Stages of growth models have been used widely in both organizational research and information technology management research. According to King and Teo (1997), these models describe a wide variety of phenomena – the organizational life cycle, product life cycle, biological growth, stages of growth in information systems, growth model for integration between business planning and information systems planning, electronic commerce evolution, stages of knowledge management technology, and a number of other interesting developments in time perspectives. These models assume that predictable patterns (conceptualized in terms of stages or levels) exist in the growth of organizations and organizational parts, the sales levels of products, and the growth of living organisms. These stages are (1) sequential in nature, (2) occur as a hierarchical progression that is not easily reversed, and (3) evolve a broad range of organizational activities and structures. This chapter starts with an introduction to stages of growth models. In the following sections we present the three-stage model for the evolution of IT outsourcing relationships (Gottschalk & Solli-Sæther, 2006). The three stages are labelled cost stage, resource stage, and partnership stage respectively. Theory-based benchmark variables for measuring maturity in IT outsourcing relationships are presented, followed by the stage hypothesis and a description of how benchmark variables are used to indicate characteristics at each stage of growth. Finally in this chapter, we present results from an exploratory study testing the stage model. The purpose of this chapter is to develop a framework for improved understanding of the current situation in an IT outsourcing relationship in terms of a specific stage, to develop strategies for moving to a higher stage in the future, and to learn from earlier stage experience.
TopStages Of Growth Models
Various multistage models have been proposed for organizational evolution over time. For example, Nolan (1979) introduced a model with six stages for information technology maturity in organizations, which later was expanded to nine stages. Earl (2000) suggested a stages of growth model for evolving the e-business, consisting of the following six stages: external communication, internal communication, e-commerce, e-business, e-enterprise, and transformation, while Rao and Metts (2003) describe a stage model for electronic commerce development in small and medium sized enterprises. In the area of knowledge management, Housel and Bell (2001) developed a five level model. In the area of knowledge management systems, Gottschalk (2007) developed a four-stage model applied to knowledge management in law enforcement. Gottschalk and Tolloczko (2007) developed a maturity model for mapping crime in law enforcement, while Gottschalk and Solli-Sæther (2008) developed a maturity model for e-government interoperability. Each of these models identifies certain characteristics that typify firms in different stages of growth.
The concept of stages of growth has been widely employed for many years. Already two decades ago, Kazanjian and Drazin (1989) found that a number of multistage models have been proposed, which assume that predictable patterns exist in the growth of organizations, and that these patterns unfold as discrete time periods best thought of as stages. These models have different distinguishing characteristics. Stages can be driven by the search for new growth opportunities or as a response to internal crises. Some models suggest that organizations progress through stages while others argue that there may be multiple paths through the stages. Kazanjian (1988) applied dominant problems to stages of growth. Dominant problems imply that there is a pattern of primary concerns that firms face for each theorized stage. In criminal organizations, for example, dominant problems can shift from lack of skills to lack of resources to lack of strategy associated with different stages of growth.
Kazanjian and Drazin (1989) argue that either implicitly or explicitly, stages of growth models share a common underlying logic. Organizations undergo transformations in their design characteristics, which enable them to face the new tasks or problems that growth elicits. The problems, tasks or environments may differ from model to model, but almost all suggest that stages emerge in a well-defined sequence, so that the solution of one set of problems or tasks leads to the emergence of a new set of problems and tasks, that the organization must address.
In IT outsourcing relationships it is often a requirement in the contracts that a relatively intimate relationship should be established between the outsourcing company and the outsourcing vendor (Kern & Blois, 2002). The existence of such a relationship may reduce the need for detailed monitoring of the performance of the outsourcing vendor by the outsourcing company. Ongoing relationships may lead to the establishment of trust and perceptions of common interest. The more the outsourcing vendor interacts with the outsourcing company the more comfortable they are likely to feel with each other (Elitzur & Wensley, 1998). As most outsourcing relationships last for several years, it is not unlikely that they develop or transform from one stage to another as time passes by.
This chapter applies cumulative theory that suggests stages of growth over time in organizational development (Frankfort-Nachmias & Nachmias, 2002; Nunnally & Bernstein, 1994). The research methodology applied in is content analysis (Weber, 1990) of outsourcing theories. This chapter uses IT outsourcing related literature and research to develop stages of growth model for IT outsourcing relationships. The model presented in the following sections might serve as a conceptual basis for further studies of this kind of relationship.