Modeling dynamic community acceptance of mining using agent-based modeling

This research attempts to provide fundamental understanding into the relationship between perceived sustainability of mineral projects and community acceptance. The main objective is to apply agent-based modeling (ABM) and discrete choice modeling to understand changes in community acceptance over time due to changes in community demographics and perceptions. This objective focuses on: 1) formulating agent utility functions for ABM, based on discrete choice theory; 2) applying ABM to account for the effect of information diffusion on community acceptance; and 3) explaining the relationship between initial conditions, topology, and rate of interactions, on one hand, and community acceptance on the other hand. To achieve this objective, the research relies on discrete choice theory, agent-based modeling, innovation and diffusion theory, and stochastic processes. Discrete choice models of individual preferences of mining projects were used to formulate utility functions for this research. To account for the effect of information diffusion on community acceptance, an agent-based model was developed to describe changes in community acceptance over time, as a function of changing demographics and perceived sustainability impacts. The model was validated with discrete choice experimental data on acceptance of mining in Salt Lake City, Utah. The validated model was used in simulation experiments to explain the model\u27s sensitivity to initial conditions, topology, and rate of interactions. The research shows that the model, with the base case social network, is more sensitive to homophily and number of early adopters than average degree (number of friends). Also, the dynamics of information diffusion are sensitive to differences in clustering in the social networks. Though the research examined the effect of three networks that differ due to the type of homophily, it is their differences in clustering due to homophily that was correlated to information diffusion dynamics --Abstract, page iii

ABS-SOCI: An Agent-Based Simulator of Student Sociograms

Sociograms can represent the social relations between students. Some kinds of sociograms are more suitable than others for achieving a high academic performance of students. However, for now, at the beginning of an educative period, it is not possible to know for sure how the sociogram of a group of students will be or evolve during a semester or an academic year. In this context, the current approach presents an Agent-Based Simulator (ABS) that predicts the sociogram of a group of students taking into consideration their psychological profiles, by evolving an initial sociogram through time. This simulator is referred to as ABS-SOCI (ABS for SOCIograms). For instance, this can be useful for organizing class groups for some subjects of engineering grades, anticipating additional learning assistance or testing some teaching strategies. As experimentation, ABS-SOCI has been executed 100 times for each one of four real scenarios. The results show that ABS-SOCI produces sociograms similar to the real ones considering certain sociometrics. This similarity has been corroborated by statistical binomial tests that check whether there are significant differences between the simulations and the real cases. This experimentation also includes cross-validation and an analysis of sensitivity. ABS-SOCI is free and open-source to (1) ensure the reproducibility of the experiments; (2) to allow practitioners to run simulations; and (3) to allow developers to adapt the simulator for different environments

Measuring citizens' preferences for protecting environmental resources: applications of choice experiment surveys, social network analysis and Deliberative Citizens' juries

2017 Spring.Includes bibliographical references.Many reasons have been suggested as explanation for observed differences in citizens' environmental conservation projects policy choices and willingness-to-pay (WTP) values. Some people attribute this distinctive decision behavior to contrasts in the overall policy outcome expectations (preference heterogeneity) and/or differences in reactions to the changes in the environmental attributes (response heterogeneity). Others attribute this to differences in individual choice rationales, personalities, encounters, and past and present experiences. In other words, regardless of the possibility that outcomes are the same, people do not have the same emotions, convictions, disposition, or motivations. In three separate essays, I investigate the possible reasons for the observed differences in citizens' environmental conservation policy choices and examine how preference and response heterogeneity arise. In the first essay, I ask if a priori environmental damage perception is a source of heterogeneity affecting conservation option choice decisions. In the second, I investigate if social networks (interactions among decision-making agents) affect choice decisions. In the third, I investigate if preferences change when decision making agents are allowed to deliberate among peers. For the first essay, I conducted an on-line choice experiment (CE) survey. The survey asked questions that help to measure citizen preference for protecting environmental public goods, ascertain the value local residents are willing-to-pay (WTP), and determine how preference heterogeneity arises. CE attributes included groundwater use (measured by share of total water use from groundwater), aquatic habitat (measured by count of spawning kokanee salmon return), natural habitat health (measured by the sensitive ecosystem area reclaimed), and rural character (measured by a decrease in urban sprawl and/or a decrease in population density in rural areas). I used a special property levy as the vehicle of payment. Random parameter logit (RP) and latent class (LC) models were estimated to capture response and preference heterogeneity. The results suggest that (1) both preference and response heterogeneities were found for the choices and all environmental attributes respectively (2) respondents who have a higher value for one environmental good will have a higher value for other environmental goods, and (3) a priori damage perception could be one of the sources of response and preference heterogeneity. In the same survey, I included people's egocentric networks, interactions, environment related activities and perceptions to empirically evaluate whether social network effect (SNE) is a source of systematic differences in preference. I estimate consumer preferences for a hypothetical future environmental conservation management alternative described by its attributes within a Nested Logit Model: nesting broader and distinct conservation options within choices impacted by individual's network structure. The results show that some network centrality measures capture preference heterogeneity, and consequently the differences in WTP values in a systematic way. Third, I compare the value estimated based on the traditional choice experiment (CE) with the results obtained using the citizen jury (CJ) approach or a group-based approach or also called the "Market Stall" in some literature. I estimate the effect of deliberation on conservation choice outcomes by removing any significant differences between the people who participated in the CJ (people who volunteered to be contacted again after deliberation treatment) and those people who did the survey twice but did not volunteer for CJ (control group) in terms of their socioeconomic status and be able attribute the changes in preferences to deliberation treatment only. CJ approach involved two 90 minute deliberations held over two days to discuss and consider their preferences and WTP values with other household members. Results show that deliberation improves individuals' valuation process and there is observed difference in choice outcomes between the deliberation treatment and control groups. Both preference and response heterogeneity relatively vanish when people were allowed to deliberate among peers

Shaking hands with common foes : Clique premium and information diffusion in private equity networks

The fastest growing segment of private equity deals is secondary buyouts (SBOs) sales from one private equity (PE) firm to another. We operationalize a novel FactSet database to map the network structures of secondary buyouts between PE firms. We offer three contributions. First, after controlling for economic covariates, we find that PE firms are almost three times more likely to transact if they share a partner, that is both firms belong to the same clique. Second, we find that the profitability of such transactions is unambiguously higher relative to the baseline only if these are the result of repeated interaction between firms belonging to the same cliques. In other words, a clique premium exists under repeated interaction. Third, we provide evidence that the economic incentive at the core of clique premium may be related to access to information. In fact, we show that information related to transactions diffuses through the network, with 23% and 16% of the information going one and two steps beyond transacting parties, respectively

Sustaining Glasgow's Urban Networks: the Link Communities of Complex Urban Systems

As cities grow in population size and became more crowded (UN DESA, 2018), the main future challenges around the world will remain to be accommodating the growing urban population while drastically reducing environmental pressure. Contemporary urban agglomerations (large or small) constantly impose burden on the natural environment by conveying ecosystem services to close and distant places, through coupled human nature [infrastructure] systems (CHANS). Tobler’s first law in geography (1970) that states that “everything is related to everything else, but near things are more related than distant things” is now challenged by globalization. When this law was first established, the hypothesis referred to geological processes (Campbell and Shin, 2012, p.194) that were predominantly observed in pre-globalized economy, where freight was costly and mainly localized (Zhang et al., 2018). With the recent advances and modernisation made in transport technologies, most of them in the sea and air transportation (Zhang et al., 2018) and the growth of cities in population, natural resources and bi-products now travel great distances to infiltrate cities (Neuman, 2006) and satisfy human demands. Technical modernisation and the global hyperconnectivity of human interactions and trading, in the last thirty years alone resulted with staggering 94 per cent growth of resource extraction and consumption (Giljum et al., 2015). Local geographies (Kennedy, Cuddihy and Engel-Yan, 2007) will remain affected by global urbanisation (Giljum et al., 2015), and as a corollary, the operational inefficiencies of their local infrastructure networks, will contribute even more to the issues of environmental unsustainability on a global scale. Another challenge for future city-regions is the equity of public infrastructure services and policy creation that promote the same (Neuman and Hull, 2009). Public infrastructure services refer to services provisioned by networked infrastructure, which are subject to both public obligation and market rules. Therefore, their accessibility to all citizens needs to be safeguarded. The disparity of growth between networked infrastructure and socio-economic dynamics affects the sustainable assimilation and equal access to infrastructure in various districts in cities, rendering it as a privilege. Yet, the empirical evidence of whether the place of residence acts as a disadvantage to public service access and use, remains rather scarce (Clifton et al., 2016). The European Union recognized (EU, 2011) the issue of equality in accessibility (i.e. equity) critical for territorial cohesion and sustainable development across districts, municipalities and regions with diverse economic performance. Territorial cohesion, formally incorporated into the Treaty of Lisbon, now steers the policy frameworks of territorial development within the Union. Subsequently, the European Union developed a policy paradigm guided by equal access (Clifton et al., 2016) to public infrastructure services, considering their accessibility as instrumental aspect in achieving territorial cohesion across and within its member states. A corollary of increasing the equity to public infrastructure services among growing global population is the potential increase in environmental pressure they can impose, especially if this pressure is not decentralised and surges at unsustainable rate (Neuman, 2006). This danger varies across countries and continents, and is directly linked to the increase of urban population due to; [1] improved quality of life and increased life expectancy and/or [2] urban in-migration of rural population and/or [3] global political or economic immigration. These three rising urban trends demand new approaches to reimagine planning and design practices that foster infrastructure equity, whilst delivering