Accurately predicting precise outcomes in business-to-business marketing
Copyright © 2018 by Emerald Publishing Limited. This chapter identifies research advances in theory and analytics that contribute successfully to the primary need to be filled to achieve scientific legitimacy: Configurations that include accurate explanation, description, and prediction-prediction h...
| Main Author: | |
|---|---|
| Format: | Book |
| Published: |
2018
|
| Online Access: | http://hdl.handle.net/20.500.11937/74909 |
| _version_ | 1848763406694219776 |
|---|---|
| author | Woodside, Arch |
| author_facet | Woodside, Arch |
| author_sort | Woodside, Arch |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Copyright © 2018 by Emerald Publishing Limited. This chapter identifies research advances in theory and analytics that contribute successfully to the primary need to be filled to achieve scientific legitimacy: Configurations that include accurate explanation, description, and prediction-prediction here refers to predicting future outcomes and outcomes of cases in samples separate from the samples of cases used to construct models. The MAJOR PARADOX: Can the researcher construct models that achieve accurate prediction of outcomes for individual cases that also are generalizable across all the cases in the sample? This chapter presents a way forward for solving the major paradox. The solution here includes philosophical theoretical, and operational shifts away from variable-based modeling and null hypothesis statistical testing (NHST) to case-based modeling and somewhat precise outcome testing (SPOT). These shifts are now occurring in the scholarly business-to-business literature. |
| first_indexed | 2025-11-14T11:02:58Z |
| format | Book |
| id | curtin-20.500.11937-74909 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:02:58Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-749092019-02-19T05:36:13Z Accurately predicting precise outcomes in business-to-business marketing Woodside, Arch Copyright © 2018 by Emerald Publishing Limited. This chapter identifies research advances in theory and analytics that contribute successfully to the primary need to be filled to achieve scientific legitimacy: Configurations that include accurate explanation, description, and prediction-prediction here refers to predicting future outcomes and outcomes of cases in samples separate from the samples of cases used to construct models. The MAJOR PARADOX: Can the researcher construct models that achieve accurate prediction of outcomes for individual cases that also are generalizable across all the cases in the sample? This chapter presents a way forward for solving the major paradox. The solution here includes philosophical theoretical, and operational shifts away from variable-based modeling and null hypothesis statistical testing (NHST) to case-based modeling and somewhat precise outcome testing (SPOT). These shifts are now occurring in the scholarly business-to-business literature. 2018 Book http://hdl.handle.net/20.500.11937/74909 10.1108/S1069-096420180000025006 restricted |
| spellingShingle | Woodside, Arch Accurately predicting precise outcomes in business-to-business marketing |
| title | Accurately predicting precise outcomes in business-to-business marketing |
| title_full | Accurately predicting precise outcomes in business-to-business marketing |
| title_fullStr | Accurately predicting precise outcomes in business-to-business marketing |
| title_full_unstemmed | Accurately predicting precise outcomes in business-to-business marketing |
| title_short | Accurately predicting precise outcomes in business-to-business marketing |
| title_sort | accurately predicting precise outcomes in business-to-business marketing |
| url | http://hdl.handle.net/20.500.11937/74909 |