Key Patterns Research Articles

Identifying key landscape pattern indices influencing the NPP: A case study of the upper and middle reaches of the Yellow River

Human activities and climate change directly affect the composition, structure, and function of ecosystems and, consequently, their net primary productivity (NPP). In this study, we explored the response relationships between landscape pattern indices and NPP changes in three major vegetation types (forest, grassland, and shrubland) in the upper and middle reaches of the Yellow River Basin using a random forest model. The results showed that landscape fragmentation increased, leading to higher landscape heterogeneity and edge effects. Patch shapes became more irregular, and spatial distribution became more dispersed. From 2000 to 2015, both vegetation types and NPP showed significant spatial heterogeneity in the study area. The number of patches (NP), largest patch index (LPI), and percent-like adjacency (PLADJ) metrics were used to determine the core landscape characteristics to assess the NPP changes in forest, shrubland, and grassland, respectively. This study provides a basis for understanding the relationships among landscape patterns, vegetation types, and NPP and serves as a reference for developing NPP predictive models in the Loess Plateau region.

IMITATION STRATEGIES IN ENTREPRENEURSHIP: BIBLIOMETRIC ANALYSIS

The article presents the research results on the evolution of key patterns of scientific publications devoted to the use of imitation strategies by business entities. End of purpose was ensured by solving two interrelated tasks: first, to form a relevant sample of scientific articles (2,302 publications on selected topic, indexed by the Scopus scientometric database, for the period from 1992 to 2022); secondly, to analyse the co-occurrence of keywords to characterise the current state of the research field and determining the perspective of its development. The terms “imitation strategy, innovation” or “innovation, imitation, strategy” were chosen as keywords. The bibliometric analysis and visualisation of its results were performed using the VOSviewer software product. On the basis of visualisation maps, five clusters of the content matching of keywords in articles and five stages of the evolutionary development of innovative behavior of enterprises were identified. The results of the research can be used in studying various aspects of the implementation the imitation strategies by business entities.

The effect of hormones insulin and glucagon on ubiquitin modifications elucidated by proteomics in liver cells

AimsInsulin action is intertwined with changing levels of glucose and counter-regulatory hormone glucagon. While insulin lowers blood sugar level, glucagon raises it by promoting the breakdown of the stored glycogen in liver and releases glucose into the bloodstream. The hormones insulin and glucagon are key in the pathogenesis of type 2 diabetes (T2D). Insulin resistance is a primary predisposing factor for diabetes. Phosphorylation of insulin signaling molecules is altered in the insulin-resistant state. However, ubiquitin (Ub) modifications in insulin-resistant state are relatively understudied. To dissect the underlying mechanisms, we performed a proteomics study on hepatoma cells to study the regulation of ubiquitination by insulin and glucagon. Materials and methodsWe performed western blotting, immunoprecipitations, and affinity pull down using tandem Ub binding entities (TUBE) reagents on hepatoma cells treated with insulin or glucagon. Next, we performed MS/MS analysis on Ub-linkage specific affinity pull down samples. Gene ontology analysis and protein-protein interaction network analysis was performed using DAVID GO and STRING db, respectively. Key findingsThe ubiquitination pattern of total Ub, K48-linked Ub, and K63-linked Ub was altered with the treatment of hormones insulin and glucagon. Ubiquitination in immunoprecipitated samples showed enrichment with total Ub and K48-linked Ub but not with K63-linked Ub. Ubiquitination by treatment with hormones mainly enriched key signaling pathways MAPK, Akt, oxidative stress etc. SignificanceOur study identified key altered proteins and signal transduction pathways which aids in understanding the mechanisms of hormonal action on ubiquitination and identify new therapeutic targets for T2D.

Information Seeking Behavior and Information Blockades: An Antithetical Relationship?

ABSTRACT With more than half of the humans on the planet becoming internet users, the amount of information created and accessed is enormous. The Internet has become the most popular medium and source for seeking information. The information-seeking behavior is exhibiting itself. In Kashmir, India – users, businesses, and institutions use Internet to access and disseminate information. But, information blockades seem to hamper the seeking and delivering of information. Information blockades have become an increasing occurrence in various countries worldwide. Most often imposed in regions that witness some form of instability, such as economic or political; information blockades disrupt the primary communication channels. However, studies exploring the relationship between information-seeking behavior and information blockades are scarce. This study is a novel call for focusing research endeavors on information-seeking behavior and its antithetical counterpart, i.e. Information blockade. This paper uses various statistical resources and employs an intensive content analysis method to analyze the literature and identify key themes and patterns of research undertaken on information-seeking behavior and information blockades, especially in Kashmir, India. For the current discourse, ostensibly, the two phenomena have an antithetical relationship and more studies need to be conducted to understand the dynamics of how these two phenomena co-exist.

