Relational Model Conflicts in Knowledge Sharing Behavior

The distributed nature of organizational knowledge makes that knowledge sharing an important factor for unlocking its potential value. In practice, however, people may have different motivations for not sharing knowledge with colleagues, which in part may be due to the relational context. In this paper, we adopt Fiske’s Relational Model Theory to investigate relational dynamics in knowledge sharing behavior. Our objective is to gain insight into how relational model conflicts affect knowledge sharing in organizations. A series of experiments have been conducted, in which the consequences of relational model conflicts for the willingness to share knowledge are evaluated. Each experiment contained four scenarios reflecting different relational models. Participants were faced with different scenarios reflecting particular relational models, and a fictitious other colleague who behaved according to a conflicting relational model. Our analysis shows that the recognition of relational model conflicts strongly depends on the relational models involved. The extent of recognition seems to be related with the nature of the exchange relationships involved in the conflict. For instance, the relational model conflict was more acutely felt by a communal sharing participant facing a market pricing colleague, than by the same participant dealing with an authority ranking response. Likewise, we find that the impact of relational model conflicts on the willingness to share knowledge depends on the relational models involved. Specifically, it appears that market pricing responses have a negative influence on participants’ willingness to share, while communal sharing responses generally have positive effects. Our research serves as a starting point for other studies aiming at a deeper understanding of the dynamics of knowledge sharing behavior of employees and for solving conflicts at work

Apollo to Artemis: Mining 50-Year Old Records to Inform Future Human Lunar Landing Systems

Under the Artemis lunar exploration program, NASA is committed to landing American astronauts on the moon by 2024. While NASAs new Space Launch System rocket and Orion capsule will carry astronauts from Earth to the Gateway, the human lunar landing system has not yet been fully defined. As in the Apollo program, there are concerns for vehicle weight and internal volume such that seats may not be desirable, and standing during lunar descent and ascent may be a preferred engineering solution. With such a design, astronauts will experience +GZ (head-to-foot) accelerations during capsule accelerations, and it is unclear whether spaceflight deconditioned astronauts can tolerate these. Apollo astronauts stood during lunar descent and ascent, and the data contained in the early program records for those missions represent a unique resource that may provide insights to the cardiovascular stress associated with this human landing system design

Cluster approximations for infection dynamics on random networks

In this paper, we consider a simple stochastic epidemic model on large regular random graphs and the stochastic process that corresponds to this dynamics in the standard pair approximation. Using the fact that the nodes of a pair are unlikely to share neighbors, we derive the master equation for this process and obtain from the system size expansion the power spectrum of the fluctuations in the quasi-stationary state. We show that whenever the pair approximation deterministic equations give an accurate description of the behavior of the system in the thermodynamic limit, the power spectrum of the fluctuations measured in long simulations is well approximated by the analytical power spectrum. If this assumption breaks down, then the cluster approximation must be carried out beyond the level of pairs. We construct an uncorrelated triplet approximation that captures the behavior of the system in a region of parameter space where the pair approximation fails to give a good quantitative or even qualitative agreement. For these parameter values, the power spectrum of the fluctuations in finite systems can be computed analytically from the master equation of the corresponding stochastic process.Comment: the notation has been changed; Ref. [26] and a new paragraph in Section IV have been adde

Post-Flight Back Pain Following International Space Station Missions: Evaluation of Spaceflight Risk Factors

INTRODUCTION Back pain during spaceflight has often been attributed to the lengthening of the spinal column due to the absence of gravity during both short and long-duration missions. Upon landing and re-adaptation to gravity, the spinal column reverts back to its original length thereby causing some individuals to experience pain and muscular spasms, while others experience no ill effects. With International Space Station (ISS) missions, cases of back pain and injury are more common post-flight, but little is known about the potential risk factors. Thus, the purpose of this project was to perform an initial evaluation of reported post-flight back pain and injury cases to relevant spaceflight risk factors in United States astronauts that have completed an ISS mission. METHODS All US astronauts who completed an ISS mission between Expeditions (EXP) 1 and 41 (2000-2015) were included in this evaluation. Forty-five astronauts (36 males and 9 females) completed 50 ISS missions during the study time period, as 5 astronauts completed 2 ISS missions. Researchers queried medical records of the 45 astronauts for occurrences of back pain and injury. A case was defined as any reported event of back pain or injury to the cervical, thoracic, lumbar, sacral, or coccyx spine regions. Data sources for the cases included the Flight Medicine Clinic's electronic medical record; Astronaut Strength, Conditioning and Rehabilitation electronic documentation; the Private Medical Conference tool; and the Space Medicine Operations Team records. Post-flight cases were classified as an early case if reported within 45 days of landing (R + 45) or a late case if reported from R + 46 to R + 365 days after landing (R + 1y). Risk factors in the astronaut population for back pain include age, sex, prior military service, and prior history of back pain. Additionally, spaceflight specific risk factors such as type of landing vehicle and onboard exercise countermeasures were included to evaluate their contribution to post-flight cases. Prior history of back pain included back pain recorded in the medical record within 3 years prior to launch. Landing vehicle was included in the model to discern if more astronauts experienced back pain or injury following a Shuttle or Soyuz landing. Onboard exercise countermeasures were noted for those astronauts who had a mission following 2009 deployment of the Advanced Resistive Exercise Device (aRED) (EXP 19 to 41). T-test and chi-squared tests were performed to evaluate the association between each individual risk factor and post-flight case. Logistic regression was used to evaluate the combined contribution of all the risk factors on post-flight cases. Separate models were calculated for cases reported by R + 45 and R + 1y. RESULTS During the study time period, there were 13 post-flight cases reported by R + 45 and an additional 5 reported by R + 1y. Most of these cases have been reported since EXP 19 with 10 cases by R + 45 and 4 by R + 1y. Individual risk factors of age, sex, landing vehicle, and prior military service were not significantly associated with post-flight cases identified at R + 45 or R + 1y (p greater than 0.05). Having back pain or injury within 3 years prior to launch significantly increased the likelihood of becoming a case by R + 1y (p = 0.041), but not at R+45 (p=0.204). Additionally, astronauts who experienced onboard exercise countermeasures that included aRED had a significantly increased risk of becoming a case at R + 45 (p = 0.024) and R + 1y (p=0.003). Multiple logistic regression evaluating all the risk factors for cases identified no significant risk factors at either the R + 45 or R + 1y time period (p greater than 0.05). Overall model fit was poor for both the R + 45 (R(exp 2) = 0.132) and R + 1y (R(exp 2) = 0.186) cases showing that there are risk factors not represented in our model. CONCLUSIONS Regardless of cause, post-flight cases are reported more often since aRED was deployed in 2009. This may reflect improved documentation or unidentified risk factors. No spaceflight risk factor explains the data fully. Post-flight cases are probably due to multi-faceted factors that are not easily elucidated in the medical data