# Developing a Recommendation Model for the Smart Factory System
## 5 Conclusions  
This study adopts the Modified Delphi Method to identify the deficiencies in the past research, and then takes Updated Information System Success Model as the primary recommendation dimension; however, different systems have different requirements, so it is unable to use past selection methods for the SFRS. Therefore, in addition to taking Updated Information System Success Model as the base of recommendation indicators, the study also adds concepts, including Function characteristics of SFS; Information Security that protects enterprises' privacy and the CIA; Perceived Value for the evaluation of gain and sacrifice; Perceived Risk that enterprises have to take; and UI Design, which refers to whether a system is easy-to-use. These dimensions are extensions that make up for the deficiencies of the Updated Information System Success Model. The results of the system in this research can be used by enterprises; they provide solutions and references on purchasing SFS, whose functions are to provide purchase ability analysis of the SFS; to support demand analysis of manufacture problems; to rank and score recommendation indicators and flexibly delete unnecessary indicators by their demands; to automatically calculate recommendation results, which mitigates inconveniences of human calculation and provides real-time ranking and the best alternative recommendation. For SFS suppliers, the results of this study can be used as references for the design and modification of the SFS and they also enable the requirements to be closer to the users' demands.  
Based on the results of the eight dimensions, the study suggests that purchasers should pay attention to: (1) information output accuracy, system stability, and information rapidness; (2) the supplier's proficiency which can explain system usage and solve possible problems; (3) demand accuracy and production schedule; (4) information security to mitigate data hack or leak; (5) how much added-value that a SFS can bring to the enterprises; (6) the SFS's expected results and operator system adaptability, and (7) ensuring that the UI design is easy to use. An SFRS developed for enterprises will provide solutions and references for purchasing SFS, with functions including purchase ability analysis, demand analysis of manufacture problems, and ranking and scoring of recommendation indicators.  
The SFRS developed in this study can make the whole recommendation processes much quicker and smoother, eliminating complicated calculations and human errors. In the future work, the study will try to provide a new recommendation venue to users. That will be a hybrid recommendation model to integrate user-based and item-based models and then use collaborative filtering and content-based filtering recommendation systems for various domains.  
**Author Contributions:** Conceptualisation, C.-Y.C.; data curation, C.-A.T.; formal analysis, C.-Y.C.; methodology, C.-A.T. and W.-L.H.; project administration, C.-Y.C.; sources, W.-L.H.; software, W.-L.H. and C.-Y.C.; supervision, C.-Y.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare that they have no conflict of interest.