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On Computing the Suitability of Non-Human Resources for Business Process Analysis 被引量:2
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作者 Abid Sohail Khurram Shahzad +3 位作者 p.d.d.dominic Muhammad Arif Butt Muhammad Arif Muhammad Imran Tariq 《Computers, Materials & Continua》 SCIE EI 2021年第4期303-319,共17页
Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service.Integral to that is analyzing the current performance of each task of the process an... Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service.Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task.In continuation of our previous work,we categorize resources into human and non-human resources.For instance,in the healthcare domain,human resources include doctors,nurses,and other associated staff responsible for the execution of healthcare activities;whereas the non-human resources include surgical and other equipment needed for execution.In this study,we contend that the two types of resources(human and non-human)have a different impact on the process performance,so their suitability should be measured differently.However,no work has been done to evaluate the suitability of non-human resources for the tasks of a process.Consequently,it becomes difficult to identify and subsequently overcome the inefficiencies caused by the non-human resources to the task.To address this problem,we present a three-step method to compute a suitability score of non-human resources for the task.As an evaluation of the proposed method,a healthcare case study is used to illustrate the applicability of the proposed method.Furthermore,we performed a controlled experiment to evaluate the usability of the proposed method.The encouraging response shows the usefulness of the proposed method. 展开更多
关键词 Business process management business process improvement process warehouse data warehouse resource suitability component resource suitability health care artificial intelligence
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