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Journal articles on the topic 'DRIVING FACTOR'

Author: Grafiati

Published: 11 September 2023

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1

Trinh,, Pham T. T., and Le P. A. Nhan,. "The Global Factors Driving Common Inflation In ASEAN." GLOBAL BUSINESS FINANCE REVIEW 28, no. 4 (2023): 90–103. http://dx.doi.org/10.17549/gbfr.2023.28.4.90.

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Purpose: This study investigates the comovements of inflation across ASEAN countries and identifies the global factors driving the common inflation dynamics of the region. Design/methodology/approach: The study uses a two-step approach. The dynamic latent factor model is first employed to estimate the common inflation of the region in the period between 2000Q1 and 2022Q2. In the second step, a bound test approach to autoregressive distributed lag (ARDL) methodology is employed to estimate the model of common inflation, which is constructed based on the aggregate supply - aggregate demand (AS-A

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Zhang, Hong Wu, Lin Yun Shi, Zi Rui Lan, and Jia Hui Yin. "Regional Difference and its Influencing Factors of China's CO₂ Emission Changes." Advanced Materials Research 524-527 (May 2012): 3655–61. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.3655.

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Abstract. Regional difference of China's CO2 emission is basically in line with the trend of China's economic development that the emission is higher in the eastern coastal areas and lower in the western inland areas. The characteristic of the changes of the total CO2 emission is that the growth rate significantly accelerated after 2000. The basic factor which acts as a drive of CO2 emission increase is economic scale factor and the energy saving factor contributes to the decrease of CO2 emission. The driving power of the population factor and energy conversion factor is weak especially the in

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Wu, Chaozhong, Wenhui Chu, Hui Zhang, and Türker Özkan. "Interactions between Driving Skills on Aggressive Driving: Study among Chinese Drivers." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 31 (2018): 10–20. http://dx.doi.org/10.1177/0361198118755683.

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Aggressive driving has attracted significant attention recently with the increase in related road traffic collisions occurring in China. This study aims to investigate the effect of driving skills on aggressive driving behaviors and traffic accidents to find implications for traffic safety improvement in China. A total of 735 Chinese drivers were recruited to complete a self-reported survey including demographic information, the translated Driver Skill Inventory (DSI), and Driver Aggression Indicator Scale (DAIS). Exploratory factor analysis was first conducted to investigate the factor struct

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Patterson, Loretta, Nadia Mullen, Arne Stinchcombe, Bruce Weaver, and Michel Bédard. "Measuring the impact of driving status: The Centre for Research on Safe Driving–Impact of Driving Status on Quality of Life (CRSD-IDSQoL) tool." Canadian Journal of Occupational Therapy 86, no. 1 (2019): 30–39. http://dx.doi.org/10.1177/0008417418824980.

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Background. Driving an automobile is often considered an activity of daily living and is crucial to quality of life for many individuals. Following driving cessation, quality of life may become compromised. Purpose. The Centre for Research on Safe Driving–Impact of Driving Status on Quality of Life (CRSD-IDSQoL) was designed to measure various elements of quality of life and how those elements are affected by driving status. Method. The CRSD-IDSQoL was cross-sectionally administered to a convenience sample of 114 individuals (mean age 65.8 years). Exploratory factor analysis was used to examin

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mahmodzadeh, mahmod, and mehdi fathabadi. "Driving Factors of Total Factor Productivity in Iranian Manufacturing Industries." Journal of Research in Economic Modeling 7, no. 26 (2017): 141–65. http://dx.doi.org/10.18869/acadpub.jemr.7.26.141.

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Schweizer, Karl, and Siegbert Reiß. "On the Contextual Conditions Driving a Difficulty Factor." International Journal of Statistics and Probability 8, no. 5 (2019): 1. http://dx.doi.org/10.5539/ijsp.v8n5p1.

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This paper reports three simulation studies conducted to identify the contextual conditions leading to the observation of a difficulty factor in confirmatory factor analysis. The data of each study were generated to show one underlying source of responding only whereas the difficulties of the simulated items constituting the contextual condition were varied. The first study showed that a broad range of difficulties of items was insufficient for driving a difficulty factor. The second study revealed that very large and small difficulties of the same size could lead to a difficulty factor if the

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Hwa, Mei Yin, Tai Yi Yu, Wen Chung Hsu, and Chien An Chen. "Establishment of Typical Driving Patterns for Light-Duty Vehicles on Different Roads in Hsin-Chu Area of Taiwan." Advanced Materials Research 356-360 (October 2011): 1505–9. http://dx.doi.org/10.4028/www.scientific.net/amr.356-360.1505.

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This study utilized the car chasing method to chase 86 light-duty vehicles on seven major roads in the Shin-Chu area and establish the typical driving patterns for various roads. The 23 parameters that associated with the driving were considered to elucidate the features of driving patterns. This work examined two manners, corrected Euclidean distance and traditional Euclidean distance methods, to elucidate a representative driven cycle. In the screening procedure of the typical driven cycle, factor analysis was applied to correct Euclidean distance and examine the 23 variables of driving cond

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Strahan, Robert F., Cletus R. Mercier, Joyce M. Mercier, and Michael W. O'Boyle. "Personality Structure of Elderly Drivers." Perceptual and Motor Skills 85, no. 2 (1997): 747–55. http://dx.doi.org/10.2466/pms.1997.85.2.747.

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This paper reports the factor structure of a 37-item personality questionnaire intended to be predictive of driving performance in elderly persons. Subjects were 191 persons 63 years of age or older, about half of whom also were given perceptual/cognitive tasks and drove on a closed driving course. Although the personality questionnaire did not predict driving skill, the factor structure of the questionnaire is of interest. Of several factor analyses, the most satisfactory was a 2-factor solution. We interpreted the approximately orthogonal factors as measuring what we labeled Competence and E

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Carvalho, Janessa O., Beth Springate, Rachel A. Bernier, and Jennifer Davis. "Psychometrics of the AAN Caregiver Driving Safety Questionnaire and contributors to caregiver concern about driving safety in older adults." International Psychogeriatrics 30, no. 3 (2017): 355–64. http://dx.doi.org/10.1017/s1041610217001727.

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ABSTRACTBackground:The American Academy of Neurology (AAN) updated their practice parameters in the evaluation of driving risk in dementia and developed a Caregiver Driving Safety Questionnaire, detailed in their original manuscript (Iverson Gronseth, Reger, Classen, Dubinsky, & Rizzo, 2010). They described four factors associated with decreased driving ability in dementia patients: history of crashes or citations, informant-reported concerns, reduced mileage, and aggressive driving.Method:An informant-reported AAN Caregiver Driving Safety Questionnaire was designed with these elements, an

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Xin-gang, Zhao, and Wang Wei. "Driving force for China’s photovoltaic industry output growth: Factor-driven or technological innovation-driven?" Journal of Cleaner Production 274 (November 2020): 122848. http://dx.doi.org/10.1016/j.jclepro.2020.122848.

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Choi, ByoungHee, JuSuk Oh, SunJin Park, and SoonChul Lee. "The relationship between multidimensional traffic locus of control and reckless driving behavior." Korean Journal of Industrial and Organizational Psychology 28, no. 1 (2015): 1–22. http://dx.doi.org/10.24230/kjiop.v28i1.1-22.

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This study investigated the relationship between Traffic Locus of Control(T-LOC) and Reckless Driving Behavior, by using correlation analysis and a hierarchical regression for the data gathered through 294 adults. First, this study examined correlation analysis between T-LOC and Driving Behavior Determinants(DBD). As a result, “Self” and “Other drivers” factors of T-LOC were positively correlated with ‘Interpersonal Anger’ factor, “Vehicle/Environment” factor was positively correlated with ‘Avoiding Problems’ factor, and external “Fate” was positively correlated with ‘Avoiding Problems’, ‘Bene

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Fan, Xiaonan, Sainan Ren, and Yang Liu. "The Driving Factors of Green Technology Innovation Efficiency—A Study Based on the Dynamic QCA Method." Sustainability 15, no. 12 (2023): 9845. http://dx.doi.org/10.3390/su15129845.

