Engineering Sector

Mobile services are becoming increasingly commonplace in everyday life; however, Mobile payment (M-payment) is not among frequently used mobile services. The slowness of the diffusion of this service is the point of departure of the current research. The authors discuss why consumers are slow in adopting M-payment service and develop a proposed model that measures the customer’s attitude and intention to use this technology in Egypt. Different theories from diverse fields are reviewed to formulate the study’s conceptual framework. Empirical data were collected via an online survey for a sample of 490 students in “open education”, a type of e-distance learning. The results suggest that although the most important determinants influencing the customer’s attitude toward the service are perceived behavioral control and perceived usefulness, those influencing the intention to use it are perceived innovativeness, perceived expressiveness, facilitating condition, perceived usefulness, and social pressure. The results of the research differ from those of previous studies because of the effect of the Egyptian culture. Service providers can benefit from the results when formulating the marketing strategies to increase the usage of this service, improving mobile commerce.

The use of water main break history as a proxy for condition has become common practice because of the high costs associated with direct assessments. Statistical deterioration models predict future water main breaks on the basis of historical patterns. Many municipalities are beginning to understand the value of utilizing water pipe break histories to manage their noncritical distribution networks via deterioration models. This paper presents a generic IDEF0 process model for developing water main deterioration models. Two common statistical deterioration models for water pipes are compared: rate-of-failure models (ROF) and transition-state (TS) models. ROF models extrapolate the breakage rate for a particular cohort of pipes and do not differentiate between the times between successive failures. On the other hand, transition-state models attempt to model the time between successive failures for pipes. This paper presents a comparison and analysis of ROF models and transition-state models by using a single data set for cast- and ductile-iron pipes in the City of Hamilton, Ontario, Canada. The paper compares the models’ ability to support breakage forecasting, long-term strategic planning, and short-term tactical planning. Best practices for pipe segmentation in support of water main deterioration models are presented.