environmental justice. Therefore, this research explores in depth the nature of growth of networked infrastructure (Graham and Marvin, 2001) as a complex system and its disparity from the socio-economic growth (or decline) of Glasgow and Clyde Valley city-region. The results of this research gain new understanding in the potential of using emerging tools from network science for developing optimization strategy that supports more cecentralized, efficient, fair and (as an outcome) sustainable enlargement of urban infrastructure, to accommodate new and empower current residents of the city. Applying the novel link clustering community detection algorithm (Ahn et al., 2010) in this thesis I have presented the potential for better understanding the complexity behind the urban system of networked infrastructure, through discovering their overlapping communities. As I will show in the literature review (Chapter 2), the long standing tradition of centralised planning practice relying on zoning and infiltrating infrastructure, left us with urban settlements which are failing to respond to the environmental pressure and the socio-economic inequalities. Building on the myriad of knowledge from planners, geographers, sociologists and computer scientists, I developed a new element (i.e. link communities) within the theory of urban studies that defines cities as complex systems. After, I applied a method borrowed from the study of complex networks to unpack their basic elements. Knowing the link (i.e. functional, or overlapping) communities of metropolitan Glasgow enabled me to evaluate the current level of communities interconnectedness and reveal the gaps as well as the potentials for improving the studied system’s performance. The complex urban system in metropolitan Glasgow was represented by its networked infrastructure, which essentially was a system of distinct sub-systems, one of them mapped by a physical and the other one by a social graph. The conceptual framework for this methodological approach was formalised from the extensively reviewed literature and methods utilising network science tools to detect community structure in complex networks. The literature review led to constructing a hypothesis claiming that the efficiency of the physical network’s topology is achieved through optimizing the number of nodes with high betweenness centrality, while the efficiency of the logical network’s topology is achieved by optimizing the number of links with high edge betweenness. The conclusion from the literature review presented through the discourse on to the primal problem in 7.4.1, led to modelling the two network topologies as separate graphs. The bipartite graph of their primal syntax was mirrored to be symmetrical and converted to dual. From the dual syntax I measured the complete accessibility (i.e. betweenness centrality) of the entire area and not only of the streets. Betweenness centrality of a node measures the number of shortest paths that pass through the node connecting pairs of nodes. The betweenness centrality is same as the integration of streets in space syntax, where the streets are analysed in their dual syntax representation. Street integration is the number of intersections the street shares with other streets and a high value means high accessibility. Edges with high betweenness are shared between strong communities. Based on the theoretical underpinnings of the network’s modularity and community structure analysed herein, it can be concluded that a complex network that is both robust and efficient (and in urban planning terminology ‘sustainable’) is consisted of numerous strong communities connected with each other by optimal number of links with high edge betweenness. To get this insight, the study detected the edge cut-set and vertex cut-set of the complex network. The outcome was a statistical model developed in the open source software R (Ihaka and Gentleman, 1996). The model empirical detects the network’s overlapping communities, determining the current sustainability of its physical and logical topologies. Initially, an assumption was that the number of communities within the infrastructure (physical) network layer were different from the one in the logical. They were detected using the Louvain method that performs graph partitioning on the hierarchical streets structure. Further, the number of communities in the relational network layer (i.e. accessibility to locations) was detected based on the OD accessibility matrix established from the functional dependency between the household locations and predefined points of interest. The communities from the graph of the ‘relational layer' were discovered with the single-link hierarchical clustering algorithm. The number of communities observed in the physical and the logical topologies of the eight shires significantly deviated

Recommender Systems

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has a great scientific depth and combines diverse research fields which makes it of interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports