Designing and evaluating business process models: An experimental approach

• Main Authors: YU, Yuecheng Martin, PELAEZ, Alexander, LANG, Karl R.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Design science; Electronic group buying; Experimental economics; Mechanism design; Social commerce; Virtualization theory; Programming Languages and Compilers; Technology and Innovation
• Online Access: https://ink.library.smu.edu.sg/sis_research/5907; https://ink.library.smu.edu.sg/context/sis_research/article/6903/viewcontent/101007_2Fs10257_014_0257_0.pdf
• Institution: Singapore Management University

This paper presents an experimental approach to compare the performance of alternative business process designs. We use an example case of an electronic group buying setting to demonstrate how our approach can be applied in practice. More specifically, we chose a standard business process, the sales process as implemented on a group buying platform, to illustrate how a business process may be redesigned in order to better meet the needs of customers. For that purpose, we introduce a social technology feature to support cooperation among buyers in the sales process and then analyze the performance impact of the proposed business process redesign. We combine principles from design science and experimental economics to aid the business redesign process. To allow for an experimental evaluation in a controlled laboratory setting, we implement a simplified prototype model and an experimental electronic group-buying platform in the laboratory. We then employ the methods of experimental economics to generate process performance data and evaluate the effectiveness of the new process model design in the lab that can provide valuable insights to platform managers for redesigning the real-world system. We posit that combining the principles of design science and experimental economics offers researchers a useful and cost-effective method to systematically evaluate theoretical predictions about process model design.