The focus of this paper is on queueing models with arrivals from several sources, where the number of waiting spaces for each arrival source is finite. The main distinction from prior studies is that in our models waiting spaces are separate. Within this context, we examine the benefit of pooling, regardless of whether arrival rates are equal or different. We present a Quasi-Birth-and-Death (QBD) model to address the general case, with simplified versions tailored to specific scenarios. One practical application of the proposed models can be found in the loading and unloading processes at container terminals. We define a measure for stochasticity-related inefficiency, denoted relative interaction delay (RID), and analyze its behavior for the case of a single waiting space for each source. We show analytically that in the base model, the RID approximation is inversely proportional to the number of pooled queues. Numerical evaluations show an added benefit of pooling when arrival rates differ, observing a linear enhancement that is notably more pronounced.

Information Systems (IS) analysts are tasked with analyzing customer needs and designing the requisite information system, commonly using models. Ensuring the high quality of these models is crucial for the success of workflow-oriented IS. This study investigates how process thinking influences the ability of novices to produce high-quality process models in IS education, focusing on quality metrics such as completeness, correctness, and irredundancy. We conducted a detailed examination of 181 students enrolled in an IS Analysis and Design course (130 students in the final sample), employing a unique three-task methodology to assess their initial process thinking levels and subsequent model quality throughout the course. Our findings reveal that students with high initial process thinking proficiency continued to excel in subsequent modeling tasks, while those with lower initial proficiency narrowed the gap and improved the quality of their models in subsequent tasks due to learning. Additionally, we found a moderate positive correlation (r = 0.233, p = 0.008) between creativity and success in modeling tasks, suggesting that fostering creativity could enhance the quality of process models. Based on these insights, we recommend that IS training include targeted error correction, preliminary workshops for foundational skill enhancement including training in process thinking, and the integration of creativity into the curriculum. These recommendations aim to better prepare students for the complexities of IS planning and design, contributing to the development of proficient IS analysts capable of producing high-quality process models, thereby directly impacting the overall quality of software development processes.