BAA Sources Sought Notice - A Usable Computational Model of Army Officer Career Dynamics.pdf

Ver. 20DEC2016

W911NF-18-S-0005-FY23

SOURCES SOUGHT NOTICE

REQUEST FOR WHITE PAPERS

BAA TOPIC A-8.d.1: Improving Talent Management through Data Science

“A Usable Computational Model of Army Officer Career Dynamics”

INTRODUCTION

Broad Agency Announcement (BAA) W911NF-18-S-0005 was publicized on SAM.gov and Grants.gov on 1 May 2018. This Sources Sought Notice calls for White Paper submissions in reference to the BAA Topic A-8.d.1: Improving Talent Management through Data Science. The United States Army Research Institute for the Behavioral and Social Sciences (ARI) Broad Agency announcement W911NF- 18-S-0005, issued under the provisions of paragraph 6.102(d)(2) of the Federal Acquisition Regulation, provides for the competitive selection of basic and applied research and that part of development not related to the development of a specific system or hardware procurement. A Proposal submitted in response to this BAA and selected for award is considered to be the result of full and open competition and in full compliance with the provisions of Public Law 98-369, “The Competition in Contracting Act of 1984," and subsequent amendments. Funding of research and development (R&D) within ARI areas of interest will be determined by funding constraints and priorities set during each budget cycle. Any award related to the submission of a White Paper and subsequent Proposal requested by this Notice is subject to funds availability and priorities. ARI may choose not to select any new award due to unavailability of funds or other factors.

The sequence of steps leading to an award is:

1) Request for White Paper initiated by ARI through this Sources Sought Notice

2) Submission of a timely White Paper no more than five pages in length to the POC for the U.S.

Army Contracting Command, wilveria.a.sanders.civ@army.mil, and copy furnish (CC) the ARI Technical Point of Contact (TPOC), rachel.c.amey.civ@army.mil.

3) Written or telephonic feedback provided to the Offeror regarding the White Paper’s scientific merit and potential contributions to the Army mission as per established criteria presented in Part

III

4) If the White Paper merits it, a request of a formal proposal initiated by ARI

5) Submission of a timely, formal proposal

6) Evaluation of the formal proposal as per established criteria presented in Part III

7) Award for selected proposal based on availability of funds or other factors

This sequence allows earliest determination of the potential for funding and minimizes the labor and cost associated with submission of a full proposal that has minimal probability of being selected for funding.

Note that an interested Offeror must submit a White Paper electronically in order to be eligible to submit a formal proposal under this Notice. This Notice requires that a White Paper be submitted electronically no later than 16 December 2022, 5:00 PM Eastern Daylight Time. See Part V, Deadlines, for additional details. BAA W911NF-18-S-0005 allows several potential instrument types (e.g., contract, grant, cooperative agreement) to result from a successful proposal. For this Notice, the intention of the Government is to award a contract.

THOSE SUBMITTING A WHITE PAPER/PROPOSAL ARE CAUTIONED THAT ONLY A

GOVERNMENT CONTRACTING OR GRANTS OFFICER CAN OBLIGATE THE GOVERNMENT

THROUGH AWARD OF A LEGAL INSTRUMENT INVOLVING EXPENDITURE OF

GOVERNMENT FUNDS.

This Sources Sought Notice for a Requested White Paper consists of seven parts as follows:

• Part I: Research and Development Interests of the Requested White Paper

• Part II: Preparation and Submission

• Part III: Evaluation Criteria

• Part IV: Feedback

• Part V: Deadlines

• Part VI: Inquiries

• Part VII: References

ACC (APG) RTP Agency Point of Contact:

The POC for the US Army Contracting Command (Aberdeen Proving Ground) Research Triangle Park Division is: Ms. Wilveria Sanders, (919) 549-4328, wilveria.a.sanders.civ@army.mil.

ARI Agency Point of Contact:

The ARI POC for technical matters for this White Paper topic is: Dr. Rachel Amey, (571) 460-6804, rachel.c.amey.civ@army.mil

I. RESEARCH AND DEVELOPMENT INTERESTS OF THE REQUESTED WHITE PAPER:

The United States Army Research Institute for the Behavioral and Social Sciences is the Army’s lead agency for the conduct of research, development, and analyses for Army readiness and performance via research advances and applications of the behavioral and social sciences that address personnel, organization, training, and leader development issues. ARI contracts with educational institutions, non-profit organizations, and private industry for research and development (R&D) in different areas, including the areas specifically identified in Paragraph 8 of W911NF-18-S-0005. Efforts funded under this White Paper request will only include Applied Research and/or Advanced Technology Development.

Applied Research provides a systematic expansion and application of knowledge to design and develop useful strategies, techniques, methods, tests, or measures that provide the means to meet a recognized and specific Army need. Applied Research precedes system specific technology investigations or development, but it should have a high potential to transition into the Advanced Technology Development (ATD) Program.

The ARI ATD Program includes the development of technologies, components, or prototypes that can be tested in field experiments and/or simulated environments. Projects in this category have a direct relevance to identified military needs. These projects should demonstrate the general military utility or cost reduction potential of technology in the areas of personnel selection, assignment, and retention;

training strategies and techniques; leader education and development; performance measurement; and team and inter-organizational mission effectiveness. These projects should be focused on a more direct operational benefit and if successful, the technology should be available for transition.

WHITE PAPER TOPIC: A Usable Computational Model of Army Officer Career Dynamics

Although U.S. Army officers receive guidance about their career progression (e.g., DA PAM 600-3), actual career choices often deviate from such guidance, and sometimes in ways that seem counterproductive to a Soldier’s career advancement. One explanation for the discrepancy between officer career guidance and actual officer career choices is that the Army’s career models have remained relatively static despite decades of global economic change (DA PAM 600-3, p. 3). Decision maker characteristics that were once considered “irrational” or “sub-optimal” (e.g., career choices made for family reasons) are now seminal for understanding how both civilians (e.g., Haenggli et al., 2021) and servicemembers (e.g., U.S. Department of Defense, 2004, 2009, 2017) alike make career choices.

For example, leader development research recognizes that leaders often become more introspective in mid-to-late parts of their careers, particularly due to non-work roles (e.g., marriage, parenthood; Liu et al., 2021); the same is true of U.S. Army Soldiers (Amey et al., 2022). Such findings support seminal social psychological theories such as Social Role Theory (Eagly and Wood, 2012), which argues that individuals may take on the roles, behaviors, and mindset of those they interact with on a frequent basis (Eagly & Wood, 2012). In other words, Social Role Theory would suggest that psychological decision maker characteristics, often overlooked from classical decision theories, might be among the most important characteristics necessary to understand contemporary Army officer career choices.

One significant challenge for modeling social roles and their impact on Army officer career choices is that Soldiers hold many work-specific roles without considering vital non-work roles. For example, although an Army officer may belong to a single area of concentration (AOC), these AOCs can be organized by functional areas (FAs) and branches. Further, a new Army officer might be assigned to a particular platoon nested within a specific company, battalion, brigade, and even higher-level Army units. In other words, a single Army officer can occupy a large number work-specific roles associated with a complex combination of core technical work characteristics (e.g., AOC, FA, branch) and membership in multiple work-relevant collectives.

Given the breadth of work roles noted above, it is not surprising that U.S. Army officers experience role-related stress that can adversely affect career choices (e.g., Bliese & Castro, 2000; Schneider et al., 2011).

It is perhaps even less surprising that officers look to non-work social roles (e.g., parent, spouse) as a means of cohering these seemingly disparate work roles and identities (e.g., Amey et al., 2022). The sheer number of work and non-work roles Soldiers can occupy makes empirically studying such problems challenging. Fortunately, recent conceptual and technological advances in modeling and simulation make such research tractable (Davis et al., 2018; NATO, 2019; Orr et al., 2019) particularly from a modeling perspective called agent based modeling (e.g., Bhattacharya et al., 2019; Fehr et al., 2021).

The purpose of this research is to develop an agent-based computational model for simulating Army officer career choices over long periods of time and as a function of key psychological characteristics

(e.g., knowledge, skills, abilities, goals, needs, preferences), particularly when those officers are members of a massively hierarchical but fluid social structure with limited entry and exit points.

White papers on this topic should describe plans to:

1. Conduct a systematic, comprehensive, and interdisciplinary review of the individual, social, and organizational factors corresponding to individual career choices in dynamic and highly interdependent social contexts.

2. Review and evaluate existing formal (e.g., computational, mathematical) judgement and decision making models based, at a minimum, on: (i) evidential basis, (ii) computational feasibility (e.g., parallelizability, required computational resources), (iii) relevance to and representativeness of career choice literature review above, (iv) generalizability to agent collectives beyond individual agents, and (v) accessibility to non-experts.

