Nowadays, patient satisfaction is an important service quality index for many hospitals. In many Asian countries, healthcare system has a mixed-type registration which accepts for both walk-in patients and scheduled patients. It is different from western countries which accept only scheduled patients. A long waiting time (WT) of outpatient clinics is caused by this complex registration system. A survey questionnaire of patient satisfaction showed that the long waiting time is the most dissatisfied service quality for healthcare providers. This study focused on improving clinical services by using collaborative approaches to reduce outpatient waiting time for the healthcare providers. The collaborative approaches are scheduling approach with results presented in this paper and agent-based collaborative control system which is currently in progress. We collected and observed data for two months from real world situation and used data from hospital database for building and validating simulation models. Seven scheduling scenarios are performed: scenarios I adjusted proportion between walk-in patients and scheduled patients, scenario II-VI adjusted patient sequencing, and scenario VII adjusted late rate and applied a late policy for late patients. The scenario I (adjusting the proportion: 10% for walk-in patients and 90% for scheduled patients) has the highest percentage of waiting time improvement (average: 37.13 % for walk-in patients and 50.82 % for scheduled patients) compared with the other scenarios. The overall results show that adjusting proportion of patient scenario and patient sequencing scenario can improve patient waiting time in the mixed-type registration and are possible to apply to any outpatient clinics.

PurposeThe semiconductor market exceeded US$250 billion worldwide in 2010 and has had a double‐digit compound annual growth rate (CAGR) in the last 20 years. As it is located far upstream of the electronic product market, the semiconductor industry has suffered severely from the “bullwhip” effect. Therefore, effective e‐based supply chain management (e‐SCM) has become imperative for the efficient operation of semiconductor manufacturing (SM) companies. The purpose of this research is to define and analyze the key success factors (KSF) for e‐SCM system implementation in the semiconductor industry.Design/methodology/approachA hierarchy of KSFs is defined first by a combination of a literature review and a focus group discussion with experts who successfully implemented an inter‐organizational e‐SCM project. Fuzzy analytic hierarchy process (FAHP) is then employed to rank the importance of these identified KSFs. To confirm the research result and further explore the managerial implications, a second in‐depth interview with the e‐SCM project executives is conducted.FindingsThe KSF hierarchy is constructed with two levels: a top‐level consisting of four dimensions and a detailed‐level consisting of 15 individual factors. The research shows that, in the top‐level, strategy is the most critically successful dimension followed by process, organization, and technical; whereas in the detailed‐level, the top management commitment, clear project goal and business requirements, and business process re‐engineering are the top three critical successful factors.Research limitations/implicationsResearch surveys and interviews were conducted with two leading companies: Taiwan Semiconductor Manufacturing Company (TSMC) and ASE; they are the largest front‐end and back‐end SM companies in the world, respectively. Although the data collected was primarily based on the experience of one successful e‐SCM project, the significant roles of these two companies and compelling contribution made by the e‐SCM project leading to the research resulted in valuable guidelines for the companies in the semiconductor industry and a useful reference for companies in other manufacturing industries.Originality/valuee‐SCM system has a high failure rate and there is little literature discussing the KSF of e‐SCM implementation from a holistic view for certain industries. This paper not only provides a structured and comprehensive list of KSFs but also illustrates the application of the most critical factors by examples. In addition to the contributions made to industries, the research results can also serve as a foundation for related academic research when comparing the KSFs of implementing e‐SCM by different industries.

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