Social media analytics

Social media has become increasingly relevant for surgeons, trainees, surgical journals, and professional organizations. This article explores the importance of advanced social media analytics, including social media metrics, social graph metrics, and altmetrics, in enhancing information exchange and promoting content in digital surgical communities. Different social media platforms give users access to free analytics, such as Twitter Analytics, Facebook Page Insights, Instagram Insights, LinkedIn Analytics, and YouTube Analytics, and various commercial applications offer advanced metrics and data visualization. Social graph metrics provide insights into a social surgical network's structure and dynamics, helping identify key influencers, communities, trends, or behavior patterns within the network. Altmetrics allow alternative ways to measure the social impact of research beyond traditional citations, including mentions, downloads, and shares on social media platforms. However, ethical issues related to privacy, accuracy, transparency, accountability, and impact on patient care must be considered when using social media analytics.

A Kaleidoscope of Play and Learning in Online Spaces during COVID-19 Times: Insights from Early Childhood Educators

Through the perspectives of early childhood educators (ECEs) working with under-fives, this article explores how play and learning featured when shifted abruptly to online spaces during COVID-19 in Malta. This work draws on Siemens’ connectivism learning theory which sees the integration of technology and social interactions as connections that empower learning in a digital age. The COVID-19 scenario called for immediately available data; consequently, a quantitative methodology was adopted. Two online surveys were held: in 2020 and 2021. Two hundred sixty-three ECEs participated in the first online survey, while seventy-nine the second. Findings locate benefits, challenges, and opportunities for play and learning online, shaped by the development of three key changing patterns in Maltese ECEC: an uneven start for ECEs, e-interactions, and curricula and pedagogies in online spaces – a kaleidoscope of play and learning in COVID-19 times. Implications for pre-service and in-service ECEs’ support, monitoring, and training are discussed to facilitate effective play and learning in online environments.

Advancements on Optimization Algorithms Applied to Wave Energy Assessment: An Overview on Wave Climate and Energy Resource

The wave energy sector has not reached a sufficient level of maturity for commercial competitiveness, thus requiring further efforts towards optimizing existing technologies and making wave energy a viable alternative to bolster energy mixes. Usually, these efforts are supported by physical and numerical modelling of complex physical phenomena, which require extensive resources and time to obtain reliable, yet limited results. To complement these approaches, artificial-intelligence-based techniques (AI) are gaining increasing interest, given their computational speed and capability of searching large solution spaces and/or identifying key study patterns. Under this scope, this paper presents a comprehensive review on the use of computational systems and AI-based techniques to wave climate and energy resource studies. The paper reviews different optimization methods, analyses their application to extreme events and examines their use in wave propagation and forecasting, which are pivotal towards ensuring survivability and assessing the local wave operational conditions, respectively. The use of AI has shown promising results in improving the efficiency, accuracy and reliability of wave predictions and can enable a more thorough and automated sweep of alternative design solutions, within a more reasonable timeframe and at a lower computational cost. However, the particularities of each case study still limit generalizations, although some application patterns have been identified—such as the frequent use of neural networks.

Immigration from Africa to the United States: key insights from recent research.

Immigration from Africa to the United States has increased dramatically in the past three decades. This paper summarizes recent findings on the growth of African immigration to the United States in recent years. In doing so, it highlights shifting sociodemographic profiles of these "new African Americans" or "new Americans," profiling the increasing diversity, yet also racialized portrait of this group. Key patterns of immigration shown include the changing racial and gender composition of immigrants, as well as rising immigration from a wider range of African countries. Some key theoretical and practical implications are outlined.

Reliable Actors with Retry Orchestration

Cloud developers have to build applications that are resilient to failures and interruptions. We advocate for a fault-tolerant programming model for the cloud based on actors, retry orchestration, and tail calls. This model builds upon persistent data stores and message queues readily available on the cloud. Retry orchestration not only guarantees that (1) failed actor invocations will be retried but also that (2) completed invocations are never repeated and (3) it preserves a strict happen-before relationship across failures within call stacks. Tail calls can break complex tasks into simple steps to minimize re-execution during recovery. We review key application patterns and failure scenarios. We formalize a process calculus to precisely capture the mechanisms of fault tolerance in this model. We briefly describe our implementation. Using an application inspired by a typical enterprise scenario, we validate the functional correctness of our implementation and assess the impact of fault preparedness and recovery on performance.