3. Develop proof of concept agent-based computational modeling system that implements one or a small number of candidate agent-based models identified above to simulate Army officer career choice dynamics under realistic conditions (e.g., Army technical experts or social scientists simulating tens of thousands of agents over five or ten virtual years using commercially available computational technologies).

Candidate agent-based computational models need not account for decisions across an entire Army Officer career span. However, models focused on a limited portion of the career spectrum should be justified based on critical Army officer positions and transitions, and the underlying modeling framework should allow for subsequent applications to other career points. While not exhaustive, examples of such positions and transitions might include CPT to MAJ, from MAJ to LTC, or from LTC to COL.

Preference will be given to white papers adopting a multi-disciplinary approach to conceptualizing career choice (e.g., labor economics, psychology, sociology, education) and formal agent-based models (e.g., engineering, psychology, sociology, economics, political science). Examples of such multi-disciplinary approaches beyond career choice might include:

Davis, P. K., O’Mahony, A., Gulden, T. R., Osoba, O. A., & Sieck, K. (2018). Priority challenges for social and behavioral research and its modeling. RAND Corporation.

Epstein, J. M. (2006). Generative social science: Studies in agent-based computational modeling.

Princeton University Press.

Fehr, A., Stoffa, J. A., Newton, J., & White, J. (2021). Growing people: Generating realistic populations and explainable, goal directed behavior. IITSEC (2021) Paper No. 21253.

Gintis, H. (2009). Game theory evolving (2nd ed.). Princeton University Press.

Krakauer, D. C. (2019)(Ed.). Worlds hidden in plain sight: The evolving idea of complexity at the

Santa Fe Institute 1984-2019. SFI Press.

March, J., & Simon, H. (1993). Organizations. Blackwell.

Ohlsson, S. (2011). Deep learning: How the mind overrides experience. Cambridge University

Press.

Orr, M. G., Lebiere, C., Stocco, a., Pirolli, P. Pires, B., & Kennedy, W. G. (2019). Multi-scale resolution of neural, cognitive and social systems. Computational and Mathematical Organization Theory, 25, 4-23. https://doi.org/10.1007/s10588-018-09291-0

Rauwolf, P., Mitchell, D. M., & Bryson, J. J. (2015). Value homophily benefits cooperation but motivates employing incorrect social information. Journal of Theoretical Biology, 367, 246-261. doi: 10.1016/j.jtbi.2014.11.023

Simon, H. A. (1996). The sciences of the artificial. The MIT Press.

Sun, R. (2016). Anatomy of the mind. Oxford University Press.

The award will have a 36-month period of performance with a budget not to exceed $950k, distributed as follows:

• Base period of 9 months, not to exceed $240k

• Option period of 12 months, not to exceed $320k

• Option period of 15 months, not to exceed $400k

The Army Contracting Command- Aberdeen Proving Ground, RTP Division has the authority to award a variety of instruments, to include contracts, grants, and cooperative agreements. The ACC (APG) RTP Division reserves the right to use the type of instrument most appropriate for the effort proposed.

II. PREPARATION AND SUBMISSION OF A WHITE PAPER:

Preparation of White Paper

A White Paper should focus on describing details of the proposed research for both the base and option approach, including how it is innovative and how it could substantially advance the state of the science.

Army relevance and potential impact should also be described, as well as an estimate of total cost for both the base and option approach. White Papers should present the effort in sufficient detail to allow evaluation of the concept's technical merit and its potential contributions to the Army mission.

A White Paper must be limited to five (5) pages plus the cover page and an addendum in which the Offeror must include a biographical sketch (up to 300 words per individual) of all key personnel (i.e., Principal Investigators and Co-Principal Investigators) who will perform the research, highlighting their qualifications and experience as discussed below. All files and forms must be compiled into a single PDF file or MS Word document before submitting. Reviewers will be advised that they are only to review the cover page and up to five pages plus the addendum. Any pages submitted in excess of the five (5) page limit will not be reviewed or evaluated.

TECHNICAL INFORMATION FOR A WHITE PAPERS:

1. Technical Approach: A detailed discussion of the effort's scientific research objectives, approach, relationship to similar research, level of effort, and estimated total cost; include the nature and extent of the anticipated results, and if known, the manner in which the work will contribute to the accomplishment of the Army's mission related to this request and how this would be demonstrated.

2. Requests for Government Support: The type of support, if any that the Offeror requests of the Government (such as facilities, equipment, demonstration sites, test ranges, software, personnel or materials) shall be identified as Government Furnished Equipment (GFE), Government Furnished Information (GFI), Government Furnished Property (GFP), or Government Furnished Data (GFD). Offeror shall indicate any Government coordination that may be required for obtaining equipment or facilities necessary to perform any simulations or exercises that would demonstrate the proposed capability.

3. Key Personnel Biographical Information: As an addendum to the White Paper, the Offeror must include a biographical sketch (up to 300 words per individual) of all key personnel (i.e., Principal Investigators and Co-Principal Investigators) who will perform the research, highlighting their qualifications and experience.

RESTRICTIVE MARKINGS ON WHITE PAPERS:

1. The Offeror must identify any proprietary data the Offeror intends to be used only by the Government. The Offeror must also identify any technical data or computer software contained in the White Paper that is to be treated by the Government as limited rights or restricted rights respectively. In the absence of such identification, the Government will assume to have unlimited rights to all technical data or computer software presented in the White Paper. Records or data bearing a restrictive legend may be included in the White Paper, but must be clearly marked. It is the intent of the Army to treat all White Papers as procurement sensitive information before the award and to disclose their contents only to Government employees or designated support contractors for the purpose of procurement related activities only. Classified, sensitive, or critical information on technologies should not be included in a White Paper.

2. An Offeror is cautioned that portions of White Papers may be subject to release under terms of the Freedom of Information Act, 5 U.S.C. 552, as amended.

Submission of White Paper

White Papers must be submitted by e-mail to the POC for the U.S. Army Contracting Command, wilveria.a.sanders.civ@army.mil, and cc’d to the ARI Point of Contact (POC), rachel.c.amey.civ@army.mil, in electronic MS Word document format or PDF file format. Cite “ARI BAA W911NF-18-S-0005-FY23, A Usable Computational Model of Army Officer Career Dynamics” in the e-mail subject line.

III. EVALUATION CRITERIA:

A White Papers and full Proposals received in response to this request will be evaluated by the ARI designated point of contact identified in this request using the following factors/criteria:

1. Overall scientific and/or technical merits of the proposed research: The Offeror must demonstrate a thorough understanding of the research problem and articulate a clear approach to addressing the research objectives. The proposed approach must be based on feasible and realistic scientific methods and provide the Government with a high level of confidence of successful completion within proposed timeline.

2. Potential contributions of the effort to the U.S. Army Research Institute’s mission: In addition to showing how the proposed research aligns with the solicited topic, the Offeror must also specify how the proposed research will contribute to or advance the current U.S. Army Research Institute’s behavioral and social science research mission.

3. The Offeror’s capabilities, related experience, facilities, techniques or unique combination of these which are integral factors for achieving the proposed research objectives: the Offeror must demonstrate relevant organizational capabilities [e.g., experience, facilities, techniques] beyond individual capability to ensure the proposed research objectives can be achieved by the organization as a whole.

4. The qualifications, capabilities, and experience of the proposed Principal Investigator and other key personnel who are critical to the achievement of the proposed research objectives: The Offeror must demonstrate that the key personnel have the education and experience necessary to successfully complete the research objectives. Personnel capabilities need to be aligned with the expertise needed to achieve the required research objectives.

5. The Offeror’s record of past performance: Past performance information obtained from the Offeror’s White Paper, centralized past performance databases, and other sources will be used to evaluate past performance on projects of similar size, scope, and complexity to determine timely compliance with Government specifications. For an Offeror with no relevant past performance, the Government may take into account information regarding the past performance of predecessor companies, subcontractors, or proposed personnel that will perform key aspects of the proposed research.

6. Realism, affordability, and appropriateness of proposed costs: The Offeror must demonstrate that the proposed costs are appropriate given the suggested research approach. The Government will also evaluate the proposed costs in relation to the scope of the research objectives and the U.S. Army Research Institute’s budget.

7. Current and/or future relationship or interface with ongoing activities in academia and/or industry: The Offeror must demonstrate how the research findings and/or products could inform current or future scientific research, impact industry, and/or meet Army needs and goals.

