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Associating street crime incidences with geographical environment in space using a zero-inflated negative binomial regression model

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CITIES 2022年 129卷

作者： Luo, Liang Deng, Min Shi, Yan Gao, Shijuan Liu, Baoju Cent South Univ Dept Geoinformat Changsha Hunan Peoples R China Cent South Univ Big Data Inst Changsha Hunan Peoples R China

Urban geographical environments play an important role in inducing the occurrences of street crimes, so they have raised attention regarding the relationships between geographical environments and street crimes. Limited by the high data acquisition costs of traditional environmental auditing methods, current related studies still lack specific investigations on how street crime risks are quantitatively associated with diverse geographical environment variables, especially the multiple inherent streetscapes elements. Moreover, it is also necessary to discover the effects of pairwise variable interactions on street crimes by considering the existing zero inflation phenomenon. Therefore, this study introduces street view images to automatically characterize built urban environments with the help of deep learning models. By combining built environment variables with socioeconomic variables, we construct a zero-inflated negative binomial regression model to quantify both single factor effects and the interaction effects among pairwise variables on street crime instances in space. By performing experiments on a real-life dataset, we find that the discovered interaction effects and seasonal variations in regression relationships yield the most comprehensive and reasonable explanations for the spatial distributions of street crime instances. These findings can guide the optimization of urban environmental element layouts and patrol policies to enhance the level of public security.

关键词： Street crimes Built urban environments zero-inflated negative binomial regression Interaction effects

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Understanding online review helpfulness: a pleasure-arousal-dominance (PAD) model perspective

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ASLIB JOURNAL OF INFORMATION MANAGEMENT 2025年第2期77卷 391-412页

作者： Xu, Wuhuan Yao, Zhong He, Dandan Cao, Ling BeiHang Univ Sch Econ & Management Beijing Peoples R China

PurposeDrawing on the pleasure-arousal-dominance (PAD) emotion model, the emotional states of consumers embedded in online reviews can be described through three dimensions, that is, pleasure, arousal and dominance, rather than only the one-dimensional positive and negative polarity, as in previous studies. Therefore, this study aims to explore the effect of online review emotion on perceived review helpfulness based on these three basic emotional ***/methodology/approachA lexicon-based method is developed to analyze PAD emotions of online reviews from ***. The zero-inflated negative binomial regression is utilized to empirically validate the study hypothesis. The authors examine the influence of pleasure, arousal, dominance, emotion diversity and emotion deviation on review helpfulness, as well as the moderating effect of product type on the relationship between all independent variables and online review *** study results show that the pleasure emotion impairs the helpfulness of online reviews, while the arousal and dominance emotions have a positive impact. Moreover, the authors find that compared with search products, the effects of pleasure, arousal and dominance on perceived helpfulness are strengthened for experience products. However, the emotional diversity and emotional deviation have opposite effects on the helpfulness of search products and experience products. Additionally, the results show that dominance emotion plays a more important role in the interaction ***/valueThe empirical findings confirm the applicability of PAD in the online review context and extend the existing knowledge of the influence of review emotion on helpfulness. A feasible scheme for extracting PAD variables from Chinese text is developed. The study findings also have significant implications for reviewers, merchants and platform managers of e-commerce websites.

关键词： Review emotion PAD model Review helpfulness Product type zero-inflated negative binomial regression Text mining Emotion lexicon

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Investigating streetscape environmental characteristics associated with road traffic crashes using street view imagery and computer vision

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ACCIDENT ANALYSIS AND PREVENTION 2025年 210卷 107851页

作者： Yue, Han Guangzhou Univ Ctr Geoinformat Publ Secur Sch Geog & Remote Sensing Guangzhou 510006 Peoples R China

