Analyzing The Strength Between Mission And Vision Statements And Industry Via Machine Learning
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| Publicado en: | Journal of Applied Business Research vol. 36, no. 3 (2020), p. 121 |
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| Autor principal: | |
| Otros Autores: | |
| Publicado: |
Knowledge and Leadership Alliance
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 022 | |a 0892-7626 | ||
| 022 | |a 2157-8834 | ||
| 024 | 7 | |a 10.19030/jabr.v36i3.10348 |2 doi | |
| 035 | |a 2713462541 | ||
| 045 | 2 | |b d20200101 |b d20201231 | |
| 084 | |a 12637 |2 nlm | ||
| 100 | 1 | |a Alshameri, Faleh | |
| 245 | 1 | |a Analyzing The Strength Between Mission And Vision Statements And Industry Via Machine Learning | |
| 260 | |b Knowledge and Leadership Alliance |c 2020 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Mission and vision statements are critical to a company’s success both from a company’s long-term goals and appearance to potential customers. We analyze a collection of 772 mission and vision statements from companies via natural language processing. This data is hand annotated into 15 industry types. We show the distinctiveness and connectiveness of each industry via text processing and machine learning techniques. The extracted features of each industry are a telling and guiding indicator of what that industry embraces. We show high predictive power via machine learning to determine an industry by looking only at the mission and vision statements | |
| 653 | |a Distinctiveness | ||
| 653 | |a Customers | ||
| 653 | |a Machine learning | ||
| 653 | |a Mission statements | ||
| 653 | |a Natural language processing | ||
| 653 | |a Long term planning | ||
| 653 | |a Employee behavior | ||
| 653 | |a Word processing | ||
| 653 | |a Companies | ||
| 653 | |a Data processing | ||
| 653 | |a Consumers | ||
| 700 | 1 | |a Nathan Green Green | |
| 773 | 0 | |t Journal of Applied Business Research |g vol. 36, no. 3 (2020), p. 121 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2713462541/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2713462541/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |