[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122177-en":3,"doc-seo-122177-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122177,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Acquisition Targeting - Toward Modelling Small Business Acquisition with Machine Learning","Small business acquisition suffers from limited information transparency, causing business buyers to evaluate targets differently and making consistent valuation difficult. This dissertation applies a case study of Sound Hardware Inc. and its management team to build a modeling approach for acquisition pricing and business planning. Machine learning is used to reduce engineered variables into a prioritized factor list tied to value. Dimensionality reduction is then followed by regression-based valuation that incorporates management domain knowledge, producing both price and a growth-aligned plan intended to support long-term success.","Digital Commons @ George Fox University  \n\n| Doctor of Business Administration (DBA) | Theses and Dissertations |\n| --- | --- |\n| 12-31-2024\u003Cbr>Acquisition Targeting: Toward Modelling Small Business Acquisition with Machine Learning\u003Cbr>Jeremy Chambers\u003Cbr>George Fox University, [jchambers19@georgefox.edu](jchambers19@georgefox.edu)\u003Cbr>Follow this and additional works at: [https://digitalcommons.georgefox.edu/dbadmin](https://digitalcommons.georgefox.edu/dbadmin)\u003Cbr> Part of the Business Commons |  |\n\nRecommended Citation  \nChambers, Jeremy, \"Acquisition Targeting: Toward Modelling Small Business Acquisition with Machine Learning\" (2024) . Doctor of Business Administration (DBA). 72.  \n[https://digitalcommons.georgefox.edu/dbadmin/72](https://digitalcommons.georgefox.edu/dbadmin/72)  \nThis Dissertation is brought to you for free and open access by the Theses and Dissertations at Digital Commons @ George Fox University. It has been accepted for inclusion in Doctor of Business Administration (DBA) by an authorized administrator of Digital Commons @ George Fox University. For more information, please contact [arolfe@georgefox.edu](arolfe@georgefox.edu).  \nAcquisition Targeting:  \nToward Modelling Small Business Acquisition with Machine Learning  \nJeremy W. Chambers  \nCollege of Business, George Fox University  \nDr. Paul Shelton  \nDecember 31, 2024  \nAbstract  \nSmall business acquisition suffers from a lack of information transparency, and many business buyers consequently value acquisitions differently. This project uses the case study methodology to analyze Sound Hardware Inc. and its management team to understand its context in-depth and provide a model that calculates an acquisition price in addition to offering business planning. It does this by using machine learning algorithms to reduce the number of engineered variables resulting in a priority list of factors contributing to value. This core process of dimensionality reduction is followed by a sample valuation that uses the results of the dimensionality reduction in a regression analysis while factoring in management domain knowledge. This results in both a price and a business plan that should match the acquisition phase of company growth to long-term success. The author hopes that this buy-side approach to strategic acquisition planning will be useful to both the academy and to business given its practical nature.  \nAcknowledgements  \nI would like to thank and appreciate my cohort in the George Fox DBA program. You have become friends and a source of inspiration. I would also like to thank Dr. Debby Thomas whose commitment to excellence is inspiring. And, I want to thank my committee including Dr. Paul Shelton, Dr. Brian Snider, and Dr. Debby Thomas, all of whom helped me grow, learn, and produce excellent results. Most of all, I appreciate beyond words my wife, Mona Chambers, and our three children Kristine, Eleanor, and Timothy. I love you dearly. Praise God for the life he has given me.  \nTable of Contents  \nChapter 1: Proposal........................................................................................................... 10  \nBackground ................................................................................................................... 11  \nPatterns.......................................................................................................................... 16  \nAdvanced Planning ................................................................................................... 16  \nHunting ..................................................................................................................... 19  \nNegotiating................................................................................................................ 23  \nOn-Boarding ............................................................................................................. 28  \nData Sources .........................................................","cbCaia6e6Yf05qeL","https://ap.wps.com/l/cbCaia6e6Yf05qeL","pdf",25607115,1,231,"English","en",105,"# Chapter 1: Proposal\n## Background\n## Patterns\n## Advanced Planning\n## Hunting\n## Negotiating\n## On-Boarding\n## Data Sources\n## Proposed Model\n## Problem Statement\n## Concept and Purpose\n## Research Objectives\n## Definitions and Terms\n## Methodology\n## Scholarly Significance and Limitations\n## Organization of the Chapters\n## Conclusion\n# Chapter 2: Literature Review\n## Feature Engineering\n## Prime Rate\n## Geographic Centroid\n## Financial Statement Analysis\n## Retailer Analytics Dashboard\n## Other Features","[{\"question\":\"What problem does the dissertation address in small business acquisition?\",\"answer\":\"It addresses limited information transparency that leads buyers to value acquisitions differently, creating challenges for consistent acquisition targeting and pricing.\"},{\"question\":\"How does the project use machine learning in its modeling approach?\",\"answer\":\"It applies machine learning to perform dimensionality reduction, reducing the number of engineered variables into a prioritized list of factors that contribute to value.\"},{\"question\":\"How is the acquisition price ultimately calculated?\",\"answer\":\"The model uses the dimensionality reduction results in a regression analysis while also incorporating management domain knowledge to inform valuation and the accompanying business plan.\"}]","Acquisition Targeting - 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