Examining the relationship between streetscape features and road traffic crashes is vital for enhancing roadway safety. Traditional field surveys are often inefficient and lack comprehensive spatial coverage. Leveraging street view images (SVIs) and deep learning techniques provides a cost-effective alternative for extracting streetscape features. However, prior studies often rely solely on semantic segmentation, overlooking distinctions in feature shapes and contours. This study addresses these limitations by combining semantic segmentation and object detection networks to comprehensively measure streetscape features from Baidu SVIs. Semantic segmentation identifies pixel-level proportions of features such as roads, sidewalks, buildings, fences, trees, and grass, while object detection captures discrete elements like vehicles, pedestrians, and traffic lights. zero-inflated negative binomial regression models are employed to analyze the impact of these features on three crash types: vehiclevehicle (VCV), vehicle-pedestrian (VCP), and single-vehicle crashes (SVC). Results show that incorporating streetscape features from combined deep learning methods significantly improves crash prediction. Vehicles have a significant impact on VCV and SVC crashes, whereas pedestrians predominantly affect VCP crashes. Road surfaces, sidewalks, and plants are associated with increased crash risks, while buildings and trees correlate with reduced vehicle crash frequencies. This study highlights the advantages of integrating semantic segmentation and object detection for streetscape analysis and underscores the critical role of environmental characteristics in road traffic crashes. The findings provide actionable insights for urban planning and traffic safety strategies.

关键词： Road traffic crashes Streetscape environment Street view images Semantic segmentation Object detection zero-inflated negative binomial regression

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Impact of environmental factors on COVID-19 transmission: spatial variations in the world

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INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023年第9期33卷 864-880页

作者： Faruk, Mohammad Omar Rana, Md Shohel Jannat, Sumiya Nur Lisa, Fariha Khanam Rahman, Md Sahidur Noakhali Sci & Technol Univ Dept Stat Noakhali 3814 Chittagong Bangladesh Noakhali Sci & Technol Univ Dept Oceanog Noakhali Bangladesh One Hlth Ctr Res & Act Dept Res & Innovat Chattogram Bangladesh

The COVID-19 pandemic caused enormous destruction to global health and the economy and has surged worldwide with colossal morbidity and mortality. The pattern of the COVID infection varies in diverse regions of the world based on the variations in the geographic environment. The multivariate generalized linear regression models: zero-inflated negative binomial regression, and the zero-inflated Poisson regression model, have been employed to determine the significant meteorological factors responsible for the spread of the pandemic in different continents. Asia experienced a high COVID-19 infection, and death was extreme in Europe. Relative humidity, air pressure, and wind speed are the salient factors significantly impacting the spread of COVID-19 in Africa. Death due to COVID-19 in Asia is influenced by air pressure, temperature, precipitation, and relative humidity. Air pressure and temperature substantially affect the spread of the pandemic in Europe. There is a substantial variation of the impacts of environmental variables on the spread of the COVID-19 pandemic in different parts of the world. Temperature and air pressure significantly impact the number of infections and death due to COVID-19 in Europe. Relative humidity, temperature, sky clearness, and wind speed posed significant positive effects on COVID-19 in Africa The spread of COVID-19 infection and death is maximum in low temperatures. The confounding effect of the maximum number of meteorological factors minimizes the transmission of the pandemic.

关键词： Spatial comparison environmental factors COVID-19 transmission death zero-inflated negative binomial regression

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Dynamic road crime risk prediction with urban open data

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Frontiers of Computer Science 2022年第1期16卷 113-125页

作者： Binbin ZHOU Longbiao CHEN Fangxun ZHOU Shijian LI Sha ZHAO Gang PAN College of Computer Science Zhejiang UniversityHangzhou310027China Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Information Science and EngineeringXiamen UniversityXiamen361005China

Crime risk prediction is helpful for urban safety and citizens’life ***,existing crime studies focused on coarse-grained prediction,and usually failed to capture the dynamics of urban *** key challenge is data sparsity,since that 1)not all crimes have been recorded,and 2)crimes usually occur with low *** this paper,we propose an effective framework to predict fine-grained and dynamic crime risks in each road using heterogeneous urban ***,to address the issue of unreported crimes,we propose a cross-aggregation soft-impute(CASI)method to deal with possible unreported ***,we use a novel crime risk measurement to capture the crime dynamics from the perspective of influence propagation,taking into consideration of both time-varying and location-varying risk *** on the dynamically calculated crime risks,we design contextual features(i.e.,POI distributions,taxi mobility,demographic features)from various urban data sources,and propose a zero-inflated negative binomial regression(ZINBR)model to predict future crime risks in *** experiments using the real-world data from New York City show that our framework can accurately predict road crime risks,and outperform other baseline methods.

