Introduction Integrated water management (IWM) involves a range of policies, actions, and organizational processes that go beyond traditional hydrology to consider multifaceted aspects of complex water resource systems. Due to its transdisciplinary nature, IWM comprises input from diverse stakeholders, each with unique perceptions, values, and experiences. However, stakeholders from differing backgrounds may disagree on best practices and collective paths forward. As such, successful IWM must address key governance principles (e.g., information flow, collective decision-making, and power relations) across social and institutional scales. Here, we sought to demonstrate how network structure impacts shared decision-making within IWM. Methods We explored a case study in Houston, Texas, USA, where decision-making stakeholders from various sectors and levels of governance engaged in a participatory modeling workshop to improve adoption of nature-based solutions (NBS) through IWM. The stakeholders used fuzzy cognitive mapping (FCM) to define an IWM model comprising multifaceted elements and their interrelationships, which influenced the adoption of NBS in Houston. We applied grounded theory and inductive reasoning to categorize tacit belief schemas regarding how stakeholders viewed themselves within the management system. We then used FCM-based modeling to explore how unique NBS policies would translate into more (or less) NBS adoption. Finally, we calculated specific network metrics (e.g., density, hierarchy, and centrality indices) to better understand the structure of human-water relations embedded within the IWM model. We compared the tacit assumptions about stakeholder roles in IWM against the quantitative degrees of influence and collectivism embedded within the stakeholder-defined model. Results and discussion Our findings revealed a mismatch between stakeholders' external belief statements about IWM and their internal assumptions through cognitive mapping and participatory modeling. The case study network was characterized by a limited degree of internal coordination (low density index), high democratic potential (low hierarchy index), and high-efficiency management opportunities (high centrality index), which transcended across socio-institutional scales. These findings contrasted with several of the belief schemas described by stakeholders during the group workshop. We describe how ongoing partnership with the stakeholders resulted in an opportunity for adaptive learning, where the NBS planning paradigm began to shift toward trans-scale collaboration aimed at high-leverage management opportunities. We emphasize how network analytics allowed us to better understand the extent to which key governance principles drove the behavior of the IWM model, which we leveraged to form deeper stakeholder partnerships by identifying hidden opportunities for governance transformation.
more »
« less
Interpretable Stochastic Block Influence Model: Measuring Social Influence Among Homophilous Communities
Decision-making on networks can be explained by both homophily and social influences. While homophily drives the formation of communities with similar characteristics, social influences occur both within and between communities. Social influences can be reasoned through role theory, which indicates that the influences among individuals depending on their roles and the behavior of interest. To operationalize these social science theories, we empirically identify the homophilous communities and use the community structures to capture such “roles”, affecting particular decision-making processes. We propose a generative model named the Stochastic Block influences Model and jointly analyzed both network formation and behavioral influences within and between different empirically-identified communities. To evaluate the performance and demonstrate the interpretability of our method, we study the adoption decisions for a microfinance product in Indian villages. We show that although individuals tend to form links within communities, there are strongly positive and negative social influences between communities, supporting the weak ties theory. Moreover, communities with shared characteristics are associated with positive influences. In contrast, communities that do not overlap are associated with negative influences. Our framework facilitates the quantification of the influences underlying decision communities and is thus a helpful tool for driving information diffusion, viral marketing, and technology adoption.
