000 02467nam a2200217Ia 4500
003 NULRC
005 20250520102820.0
008 250520s9999 xx 000 0 und d
020 _a9781489978332
040 _cNULRC
050 _aQA 76.27 .A38 2014
245 0 _aAdvances in research methods for information systems research:
_bdata mining, data envelopment analysis, value focused thinking /
_cedited by Kweku-Muata Osei-Bryson and Ojelanki Ngwenyama
260 _aNew York :
_bSpringer,
_cc2014
300 _avii, 231 pages :
_billustrations ;
_c23 cm.
365 _bUSD53.96
504 _aIncludes index.
505 _aChapter1. Introduction -- Chapter2. Logical Foundations of Social Science Research -- Chapter3. Overview on Decision Tree Induction -- Chaptyer4. An Approach for Using Data Mining to Support Theory Development -- Chapter5. Application of a Hybrid Induction-Based Approach for Exploring Cumulative Abnormal Returns -- Chapter6. Ethnographic Decision Tree Modeling: An Exploration Cumulative Abnormal Returns -- Chapter7. Using Association Rules Mining to Facilitate Qualitative Data Analysis in Theory Building -- Chapter8. Overview on Multivariate Adaptive Regression Splines -- Chapter9. Reexamining the Impact of Information Technology Investment on Productivity Using Regression Tree and MARS -- Chapter10. Overview on Cluster Analysis -- Chapter11. Overview on Data Envelopment Analysis -- Chapter12. Exploring the ICT Utilization using Data Envelopment Analysis -- Chapter13. A DEA-centric Decision Support System for Monitoring Efficiency-Based Performance -- Chapter14. Overview on the Value Focused Thinking Methodology -- Chapter15. A Hybrid VFT-GQM Method for Developing Performance Criteria and Measures .
520 _aAdvances in social science research methodologies and data analytic methods are changing the way research in information systems is conducted. New developments in statistical software technologies for data mining (DM) such as regression splines or decision tree induction can be used to assist researchers in systematic post-positivist theory testing and development. Established management science techniques like data envelopment analysis (DEA), and value focused thinking (VFT) can be used in combination with traditional statistical analysis and data mining techniques to more effectively explore behavioral questions in information systems research.
650 _aCOMPUTER LITERACY
942 _2lcc
_cBK
999 _c16002
_d16002