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The problems of environmental pollution and resource shortages are becoming increasingly prominent with the advances in technology and the improvements in social productivity levels. How to coordinate the innovating subjects, and strengthen the interaction and cooperation among the subjects to improve the green technology innovation efficiency (GTI efficiency) is an important issue to be solved urgently. This paper constructs a multisubject collaborative analysis framework of “government–market–society” for the GTI efficiency based on the pluralistic co-governance theory. Using 30 provinces (o

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Fitriyah, Naning Lailatul, Tutut Dwi Sutiknjo, Eko Yuliarsha Sidhi, and Agustia Dwi Pamujiati. "Pendekatan Eskalasi Usaha Perikanan Mas Koki (Carrasius auratus) di Kabupaten Tulungagung." JINTAN : Jurnal Ilmiah Pertanian Nasional 2, no. 2 (2022): 116. http://dx.doi.org/10.30737/jintan.v2i2.2784.

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Goldfish (Carassius auratus) is an ornamental fish with promising agribusiness prospects. One of the cultivation areas with potential for development is Tulungagung Regency. The research was conducted at the Fish Cultivation Group (Pokdakan) Tirto Mulyo Asri, located in Wajak Lor Village, to analyze a particular approach to escalating goldfish culture in the area. The study adopted the Force Field Analysis (FFA) method with a qualitative descriptive analysis approach. The analysis showed five factors driving and inhibiting goldfish cultivation at the research site. The highest driving factor i

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Yusoff, Mazirah, Fraser McLeay, and Helen Woodruffe-Burton. "Dimensions driving business student satisfaction in higher education." Quality Assurance in Education 23, no. 1 (2015): 86–104. http://dx.doi.org/10.1108/qae-08-2013-0035.

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Purpose – This study aims to identify the dimensions of business student satisfaction in the Malaysian private higher educational environment and evaluate the influence that demographic factors have on satisfaction. Design/methodology/approach – A questionnaire was developed and distributed to 1,200 undergraduate business students at four private higher educational (PHE) institutions in Malaysia. Exploratory factor analysis was used to identify the underlying dimensions that drive student satisfaction. ANOVA and t-tests were conducted to evaluate the influence that demographic factors have on

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Ochotnický, Pavol, Martin Alexy, and Marek Káčer. "Driving Forces of Total Factor Productivity in Europe." Ekonomický časopis 68, no. 10 (2020): 1002–20. http://dx.doi.org/10.31577/ekoncas.2020.10.02.

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Mooli, Raja Gopal Reddy, and Sadeesh K. Ramakrishnan. "Liver Steatosis is a Driving Factor of Inflammation." Cellular and Molecular Gastroenterology and Hepatology 13, no. 4 (2022): 1267–70. http://dx.doi.org/10.1016/j.jcmgh.2022.01.007.

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Ristic, Natasa, Vladimir Vukajlovic, and Pavle Brazakovic. "Innovation as a driving factor of economic development." Ekonomija: teorija i praksa 9, no. 1 (2016): 19–34. http://dx.doi.org/10.5937/etp1601019r.

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Liozu, Stephan M., and Andreas Hinterhuber. "The confidence factor in pricing: driving firm performance." Journal of Business Strategy 34, no. 4 (2013): 11–21. http://dx.doi.org/10.1108/jbs-09-2012-0043.

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SUDA, Yoshihiro, Takayuki TAGUCHI, and Masaaki ONUKI. "Development of Driving Simulator for Human Factor Analysis." Proceedings of the Transportation and Logistics Conference 2004.13 (2004): 217–20. http://dx.doi.org/10.1299/jsmetld.2004.13.217.

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Viganò, Elena, and Alessandra Mortellaro. "Caspase-11: The driving factor for noncanonical inflammasomes." European Journal of Immunology 43, no. 9 (2013): 2240–45. http://dx.doi.org/10.1002/eji.201343800.