DIY (Do-It-Yourself) English Language Learning and Practice at Universitas Negeri Makassar

This phenomenological study explores the experiences, motivations, and challenges of students at Universitas Negeri Makassar engaging in DIY (Do-It-Yourself) English language learning and practice. The research aims to gain insights into self-directed language learning and provide valuable information for educational practices and policies in the university context. A purposeful sample of 15-20 students, representing a diverse range of experiences, was selected to participate in the study. Data collection involved a combination of semi-structured interviews, focus group discussions, and reflective journals, allowing for a comprehensive understanding of the students' perspectives. Inductive thematic analysis was employed to identify key themes and patterns in the data, with the findings presented as a rich, descriptive narrative. Strategies for establishing trustworthiness included triangulation of data sources, member checking, and peer debriefing. This study contributes to our understanding of DIY language learning by highlighting the DIY English language learning strategies, benefits and challenges, and students’ ways of assessing DIY English language learning at Universitas Negeri Makassar, ultimately informing future educational practices and policies.

Informal carer support needs, facilitators and barriers in transitional care for older adults from hospital to home: A scoping review.

To synthesise evidence about informal carers' (carers) experience of their support needs, facilitators and barriers regarding transitional care of older adults with multimorbidity. Carers provide crucial support for older adults during care transitions. Although health practitioners are well positioned to support carers, system factors including limited healthcare resources can compromise the quality of care transitions. Scoping review. Searches were undertaken of the published literature. Five databases were searched including MEDLINE, CINAHL, EMBASE, PsycINFO and the Cochrane Library. Two reviewers independently screened articles to identify relevant studies. Studies were retrieved from January 2000 to July 2022. Data were extracted and tabulated for study characteristics, support needs, facilitators and barriers. Key themes and patterns were synthesised across the studies. Eighteen studies including N = 3174 participants were retrieved. Most studies (n = 13) employed qualitative designs. Five studies used surveys. Carers reported their need to: be involved in coordinated discharge planning; advocate and be involved in decision-making; and receive community-based follow-up. Carers described facilitators and barriers in four themes: (1) relationships with the older adult and health practitioners, (2) being involved in coordinated discharge planning; (3) communication and information strategies; and (4) community-based follow-up. Synthesis of themes across all studies resulted in the identification of five areas of research: carers' health literacy; community-based care; carers' involvement in transitional care planning; inpatient and community health practitioners' communication skills; and culturally diverse carers' experiences. The review highlights the importance of quality communication and relationships between carers, older adults, health practitioners and health organisations. Although information and education are important there is a need for further research to examine systems that support communication between carers, older adults and health practitioners and health literacy for all carers including culturally diverse carers.

Deep Learning Driven Instinctive Surveillance

It is a very boring and laborious job providing observation security. In order to determine whether the exercises that were caught were unusual or suspicious, a labour force is needed. Here, we’ll put together a structure to automate the task of reviewing video reconnaissance. We will regularly review the camera feed to look for any unusual activities like surprising or suspicious ones. and an automatic acknowledgment will be sent to the user with an alert email along with the suspicious frames and SMS to mobile number. Deep learning computations for deep reconnaissance have improved from earlier encounters. These developments have revealed a key pattern in thorough reconnaissance and promise a significant increase in efficacy. Deep observation is typically used for things like identifying evidence of burglary, finding violence, and recognising explosion potential. We will propose a spatio-temporal auto-encoder for this project that relies on a 3D convolutional brain structure. The decoder then reproduces the edges after the encoder section has removed the spatial and transient data. By recording the recreation misfortune using the Euclidean distance between the original and replicated batch, the odd occurrences are distinguished.

Scientometric Analysis on Cash Waqf Linked Sukuk (CWLS)

This study aims to conduct a scientometric analysis of the literature related to Cash Waqf Linked Sukuk (CWLS) in the context of waqf. The scientometric method is used to measure and analyze the development patterns, research contributions, and interactions between researchers in the CWLS domain. Data was collected through the scientific literature platform Dimensions.ai with relevant keywords. Data visualization was also used to understand the relationship between authors, publications, and key concepts in CWLS literature. The results of this analysis provide insights into the development of research, key contributions of researchers, as well as the evolution of concepts in CWLS. This study provides a more comprehensive view through research paths with specific theme clusters of the CWLS-related literature and helps identify key patterns and important contributions in understanding the implications of Islamic economics and finance in the context of waqf.

The RESECT study: Factors associated with overall survival (OS) and relapse-free survival (RFS) among patients with stages I–III resected NSCLC without known EGFR mutations.

8541 Background: Approximately one-third of patients with Stages I–III resected non-small-cell lung cancer (NSCLC) do not survive 5 years from diagnosis. This retrospective observational study analyzed factors associated with OS and real-world (rw) RFS among Stage I–III NSCLC patients before the introduction of immuno-oncology (IO) treatment. Methods: We analyzed data from the US CancerLinQ database for adult patients with no known EGFR mutations and no other cancers, who were diagnosed with Stage I–III NSCLC from 2014–2019 and had surgical resection within 140 days after initial diagnosis. 3081 patients met the study criteria of whom 1677 were Stage I, 853 were Stage II, and 551 were Stage III; 4 Stage I patients who received neoadjuvant or perioperative treatment were excluded (too few for analysis). Most patients received surgery only (71.5%); the rest also received adjuvant (24.7%), neoadjuvant (2.4%) or perioperative (1.5%) treatment, most often chemotherapy ± radiotherapy. Key demographics, clinical characteristics, treatment patterns, and relevant 2-way interactions were considered for inclusion in the model, based on Cox regression analyses and medical insights. Multivariable Cox regression analysis (backwards selection, p<0.05) was used to model OS and rwRFS. Results: In the multivariable analyses (in which no Stage I patients with neoadjuvant or perioperative treatment were included), factors associated with both OS and rwRFS (p<0.05) were disease stage, race, ethnicity, year of diagnosis, ECOG performance status, and neoadjuvant treatment. Factors associated with OS (p<0.05), but not rwRFS, were age, sex, time from diagnosis to surgery, and type of surgery. Factors associated with rwRFS (p<0.05), but not OS, were geographic region, nodal status, and adjuvant treatment in Stage II and III patients but not Stage I patients. Conclusions: This study identified several risk factors associated with OS and rwRFS, many of which are known. Notably, in this analysis, neoadjuvant treatment was associated with both improved OS and rwRFS in Stage II–III patients and was not evaluable in Stage I patients. However, adjuvant treatment was only associated with improved rwRFS, and only in Stage II–III patients. Based on these findings, there remains an unmet need for Stage I–III NSCLC patients. The recent introduction of IO treatment in this setting may help improve patient outcomes.

Macrophage scavenger receptor A1 antagonizes abdominal aortic aneurysm via upregulating IRG1

AimsAbdominal aortic aneurysm (AAA) is a common, usually asymptomatic disease with high mortality and limited therapeutic options. Extensive extracellular matrix (ECM) fragmentation and transmural inflammation act as major pathological processes of AAA. However, the underlying regulatory mechanisms remain incompletely understood. Herein, we aimed to investigate the role of scavenger receptor A1 (SR-A1), a key pattern recognition receptor modulating macrophage activity, in pathogenesis of AAA. Methods and resultsThe AAA model was generated by administration of angiotensin II (Ang II) into apolipoprotein E knockout mice or peri-arterial application of calcium phosphate in C57BJ/6L mice. We found that SR-A1 was markedly down-regulated in the macrophages isolated from murine AAA aortas. Global or myeloid-specific ablation of SR-A1 aggravated vascular inflammation, loss of vascular smooth muscle cells and degradation of the extracellular matrix. These effects of SR-A1 deficiency on AAA development were mediated by suppressed immunoresponsive gene 1 (IRG1) and increased inflammatory response in macrophages. Mechanically, binding of SR-A1 with Lyn led to STAT3 phosphorylation and translocation into the nucleus, in which STAT3 promoted IRG1 transcription through directly binding to its promoter. Restoration of macrophage SR-A1 in SR-A1-deficient mice by bone marrow transplantation or administration of 4-octyl itaconate, the derivate of IRG1 product itaconate, could relieve murine AAA. ConclusionOur study reveals a protective effect of macrophage SR-A1–STAT3–IRG1 axis against aortic aneurysm formation via inhibiting inflammation.

Reimagining Hair Science: A New Approach to Classify Curly Hair Phenotypes via New Quantitative Geometric and Structural Mechanical Parameters.

