Communication models adopted in large-scale software engineering projects have significant impact on the efficacy of communication. We strove to understand these models by empirically examining synchronous communication within distributed and collocated teams at a large Fortune 500 organization. Our data imply that the overhead for tool support of synchronous communication for distributed teams are generally unacceptably high and that collocated teams are as likely to employ alternatives to face-to-face communication with collocated team members as distributed. Data also imply that communication patterns and models for both distributed and collocated teams evolve naturally over time to meet needs as opposed to a well-defined process delineated at project inception. Finally, data imply that communication models tend to be hybrids of existing communication models, suggesting a continual evolution of team communications over time. These implications collectively suggest that developers are adapting to collaborating with remote team members within this organization, perhaps realizing a new stage of evolution within the software engineering community.

The successful implementation of large-scale enterprise information systems is a central concern for the modern organization. In particular, it is important to assure management that these systems are functioning to their proper capacity and providing their indicated services. To this end, it is exceedingly important to obtain accurate measurements on the performance of the implemented systems without unduly burdening system administrators with additional management tasks. In this research, we examine the effectiveness of low administrative overhead approaches such as operational analysis and transaction-based approaches for determining the performance of implemented enterprise systems. In particular, this research examines where each approach is applicable through the use of a full-factorial experiment.

Businesses that are involved in offshore software development often operate in a virtual project environment in which peer teams located at customer premise exchange project specifications with the offshore software development facility. To understand the complex issues in such a virtual project environment during the requirements definition phase of the software development cycle, we conducted an exploratory research study, involving 24 virtual teams based in Canada and India, working on defining business requirements for software projects, over a period of five weeks. The study indicates that trust between the teams and well-defined task structure positively influence the efficiency, effectiveness, and satisfaction level of global virtual teams.

In conventional commerce, customer groups with similar interests or behaviours can be observed. Similarly, customers in E-commerce naturally form groups. These groups allow the organization to provide quality of service (QoS) and perform capacity planning. From a system point of view, overall server performance can be improved and resources managed considering customer session behaviour.Previous studies have grouped customers using clustering techniques. Different data metrics have been selected as criteria for grouping, in order to analyze different problems. The limitation for these approaches is that problems areanalyzed separately. In order to manage an E-commerce server well, we must analyze many related problems comprehensively rather than separately. For example, we would like to know what is the impact on resource usage when optimizing revenue. Thus, we must understand the differences and similarities between session groups chosen by different metrics.This paper characterizes customer groups for an E-rental business and compares customer groups created according to different criteria including services requested, navigation pattern and resource usage. A significant finding of this study shows that using each of the three criteria independently yields roughly similar results, since customers looking for similar services tend to have similar navigation pattern as well as similar server resource usage. Thus, it issufficient to group customers in only one of these ways. Grouping customers by services requested is suggested since this method yields relatively better results and is simple to implement.