Human error in sozio-technical systems. A research about the influence and causality of human factors on dynamic decision making

Master's Thesis from the year 2017 in the subject Psychology - Work, Business, Organisation, grade: 1,5, Rhine-Waal University of Applied Sciences, language: English, abstract: The present work addresses human error in socio-technical systems, by considering the influence and causality of human factors on dynamic decision making. The theoretical framework is built by the SHEL-Model from Hawkins (1993). This system-based model illustrates a spectrum of Human Factors (Software, Hardware, Environment, Liveware) and interfaces (Liveware-Software, Liveware-Hardware, Liveware-Environment, Liveware-Liveware) between its elements in socio-technical systems (STS). The model of situation awareness in dynamic decision making from Endsley (1995a) is additionally used to describe the complex decision making process in STS based on the situation awareness (SA), allocated in perception, comprehension and projection and influenced by system and task as well as individual factors.

A study was conducted in a company, producing airconditioning technology with the purpose to investigate and optimize problems related to the usage of company-specific software among the department¿s sales and order processing. Additionally the information flow between these departments was examined. In order to specify the problem description from the company itself research questions were formulated within the scope of the mentioned theories: (1) Which SHEL-categories or interfaces should be improved in order to reduce failures and problems in the work within the configuration software? and (2) Which insights of the model of situation awareness should additionally be considered regarding the reduction of failures and problems in the decision making process within the configuration software?

For answering the research questions, first the need for imrprovement was identified within six self-conducted interviews with the sales staff from the outdoor service (n=2), sales staff from the indoor service (n=1), order processing (n=2) and one expert, who was responsible for the sales staff in other countries (n=1). Within Mayring¿s (2002, 2010) qualitative data analysis, critical incidents were extracted and related to the SHEL-categories. Additionally categories were inductively builded, based on Endsley¿s model.