3/30/2023 0 Comments Sequential analysisKey challenges for users are to efficiently interact with BI&A platforms and quickly comprehend the insights. Furthermore, findings are potentially transferable to other domains.Ĭompanies nowadays use various business intelligence and analytics (BI&A) platforms to support de-cision making. This knowledge assists effective problem-solving activity to support search and decision making, and to mitigate uncertainty during the x-ray screening task.įindings can inform future security screening processes, screener training, and technology support tools. It demonstrates that security screeners develop knowledge that is specific to problem solving. This study expands current understandings of airport security screening. Insufficient knowledge led screeners to seek assistance and defer decision making. Lag-sequential analysis using combined data from both screener groups showed that situational knowledge facilitated effective problem-solving activity to support search and decision making. When interacting with other security screeners, more-experienced screeners demonstrated situational knowledge more than less-experienced screeners, whereas less-experienced screeners experienced more insufficient knowledge. Participants wore eye-tracking glasses and delivered concurrent verbal protocol. Sixteen more-experienced and 24 less-experienced security screeners were observed as they performed x-ray screening in the field at an Australian international airport’s departure security checkpoint. Although search and decision making are essential aspects of security screening, few studies have investigated the problem-solving knowledge and activities that support security screening task performance. We argue that the development of problem-solving knowledge enables security screeners to perform effective problem-solving activity, which assists search and decision-making processes.Īirport security screening research has investigated the many variables that affect security screeners’ search and decision making during simulated threat-detection tasks. The spreadsheet instructions needed to implement the prior relativities approach for two different types of algorithms each with two different ways of handling the good driver discount are completely worked out in examples.This research investigates security screeners’ knowledge and the effect that differences in knowledge have on the performance of problem-solving activities. Both approaches are mathematically equivalent and produce the same results. The prior relativities approach is based on adjusting a rating factor's relativities by the average relativity of prior factors. The loss residual approach is based on evaluating the variations in losses that have not been accounted for by previous factors. The key task is measuring the influence of prior rating factors and adjusting for it. A sequential analysis proceeds one step at a time. The types of data needed to perform a sequential analysis are discussed and detailed examples of two approaches are presented. This paper describes the context in which the requirement for a sequential analysis was developed and provides technical guidelines for performing the analysis. "Sequential Analysis Guidelines," California Department of Insurance, September.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |