The authors developed an Army Enlistment Options Optimizer approach that creates bundles of bonus and non-bonus enlistment incentives, often paired with smaller, supplemental bonuses. If implemented, potential recruits would choose the bundle they most value from those available according to job type, term length, recruit characteristics, and recruiting environment. This gives recruits greater agency in choosing their enlistment options, potentially increasing satisfaction and enlistments. At the same time, the recruit cohorts would have the characteristics desired by the Army and the Army would benefit from cost savings resulting from reduced bonus expenditures. Through two surveys of young adults ages 18-27, the authors found that non-bonus incentives were as attractive as bonuses of $10,000-$15,000. Options that included non-bonus incentives and supplemental bonuses were chosen more often than larger stand-alone bonus options. Respondents choosing those options rated their likelihood of joining the Army in the next few years to be as high as or higher than respondents choosing stand-alone bonuses. The results also indicate that the student loan repayment option is very popular among today's young adults. It could be used to help penetrate the college market and could save recruiting resources when used in a controlled fashion as an element of the option menus. The results suggest that providing information in the recruiting marketing process on the many jobs that the Army offers and the pay and benefits of serving could increase consideration of joining the Army.

Chapter One: Introduction -- Chapter Two: Design of Survey 1 -- Chapter Three: Analysis of Survey 1 -- Chapter Four: Design of Survey 2 -- Chapter Five: Analysis of Survey 2 -- Chapter Six: Potential Cost Savings -- Chapter Seven: Conclusion -- Appendix A: Survey 1 Questions and Responses -- Appendix B: Survey 1 Regressions on "How Likely Is It That You Would Actively Consider Serving in the Army in the Next Few Years?" -- Appendix C: Analysis of Survey 1 Best-Worst Data with a Logit Choice Probability Model -- Appendix D: Predicting Respondent AFQT Score -- Appendix E: Average and Maximum Enlistment Bonuses by Job -- Appendix F: Constructing Equal-Value Enlistment Options -- Appendix G: Expected Sample Sizes by Job Type -- Appendix H: Survey 2 Questions and Responses -- Appendix I: Logit Choice Regressions by Gender and AFQT -- Appendix J: Logit Choice Regressions by Job Type and AFQT.