Name
Title | ||
|---|---|---|
Model based interpretation of survey data: A case study of enterprise resource planning implementations |
Abstract | ||
|---|---|---|
The selection of the appropriate analysis tools for survey data is an important decision for all researchers dealing with responses on questionnaires. Over the last two decades a number of approaches have been used for classifying variables, statistically measuring significance and developing predictions of outcomes. This paper compares and evaluates the use of regression analysis, logistic (logit) models, discriminate analysis and data envelopment analysis (DEA), for empirical data from a survey of enterprise resource planning (ERP) implementations in the US manufacturing sector. The data collected from this survey contains a mix of subjective and objective data, and provides an opportunity to assess the impact of these modeling techniques on measuring outcomes and a decision-maker's acceptability of the results. The analysis illustrates that regression based tools are more valuable in developing predictive models, while logit and discriminate models are powerful in classifying the outcomes. The genetic search-based discriminate model is intuitively appealing, whereas DEA provides additional information with respect to understanding the process of arriving at the outcome over other tools. The analysis further shows that these techniques can be used in a complementary manner to insights that they cannot provide when used individually. In addition to the feasibility of these techniques, this analysis also provides important insights into ERP implementations. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.mcm.2005.12.008 | Mathematical and Computer Modelling |
Keywords | Field | DocType |
discriminate model,data envelopment analysis (dea),case study,empirical data,genetic search-based discriminate model,objective data,discriminate analysis,enterprise resource planning implementation,survey data,enterprise resource planning (erp),appropriate analysis tool,regression analysis,logistic models,erp implementation,data envelopment analysis,sample survey,logit model,discriminant analysis,prediction model,discriminative model,manufacturing,data envelope analysis,feasibility,fabrication,logistic distribution,logistic model,regression model,decision maker,data collection,applied mathematics,genetics,mathematical model | Data mining,Enterprise resource planning,Regression analysis,Survey sampling,Data envelopment analysis,Artificial intelligence,Logistic regression,Logit,Survey data collection,Mathematical optimization,Linear discriminant analysis,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
44 | 1-2 | Mathematical and Computer Modelling |
Citations | PageRank | References |
5 | 0.42 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincent A. Mabert | 1 | 142 | 5.35 |
| Ashok Soni | 2 | 117 | 3.73 |
| M. A. Venkataramanan | 3 | 245 | 20.52 |