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Vu, Nam Hoai, Dinh Do Duy, Dung Huu Nguyen, Tho Phan Cao, and Long Quoc Hoang. "Effect of Driver Safety Attitude and Risk Perception on Driving Behaviors in Vietnam." IOP Conference Series: Materials Science and Engineering 1289, no. 1 (2023): 012052. http://dx.doi.org/10.1088/1757-899x/1289/1/012052.

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Abstract Road traffic accidents are a significant contributor to the global disease burden and a major cause of fatalities worldwide. In order to enhance traffic safety and minimize accidents, this study investigated the effect of driver safety attitudes and risk perception on driving behavior. To gather responses on risk perception and safety attitudes, surveys were conducted both online and on paper in three Vietnamese cities: Hanoi, Yenbai, and Laocai, and data was collected from 500 drivers. Exploratory factor analysis was performed on the 48 items in the questionnaire, resulting in eight

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Klauer, Sheila G., Vicki L. Neale, Thomas A. Dingus, David Ramsey, and Jeremy Sudweeks. "Driver Inattention: A Contributing Factor to Crashes and Near-Crashes." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 22 (2005): 1922–26. http://dx.doi.org/10.1177/154193120504902208.

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Driver distraction, or inattention, has been receiving wide media attention recently as many state legislatures are considering various levels of restricting cell phone use. Research has been conducted using a variety of experimental methods to determine the level of risk associated with driving inattention. While most of this research suggests that inattention impairs driving, there have been no studies to directly link driving inattention to crashes. Data from the 100-Car Naturalistic Driving Study, an instrumented vehicle study for which data was collected on 100 drivers in the Washington,

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Song, HunHwa, and SoonChul Lee. "Changes in traffic accident risk degree according to driving workload rate and moderate effect of ego-resilience." Korean Journal of Industrial and Organizational Psychology 24, no. 1 (2011): 29–50. http://dx.doi.org/10.24230/kjiop.v24i1.29-50.

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This research was conducted to verify changes in traffic accident risk level according to driving workload rate and the moderate effect of ego-resilience. Several hypotheses were made by considering previous studies, in which the traffic accident risk level measured according to Traffic Accident Risk Index (TARI) and Driving Behavior Determinants (DBD) differed from the driving workload rate. Furthermore, Ego-resilience was also considered as a human factor, which has the moderate effect between workload and TARI, DBD. A total of 260 drivers participated in the survey. The result of the factor

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Xu, Wenxiang, Junhua Wang, Ting Fu, Anae Sobhani, and Matin Nabavi Niaki. "Investigating Contributing Factors on Aggressive Driving Based on a Structural Equation Model." Journal of Advanced Transportation 2022 (March 20, 2022): 1–14. http://dx.doi.org/10.1155/2022/1783392.

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Tailored countermeasures that may significantly improve road traffic safety can be proposed and implemented if the relationship between various associated factors and aggressive driving is well understood. However, this relationship remains unknown, as driving behavior is complex, and the interrelationships among variables are not easy to identify. Considering this situation, this paper constructed a model based on a structural equation model (SEM) and factor analysis (FA), which is a multivariate statistical analysis technique used to analyze structural relationships. The model is applied in

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Sun, Chuan, Bijun Li, Yicheng Li, and Zhenji Lu. "Driving Risk Classification Methodology for Intelligent Drive in Real Traffic Event." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 09 (2019): 1950014. http://dx.doi.org/10.1142/s0218001419500149.

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To solve the problem that existing driving data cannot correlate to the large number of vehicles in terms of driving risks, is the functionality of intelligent driving algorithm should be improved. This paper deeply explores driving data to build a link between massive driving data and a large number of sample vehicles for driving risk analysis. It sorted out certain driving behavior parameters in the driving data, and extracted some parameters closely related to the driving risk; it further utilized the principal component analysis and factor analysis in spatio-temporal data to integrate cert

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Qiu, Hongbo, Wenfei Yu, Bingxia Tang, Weili Li, Cunxiang Yang, and Yanfeng Wang. "Effects of driving modes on permanent magnet motor electromagnetic and temperature fields at limit conditions." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 35, no. 6 (2016): 2045–62. http://dx.doi.org/10.1108/compel-04-2016-0148.

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Purpose Taking a 2,000 r/min 10 kW permanent magnet motor as an example, the purpose of this paper is to study the influence of driving modes on the performance of permanent magnet motor at limit conditions, and researched the variation mechanism of motor performance influenced by different driving modes. Design/methodology/approach A two-dimensional electromagnetic field model of the permanent magnet motor was established, and a rectangular-wave driving circuit was built. By using the finite element method, the electromagnetic field, current, harmonic content and eddy current loss were calcul

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Gao, Yazhou. "Measurement and Driving Factors of Green Total Factor Manufacturing Energy Efficiency in China." International Journal of Sustainable Development and Planning 15, no. 7 (2020): 1017–23. http://dx.doi.org/10.18280/ijsdp.150706.

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As the largest manufacturer in the world, China has attracted much attention in the green transformation of manufacturing. This paper firstly designs an evaluation index system (EIS) of green total factor manufacturing energy efficiency (GTFMEE), which covers the three industrial wastes as the undesired output. Based on the EIS, the directional distance function (DDF) was adopted to measure the GTFMEEs of 30 provincial administrative regions (provinces) in China from 2010 to 2017. Then, the Tobit model was introduced to empirically analyze the driving factors of the GTFMEE. The results show th

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Wang, Feng, Yijie Jiang, Wulin Zhang, and Fang Yang. "Elasticity of factor substitution and driving factors of energy intensity in China’s industry." Energy & Environment 30, no. 3 (2018): 385–407. http://dx.doi.org/10.1177/0958305x18790960.

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Based on the translog cost function and factor substitution theory, the input and output data from China’s industrial sector and the three sub-sectors during the period 1984–2011 are firstly used to calculate substitution elasticity among capital, labor, energy, and intermediate input. And then from the perspective of factor substitution, the driving factors of energy intensity in China’s industry are explored. The main findings introduced in this paper are listed as follows: firstly, the production of China’s industrial sector is sensitive to changes of energy and labor prices; secondly, exce

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Zhou, Zhou, Jianqiang Duan, Shaoqing Geng, and Ran Li. "Spatial Network and Driving Factors of Agricultural Green Total Factor Productivity in China." Energies 16, no. 14 (2023): 5380. http://dx.doi.org/10.3390/en16145380.

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Agricultural green total factor productivity (AGTFP) is an important indicator to reflect the sustainability level of agriculture. The AGTFP network reflects the spatial correlations of the AGTFP among regions; thus, exploring its network structure and influencing factors can provide targeted policy guidance to the coordinated development of the agriculture sector. This study builds an epsilon-based measurement data envelopment analysis (EBM-DEA) model to calculate 31 provincial AGTFPs in China from 2002 to 2020. Then, social network analysis (SNA) was utilized to explore the characteristics o

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Shao, Hai-peng, Juan Yin, Wen-hao Yu, and Qiu-ling Wang. "Aberrant Driving Behaviours on Risk Involvement among Drivers in China." Journal of Advanced Transportation 2020 (June 29, 2020): 1–8. http://dx.doi.org/10.1155/2020/8878711.

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The purpose of this study is to validate the version of Driver Behaviour Questionnaire (DBQ) by considering distractions, fatigue, and drunk driving, the main reasons for accidents in China, as independent parts of violations and errors and further explore the effects of demographic/driving variables and all factors on risk involvement (accident involvement and penalized points). 241 drivers filled in a self-completion questionnaire with 28 items conducted in Xi’an in August 2018. Exploratory factor analysis confirmed a five-factor structure, including violations, distracted driving, errors, d

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Liang, Samuel Xin. "The Driving Forces of Stock Returns in Hong Kong." Accounting and Finance Research 8, no. 4 (2019): 1. http://dx.doi.org/10.5430/afr.v8n4p1.