The request for a proposal will be made based on the overall evaluation of a White Paper using the seven criteria listed above. The overall scientific and/or technical merit of the proposed approach will be weighted more strongly than all of the other factors combined. A request for proposal may not necessarily be made to the lowest proposed price. During the evaluation of White Papers, ARI’s POC for technical matters may request a discussion with an Offeror, but discussions are not guaranteed nor required for competition and award purposes. ARI’s POC for technical matters reserves the right to evaluate a White Paper and request a proposal without discussions The Offeror’s initial submission should contain the Offeror’s best terms from a technical and price standpoint. Once a full proposal has been requested, all communications must go through the POC for the U.S. Army Contracting Command.

If the White Paper evaluation results in the request and submission of a full proposal, the proposal will be evaluated by a panel of scientific peers using the same factors/criteria as those listed above under Evaluation Criteria. A request for a full proposal does not guarantee an award. The decision to award will be based on feedback from the panel, considerations presented by ARI’s POC for technical matters identified in this document, and other factors like budgetary constraints. ARI may choose not to select any award due to unavailability of funds or other factors.

IV. FEEDBACK:

Written or telephonic feedback will be provided to the Offeror regarding the White Paper’s scientific merit and potential contributions to the Army mission. If the Government decides to request a full proposal, a written request will be sent to the Offeror. The Written Request will, at a minimum, invite a full proposal. The request may also include feedback intended to improve the proposal’s potential for award.

V. DEADLINES:

Electronic versions of the White Paper must be received by the POC for the U.S. Army Contracting Command and the ARI POC, with e-mail subject line “ARI BAA W911NF-18-S-0005-FY23, A Usable Computational Model of Army Officer Career Dynamics” by e-mail no later than 5:00 PM Eastern Daylight Time on 16 December 2022. Any extension to the White Paper submission deadline will be posted to SAM.gov as an amendment to this Notice. Note that a timely White Paper received under this Notice will be evaluated and considered for proposal requests throughout the period beginning 16 December 2022 and ending 16 March 2023. An extension of this timeline may be granted based on the number of White Papers submitted or other factors out of the control of the designated point of contact reviewing the White Papers. An Offeror will be notified by email if the White Paper evaluation timeline is extended beyond 15 March 2023.

Instructions for the submission of a full Proposal will be provided by the U.S. Army Contracting Command to an Offeror invited to submit based on the evaluation of their White Paper.

An Offeror is responsible for submitting an electronic White Paper or full proposal so as to be received and accepted at the Government site indicated in this Notice no later than the date and time specified above. When sending electronic files, an Offeror shall account for potential delays in file transfer from the originator’s computer to the Government website/computer server. An Offeror is encouraged to submit their response early to avoid potential file transfer delays due to high demand or problems encountered in the course of submission.

An Offeror should receive confirmation of delivery at the Government site, not just successful relay from the Offeror’s system. Acceptable evidence to establish the time of receipt at the Government site includes documentary and electronic evidence of receipt maintained by the Government site. All submissions shall be submitted before the deadline identified above in order to be considered – no exceptions.

If an emergency or unanticipated event interrupts normal Government processes so that a White Paper or full proposal cannot be received at the site designated for receipt by the date and time specified above, then the date and time specified for receipt will be deemed to be extended to the same day and time specified in this Notice on the first work day on which normal Government processes resume.

An Offeror agrees to hold the terms of their White Paper and any subsequent proposal valid for 180 calendar days from the date of submission.

VI. INQUIRIES:

ACC (APG) RTP Agency Point of Contact (Contractual Questions)

The POC for the US Army Contracting Command (Aberdeen Proving Ground) Research Triangle Park Division is: Ms. Wilveria Sanders, (919) 549-4328, wilveria.a.sanders.civ@army.mil.

ARI Agency Point of Contact (Technical Questions)

The ARI POC for technical matters for this White Paper topic is: Dr. Rachel Amey, (571) 460-6804, rachel.c.amey.civ@army.mil.

VII. REFERENCES:

The following documents may be useful references for understanding Army personnel-related processes and background:

• DA PAM 600-3. Officer Professional Development and Career Development. Washington, DC:

U.S. Army.

• AR 611-5. Personnel and Classification Testing. Washington, DC: US Army.

• AR 621-5. Army Continuing Education System. Washington, DC: US Army.

• U.S. Army (2019). The Army People Strategy. Washington, DC: U.S. Army.

• U.S. Army (2021). Army Modernization Strategy: Investing in the Future. Washington, DC: U.S.

Army.

• U.S. Army Training and Doctrine Command. (2019). Training Development in Support of the

Operational Training Domain. Fort Eustis, VA: U.S. Army

• U.S. Army War College. 2021-2022 How the Army Runs: A Senior Leader Reference Handbook.

