Many argue that offshoring is an inexorable trend, since a variety of information technology (IT) skills have become global commodities and they are vastly cheaper in other parts of the world. According to this view, most IT work would be drained from the United States to overseas locations. However, the loss of jobs to offshoring has increased pressure to impose restrictions. On the supply side, as IT salaries in outsourcing vendor nations increase, they become less attractive for offshoring. The literature identifies multiple factors--some enhancing, others inhibiting--that affect the growth of offshoring. In this paper, we attempt to add to that knowledge by asking, "What are the mechanics by which these factors interact to produce the observed growth in IT offshoring?" We use the system dynamics methodology to build a two-country simulation model of offshoring growth that captures individual cause-effect relationships generated by its supply and demand drivers. Examined as a whole, these individual relationships reveal larger feedback loops that constitute the mechanism underlying offshoring growth between the two countries. Simulation experiments show how the dynamic behavior of offshoring is likely to evolve beyond the current high-growth period. The model contributes to our understanding of offshoring by offering a causal foundation for its growth pattern. It can also be used to computationally study different scenarios of offshoring growth.
As demand for online network services continues to grow, service providers are looking to meet this need and avail themselves of business opportunities. However, despite strong growth in demand,providers continue to have dif .culty achieving profitability, customer churn remains high,and network performance continues to draw complaints. We suggest that strategicbusiness planning for network services would benefit from a systems thinking approach that analyzes the feedback effects present in the underlying business process. These feedback loops can be complex and have significant impact n business performance. For instance, while the size of a providers customer base depends on price and network performance, network performance is itself dependent on the size of the customer base. In this paper, we develop a planning model that represents these feedback effects using the finite difference equations methodology of systems dynamics.The model is validated by showing its fit with essential characteristics of the underlying problem domain,and by showing its ability to rep- licate observed reference mode behaviors.Simulations are then carried out under a variety of scenarios to examine issues important to service providers.Among other findings,the simulations suggest that (a) under flat-rate pricing, lowering price to increase customer base can hurt profitability as well as network performance; (b) under usage-based pricing, lowering price need not necessarily lead to a larger customer base; and (c) in addition to price, the customers of threshold of tolerance for performance degradation plays a significant role in balancing market share with profitability. We briefly present a prototype decision support system based on the systems thinking approach, and suggest ways in which it could be used to help business planning for network services.
The pervasive role of telecommunications in contemporary commerce is well documented, and has dramatically increased the demand for services. Across the world, countries are seeking to improve telecommunications infrastructure and benefit from anticipated increases in economic activity, and a causal relation between the two is often tacitly assumed. This paper analyzes aggregate data at the national level to see if there is any empirical evidence that supports this assumption. We apply the well established Granger test for causality using time series data for levels of telecommunications infrastructure and economic activity from thirty countries. We find that the evidence for causality from levels of telecommunications infrastructure to economic activity is stronger than that for causality in the opposite direction. Moreover, this pattern appears to hold for both industrialized and developing economies, even though the former has strong service sectors that are heavily dependent on telecommunications. These findings provide additional insights into the complex relationship between telecommunications and economic activity. Some potential policy implications are also discussed. Granger causality tests have not seen much application in the IS Literature, and we mention some IS research issues that may benefit from such analysis.