Fitzgerald, 2005). Although the empirical validation of the concept of

“stages” is limited, these models provide a basis for estimating the stages of growth or for understanding the hierarchical progression of e-business maturity in organizations.

Thus in order to get an understanding of the stage theory, three models that might be relevant to this study is presented.

2.4.1.1 Nolan’s model

Gibson and Nolan (1974) noted that organizations progress through a number of states when assimilating technology. They proposed that the growth of computing within an organization follows an S-shaped curve and can be divided into four stages; initiation, contagion, control, and integration (Gibson & Nolan, 1974; Nolan, 1973). Based on the analysis of ICT usage in a number of US firms Nolan (1979) proposed an evolutionary model by extending the four stage model to comprise six stages.

As illustrated in Figure 1, the categories of the six stages are; initiation, contagion, control, integration, data administration, and maturity. Nolan (1979) posited that growth phases can be identified primarily according to the level of data processing (DP) expenditure as a proportion of sales revenue. In addition to DP expenditure, he indicated four growth processes; application portfolio, data processing organization, data processing, planning and control and, user awareness. The growth progression will follow an S-curve over time. Each of these stages involves analysis of six benchmarks in addition to DP expenditure, namely; rate of ICT expenditure, technological configuration, application portfolio, ICT planning and control approaches, ICT management organization, and awareness of users.

59 Figure 1: Six stages of data processing growth (Nolan, 1979, p. 117).

Growth Processes

Burgess and Cooper (1998) propose the Model of Internet Commerce Adoption (MICA) to explain the different stages of e-commerce that small businesses pass through in developing their websites. The MICA model was based on an analysis of the metal fabrication industry of Australia. The model suggests that in developing commercial websites, organizations typically start by having a “presence” on the web and build on functionality over time as their level of technical skills/expertise in the use of Internet technologies increases.

The MICA model, as illustrated in Figure 2, describes the relative maturity of a business in Internet commerce. It consists of three layered stages and incorporates three levels of business process, developed from Ho’s(1997) Model that covers promotion, provision, and processing. At stage one, promotion; businesses are mainly using electronic channels to promote their products and service. Stage two, provision or consolidation,

Transition point

60 focuses on the interaction between the business and its customers. At Stage three, processing or the level of maturity, the organizationhas a fully integrated site to communicate between parties involved in a buyer-supplier relationship. The addition of layers is synonymous with the business moving from a static Internet presence, progressing through increasing levels of interactivity to a dynamic site incorporating value chain integration and innovation application to add value through information management and rich functionality (Timmers, 2000).

Figure 2: Model of Internet Commerce Adoption (MICA)(Burgess & Cooper, 1998).

Further, the MICA model provides a roadmap (an alternative representation as illustrated in Figure 3), which indicates where a business or industry sector is in its development of Internet Commerce application. The graph represents time and complexity versus functionality. The organization’s web site evolves from static to dynamic pages as it develops in functionality and complexity over time.

STAGE 3

61 Figure 3: Internet Commerce (IC) roadmap (Burgess & Cooper, 1998)

2.4.1.3 Martin and Matlay’s model

Similarly, Martin and Matlay (2001) show the adoption of e-commerce classified along steps of increasing complexity to full integration in an “adoption ladder”. This model is adapted from a Cisco-led Information Age-Partnership study on e-commerce in small businesses. This is depicted in Figure 4. The ladder shows that e-commerce adoption begins with the adoption of e-mail, progressing through the steps of adoption of a website, e-commerce, and e-business to a transformed organization.

Figure 4: Growth model adapted from Cisco led Information Age Partnership study on e-commerce in small business (cited in Martin & Matlay, 2001)

Functionality

62 Subsequent to Nolan’s model, Burgess and Cooperand Martin and Matlay have provided models to understand how an organization could place itself at a particular stage of ICT maturity. These models describe the elements within an organization. The Burgess and Cooper model and the stages of IC maturity in the Mckay, Marshall and Prananto model could be used as a lens to understand the progression of web site maturity. The elements describing IT maturity in Martin and Matlay’s Model, could be used as a guide to understanding how organizations progress in assimilating ICT technologies.