Hair is a natural polymeric composite primarily composed of tight macrobundles of keratin proteins, which are highly responsive to external stimuli, similarly to the hydrogels and other natural fibrous gel systems like collagen and fibrin.Hair and its appearance play a significant role in human society. As a highly complex biocomposite system, it has been traditionally challenging to characterize and thus develop personal care products. Over the last few decades, a significant societal paradigm shift occurred among those with curly hair, accepting the natural morphological shape of their curls and styling their hair according to its innate, distinct, and unique material properties, which has given rise to the development of new hair classification systems, beyond the traditional and highly limited race-based distinction (Caucasian, Mongolian, and African). L'Oréal developed a hair typing taxonomy based on quantitative geometric parameters among the four key patterns─straight, wavy, curly, and kinky, but it fails to capture the complex diversity of curly and kinky hair. Acclaimed celebrity hair stylist Andre Walker developed a classification system that is the existing gold standard for classifying curly and kinky hair, but it relies upon qualitative classification measures, making the system vague and ambiguous of phenotypic differences. The goal of this research is to use quantitative methods to identify new geometric parameters more representative of curly and kinky hair curl patterns, therefore providing more information on the kinds of personal care products that will resonate best with them and thus maximize desired appearance and health, and to correlate these new parameters with its mechanical properties. This was accomplished by identifying new geometric and mechanical parameters from several types of human hair samples.Geometric properties were measured using scanning electron microscopy (SEM), photogrammetry, and optical microscopy. Mechanical properties were measured under tensile extension using a texture analyzer (TA) and a dynamic mechanical analyzer (DMA), which bears similarity to the common act of brushing or combing. Both instruments measure force as a function of applied displacement, thus allowing the relationship between stress and applied stretch ratio to be measured as a hair strand uncurls and stretches to the point of fracture. From the resulting data, correlations were made between fiber geometry and mechanical performance. This data will be used to draw more conclusions on the contribution that fiber morphology has on hair fiber mechanics and will promote cultural inclusion among researchers and consumers possessing curly and kinky hair.

Key Patterns of LGBTQ Experiences in STEM: From Institutional Barriers to Transnationality

For decades, scholars have researched social inequalities of race, gender and other minority groups experiences in science, technology, engineering, and mathematics (STEM). Nonetheless, whether lesbian, gay, bisexual, transgender and queer (LGBTQ) professionals experience parallel disadvantaged circumstances remains to be further surveyed substantively. This paper draws on relevant literature concerning the normative STEM environment and different views (constructivism, liberalism, etc.), seeking to unpack the intersectionality between LGBTQ and STEM. Through conducting surveys targeted at international LGBTQ students regarding their academic, social, and mental experiences in STEM specifically, this paper argues that there exists a shared common dilemma for this group: sexual objectification and extra stress to increase their STEM competence. This paper comparatively analyzes the results and reveals the institutional and transnational barriers for those LGBTQ students of different cultural backgrounds in the context of globalization and international interactions and cooperation. This paper also contends that LGBTQ professionals in STEM become victims of sexual objectification mainly due to hypermasculinity and male-female dichotomy.

Preservation of stable isotope signatures of amino acids in diagenetically altered Middle to Late Holocene archaeological mollusc shells