more »
« less
- Award ID(s):
- 2153468
- NSF-PAR ID:
- 10451835
- Date Published:
- Journal Name:
- IEEE Transactions on Knowledge and Data Engineering
- ISSN:
- 1041-4347
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Motivation: The question of what combination of attributes drives the adoption of a particular software technology is critical to developers. It determines both those technologies that receive wide support from the community and those which may be abandoned, thus rendering developers' investments worthless. Aim and Context: We model software technology adoption by developers and provide insights on specific technology attributes that are associated with better visibility among alternative technologies. Thus, our findings have practical value for developers seeking to increase the adoption rate of their products. Approach: We leverage social contagion theory and statistical modeling to identify, define, and test empirically measures that are likely to affect software adoption. More specifically, we leverage a large collection of open source repositories to construct a software dependency chain for a specific set of R language source-code files. We formulate logistic regression models, where developers' software library choices are modeled, to investigate the combination of technological attributes that drive adoption among competing data frame (a core concept for a data science languages) implementations in the R language: tidy and data.table. To describe each technology, we quantify key project attributes that might affect adoption (e.g., response times to raised issues, overall deployments, number of open defects, knowledge base) and also characteristics of developers making the selection (performance needs, scale, and their social network). Results: We find that a quick response to raised issues, a larger number of overall deployments, and a larger number of high-score StackExchange questions are associated with higher adoption. Decision makers tend to adopt the technology that is closer to them in the technical dependency network and in author collaborations networks while meeting their performance needs. To gauge the generalizability of the proposed methodology, we investigate the spread of two popular web JavaScript frameworks Angular and React, and discuss the results. Future work: We hope that our methodology encompassing social contagion that captures both rational and irrational preferences and the elucidation of key measures from large collections of version control data provides a general path toward increasing visibility, driving better informed decisions, and producing more sustainable and widely adopted software.more » « less
-
We use high-resolution mobile phone data with geolocation information and propose a novel technical framework to study how social influence propagates within a phone communication network and affects the offline decision to attend a performance event. Our fine-grained data are based on the universe of phone calls made in a European country between January and July 2016. We isolate social influence from observed and latent homophily by taking advantage of the rich spatial-temporal information and the social interactions available from the longitudinal behavioral data. We find that influence stemming from phone communication is significant and persists up to four degrees of separation in the communication network. Building on this finding, we introduce a new “influence” centrality measure that captures the empirical pattern of influence decay over successive connections. A validation test shows that the average influence centrality of the adopters at the beginning of each observational period can strongly predict the number of eventual adopters and has a stronger predictive power than other prevailing centrality measures such as the eigenvector centrality and state-of-the-art measures such as diffusion centrality. Our centrality measure can be used to improve optimal seeding strategies in contexts with influence over phone calls, such as targeted or viral marketing campaigns. Finally, we quantitatively demonstrate how raising the communication probability over each connection, as well as the number of initial seeds, can significantly amplify the expected adoption in the network and raise net revenue after taking into account the cost of these interventions. History: Sam Ransbotham, Senior Editor; Yan Huang, Associate Editor. Funding: Y. Leng acknowledges the support provided by the National Science Foundation [Grant IIS-2153468]. E. Moro acknowledges the support provided by the National Science Foundation [Grant 2218748]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2023.1231 .more » « less
-
null (Ed.)In recent years, studies in engineering education have begun to intentionally integrate disability into discussions of diversity, inclusion, and equity. To broaden and advocate for the participation of this group in engineering, researchers have identified a variety of factors that have kept people with disabilities at the margins of the field. Such factors include the underrepresentation of disabled individuals within research and industry; systemic and personal barriers, and sociocultural expectations within and beyond engineering education-related contexts. These findings provide a foundational understanding of the external and environmental influences that can shape how students with disabilities experience higher education, develop a sense of belonging, and ultimately form professional identities as engineers. Prior work examining the intersections of disability identity and professional identity is limited, with little to no studies examining the ways in which students conceptualize, define, and interpret disability as a category of identity during their undergraduate engineering experience. This lack of research poses problems for recruitment, retention, and inclusion, particularly as existing studies have shown that the ways in which students perceive and define themselves in relation to their college major is crucial for the development of a professional engineering identity. Further, due to variation in defining ‘disability’ across national agencies (e.g., the National Institutes of Health, and the Department of Justice) and disability communities (with different models of disability), the term “disability” is broad and often misunderstood, frequently referring to a group of individuals with a wide range of conditions and experiences. Therefore, the purpose of this study is to gain deeper insights into the ways students define disability and disability identity within their own contexts as they develop