Herd Effect Research Articles

Exploring bimodal multi‐level networks: Network structure and dynamics driving herding effects and growth in livestreaming

AbstractThe majority of social network research in the IS field relies on assumptions that social networks are single‐level unified entities, disregarding the potential bimodal network structure with the coexistence of centralized and decentralized networks and overlooking the essential role of adjacent nodes as decision‐makers. By challenging these assumptions, we propose that both centralized and decentralized networks can coexist within multi‐level bimodal platforms via various role‐based subgroups with different types of decision‐makers. Livestreaming platforms, exemplifying the coexistence of multi‐level networks within a single digital ecosystem, have become increasingly popular in various industries. Drawing on social impact theory (SIT), we examine the role of information from host‐audience centralized and host–host decentralized networks in shaping subscription increment and herding effects. Using a panel dataset in livestreaming, we find that bidirectional ties in host–host networks strengthen fan acquisition and herding effect in the host‐audience decentralized network, with hosts of lower social status gaining more fans than those with higher status in bidirectional ties. Our study contributes to the understanding of social network structure, herding effect, SIT and livestreaming by problematizing assumptions and offering a contextual explanation of livestreaming. Moreover, our work provides practitioners with valuable insights into leveraging network effects for hosts' success in livestreaming.

Hind feet position score: A novel trait to genetically reduce lameness incidence

Lameness is an important health and welfare issue that causes considerable economic losses in dairy herds. The objective of this study was to investigate whether the hind feet position score (HFPS) can be used as an auxiliary trait for genetic evaluation of lameness. The HFPS is evaluated by visual scoring of the position of both the hind-digits to the mid-line of the cow's body. The higher the heel height of the lateral claw, the higher is the HFPS, and the higher is the risk for development of lameness. In total, 3,478 records from 1,064 Fleckvieh cows from 35 farms were obtained between September 1, 2021, and March 5, 2022. Data collection was carried out by the regional milk recording organizations. Hind feet position was scored visually by trained personnel during routine milk performance testing in the milking parlor using a 3-class scoring system: score 1 = 0° to <17° indicating a balanced heel height of both the medial and the lateral claw; score 2 = angle of 17° to 24°; score 3 = angle of >24°. After all cows had been milked, locomotion scoring was performed for each animal using a 5-class scoring system with locomotion scores ranging between 1 (normal) and 5 (severely lame). Using HFPS, sensitivity and specificity were 69.5% and 66.8%, respectively, for detecting lameness defined by locomotion score ≥2. For genetic analyses, a bivariate linear animal model was fitted with fixed effects of herd, parity, lactation stage, and classifier, and random effects of animal and permanent environment. Heritabilities for HFPS and locomotion score were 0.07 and 0.10, respectively, and the genetic correlation between the 2 traits studied was 0.80. These results suggest that the HFPS could be used for genetic evaluations to reduce lameness incidence in dairy cattle.

Role of Allee Effect, Hunting Cooperation, and Dispersal to Prey–Predator Model

In prey–predator interaction, many factors, such as the fear effect, Allee effect, cooperative hunting, and group behavior, can influence the population dynamics. Hence, studying these factors in prey–predator makes the model more realistic. In this paper, we have proposed the prey–predator model having herd and Allee effect in prey population, where predators follow hunting cooperation. We have employed temporal analysis to examine the role of the Allee effect and hunting cooperation. Furthermore, we have extended the analysis to spatiotemporal analysis to examine the role of dispersal and the type of spatial structure formed by the population due to random movement. We first discuss the proposed model’s existence and positivity, then the stability of the existing equilibrium points through Routh–Hurwitz criteria. The temporal analysis is carried out through Hopf-bifurcation at the coexistence equilibrium point by considering the Allee threshold ([Formula: see text]), hunting cooperation ([Formula: see text]), and attack rate ([Formula: see text]) as controlled parameters. With the addition of diffusion to the model, we examine the spatial model stability and derive the Turing instability condition, which will give rise to various Turing patterns. Finally, numerical simulations are performed to validate the analytical results. The theoretical study and numerical simulation results demonstrate that the Allee effect, hunting cooperation, and diffusion coefficient are sensitive parameters to the model’s stability.

Information Acquisition Ability and Farmers’ Herd Behavior in Rice–Crayfish Coculture System Adoption

Rice–crayfish coculture systems (RCSs) have been widely promoted in China as an efficient circular agriculture model that can simultaneously improve rice quality, raise the efficiency of utilization of resources, and increase farmers’ incomes. However, the herd behavior of farmers in the adoption of the rice–crayfish coculture system warrants more attention, as the rational adoption of this system by farmers is a prerequisite for achieving the above objectives. This paper analyses the formation mechanism of farmers’ herd behavior based on information cascade theory. Using micro-survey data from 603 farmers in China and a bivariate probit model, we examine the existence of herding effects in the adoption of RCSs by farmers and the inhibitory effect of information acquisition capability on herd behavior. To address possible endogeneity issues, we also conducted a robustness test using the IV-probit model. Furthermore, we tested for between-group differences in agricultural income between farmers with herding adoption and non-herding adoption. The study reveals that the larger the number of prior adopters, the higher the probability of blind adoption behavior by farmers, indicating the existence of a herd effect. Information acquisition ability could significantly inhibit the herd behavior of farmers in the adoption of RCSs. We also found that farmers’ herd behavior in the adoption of these systems was not economically rational. Based on the research findings, we proposed several constructive suggestions for policy perfection.

Relationships of beta-casein genetics with production, fertility, and survival of purebred organic Holstein dairy cows

The objective of this study was to compare β-casein genotype of purebred certified-organic Holstein cows, and their effect on production, fertility, and survival. Holstein cows (n = 1,982) from 13 certified-organic dairy herds from the western, midwestern, and northeastern United States were genomically tested with CLARIFIDE Plus (Zoetis) for β-casein genotype. Two hundred fourteen cows were A1A1 (11%), 848 cows were A1A2 (43%), and 920 cows were A2A2 (46%). In total, 2,249 lactation records, 1,025 from the first parity and 1,224 records during second and greater parities were used. Test-day milk, fat, and protein production (305-d) and somatic cell score were obtained from the Dairy Herd Improvement Association. A lower limit of 50 d for days open was applied, and cows with more than 250 d open had days open set to 250 d. Independent variables for statistical analysis were the fixed effects of herd, parity, β-casein genotype (A1A1, A1A2, A2A2), and β-casein genotype by parity interaction. Cow nested within parity was the random effect in the statistical models for fertility and production traits. Herd had a significant effect on all fertility, production, and survival variables. Parity affected the number of times bred per pregnancy and days open, milk, fat, and protein production, and somatic cell score. Beta-casein genotype and herd influenced the percentage of cows surviving to first and second lactation. Results indicate no difference in production and fertility regarding β-casein genotype for organic dairy herds. Survival was biased against the A1 allele, which is indicated by lower survival rates during first lactation. These results may offer organic producers more flexibility in breeding and culling decisions to produce A2A2 milk.

Exploring the sources of variation of electrical conductivity and total and differential somatic cell count in Italian Mediterranean buffaloes

In the buffalo dairy sector, a huge effort is still needed to improve mastitis prevention, detection, and management. Electrical conductivity (EC) and total somatic cell count (SCC) are well-known indirect indicators of mastitis. Differential somatic cell count (DSCC), which represents the proportion of neutrophils and lymphocytes on the total SCC, is instead a novel phenotype collected in the dairy cattle sector in the last lustrum. As little is known about this novel trait in dairy buffalo, in the present study we explored the nongenetic factors affecting DSCC, as well as EC and total somatic cell score (SCS), in the Italian Mediterranean buffalo. The data set used for the analysis included 14,571 test-day (TD) records of 1,501 animals from 6 herds, and climatic information of the sampling locations. The original data were filtered to exclude animals with less than 3 TD per lactation and, for the investigated traits, outliers beyond 4 standard deviations. In the statistical model we included the fixed effects of herd (6 classes), days in milk (DIM; 10 classes of 30 d, with the last being an open class until 360 d), parity (6 classes, from 1 to 6+), year-season of calving (11 classes, from summer 2019 to winter 2021/2022), year-season of sampling (9 classes, from spring 2020 to spring 2022), production level (4 classes based on quartiles of average milk yield by herd), and temperature-humidity index (THI; 4 classes based on quartiles, calculated using the average temperature and relative humidity of the 5 d before sampling). Average EC, SCS, and DSCC vary across herds. Considering DIM, greater EC values were observed at the beginning and the end of lactation; SCS was slightly lower, but DSCC was greater around the lactation peak. Increased EC, SCS, and DSCC levels with increasing parity were reported. Year-season calving and year-season sampling only slightly affected the variation of the investigated traits. Milk of high-producing buffaloes was characterized by lower EC and SCS mean values, nevertheless it had slightly greater DSCC percentages. Buffaloes grouped in the highest THI classes (classes 3 and 4) showed, on average, greater EC, SCS, and DSCC in comparison to the lower classes, especially to class 2. Results of the present study represent a preliminary as well as necessary step for the possible future inclusion of EC, SCS, or DSCC in breeding programs aimed to improve mastitis resistance in dairy buffaloes.

An Empirical Study on the Linkage between S&amp;P 500 Index and CSI 300 Index under COVID-19

Studying the linkage between US and Chinese stock markets under the context of COVID-19 outbreak in 2020 can help us to prevent related financial risks, regulate corresponding monetary policies, and avoid the herd effect of investors being blindly optimistic or pessimistic. Between January 1, 2020 and November 10, 2022, using the returns of the S&amp;P 500 index as a proxy for the US stock market and the CSI 300 index as a proxy for the Chinese stock market, the VAR-GARCH-BEKK model was used to empirically analyze the relationship between the two. According to the findings, the rise and fall of the S&amp;P 500 index has some favorable effects on the rise and fall of the CSI 300 index. Yet, the CSI 300 index's movement is largely determined by past data, suggesting that the S&amp;P 500's volatility, which represents the US stock market, has little effect on the Chinese stock market, which is represented by the CSI 300.

Association between hyperketolactia and production in early-lactating dairy cows

Study aims were to investigate associations of hyperketolactia (HYKL) status of Holstein dairy cows between 6 and 60 d in milk (DIM), defined by milk acetone (mACE) and β-hydroxybutyrate (mBHB) content, with daily milk yield and composition. Milk samples (∼5.0 million) were collected over a 5-yr period (2014-2019) within the milk recording system in Poland. Concentrations of mACE and mBHB determined by Fourier-transform infrared spectroscopy were used to categorize samples into 4 ketolactia groups. Based on threshold values of ≥0.15 mmol/L mACE and ≥0.10 mmol/L mBHB, ketolactia groups were normoketolactia (NKL; mACE <0.15 mmol/L and mBHB <0.10 mmol/L), BHB hyperketolactia (HYKLBHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), ACE hyperketolactia (HYKLACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L), and ACE and BHB hyperketolactia (HYKLACEBHB; mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L). To investigate ketolactia association with production outcomes, a linear model was developed, including ketolactia group, DIM, parity, their interactions, year-season as fixed effects, and random effects of herd and cow. Among all milk samples, 31.2% were classified as HYKL, and of these, 52.6%, 39.6%, and 7.8% were HYKLACEBHB, HYKLBHB, and HYKLACE, respectively. Ketolactia groups differed for all traits studied in all parities and DIM. Among HYKL groups, lowest milk yield was found in HYKLACEBHB cows, except for 6 to 30 DIM in first- and second-lactation cows. Milk yield of HYKLBHB cows was higher than that of NKL cows until 20 to 30 DIM, and then it was lower than NKL cows. Milk yield of HYKLACE cows was mostly lower than NKL cows. Energy-corrected milk (ECM) yield of HYKLACEBHB cows was higher than that of NKL cows until 30 to 35 DIM for second lactation and third lactation or greater, and in the whole study period for first lactation. The yield of ECM for HYKLBHB cows was mostly higher than that of NKL cows, whereas HYKLACE cows had higher ECM than NKL cows until 15 to 25 DIM and then was lower for the HYKLACE group. Milk composition differed among HYKL groups. Highest milk fat (MF) and lowest milk lactose (ML) contents were observed in HYKLACEBHB cows. Cows in HYKLACEBHB and HYKLBHB groups had higher MF and lower milk protein (MP; except in 6-8 DIM in first lactation) and ML content than NKL cows. Milk fat content was higher in HYKLACE than NKL cows in first lactation and during the first 30 to 40 DIM in older cows. Lactose content was lower in HYKLACE than in NKL cows within 30 to 40 DIM; afterward it was higher in NKL cows. Lower MP content was found in HYKLACE than in NKL cows, except during 6 to 9 DIM for cows in first lactation and third lactation or greater. In conclusion, HYKL is associated with altered milk production in all parities, but a range of these negative relations depends on ketone status addressing both ACE and BHB contents. Further research is needed to ascertain underpinning biochemical defects of HYKL from elevated ACE, alone or in combination with BHB, during early lactation.

Between mandatory vaccination and the COVID-19 pandemic: effects on the vaccination coverage trend inaprovince of Southern Italy.

Although vaccination is considered an extraordinarily effective and safe tool for the prevention of infectious diseases, from 2013 to 2016 CVs at national level showed a downward trend, falling well below the 95% threshold recommended by the WHO to limit the circulation of viruses and bacteria in the community and to obtain the so-called herd effect in addition to the protection of individual vaccinated individuals. The aim of the study was to assess vaccination coverage data following the introduction of Law 119/2017 and in like to COVID-19 pandemic the impact on vaccination coverage. The study was conducted from 1 October 2019 to 1 October 2022, using the OnVac programme. The analysis of the coverage rates of hexavalent vaccination during the entire study period shows that there was an increase in vaccinations during the two-year period 2020-2021, followed by a drastic decrease down to values below 95%. where variable coverage was noted between the two genders with higher percentages in the female sex. Contrary to expectations, 2021 did not allow the recovery of the defaulting cohorts, with a drop in coverage much higher than in previous years (with values approaching the values of 2008), not only for polio, diphtheria and tetanus, but also for measles, mumps, rubella, chicken pox and HPV, effectively getting worse over the previous decade. immunization challenges need to be addressed to ensure that every child, adolescent or patient at risk is immunized, especially but not only for COVID-19.

Effect of 13-valent pneumococcal conjugate vaccine on experimental carriage of Streptococcus pneumoniae serotype 6B in Blantyre, Malawi: a randomised controlled trial and controlled human infection study

The effect of childhood pneumococcal conjugate vaccine implementation in Malawi is threatened by absence of herd effect. There is persistent vaccine-type pneumococcal carriage in both vaccinated children and the wider community. We aimed to use a human infection study to measure 13-valent pneumococcal conjugate vaccine (PCV13) efficacy against pneumococcal carriage. We did a double-blind, parallel-arm, randomised controlled trial investigating the efficacy of PCV13 or placebo against experimental pneumococcal carriage of Streptococcus pneumoniae serotype 6B (strain BHN418) among healthy adults (aged 18-40 years) from Blantyre, Malawi. We randomly assigned participants (1:1) to receive PCV13 or placebo. PCV13 and placebo doses were prepared by an unmasked pharmacist to maintain research team and participant masking with identification only by a randomisation identification number and barcode. 4 weeks after receiving either PCV13 or placebo, participants were challenged with 20 000 colony forming units (CFUs) per naris, 80 000 CFUs per naris, or 160 000 CFUs per naris by intranasal inoculation. The primary endpoint was experimental pneumococcal carriage, established by culture of nasal wash at 2, 7, and 14 days. Vaccine efficacy was estimated per protocol by means of a log-binomial model adjusting for inoculation dose. The trial is registered with the Pan African Clinical Trials Registry, PACTR202008503507113, and is now closed. Recruitment commenced on April 27, 2021 and the final visit was completed on Sept 12, 2022. 204 participants completed the study protocol (98 PCV13, 106 placebo). There were lower carriage rates in the vaccine group at all three inoculation doses (0 of 21 vs two [11%] of 19 at 20 000 CFUs per naris; six [18%] of 33 vs 12 [29%] of 41 at 80 000 CFUs per naris, and four [9%] of 44 vs 16 [35%] of 46 at 160 000 CFUs per naris). The overall carriage rate was lower in the vaccine group compared with the placebo group (ten [10%] of 98 vs 30 [28%] of 106; Fisher's p value=0·0013) and the vaccine efficacy against carriage was estimated at 62·4% (95% CI 27·7-80·4). There were no severe adverse events related to vaccination or inoculation of pneumococci. This is, to our knowledge, the first human challenge study to test the efficacy of a pneumococcal vaccine against pneumococcal carriage in Africa, which can now be used to establish vaccine-induced correlates of protection and compare alternative strategies to prevent pneumococcal carriage. This powerful tool could lead to new means to enhance reduction in pneumococcal carriage after vaccination. Wellcome Trust.

Genetic evaluation of health costs in US organic Holstein calves and cows

Minimizing the incidence of disease on organic dairy farms is important for both economic and animal welfare purposes. The objective of this study was to estimate genetic parameters for total disease treatment costs using producer-recorded treatments in organic Holstein dairy calves and cows. Individual cow and calf health data were collected from 16 USDA certified organic farms from across the United States. Eleven of these farms provided treatment costs for some or all of the following cow health issues (mean cost): mastitis ($46.10), milk fever ($39.05), ketosis ($29.81), metritis ($28.66), retained placenta ($45.59), displaced abomasum ($439.71), lameness ($66.36), indigestion ($22.94), respiratory ($48.35), and died ($64.98). These farms also provided the following health costs for calves (mean cost): respiratory ($56.37) and scours ($25.21). Costs included consultant fees, therapeutics, and producer labor. The total lactational health cost (HCOST) was analyzed using animal models adjusted for the fixed effects of lactation and herd and the random effect of herd-year-season of calving with animal relationships based on the blending of pedigree and genomic relationships established from 2,347 genotyped cows. Along with HCOST, the binary traits stayability and presence of disease were included in a trivariate model such that lactations absent of disease were considered to be missing HCOST. To estimate the genetic relationship between nulliparous and primiparous health costs, a 2-trait linear model was fitted for total nulliparous health costs (NHCOST) and first lactation HCOST. The most expensive cow-lactation was $643.86 and 26.5% of lactations encountered disease. The heritability for HCOST was 0.03 ± 0.01, and the repeatability was 0.21 ± 0.01. The heritability of NHCOST was 0.06 ± 0.01, and the genetic correlation between NHCOST and HCOST was 0.98 ± 0.51. Traits representing the repeated nature of disease have a genetic component that should foster improved disease resistance among organic Holstein dairy cows. However, total cost of disease did not lead to gains in genetic variation over consideration of disease traits considered as binary variables and is a more laborious phenotype to obtain, diminishing its appeal for use in routine genetic evaluations.

What is the Effect of VIX and (un)Expected Illiquidity on Sectoral Herding in US REITs during (Non)Crises? Evidence from a Markov Switching Model (2014 – 2022)

The study investigates the impact of sector and market-wide illiquidity shocks on herding within US Real Estate Investment Trusts (REITs), on a sub-sector level, including health, hotel, mortgage, residential, retail and Warehouse REITs. Using daily data from January 2014 to February 2022, and consistent with noise trader risk theory, the research confirms the existence of herding behavior within US REITs on a sub-sector level, along with identifying that herding effects are intense on days with negative market returns as compared to days with positive market returns. Assessing the impact of investor sentiments via the VIX index, we find that herding behavior rises with a hike in investor uncertainty and fear. Motivated by the presence of a structural break within our data set corresponding to the Covid-19 outbreak, we use a Markov Switching approach and find significant evidence of sub-sector herding being more intense during the crash regime/covid-19 phase, relative to the expansionary phase. When assessing illiquidity, our results confirm that i) during the expansionary phase only expected illiquidity (market and sector-wide) enhances sub-sector herding within US REITs while ii) during the crash phase only unexpected illiquidity (market and sector-wide) enhances sub-sector herding within US REITs.

Indirect impact of PCV10 children vaccination on the serotype distribution and antimicrobial resistance of Streptococcus pneumoniae causing invasive disease in adults over 50 in Colombia, 2005–2019: Observational analysis

IntroductionThe introduction of pneumococcal conjugate vaccine (PCV) into childhood vaccination programmes has reduced the prevalence of vaccine serotypes (VTs) that cause invasive pneumococcal disease (IPD) in children. In the elderly population, an impact has also been seen through indirect protection (herd effect). The aim of this study was to estimate the changes in serotype distribution and antimicrobial susceptibility of Streptococcus pneumoniae isolates recovered from adult IPD and to evaluate the indirect effect of immunization with PCV10 based on laboratory records by analyzing the period from 2005 to 2019 for six years before and eight years after the universal PCV10 administration to Colombian children. MethodsA total of 2204 S. pneumoniae isolates from adults (≥50 years) with IPD were analyzed. The analysis examined the percentage changes in proportions (prevalence) and percentage variations in population rates (annual reported rates – ARR) of VTs between the pre-PCV10 (2005–2009) and post-PCV10 (2015–2019) periods. ResultsThe findings were (1) evidence of a significant percentage decrease of pneumococcal VT10 causing IPD in adults (50% pre-PCV10 and 16% post-PCV10); (2) significant increase of serotype 19A (from 1.6% to 14.8%) and less important increase of serotype 3 (from 10.5% to 14.5%) and non-vaccine serotypes (NVT) (from 21.4% to 38.4%) non-significant; and (3) meningitis and non-meningitis multidrug resistant isolates associated with serotype 19A. An improvement in the surveillance system is associated with the immunization of children, as noted by the increased ARRs across the analysis period. ConclusionsOur results show the indirect impact of PCV10 vaccination in children on the VT10 distribution and antimicrobial resistance of S. pneumoniae causing IPD in Colombian adults over 50 when comparing the pre-PCV10 (2005–2009) and post-PCV10 (2015–2019) periods.

Evaluation of Bayesian Hui-Walter and logistic regression latent class models to estimate diagnostic test characteristics with simulated data.

Estimation of the accuracy of diagnostic tests in the absence of a gold standard is an important research subject in epidemiology (Dohoo et al., 2009). One of the most used methods the last few decades is the Bayesian Hui-Walter (HW) latent class model (Hui and Walter, 1980). However, the classic HW models aggregate the observed individual test results to the population level, and as a result, potentially valuable information from the lower level(s) is not fully incorporated. An alternative approach is the Bayesian logistic regression (LR) latent class model that allows inclusion of individual level covariates (McInturff et al., 2004). In this study, we explored both classic HW and individual level LR latent class models using Bayesian methodology within a simulation context where true disease status and true test properties were predefined. Population prevalences and test characteristics that were realistic for paratuberculosis in cattle (Toft et al., 2005) were used for the simulation. Individual animals were generated to be clustered within herds in two regions. Two tests with binary outcomes were simulated with constant test characteristics across the two regions. On top of the prevalence properties and test characteristics, one animal level binary risk factor was added to the data. The main objective was to compare the performance of Bayesian HW and LR approaches in estimating test sensitivity and specificity in simulated datasets with different population characteristics. Results from various settings showed that LR models provided posterior estimates that were closer to the true values. The LR models that incorporated herd level clustering effects provided the most accurate estimates, in terms of being closest to the true values and having smaller estimation intervals. This work illustrates that individual level LR models are in many situations preferable over classic HW models for estimation of test characteristics in the absence of a gold standard.

Distributed Dispatching in the Parallel Server Model

With the rapid increase in the size and volume of cloud services and data centers, architectures with multiple job dispatchers are quickly becoming the norm. Load balancing is a key element of such systems. Nevertheless, current solutions to load balancing in such systems admit a paradoxical behavior in which more accurate information regarding server queue lengths degrades performance due to herding and detrimental incast effects. Indeed, both in theory and in practice, there is a common doubt regarding the value of information in the context of multi-dispatcher load balancing. As a result, both researchers and system designers resort to more straightforward solutions, such as the power-of-two-choices to avoid worst-case scenarios, potentially sacrificing overall resource utilization and system performance. A principal focus of our investigation concerns the value of information about queue lengths in the multi-dispatcher setting. We argue that, at its core, load balancing with multiple dispatchers is a distributed computing task. In that light, we propose a new job dispatching approach, called Tidal Water Filling, which addresses the distributed nature of the system. Specifically, by incorporating the existence of other dispatchers into the decision-making process, our protocols outperform previous solutions in many scenarios. In particular, when the dispatchers have complete and accurate information regarding the server queues, our policies significantly outperform all existing solutions.

Impact of Liquidity and Investors Sentiment on Herd Behavior in Cryptocurrency Market

This research addresses the impact of individual investors on the cryptocurrency market, focusing specifically on the development of herd behavior. Although the phenomenon of herd behavior has been studied extensively in the stock market, it has received limited research in the context of cryptocurrencies. This study aims to fill this research gap by examining the impact of liquidity and sentiment on herd behavior using the CSAD model, considering small, medium, and large cryptocurrencies. The results show different outcomes for cryptocurrencies of different sizes, consistently demonstrating that the herding effect is more pronounced under conditions of lower liquidity, as determined by the turnover volume and liquidity ratio of cryptocurrencies. Proxy measures such as the Twitter Hedonometer and CBOE VIX were used to measure investor sentiment and show the prevalence of herding behavior in optimistic times for all cryptocurrencies, regardless of their market capitalization. Consequently, this study provides valuable insights into the manifestation of herd behavior in the cryptocurrency market and highlights the importance of liquidity and sentiment as influencing factors. These findings improve our understanding of investor behavior and provide guidance to market participants and policymakers on how to effectively manage the risks associated with herd effects.

Quadrivalent HPV vaccine effectiveness against anogenital warts: A registry-based study of 2,2 million individuals

BackgroundIn 2009, Norway initiated routine quadrivalent HPV (qHPV) vaccination for girls at 12–13 years of age to protect against virus types causing cervical cancer, HPV16/18, and HPV6/11 which cause anogenital warts (AGW). We wanted to investigate qHPV vaccine effectiveness (VE) against AGW in females before and after first AGW episode and to assess the impact of female vaccination in males. Materials and methodsQHPV vaccination and AGW episodes were collected for the time period 2006–2016 for birth cohorts 1975–2003. Cox models were applied to age at first, as well as at second AGW episode. Finally, we estimated the impact of the female vaccination program on unvaccinated males. ResultsThe VE against the first episode of AGW was strongly dependent on vaccination age, with hazard ratios (HRs) compared to unvaccinated individuals of 0.2, 0.2, 0.3, 0.5, 1.0, 1.3, and 2.7, for age groups of ⩽13, 14–15, 16–17, 18–19, 20–24, 25–29, and 30+ years at first vaccination, respectively. Among women who had suffered a first episode of AGW, subsequent qHPV vaccination did not protect against a second episode, with HRs of 0.8, 1.0, and 1.4, for age groups of ⩽17, 18–24, and 25+ years at first vaccination. A gradually decreasing AGW risk was seen in unvaccinated male cohorts neighboring the first routinely vaccinated female 1997 cohort. ConclusionsWhen administered before 14 years of age, qHPV vaccination reduced the probability of AGW about fivefold. The effect decreased sharply with vaccination age, and was not significant among women vaccinated after age 20 years. QHPV administered after the first AGW episode did not protect against a second AGW episode. Herd effects were indicated in unvaccinated males, as we observed a gradual decrease in AGW rates from the 1993 male birth cohort and onwards.

PENGARUH HERDING, OVERCONFIDENCE, RISK PERCEPTION, DAN ACCOUNTING KNOWLEDGE TERHADAP KEPUTUSAN INVESTASI DI BURSA SAHAM

The effect of herding, overconfidence, accounting knowledge and risk perception on investment decisions on the stock market. In today's unstable economic conditions, investment is one of the decisions to save or even seek additional income. Investors are competing to benefit from every investment decision they make. Based on this, this study aims to analyze what factors influence investment decisions. This study will examine the effect of herding, overconfidence, risk perception, and accounting knowledge variables on investment decisions. The respondents of this research are investors in Yogyakarta who invest in the stock market. The number of samples in this study were 101 respondents with simple random sampling technique. The analysis of this research uses the help of the IBM SPSS program. The results of this study indicate that accounting knowledge has a positive and significant influence on investment decisions. However, herding, overconfidence, and risk perception do not have a positive and significant influence on investment decisions. Although there are variables that partially have no effect on investment decisions, this study finds that simultaneously all variables have an influence on investment decisions. The limitations of this study include the number of variables that are still small when compared to the existing population. In addition, researchers also did not select investors based on the category or type of investment made. In addition, this study found that the dependent variables in this study only had an effect of 27,8% to the independent variable (Investment Decision). Based on the result there are many more factors that influence investment decision.

The Role of Risk Tolerance in Mediating the Effect of Overconfidence Bias, Representativeness Bias and Herding on Investment Decisions

This study aims to analyze the impact of Overconfidence Bias, Representativeness Bias, and Herding towards investment decision making through Risk Tolerance, where psychological and social factors could have effect on the investors' decision making process. The sample was gathered using Snowball Sampling technique on 200 stock investors who have made transactions in the Indonesian Stock Exchange. The data was analyzed using SEM PLS with Smart PLS 3.2.9 application. The result shows that Overconfidence Bias and Representativeness Bias have significant impact on both direct and indirect investment decision making process through Risk Tolerance. On the other hand, Herding shows no effect on direct and indirect investment decision making process through Risk Tolerance.

The Impact of Sales Volume and Limited Quantity on Intertemporal Choice in an Online Consumption Context.

In the context of online consumption, consumers are often faced with a decision between buying now or later. This study examines intertemporal choice by conducting two mixed experimental designs on a total of 206 college students to investigate the impact of combining sales volume and limited quantity on online consumption decisions. Experiment 1 revealed that under unlimited conditions, the same option with high sales volume was relatively more attractive and participants were more inclined to choose it, leading to a herding effect. However, under limited conditions, there was no scarcity effect. Experiment 2 built upon the findings of Experiment 1 and added dynamic change in sales volume. It was found that even with dynamic changes in sales volume, high sales volumes could still lead to a herding effect. In the case of unlimited conditions, dynamic changes in sales offset the effect of sales volume on intertemporal choice. