System optimization model of adoption of a new infrastructure with multi-resource and multi-demand sites

This study develops a conceptual system optimization model of adoption of a new infrastructure technology with multiple resource sites and multiple demand sites. With the model, this paper analyzes how the distance, spillover effect, demand, initial investment cost, and learning rate influence the adoption of the new infrastructure technology and presents optimization results of the model in different scenarios. The main findings of the study are: from the perspective of system optimization, (1) different distances among different resource-demand pairs will result in different adoption time of a new infrastructure; (2) technological spillover among different resource-demand pairs will accelerate the adoption of a new infrastructure; (3) it is hard to say that higher demand will pull faster adoption of a new infrastructure, and the optimal time of adopting of a new infrastructure is very sensitive to its technological learning rate

Adoption of an emerging infrastructure with uncertain technological learning and spatial reconfiguration

This paper develops a stylized (or conceptual) system optimization model to analyze the adoption of an emerging infrastructure associated with uncertain technological learning and spatial reconfigurations. The model first assumes that the emerging infrastructure will be implemented for the entire system when it is adopted. With the model, this paper explores (1) how the emerging infrastructure's initial investment cost, technological learning and its uncertainty, market size, and efficiency influence the adoption of the emerging infrastructure and (2) how the efficiency and investment cost of the associated technology (which will be located in a different place with the adoption of the emerging infrastructure) influence the adoption of the emerging infrastructure. Then, this paper extends the model and explores whether it is a better solution to implement the emerging infrastructure for part of the distance from resource site to demand site if its efficiency is a function of the implemented distance. With optimizations under three types of efficiecy dynamics, this paper finds that whether the emerging infrastructure should be implemented partly or entirely is not determined by the value of its efficiecy but by the dynamics of its efficiency

An exploratory study of the adoption of mobile telecommunications service in order to improve mobile health service development

Doctor of PhilosophyDepartment of Industrial & Manufacturing Systems EngineeringMalgorzata J. RysThis dissertation is the result of exploring the phenomenon of the adoption of a service innovation, in particular mobile telecommunications service, with the goal of informing the design of mobile health services. A grounded research study led to the finding that older adults may not abandon a legacy service, such as landline telecommunications service, when they adopted mobile telecommunications service. To further understand the results of the first study, a multidisciplinary literature review was undertaken and resulted in a typology of the factors of individual-level innovation adoption that can be applied by human factors professionals in the field. The three categories of factors included macro environmental, innovation-specific, and human factors. A research analysis of a study done by a county health department provided insights into what older adults contributed to the service production process in healthcare services including which common proxies do not accurately reflect the situations of older adults. A three-state process model of individual-level innovation adoption, which incorporated the role of a legacy system, was developed using the adoption patterns of mobile telecommunications services. In this model, individuals move from a state of using a legacy system to adopting a innovative system while still using the legacy system. After a period of time, the individual moves from the state of dual use to fully abandoning the legacy system and using only the innovative system. A compartmental mathematical model is developed to allow the model to be simulated and future service demand needs can be better predicted. Two decision-making processes were identified to be employed by individuals in the abandonment of a landline telecommunications services. Finally, recommendations for the design of mobile health services are provided