Simulation of the Long-Term Effects of Decentralized and Adaptive Investments in Cross-Agency Interoperable and Standard IT Systems

Governments have come under increasing pressure to promote horizontal flows of information across agencies, but investment in cross-agency interoperable and standard systems have been minimally made since it seems to require government agencies to give up the autonomies in managing own systems and its outcomes may be subject to many external and interaction risks. By producing an agent-based model using 'Blanche' software, this study provides policy-makers with a simulation-based demonstration illustrating how government agencies can autonomously and interactively build, standardize, and operate interoperable IT systems in a decentralized environment. This simulation designs an illustrative body of 20 federal agencies and their missions. A multiplicative production function is adopted to model the interdependent effects of heterogeneous systems on joint mission capabilities, and six social network drivers (similarity, reciprocity, centrality, mission priority, interdependencies, and transitivity) are assumed to jointly determine inter-agency system utilization. This exercise simulates five policy alternatives derived from joint implementation of three policy levers (IT investment portfolio, standardization, and inter-agency operation). The simulation results show that modest investments in standard systems improve interoperability remarkably, but that a wide range of untargeted interoperability with lagging operational capabilities improves mission capability less remarkably. Nonetheless, exploratory modeling against the varying parameters for technology, interdependency, and social capital demonstrates that the wide range of untargeted interoperability responds better to uncertain future states and hence reduces the variances of joint mission capabilities. In sum, decentralized and adaptive investments in interoperable and standard systems can enhance joint mission capabilities substantially and robustly without requiring radical changes toward centralized IT management.Public IT Investment, Interoperability, Standardization, Social Network, Agent-Based Modeling, Exploratory Modeling

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human action is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems toward either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services toward some human end. We trace the salient features of modeled representations of human systems by organizing the typology around two key questions: (a) Who are the actors in MSD systems and what are their actions? (b) How and for what purpose are these actors and actions operationalized in a computational model? We use this typology to critically examine existing models and chart the frontier of human systems modeling for MSD research

Extemporaneous Coordination in Specialist Teams: The Familiarity Complementarity

Team production is ubiquitous in the economy, but managing teams effectively remains a challenge for many organizations. This paper studies how familiarity amongst teammates influences the performance of specialist teams, relative to non-specialist teams. Applying theories of team production to contexts where team members coordinate interdependent activities extemporaneously, we develop predictions about factors that shift the marginal returns to specialization along two dimensions of familiarity: social familiarity and functional familiarity. We test our hypotheses in the context of DOTA2, a major e-sports game where, in some formats, players are exogenously assigned to five- person teams. After analysing nearly 6.5 million matches, we find that specialist teams are relatively more successful when members are more socially and functionally familiar with one another. The results suggest that the “plug and play” perspective on specialist teams is incomplete; rather, specialization and familiarity are complements in dynamic environments where team members coordinate extemporaneously

Improved modelling of lifestyle changes in Integrated Assessment Models : Cross-disciplinary insights from methodologies and theories

Recent studies show that lifestyle changes can provide an essential contribution to achieving the Paris climate targets. While some efforts have been made to incorporate lifestyle changes into model-based scenarios, the attempts are currently very stylised and included exogenously. This paper discusses current efforts to represent lifestyle change in models, and analyses potential insights from relevant scientific disciplines to improve the representation of lifestyle changes in models – including modelling specific behaviour changes, identifying cross-cutting lifestyle solutions, representing the intentions behind the changes and quantifying their impacts. As such, this research attempts to bridge the gap between qualitative and quantitative theories and methodologies. Based on the results of this literature analysis, we recommend defining lifestyle changes more harmoniously, exploring an expanded range of approaches, domains and transformative solutions, adopting a whole-systems approach, and addressing the trade-offs between the use of exogenous inputs and endogenous modelling. © 2019 The AuthorsPeer reviewe

Denitrification-derived nitric oxide modulates biofilm formation in Azospirillum brasilense

