Pavol Jurik , Peter Schmidt , Martin Misut , Ivan Brezina , Marian Reiff
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引用次数: 0
摘要
文章介绍了复杂流程组合图（Composition Diagram of a Complex Process，CDCP），这是一种新的图示方法，用于为具有复杂垂直结构的业务流程建模。该方法解决了 BPMN、活动图 (AD) 和事件驱动流程链 (EPC) 等传统建模技术的局限性。主要目的是评估 CDCP 与既有方法相比的可用性和有效性，重点关注两项主要任务：解释和创建图表。根据任务的客观结果和问卷的主观反馈，对参与者的表现进行了评估。结果表明，CDCP 是阅读和绘制任务的有效方法，在理解和易用性方面优于 BPMN 和 EPC。方差统计分析显示，虽然学习年份对成绩没有显著影响，但所使用的学习程序和方法却有显著影响。这些研究结果凸显了 CDCP 作为一种更易用、更直观的业务流程建模工具的潜力，即使是对没有多少经验的用户来说也是如此。
The composition diagram of a complex process: Enhancing understanding of hierarchical business processes
The article presents the Composition Diagram of a Complex Process (CDCP), a new diagramming method for modelling business processes with complex vertical structures. This Method addresses the limitations of traditional modelling techniques such as BPMN, Activity Diagrams (AD), and Event-Driven Process Chains (EPC).
The experiment was carried out on 277 students from different study programs and grades to determine the effectiveness of the methods. The main objective was to evaluate the usability and effectiveness of CDCP compared to established methods, focusing on two primary tasks: interpretation and diagram creation. The participant's performance was evaluated based on the objective results of the tasks and the subjective feedback of the questionnaire. The results indicate that CDCP was the effective method for the reading and drawing tasks, outperforming BPMN and EPC in terms of understanding and ease of use. Statistical analysis of variance showed that while the year of the study did not significantly affect performance, the study program and Method used had a significant effect. These findings highlight the potential of CDCP as a more accessible and intuitive business process modelling tool, even for users with minimal prior experience.
期刊介绍：
Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems.
Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.
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