Stable isotope proxies measured in the proteinaceous fraction of archaeological mollusc shell represents an increasingly important archive for reconstructing past ecological and biogeochemical conditions of nearshore environments. A major issue, however, is understanding the impact of diagenetic alteration in sub-fossil shell isotope values. “Bulk” stable isotope values of nitrogen (δ15N), and especially carbon (δ13C) often shift strongly with increasing C/N ratios in degraded shell, resulting in unreliable data. Here, we examine preservation of an entirely new set of shell paleo-proxies, compound-specific isotopes of amino acids (CSI-AA). We examine carbon (δ13CAA) and nitrogen (δ15NAA) patterns and values from the organic fraction of California mussel (Mytilus californianus) shells from the California Channel Islands. Archaeological shell samples ranging in age from ca. 6,100 to 250 cal BP exhibiting a wide range of degradation states were collected from varied depositional environments (e.g., exposed coastal bluff, buried strata, etc.), and were directly compared to modern shells of the same species and region.Our results indicate organic matter C/N ratios as the best bulk diagnostic indicator of the relative degradation state of shell organic fraction, including changes at the molecular level. Modern shell organic C/N ratios ranged from 2.8 to 3.5, while those in archaeological shell were substantially elevated (3.4–9.5), exhibiting strong and significant negative correlations with bulk δ13C values, weight %C, and weight %N, and a significant but weaker correlation with δ15 N values. An additional “cleaning” step using weak NaOH helped to remove possible exogenous contaminants and improved bulk values of some samples. However, relative molar AA abundances revealed that some AAs, especially the two most abundant, Glycine and Alanine, progressively decreased with increasing C/N ratio. The loss of these amino acids permanently alters bulk isotope values regardless of removal of contaminants. Modeling the bulk isotope change expected due to amino acid molar composition showed major and predictable shifts in bulk δ13C values from selected AA loss, and similarly large but far more variable impacts from exogenous contaminants.In contrast to bulk data, key CSI-AA values and patterns remained almost entirely unaltered, even in the most degraded shell samples, closely matching expected biosynthetic isotope patterns in modern mussel shell. AA isotope proxies for “baseline” (δ15N-Phenylalanine and average δ13C-Essential AAs) and planktonic trophic structure (δ15N-Glutamic Acid and δ15N-Phenylalanine) were not statistically altered with degradation in any sample. Overall, we conclude that while bulk isotopes, particularly δ13C, are very likely to be unreliable in archaeological or subfossil shell with C/N ratios higher than ∼4.0, CSI-AA proxies can still be used to reconstruct past climatic and ecological conditions of the nearshore marine environment.

Political Transformation of Social Conflicts in the Context of Global Political Risks and Threats (Theoretical View)

Relevance. The phenomena and processes observed in the social system in the modern objectively conditioned conditions of dynamization and politicization have a stable tendency to the formation and accumulation of transformational potential. In this sense, social conflicts at the present stage are often transformed into political conflicts within the framework of an unprecedentedly developing and increasingly complex socio-political space. Of particular research interest is the identification of key features and patterns of political transformation of social conflicts in the focus of global political risks and threats. It also seems appropriate to formulate specific practical measures of approximating specifics in the direction of managing the political and transformational potential of modern social conflicts.Purpose. The main purpose of this article is to present a theoretical overview of the transformation of social conflicts in the context of global political risks and threats.Objectives: formulation of global political risks and threats at the ideological-conceptual, activity-functional, structural and institutional, resource and interactive levels, identification of key features and patterns of political transformation of social conflicts.Methodology. The author mainly used the following group of methods in the process of writing the article: information analysis, content analysis, event analysis, sociological analysis.Results. Taking into account the stated research issues, it seems appropriate to formulate specific practical measures of approximating specifics in the direction of managing the political and transformational potential of modern social conflicts.Conclusion. Within the framework of the modern global socio-political reality, generating and reproducing a huge number of social and other conflicts, it is necessary to pay more attention to the phenomenology of social conflict as such, implying, firstly, a positive and naturalistic perception of the conflictogenic nature of political phenomena and processes, and secondly, the implementation of targeted monitoring of political and conflict dynamics, thirdly, the organization of discussions on open and verified platforms, and fourthly, improving the effectiveness of existing regulatory and legal regulations and formal procedures.

A Dynamic Perspective on Collaborative Innovation for Smart City Development: The role of uncertainty, governance, and institutional logics

Collaborative innovation is at the heart of smart city development, yet also notoriously challenging due to fundamental differences between public and private sector actors that need to collaborate, while dealing with high levels of uncertainty. Whereas existing practice-based work on collaborative innovation describes various relevant antecedents, barriers and success factors, this prior work potentially underestimates the true complexity of collaborative innovation initiatives. Therefore, scholars have increasingly called for a more dynamic, theoretical understanding of collaborative innovation. In response to these calls, our study draws on institutional theory to build a dynamic understanding of collaborative innovation for smart city development. Specifically, we conduct a longitudinal in-depth case study to develop a causal loop model, grounded in rich qualitative data, to capture and theorize the key behavioural patterns of a collaborative innovation initiative for smart city development. The model describes how the dynamic interplay between uncertainty, adherence to own institutional logics and governance complexity can both enable and undermine collaborative initiatives. We contribute by developing a dynamic theoretical perspective on collaborative innovation, one that promotes cross-fertilization at the intersection of the smart city theory, organization theory and collaborative innovation literature. Moreover, our findings highlight the important role of organization theory, specifically institutional logics, in explaining the collaborative dynamics of smart city development.