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We comprehensively investigate what drives stock returns in Hong Kong stock market which has been consistently ranked as one of the most important markets for IPOs. We find that Hong Kong inflation rate is a systematic pricing factor across stocks after controlling for Fama-French three-factor. It is different from the U.S. market and other developed markets that the momentum, dividend yield, cash-flow yield, earnings yield, and return-reversal factors are not significant pricing factors for stock returns in Hong Kong. Our Fama-MacBeath (1973) regressions show that a stock’s value (cash-flow y

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Tang, Liang, Haifeng Jiang, Zhenling Zhang, Shanshan Hou, and Bo Liu. "The Driving Path of China’s Urban Resilience Enhancement in the Digital Economy Era." Discrete Dynamics in Nature and Society 2023 (April 14, 2023): 1–16. http://dx.doi.org/10.1155/2023/9992474.

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Promoting the development of China’s digital economy and the level of urban disaster reduction and governance is of great significance for accelerating the improvement of China’s urban resilience and promoting the coordinated development of regional cities. This paper analyzed the spatial and temporal distribution characteristics and driving paths of urban resilience in 31 Chinese provinces, autonomous regions, and municipalities directly under the central government and proposed relevant measures to promote urban resilience. First, the urban resilience evaluation system was constructed and th

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Ge, Yuankai, Longlong Zhao, Jinsong Chen, et al. "Study on Soil Erosion Driving Forces by Using (R)USLE Framework and Machine Learning: A Case Study in Southwest China." Land 12, no. 3 (2023): 639. http://dx.doi.org/10.3390/land12030639.

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Soil erosion often leads to land degradation, agricultural production reduction, and environmental deterioration, which seriously restricts the sustainable development of regions. Clarifying the driving factors of soil erosion is the premise of preventing soil erosion. Given the lack of current research on the driving factors/force changes of soil erosion in different regions or under different erosion intensity grades, this paper pioneered to use machine learning methods to address this problem. Firstly, the widely used (Revised) Universal Soil Loss Equation ((R)USLE) framework was applied to

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Sun, Long, Yueying Pan, and Ye Tian. "Psychometric properties of the Chinese version of the Attitudes Toward Accompanied Driving Scale and its relationship with driving styles." PLOS ONE 15, no. 11 (2020): e0242374. http://dx.doi.org/10.1371/journal.pone.0242374.

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The present study aimed to adapt the Attitudes Toward Accompanied Driving Scale (ATADS) to a Chinese drivers sample and to examine its reliability and validity. Five hundred and seventy-two drivers aged 18 to 25 years old were asked to complete the ATADS and a validated Chinese version of the Multidimensional Driving Style Inventory. The factorial structure of the ATADS was examined using exploratory factor analysis (N = 259) and confirmatory factor analysis (N = 313). The validity of the scale was evaluated by examining the associations between the ATADS factors, demographic variables and dri

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Mouloua, Mustapha, J. Christopher Brill, and Edwin Shirkey. "Gender Differences and Aggressive Driving Behavior: A Factor Analytic Study." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 18 (2007): 1283–86. http://dx.doi.org/10.1177/154193120705101850.

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Aggressive driving behavior can be manifested in a wide variety of unsafe driving practices such as tailgating, honking, obscene and rude gestures, flashing high beams at slower traffic, and speeding. According the National Highway Traffic Safety Administration 2000 report, aggressive driving was a major cause of traffic accidents and injury. The present study was designed to systematically examine 5 previously developed scales related to aggressive driving behavior using a factor analytic approach. A sample of 253 students were administered these five questionnaires and the data were coded an

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Tian, Gang, Yanshun Jia, Zeqi Chen, et al. "Evaluation on Lateral Stability of Vehicle: Impacts of Pavement Rutting, Road Alignment, and Adverse Weather." Applied Sciences 13, no. 5 (2023): 3250. http://dx.doi.org/10.3390/app13053250.

