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Transfer and utilization of organizational research knowledge by managerial personnel in complex organizational settings
Research and analysis outline for organizational behavior and administration of scientific and engineering facilities
Issues of crew productivity during design work on space station are discussed. The crew productivity is defined almost exclusively in terms of human factors engineering and habitability design concerns. While such spatial environmental conditions are necessary to support crew performance and productivity, they are not sufficient to ensure high levels of crew performance and productivity on the post-Initial Operational Configurations (IOC) space station. The role of the organizational environment as a complement to the spatial environment for influencing crew performance in such isolated and confined work settings is examined. Three possible models of operation for post-IOC space station's organizational environment are identified and it is explained how they and space station's spatial environment will combine and interact to occasion patterns of crew behavior is suggested. A three phase program of research design: (1) identify patterns of crew behavior likely to be occasioned on post-IOC space station for each of the three models of operation; and (2) to determine proactive/preventative management strategies which could be adopted to maximize the emergence of preferred outcomes in crew behavior under each of the several spatial and organizational environment combinations.
Abstract It was last estimated that in 2020, data centers comprised approximately 2% of total US electricity consumption, with an estimated annual growth rate of 4%. As our country increasingly relies on information technology (IT), our data centers (DCs) will need to increase their energy efficiency (EE) to stabilize their energy consumption. The task of studying EE in DCs is complicated by the interconnected nature of humans and mission-critical technical systems. Moreover, the literature tends to focus on technology solutions such as improvements to IT equipment, cooling infrastructure, and software, without addressing organizational and psychological drivers. Our research demystifies the complex interactions between humans and DCs, by asking What non-technical barriers impede EE investment decision-making and/or implementing energy management strategies? To begin to answer this question, we perform a literature review of 86 resources, ranging from peer-reviewed journal publications to handbooks. We also consider related fields such as organizational behavioral management and energy intensive buildings. We develop a public Zotero library, perform content coding, and complete a rudimentary network analysis. Our findings from the literature review suggest that (1) technological solutions are abundant in the literature but fall short of providing practical guidance on the pitfalls of implementation, (2) making energy efficiency a priority at the executive level of organizations will be largely ineffective if the IT and facilities staff are not directly incentivized to increase EE, and (3) there is minimal current understanding of how the individual psychologies of IT and facilities staff affect EE implementation in DCs. In the next phase of our research, we plan to interview data center operators/experts to ground-truth our literature findings and collaboratively design decarbonization policy solutions that target organizational structure, empower individual staff, and foster a supportive external market.
Organizations play a key role in supporting various societal functions, ranging from environmental governance to the manufacturing of goods. Here, the behaviors of organization are impacted by various influences, including information, technology, authority, economic leverage, historical experiences, and external factors, such as regulations. This paper introduces a generalized framework, focused on the relative structure of an organization (tight vs. loose), that can be used to understand how different influence pathways can impact decision-making within differently structured organizations. This generalized framework is then translated into a modeling and simulation platform to support and assess implications of these structural differences in resilience to disinformation (measured by organizational behaviors of timeliness and inclusion of quality information) using a systems dynamics approach Preliminary results indicate that a tightly structured organization may be less timely at processing information but could be more resilient against using poor quality information in organizational decisions compared to a loosely structured organization. Ongoing work is underway to understand the robustness of these findings and to validate current model design activities with empirical insights.
Researchers from Sandia National Laboratories (Sandia) and the University of Texas at Austin (UT) conducted this study to explore the effectiveness of commercial artificial neural network (ANN) software to improve insider threat detection and mitigation (ITDM). This study hypothesized that ANNs could be "trainee to learn patterns of organizational behaviors, detect off-normal (or anomalous) deviations from these patterns, and alert when certain types, frequencies, or quantities of deviations emerge. The ReconaSense ANN system was installed at UT's Nuclear Engineering Teaching Laboratory (NETL) and collected 13,653 access control data points and 694 intrusion sensor data points over a three-month period. Preliminary analysis of this baseline data demonstrated regularized patterns of life in the facility, and that off-normal behaviors are detectable under certain situations -- even for a facility with anticipated highly non-routine, operational behaviors. Completion of this pilot study demonstrated how the ReconaSense ANN could be used to identify expected operational patterns and detect unexpected anomalous behaviors in support of a data-analytic approach to ITDM. While additional studies are needed to fully understand and characterize this system, the results of this initial study are overall very promising for demonstrating a new framework for ITDM utilizing ANNs and data analysis techniques.
Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.