professional identities. Specifically, we ask the following research question: How do students describe and conceptualize non-apparent disabilities? To answer this research question, we draw from emergent findings from an on-going grounded theory exploration of professional identity formation of undergraduate civil engineering students with disabilities. In this paper, we focus our discussion on the grounded theory analyses of 4 semi-structured interviews with participants who have disclosed a non-apparent disability. Study participants consist of students currently enrolled in undergraduate civil engineering programs, students who were initially enrolled in undergraduate civil engineering programs and transferred to another major, and students who have recently graduated from a civil engineering program within the past year. Sensitizing concepts emerged as findings from the initial grounded theory analysis to guide and initiate our inquiry: 1) the medical model of disability, 2) the social model of disability, and 3) personal experience. First, medical models of disability position physical, cognitive, and developmental difference as a “sickness” or “condition” that must be “treated”. From this perspective, disability is perceived as an impairment that must be accommodated so that individuals can obtain a dominantly-accepted sense of normality. An example of medical models within the education context include accommodations procedures in which students must obtain an official diagnosis in order to access tools necessary for academic success. Second, social models of disability position disability as a dynamic and fluid identity that consists of a variety of physical, cognitive, or developmental differences. Dissenting from assumptions of normality and the focus on individual bodily conditions (hallmarks of the medical model), the social model focuses on the political and social structures that inherently create or construct disability. An example of a social model within the education context includes the universal design of materials and tools that are accessible to all students within a given course. In these instances, students are not required to request accommodations and may, consequently, bypass medical diagnoses. Lastly, participants referred to their own life experiences as a way to define, describe, and consider disability. Fernando considers his stutter to be a disability because he is often interrupted, spoken over, or silenced when engaging with others. In turn, he is perceived as unintelligent and unfit to be a civil engineer by his peers. In contrast, David, who identifies as autistic, does not consider himself to be disabled. These experiences highlight the complex intersections of medical and social models of disability and their contextual influences as participants navigate their lives. While these sensitizing concepts are not meant to scope the research, they provide a useful lens for initiating research and provides markers on which a deeper, emergent analysis is expanded. Findings from this work will be used to further explore the professional identity formation of undergraduate civil engineering students with disabilities. These findings will provide engineering education researchers and practitioners with insights regarding the ways individuals with disabilities interpret their in- and out-of-classroom experiences and navigate their disability identities. For higher education, broadly, this work aims to reinforce the complex and diverse nature of disability experience and identity, particularly as it relates to accommodations and accessibility within the classroom, and expand the inclusiveness of our programs and institutions.more » « less
-
null (Ed.)his panel paper presents research on connecting theory to practice and the lessons learned in a change project, with a focus on team formation during the early stages of change making. An important yet often overlooked step in any change project is pulling together individuals to form a competent and efficient team. A functional change-making team requires a variety of complementary skill sets, which may come from different disciplinary backgrounds and/or different prior experiences. Kotter (1996) uses the term “guiding coalition” to refer to an effective change-making team. He identifies four key characteristics of guiding coalitions: position power, expertise, credibility, leadership. Kotter also goes on to examine the importance of trust and a common goal. In a review of the literature on guiding coalitions, Have, Have, Huijsmans, and Otto (2017) found that though the concept of a guiding coalition is widely advocated in the literature, only one study showed a moderate correlation between the existence of a guiding coalition and the success of a change process (Abraham, Griffin, & Crawford, 1999). Have et al. (2017) conclude that while the literature provides little evidence to the value of a guiding coalition, it does provide evidence that Kotter’s characteristics of a guiding coalition (position power, expertise, credibility, leadership skills, trust in leadership, and setting common goals) individually have positive effects on the outcomes of a change project. However, we don’t know how these characteristics interact. This analysis of team building and complementary skill sets emerges from our participatory action research with the NSF REvolutionizing engineering and computer science Departments (RED) teams to investigate the change process within STEM higher education. The research-to-practice cycle is integral to our project; data gathered through working with the RED teams provides insights that are then translated into applied, hands-on practices. We utilize an abductive analysis approach, a qualitative methodology that moves recursively between the data and theory-building to remain open to new or contradictory findings, keeping existing theory in mind while not developing formal hypotheses (Timmermans & Tavory, 2012). We find that many of the teams have learned lessons in the early stages of the change process around the guiding coalition characteristics, and our analysis builds on the literature by examining how these characteristics interact. For example, the expertise of the social scientists and education researchers help discern which change strategies have supporting evidence and fit the context, in addition to what is reasonable for planning, implementation, and evaluation. The results presented in this paper connect theory to practice, clarifying practices for building effective change-making teams within higher education.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/TKDE.2023.3289848