关键词： crime prediction road crime risk urban computing data sparsity zero-inflated negative binomial regression

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Fragmented landscapes affect honey bee colony strength at diverse spatial scales in agroecological landscapes in Kenya

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ECOLOGICAL APPLICATIONS 2022年第1期32卷 1-13页

作者： Ochungo, Pamela Veldtman, Ruan Abdel-Rahman, Elfatih M. Mule, Elliud Ng'ang'a, James Tonnang, Henry E. Z. Landmann, Tobias Int Ctr Insect Physiol & Ecol Icipe POB 30772-00100 Nairobi Kenya Stellenbosch Univ Dept Conservat Ecol & Entomol Private Bag X1 ZA-7602 Matieland South Africa Kirstenbosch Res Ctr South African Natl Biodivers Inst Private Bag X7 ZA-7735 Claremont South Africa South Eastern Kenya Univ Dept Life Sci Kitui Kenya Remote Sensing Solut RSS GmBH Isarstr 3 D-82065 Baierbrunn Germany

Landscape fragmentation and habitat loss at multiple scales directly affect species abundance, diversity, and productivity. There is a paucity of information about the effect of the landscape structure and diversity on honey bee colony strength in Africa. Here, we present new insights into the relationship between landscape metrics such as patch size, shape, connectivity, composition, and configuration and honey bee (Apis mellifera) colony strength characteristics. Remote-sensing-based landscape variables were linked to honey bee colony strength variables in a typical highly fragmented smallholder agroecological region in Kenya. We examined colonies in six sites with varying degrees of land degradation during the period from 2017 to 2018. Landscape structure was first mapped using medium resolution bitemporal Sentinel-1 and Sentinel-2 satellite imagery with an optimized random forest model. The influence of the surrounding landscape matrix was then constrained to two buffer distances, i.e., 1 km representing the local foraging scale and 2.5 km representing the wider foraging scale around each investigated apiary and for each of the six sites. The results of zero-inflated negative binomial regression with mixed effects showed that lower complexity of patch geometries represented by fractal dimension and reduced proportions of croplands were most influential at local foraging scales (1 km) from the apiary. In addition, higher proportions of woody vegetation and hedges resulted in higher colony strength at longer distances from the apiary (2.5 km). Honey bees in moderately degraded landscapes demonstrated the most consistently strong colonies throughout the study period. Efforts towards improving beekeeper livelihoods, through higher hive productivity, should target moderately degraded and heterogeneous landscapes, which provide forage from diverse land covers.

关键词： honey bees Kenya landscape fragmentation Sentinel-1 Sentinel-2 zero-inflated negative binomial regression

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Social Indicators Research: A Retrospective Using Bibliometric Analysis

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SOCIAL INDICATORS RESEARCH 2022年第1期162卷 413-448页

作者： Kumar, Satish Maggino, Filomena Mahto, Raj, V Sureka, Riya Alaimo, Leonardo Salvatore Lim, Weng Marc Malaviya Natl Inst Technol Jaipur Dept Management Studies Jaipur 302017 Rajasthan India Swinburne Univ Technol Sch Business Kuching 93350 Malaysia Sapienza Univ Rome Dept Stat Rome Italy Univ New Mexico Anderson Sch Management Albuquerque NM 87131 USA Sapienza Univ Rome Dept Social Sci & Econ Rome Italy Italian Natl Inst Stat Istat Rome Italy Swinburne Univ Technol Swinburne Business Sch Hawthorn Vic 3122 Australia

Social Indicators Research (SIR) publishes novel and groundbreaking research focusing on social indicators related to quality of life and sustainability. Using bibliometrics, this study aims to offer a retrospective of the major trends (e.g., publication, citation, and top contributing authors, institutions, and countries) and intellectual structure of SIR. The retrospective indicates that SIR, which has grown substantially in productivity and impact, attracts contributions worldwide, notably from the USA, with 11 major themes revealed between 1974 and 2019. Using a zero-inflated negative binomial regression, this study also reveals the factors that influence the citation count of SIR publications, namely article age, number of author keywords, title novelty, title length, USA affiliation, and number of authors. Noteworthily, this study, which represents the inaugural review of SIR, should be useful for readers to gain rich insights into the state of research on social indicators related to quality of life and sustainability.