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The combination of pavement rutting, poor road alignment, and extreme adverse weather will seriously threaten the driving safety of vehicles, whereas only a few of these factors are commonly concerned. This study aims to efficiently evaluate the impacts of various driving conditions on the lateral stability of the vehicle and produce a practical recommendation for pavement maintenance in what concerns rutting. A systematic framework was, thus, developed to conduct a comprehensive evaluation of the lateral stability of the vehicle, which incorporates a single-factor test and multi-factor test b

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Hasegawa, Yasushi, Yoshitaka Marumo, Hitoshi Tsunashima, and Takashi Kojima. "356428 ANALYSIS OF BRAKING BEHAVIOR FOR TRAIN DRIVER'S TO DETECT UNUSUAL DRIVING(Human Factor,Technical Session)." Proceedings of International Symposium on Seed-up and Service Technology for Railway and Maglev Systems : STECH 2009 (2009): _356428–1_—_356428–6_. http://dx.doi.org/10.1299/jsmestech.2009._356428-1_.

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Wang, Mo, Xiaoping Fu, Dongqing Zhang, et al. "Urban Flooding Risk Assessment in the Rural-Urban Fringe Based on a Bayesian Classifier." Sustainability 15, no. 7 (2023): 5740. http://dx.doi.org/10.3390/su15075740.

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Urban flooding disasters have become increasingly frequent in rural-urban fringes due to rapid urbanization, posing a serious threat to the aquatic environment, life security, and social economy. To address this issue, this study proposes a flood disaster risk assessment framework that integrates a Weighted Naive Bayesian (WNB) classifier and a Complex Network Model (CNM). The WNB is employed to predict risk distribution according to the risk factors and flooding events data, while the CNM is used to analyze the composition and correlation of the risk attributes according to its network topolo

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Yang, Zhen, Xiangjun Ou, and Huxiao Zhu. "Population Dynamics and Its Driving Forces in China from 2000 to 2020." Sustainability 15, no. 12 (2023): 9415. http://dx.doi.org/10.3390/su15129415.

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Exploring population dynamics and its driving factors has important practical significance for guiding reasonable population distribution. In view of this, this paper systematically analyzes the population dynamics and driving factors in China based on the latest three decennial censuses, using research methods such as the population concentration index, the center of gravity model, relative change in population density and multiple linear regression. The conclusions are as follows: (1) China’s population distribution is uneven, and the trend of polarization in population distribution is incre

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Zhang, Pan, Weiying Sun, Peiqing Xiao, Wenyi Yao, and Guobin Liu. "Driving Factors of Heavy Rainfall Causing Flash Floods in the Middle Reaches of the Yellow River: A Case Study in the Wuding River Basin, China." Sustainability 14, no. 13 (2022): 8004. http://dx.doi.org/10.3390/su14138004.

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In the context of climate change, extreme rainfall events have greatly increased the frequency and risk of flash floods in the Yellow River Basin. In this study, the heavy rainfall and flash flood processes were studied as a system. Taking the driving factors of the heavy rainfall causing the flash floods as the main focus, the key factors of the heavy rainfall causing typical flash flood processes were identified, and the driving mechanism by which the heavy rainfall caused flash floods was revealed. Through comparative analysis of the rainfall related to 13 floods with peak discharges of gre

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Wang, Wenhui, Yi He, Lifeng Zhang, Youdong Chen, Lisha Qiu, and Hongyu Pu. "Analysis of surface deformation and driving forces in Lanzhou." Open Geosciences 12, no. 1 (2020): 1127–45. http://dx.doi.org/10.1515/geo-2020-0128.

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AbstractSurface deformation has become an important factor affecting urban development. Lanzhou is an important location in the Belt and Road Initiative, an international development policy implemented by the Chinese government. Because of rapid urbanization in Lanzhou, surface deformation occurs easily. However, the spatial-temporal characteristics of surface deformation and the interaction of driving forces behind surface deformation in Lanzhou are unclear. This paper uses small baseline subset InSAR (SBAS-InSAR) technology to obtain the spatial-temporal characteristics of surface deformatio

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Adamski, Wojciech, Krzysztof Brzozowski, Jacek Nowakowski, Tomasz Praszkiewicz, and Tomasz Knefel. "Excess Fuel Consumption Due to Selection of a Lower Than Optimal Gear—Case Study Based on Data Obtained in Real Traffic Conditions." Energies 14, no. 23 (2021): 7979. http://dx.doi.org/10.3390/en14237979.

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Appropriate driving technique, in compliance with eco-driving principles, remains an effective method to reduce fuel consumption. The selection of the correct gear is one of the pertinent factors when driving a car with a manual gearbox. In this study we have analyzed fuel overconsumption based on data recorded in real traffic conditions for vehicles driven by experienced drivers, using a black-box model. It was found that the total share of trip time with a lower than optimal gear selected amounted to from c.a. 3% for motorway driving up to 28% on rural roads. The mean fuel consumption reduct

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KALYONCUOĞLU, Figen Ş., and Mesut TIĞDEMİR. "The Effects of the Daily Driven Distance and Age Factor on the Traffic Accidents." PROMET - Traffic&Transportation 26, no. 3 (2014): 201–7. http://dx.doi.org/10.7307/ptt.v26i3.1306.

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Based on Turkish traffic survey data (n=5,520), driver accident rates per million kilometre-driver were compared according to the daily driven distances (DDD) for each age group as very old (65+, n=39), old (56-65, n=183), above middle-aged (36-55, n=1,875), middle-aged (26-35, n=2,204), and young (25-, n=1,219). When the accidents-per-km comparison was made in groups matched for daily exposure, there was no evidence of higher risk with increasing age. In all age groups, risk per km decreased with increasing daily driving distance. With this study the accident involvement prediction models hav

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He, Jiaying, Xiaohui Jiang, Yuxin Lei, Wenjuan Cai, and Junjun Zhang. "Temporal and Spatial Variation and Driving Forces of Soil Erosion on the Loess Plateau before and after the Implementation of the Grain-for-Green Project: A Case Study in the Yanhe River Basin, China." International Journal of Environmental Research and Public Health 19, no. 14 (2022): 8446. http://dx.doi.org/10.3390/ijerph19148446.

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To curb soil erosion, the Grain-for-Green Project has been implemented in the Loess Plateau region, and there have been few quantitative evaluations of the impact of ecological engineering on the spatial distribution of soil erosion on the Loess Plateau. In this paper, we used ArcGIS software, the Revised Universal Soil Loss Equation (RUSLE) model and the Geographic Detector (GeoDetector) model to investigate the changes in the spatial distribution of soil erosion and driving forces before and after the implementation of the Grain-for-Green Project in Yanhe River Basin, a typical area on the L

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&NA;. "TQM - the driving factor in the management of infections." Inpharma Weekly &NA;, no. 929 (1994): 8. http://dx.doi.org/10.2165/00128413-199409290-00014.

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Shin, sora. "The Predictive factor of risky and aggressive driving victimization." Korean Association of Public Safety and Criminal Justice 29, no. 1 (2020): 75–98. http://dx.doi.org/10.21181/kjpc.2020.29.1.75.

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Untersmayr, Eva, Annette Brandt, Larissa Koidl, and Ina Bergheim. "The Intestinal Barrier Dysfunction as Driving Factor of Inflammaging." Nutrients 14, no. 5 (2022): 949. http://dx.doi.org/10.3390/nu14050949.

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The intestinal barrier, composed of the luminal microbiota, the mucus layer, and the physical barrier consisting of epithelial cells and immune cells, the latter residing underneath and within the epithelial cells, plays a special role in health and disease. While there is growing knowledge on the changes to the different layers associated with disease development, the barrier function also plays an important role during aging. Besides changes in the composition and function of cellular junctions, the entire gastrointestinal physiology contributes to essential age-related changes. This is also

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&NA;. "Is cost a driving factor for prescribing in PD?" Inpharma Weekly &NA;, no. 1497 (2005): 5. http://dx.doi.org/10.2165/00128413-200514970-00008.

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Klingenhoefer, S., and F. Bremmer. "Foveation Time as a Driving Factor of Saccade Adaptation." Journal of Vision 10, no. 7 (2010): 501. http://dx.doi.org/10.1167/10.7.501.

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Jirgl, M., P. Fiedler, and Z. Bradac. "Using Matlab-based Driving Simulator for Human Factor Assessment." IFAC-PapersOnLine 52, no. 27 (2019): 27–32. http://dx.doi.org/10.1016/j.ifacol.2019.12.727.

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