Azospirillum brasilense is a rhizobacterium that provides beneficial effects on plants when they colonize roots. The formation of complex bacterial communities known as biofilms begins with the interaction of planktonic cells with surfaces in response to appropriate signals. Nitric oxide (NO) is a signaling molecule implicated in numerous processes in bacteria, including biofilm formation or dispersion, depending on genera and lifestyle. Azospirillum brasilense Sp245 produces NO by denitrification having a role in root growth promotion. We analyzed the role of endogenously produced NO on biofilm formation in A. brasilense Sp245 and in a periplasmic nitrate reductase mutant (napA::Tn5; Faj164) affected in NO production. Cells were statically grown in media with nitrate or ammonium as nitrogen sources and examined for biofilm formation using crystal violet and by confocal laser microscopy. Both strains formed bio- films, but the mutant produced less than half compared with the wild type in nitrate medium showing impaired nitrite production in this condition. NO measurements in biofilm confirmed lower values in the mutant strain. The addition of a NO donor showed that NO influences biofilm formation in a dose-dependent manner and reverses the mutant phenotype, indicating that Nap positively regulates the formation of biofilm in A. brasilense Sp245.Fil: Arruebarrena Di Palma, Andrés. Universidad Nacional de Mar del Plata; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pereyra, Cintia Mariana. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; ArgentinaFil: Moreno Ramírez, Lizbeth. Benemérita Universidad Autónoma de Puebla; MéxicoFil: Xiqui Vazquez, Maria L.. Benemérita Universidad Autónoma de Puebla; MéxicoFil: Baca, Beatriz E.. Benemérita Universidad Autónoma de Puebla; MéxicoFil: Pereyra, María Alejandra. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lamattina, Lamattina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Biológicas. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Biológicas; ArgentinaFil: Creus, Cecilia Mónica. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Modelling the effect of learning and evolving rules on the use of common-pool resources

The extend to which common-pool resources are used and managed sustainably depends highly on incentives. Incentives influence the behaviour of individuals with respect to natural resource management and are determined by institutional arrangements comprising of formal and informal rules and markets. Changes in institutional arrangements will affect individual incentives and will therefore have an impact on resource use. In order to model the connections between institutional arrangements and the sustainable use of common-pool resources we must take into consideration the behaviour of individuals. Game-theoretical models appear to be an adequate modelling technique with which to assess the behaviour of individuals as well as the development of institutions with regards to common-pool resource regimes. The implementation of a game-theoretical framework in the form of an agent-based model appears to be a particularly appropriate tool with which to assess common-pool resource use regimes as such models enable the behaviour of different agents to be modelled as strategies. Traditionally with agent-based models, the strategies that agents pursue are given, with their expression endogenously determined by the set of rules which govern their behaviour. In this paper I focus on the implementation of mechanisms that also allow for rules to adapt endogenously. Such an approach will be applied to common-pool resource use in order to analyse the effect of rule changes.Institutional arrangements, agent-based modelling, learning, evolving rules

Rural investment to accelerate growth and poverty reduction in Kenya:

"Kenya's economy is relatively diverse, with both agricultural and industrial potential. However, the economy has performed poorly over the last decade, and poverty and inequality have risen. This paper examines the impact of alternative growth paths and rural investments on poverty using an economy-wide model. It finds that if Kenya continues along its current growth path, its economy will have to grow by more than 10 percent per year over the coming decade to meet the Millennium Development Goal (MDG) of halving poverty by 2015. Therefore, Kenya must search for alternative sources of poverty-reducing growth. The results of the model indicate that poverty is unlikely to decline significantly without an acceleration of agricultural growth. Growth in agriculture is found to benefit both urban and rural households, whereas industry-led growth benefits a smaller segment of the urban population, thus exacerbating inequality. Kenya's current Economic Recovery Strategy, however, is not optimistic about agriculture's growth potential, focusing more heavily on industry-led growth. Therefore, as Kenya prepares its new national strategy, the country should place greater emphasis on and direct resources toward accelerating agricultural growth. In assessing the impact of rural investments on growth and poverty, the paper finds that increasing agricultural spending to meet the 10 percent target set by the Maputo Declaration would lift an additional 1.5 million people above the poverty line by 2015. Specific agricultural investments have higher returns in different parts of the country, however. Irrigation favors the lowlands and the poorest segment of the population, while research and extension (R&E) favors the midlands and highlands. Investment in R&E is also found to have the highest returns in both growth and poverty reduction. However, increasing agricultural spending to 10 percent of total spending is insufficient to meet either the MDG or the 6 percent agricultural growth target of the Comprehensive African Agriculture Development Program, which Kenya has recently adopted. . Achieving this target requires nonagricultural investments, such as in roads and market development. Building rural roads and reducing agricultural transaction costs significantly reduces poverty and encourages growth beyond rural areas. While it is necessary to increase spending on agriculture, the fiscal burden of an agricultural strategy can be greatly reduced by improving investment efficiency." from Author's AbstractAgriculture, Rural investment, Public investment, Poverty reduction, Inequality, Pro-poor growth,

Organizational and social challenges in the implementation of interdisciplinary postgraduate curricula

The institutionalization of interdisciplinary programmes is one way in which attempts are made to deepen the socially responsive nature of South African higher education. In this minor dissertation, two postgraduate interdisciplinary programmes that appear to be socially responsive in nature are examined to better understand the challenges of implementation that such programmes face. The aim is to gain insight into the ways in which these challenges may stem from the inherent difficulty of cross-disciplinary work, and to understand ways in which the institutional context works to support or inhibit such initiatives. The formal method of research is the case study; two case studies are made for comparative purposes. The data collected for this study suggests that both cases experienced some difficulty as a result of the social and epistemological differences which often arise when individuals from varying disciplines are brought together