关键词： Bibliometric analysis Quality of life Social indicators Sustainability zero-inflated negative binomial regression

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Profit uplift modeling for direct marketing campaigns: approaches and applications for online shops

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Journal of Business Economics 2022年第4期92卷 645-673页

作者： Baier, Daniel Stöcker, Björn Chair of Marketing and Innovation University of Bayreuth Universitätsstraße 30 Bayreuth 95447 Germany Head of CRM BAUR Versand Bahnhofstraße 10 Burgkunstadt 96224 Germany

In order to select “best” customers for a direct marketing campaign, response models are widespread: a sample of customers receives an ad, a catalog, a sample pack, or a discount offer on a test basis. Then, their responses (e.g., website visits, conversions, or revenues) are used to build a predictive model. Finally, this model is applied to all customers in order to select “best” ones for the campaign. However, up to now, only models that reflect website visits, conversions, or revenues have been proposed. In this paper, we discuss the shortcomings of these traditional approaches and propose profit uplift modeling appoaches based on one-stage ordinary regression and random forests as well as two-stage Heckman sample selection and zero-inflated negative binomial regression for parameter estimation. The new approaches demonstrate superiority to the traditional ones when applied to real-world datasets. One dataset reflects recent discount offers of a large online fashion retailer. The other is the well-known Hillstrom dataset that describes two Email campaigns. © 2021, The Author(s).

关键词： Heckman sample selection model Online shops Random forests Uplift modeling zero-inflated negative binomial regression

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Linking TNC with passengers: Investigating TNC use among lower-income residents with limited access to cars

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TRAVEL BEHAVIOUR AND SOCIETY 2022年 27卷 184-191页

作者： Dong, Xiaoxia Univ Penn Dept City & Reg Planning 127 Meyerson Hall210 S 34th St Philadelphia PA 19104 USA

Due to the lack of data, there have been limited studies that link TNC (e.g., Uber and Lyft) usage and trips with demographic and socio-economic characteristics of individual customers, especially customers who might be financially vulnerable and lack car access. Using Chicago region's 2018-19 household travel survey, this paper bridges the gap between TNC usage, trip characteristics, and individual's demographic and socio-economic characteristics. The first analysis examines the trip purposes, travel time, and origins and destinations of TNC trips recorded in the travel survey to explore how and why residents use TNC services. The second analysis uses zero-inflated negative binomial regression to explore the associations between TNC adoption, usage, and a series of demographic and socio-economic variables. Both analyses pay particular attention to financially disadvantaged residents who lack access to private cars. The analyses reveal that TNC use decreases with vehicle ownership. Compared to higher-income carless residents, lower-income carless residents use TNC services more for essential trips, especially during hours with infrequent transit services. For essential TNC trips, lower-income residents likely pay a bigger share of their income than higher-income residents do. The findings have implications on transit planning and transportation benefit programs that aim to integrate TNC services to enhance access for lower-income residents.

关键词： Chicago Household travel survey Low-income TNC Transit zero-inflated negative binomial regression

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Generalized linear model based monitoring methods for high-yield processes

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QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 2020年第5期36卷 1570-1591页

作者： Mahmood, Tahir City Univ Hong Kong Dept Syst Engn & Engn Management Kowloon Tat Chee Ave Hong Kong Peoples R China

Emerge in technology brought well-organized manufacturing systems to produce high-quality items. Therefore, monitoring and control of products have become a challenging task for quality inspectors. From these highly efficient processes, produced items are mostly zero-defect and modeled based on zero-inflated distributions. The zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) distributions are the most common distributions, used to model the high-yield and rare health-related processes. Therefore, data-based control charts under ZIP and ZINB distributions (i.e., Y-ZIP and Y-ZINB) are proposed for the monitoring of high-quality processes. Usually, with the defect counts, few covariates are also measured in the process, and the generalized linear model based on the ZIP and ZINB distributions are used to estimate their parameters. In this study, we have designed monitoring structures (i.e., PR-ZIP and PR-ZINB) based on the ZIP and ZINB regression models which will provide the monitoring of defect counts by accounting the single covariate. Further, proposed model-based charts are compared with the existing data-based charts. The simulation study is designed to access the performance of monitoring methods in terms of run length properties and a case study on the number of flight delays between Atlanta and Orlando during 2012-2014 is also provided to highlight the importance of the stated research.

关键词： Pearson residuals statistical process control zero-defect zero-inflated negative binomial regression zero-inflated poisson regression

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