| dc.contributor | 資管系 | - |
| dc.creator (作者) | 杜雨儒 | - |
| dc.creator (作者) | Tu, Tony Yu-Ju | - |
| dc.creator (作者) | Huang, Yu-Hsiang (John) | - |
| dc.creator (作者) | Strader, Troy J. | - |
| dc.creator (作者) | Subramanyam, Ramanath (Ram) | - |
| dc.creator (作者) | Shaw, Michael J. | - |
| dc.date (日期) | 2019-10 | - |
| dc.date.accessioned | 26-May-2020 15:11:08 (UTC+8) | - |
| dc.date.available | 26-May-2020 15:11:08 (UTC+8) | - |
| dc.date.issued (上傳時間) | 26-May-2020 15:11:08 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/129966 | - |
| dc.description.abstract (摘要) | To better assist decision-makers (e.g., enterprise executives) in selecting the most desirable IT portfolio, this study proposes a new IT Portfolio Efficient Frontier model that incorporates the decision-maker`s risk tolerance levels. The proposed model, built on portfolio optimization along with experimental design and simulation data, considers three IT portfolio scenarios: even distribution-based IT portfolios, uneven distribution-based IT portfolios, and dominant IT portfolios. Our findings show that the IT portfolio efficient frontiers derived from both an even distribution-based IT portfolio and an uneven distribution-based IT portfolio have a relatively positive relationship between IT portfolio risk and return. Our findings also indicate that if IT investments are part of a dominant IT portfolio, an inflection point of the IT portfolio efficient frontier appears under the decision-maker`s medium risk tolerance level, and the most desirable IT portfolio is generated when a decision maker`s risk tolerance level is medium or higher. | - |
| dc.format.extent | 262601 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Information Resources Management Journal, Vol. 32, No.4, pp.1-19 | - |
| dc.title (題名) | Selecting the Most Desirable IT Portfolio under Various Risk Tolerance Levels | - |
| dc.type (資料類型) | article | - |
| dc.identifier.doi (DOI) | 10.4018/IRMJ.2019100101 | - |
| dc.doi.uri (DOI) | https://doi.org/10.4018/IRMJ.2019100101 | - |