We present a methodology to access the proclivity of an organization to commit violence against nongovernment personnel. We fitted a Random Forest model using the Minority at Risk Organizational Behavior (MAROS) dataset. The MAROS data is longitudinal; so, individual observations are not independent. We propose a modification to the standard Random Forest methodology to account for the violation of the independence assumption. We present the results of the model fit, an example of predicting violence for an organization; and finally, we present a summary of the forest in a "meta-tree,"
Large organizations wield considerable market power, their procurement activities can be leveraged to achieve social, economic and environmental goals by ‘pulling’ more desirable products into the market. However, while there is substantial research in individual consumer buying behavior and market barriers to sustainable technology adoption, less is known about large organizational buying behavior and the impact of institutional barriers in this area. To address these research gaps, in this work we conducted an exploratory study aimed at better understanding the process through which large organizations purchase sustainable energy technologies and what internal barriers they experience during that process. Additionally, we surveyed and interviewed 120 individuals involved in procurement from Californian organizations representing both public and private sectors. Survey results indicate the need to resolve the conflict between prioritizing lowest first cost and lowest life cycle cost, better engage multiple stakeholders involved in internal decision-making around purchasing, and improve existing procurement tools or offer new ones. We provide recommendations for how policymakers can apply our findings to increase the adoption of sustainable energy technologies in their own organizations and communities.
Abstract It was last estimated in 2016 that data centers (DCs) comprise approximately 2% of total US electricity consumption. However, this estimate is currently being updated to account for the massive increase in computing needs due to streaming, cryptocurrency, and artificial intelligence (AI). To prevent energy consumption that tracks with increasing computing needs, it is imperative we identify energy efficiency strategies and investments beyond the low-hanging fruit solutions. In a two-phased research approach, we ask: What non-technical barriers still impede energy efficiency (EE) practices and investments in the data center sector, and what can be done to overcome these barriers? In particular, we are focused on social and organizational barriers to EE. In Phase I, we performed a literature review and found that technical solutions are abundant in the literature, but fail to address the top-down cultural shifts that need to take place in order to adapt new energy efficiency strategies. In Phase II, reported here, we interviewed 16 data center operators/experts to ground-truth our literature findings. Our interview protocols focus on three aspects of DC decision-making: procurement practices, metrics and monitoring, and perceived barriers to energy efficiency. We find that vendors are the key drivers of procurement decisions, advanced efficiency metrics are facility-specific, and there is convergence in the design of advanced facilities due to the heat density of parallelized infrastructure. Our ultimate goals for our research are to design DC decarbonization policies that target organizational structure, empower individual staff, and foster a supportive external market.
Organizations face rising pressure to take action to reduce their climate-affecting emissions (i.e., decarbonize). While many responses are possible, an essential approach—strategically managing their energy consumption as an essential business practice via an ISO 50001-based energy management system—is not yet widely recognized as a framework for decarbonization. This study analyzes interim survey results from 24 organizations (a 48% response rate) implementing a rigorous energy management system, one deployed by the U.S. Department of Energy as “50001 Ready”, to test whether participating organizations perceive the energy management system under development as an essential aspect of their decarbonization efforts. The results are preliminary in nature, given the ongoing nature of the program and associated data collection; however, they are sufficient to refute our hypothesis that energy management systems are perceived by organizations participating in 50001 Ready cohorts to primarily affect energy performance with little-to-no connection regarding decarbonization efforts. Major findings include that participants’ decarbonization targets and commitments are driven by market imperatives (highlighting the importance of ISO 50001 as a management system tool) and that they see energy efficiency as vital to decarbonizing. We conclude by suggesting future research directions to further establish the premise that energy management systems are an effective, efficient, and long-lasting decarbonization strategy.
Aviation is a dynamic industry which is constantly changing. These changes require the continuous update of people’s knowledge and skills. A fundamental part of that knowledge and skill is procedures, because procedures form the backbone of aviation operations. On the flightdeck, on the ramp, and in the maintenance shop, procedures and checklists help support pilots, line crews, and mechanics in performing their work effectively, efficiently, and thus -- safely. To design effective and efficient procedures and checklists, one must take into account the full operational context within which these procedures are embedded. This context is defined by the requirements of the technology, the capabilities and limitations of the human operators, and the constraints and affordances of the operational environment. The complexity of this context arises from the interactions of the human, machine, and environment. Procedures are in place to govern those interactions. We present a model of that operational context, namely THE Model (Technology, Human, Environment in the context of a Mission), that lays a foundation for the analysis of each of these elements and their interactions. But procedures have their limitations, and there are risks involved in over-proceduralizing. To understand these limitations and risks, and to determine when to proceduralize and when not, we present the 4P Framework (Practice, Procedures, Policies, Philosophy) as a holistic approach to procedures. This approach brings together the understanding of human behavior, of organizational and operational factors, and of the technologies involved.
Today's air traffic control system is approaching the point of saturation, as evidenced by increasing delays across the National Airspace System (NAS). There exists an opportunity to enhance NAS efficiency and reduce delays by improving strategic communication throughout the ATC system. Although several measures have been taken to improve communication (e.g., Collaborative Decision Making tools), communication issues between ATC facilities remain. It is hypothesized that by identifying the key issues plaguing inter-facility strategic communication, steps can be taken to enhance these communications, and therefore ATC system efficiency. In this report, a series of site visits were performed at Boston and New York ATC facilities as well as at the Air Traffic Control System Command Center. The results from these site visits were used to determine the current communication and coordination structure of Traffic Management Coordinators, who hold a pivotal role in inter-facility communications. Several themes emerged from the study, including: ambiguity of organizational structure in the current ATC system, awkward coordination between ATC facilities, information flow issues, organizational culture issues, and negotiation behaviors used to cope with organizational culture issues.
Domestic violent extremism has been on the rise in recent years, fueled by growing political polarization, the COVID-19 pandemic, and the spread of misinformation online. This concerning trend raises an important question: has this increase in extremist violence manifested in more incidents involving radioactive or nuclear (RN) materials and a corresponding security concern? To explore this question, we analyzed existing data on events involving chemical, biological, radiological, or nuclear materials over time. Specifically, we examined the rate of RN-related incidents, the targets of these events, and the ideologies motivating the perpetrators by using the Violent Non-State Actor Chemical, Biological, Radiological, and Nuclear Event Database from the National Consortium for the Study of Terrorism and Responses to Terrorism. Our analysis aimed to determine whether the broader rise of violent extremism has translated to an elevated risk of attacks involving RN materials. Results of the analysis revealed that there was no clear increase in events involving RN material in the dataset. However, given the rarity of these events, this conclusion does not indicate that such a trend might not appear in coming years if violent extremism continues to rise. To address the potential risk presented by violent extremism, in addition to quantifying the frequency of RN events, we also reviewed traits that could make organizations more susceptible to insider threats from radicalized employees. Focusing on the literature around counterproductive workplace behavior, we identified organizational characteristics that might increase the risk of malicious acts committed by radicalized insiders. These risk factors include abusive leadership, situational constraints, and organizational injustice. Finally, using these organizational risk characteristics, we discuss interventions that organizations with RN material can take to reduce their risk of attacks stemming from violent extremism while still protecting individual rights to privacy and civil liberties. Overall, this article provides an overview of the intersections between rising domestic extremism, insider threats, and risks posed by RN materials. We present current data on trends and patterns in this space as well as practical guidance for organizational resilience.
NASA is working to increase the likelihoods of human health and performance success during exploration missions, and subsequent crew long-term health. To manage the risks in achieving these goals, a system modeled after a Continuous Risk Management framework is in place. "Human System Risks" (Risks) have been identified, and approximately 30 are being actively addressed by NASA's Human Research Program (HRP). Research plans for each of HRP's Risks have been developed and are being executed. Ties between the research efforts supporting each Risk have been identified, however, this has been in an ad hoc fashion. There is growing recognition that solutions developed to address the full set of Risks covering medical, physiological, behavioral, vehicle, and organizational aspects of the exploration missions must be integrated across Risks and disciplines. We will discuss how a framework of factors influencing human health and performance in space is being applied as the backbone for bringing together sometimes disparate information relevant to the individual Risks. The resulting interrelated information is allowing us to identify and visualize connections between Risks and research efforts in a systematic and standardized way. We will discuss the applications of the visualizations and insights to research planning, solicitation, and decision-making processes.
Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.
This presentation, Risk-Based, Graded Approach to Insider Threat Mitigation: Human Measures, introduces a structured framework for managing insider threat risk using internationally recognized guidance from the International Atomic Energy Agency (IAEA) Nuclear Security Series No. 8-G (Rev. 1) and the Joint Statement on Mitigating Insider Threats (INFCIRC/908). The presentation emphasizes that effective insider threat mitigation (ITM) depends on both positional controls, which manage inherent risk based on access, authority, and knowledge, and human measures, which address residual risk reflected in behavior, motivation, and reliability. Using a risk-informed and graded approach, the presentation outlines methods for identifying and prioritizing high-risk positions, applying layered organizational controls, and integrating human reliability mechanisms such as the Behavior Observation Program (BOP), Fitness-for-Duty (FFD) evaluations, Employee Assistance Programs (EAP), and Nuclear Security Culture (NSC). The human-focused portion examines behavioral and organizational indicators of opportunity, vulnerability, motivation, and crisis, demonstrating how early detection, deterrence, and response can prevent insider events. The session concludes with a case review of the Millstone Nuclear Power Station incident involving engineer George Galatis. The case illustrates how weak leadership and a poor safety culture can create conditions for failure and how a comprehensive ITM framework could have altered the outcome. The objective of this presentation is to help practitioners apply a risk-based, graded philosophy to human factors and promote a culture of accountability, communication, and resilience within nuclear organizations.
Human collaboration in distributed knowledge sharing groups depends on the functionality of information and communication technologies (ICT) to support performance. Since many of these dynamic environments are constrained by time limits, knowledge must be shared efficiently by adapting the level of information detail to the specific situation. This paper focuses on the process of knowledge and context sharing with and without mediation by ICT, as well as issues to be resolved when determining appropriate ICT channels. Both technology-rich and non-technology examples are discussed.