Carlisle, PA: U.S. Army War College.

• U.S. Department of Defense (2020). DoD Data Strategy: Unleashing Data to Advance the

National Defense Strategy. Washington, DC: Department of Defense.

• U.S. Department of Defense (2004). Report of the 1st Quadrennial Quality of Life Review.

Retrieved from https://www.militaryonesource.mil/data-research-and-statistics/reports/

• U.S. Department of Defense (2009). Report of the 2nd Quadrennial Quality of Life Review.

Retrieved from https://www.militaryonesource.mil/data-research-and-statistics/reports/

• U.S. Department of Defense (2017). Report of the 3rd Quadrennial Quality of Life Review.

Retrieved from https://www.militaryonesource.mil/data-research-and-statistics/reports/

• National Academies of Sciences, Engineering, and Medicine. (2017). Strengthening Data Science

Methods for Department of Defense Personnel and Readiness Missions. Washington, DC: The

The following sources were cited within the “Research and Development Interests of the Requested White Paper” section of this Sources Sought notice:

• Amey, R. C., Shaughnessy, S. P., Vu, K. T. (2022 March 7-10) The Strength of Our Soldiers is Our Families [Conference Symposium Talk]. International Military Testing Association 2022 Convention, Raleigh, NC, United States.

• Bhattacharya, P. et al. (2019). The Matrix: An Agent-Based Modeling Framework for Data Intensive Simulations. Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems. Montreal, Canada.

• Bliese, P. D., & Castro, C. A. (2000). Role clarity, work overload and organizational support:

multilevel evidence of the importance of support. Work & Stress, 14(1), 65-73.

• Davis, P. K., O’Mahony, A., Gulden, T. R., Osoba, O. A., & Sieck, K. (2018). Priority challenges for social and behavioral research and its modeling. RAND Corporation.

• Eagly, A. H., & Wood, W. (2012). Social role theory. In P. A. M. Van Lange, A. W. Kruglanski, & E. T. Higgins (Eds.), Handbook of theories of social psychology (pp. 458–476). Sage Publications Ltd.

• Epstein, J. M. (2006). Generative social science: Studies in agent-based computational modeling.

Princeton University Press.

• Fehr, A., Stoffa, J. A., Newton, J., & White, J. (2021). Growing people: Generating realistic populations and explainable, goal directed behavior. IITSEC (2021) Paper No. 21253.

• Gintis, H. (2009). Game theory evolving (2nd ed.). Princeton University Press.

• Haenggli, M., et al. (2021). Exploring the dynamics of protean career orientation, career management behaviors, and subjective career success: An action regulation theory approach.

Journal of Vocational Behavior, 131.

• Krakauer, D. C. (2019)(Ed.). Worlds hidden in plain sight: The evolving idea of complexity at the Santa Fe Institute 1984-2019. SFI Press.

• Liu, Z. et al. (2021). Leader development across the lifespan: A dynamic experiences-grounded approach. Leadership Quarterly, 32.

• March, J., & Simon, H. (1993). Organizations. Blackwell.

• North Atlantic Treaty Organization (2019). Modelling and Simulation as a Service, Volume 1:

MSaaS Technical Reference Architecture. STO Technical Report (Report TR-MSG-136-Part-IV).

• Ohlsson, S. (2011). Deep learning: How the mind overrides experience. Cambridge University

Press.

• Orr, M. G., Lebiere, C., Stocco, a., Pirolli, P. Pires, B., & Kennedy, W. G. (2019). Multi-scale resolution of neural, cognitive and social systems. Computational and Mathematical Organization Theory, 25, 4-23. https://doi.org/10.1007/s10588-018-09291-0

• Rauwolf, P., Mitchell, D. M., & Bryson, J. J. (2015). Value homophily benefits cooperation but motivates employing incorrect social information. Journal of Theoretical Biology, 367, 246-261.

doi: 10.1016/j.jtbi.2014.11.023

• Schneider, R. J. et al. (2011). Development and evaluation of a career continuance model for company grade officers in the United States Army. ARI Research Note 2011-05 (DTIC report no.

ADA543634).

• Simon, H. A. (1996). The sciences of the artificial. The MIT Press.

• Sun, R. (2016). Anatomy of the mind. Oxford University Press.

The ARI POC for technical matters for this White Paper topic is: Dr. Rachel Amey, (571) 460-6804, rachel.c.amey.civ@army.mil.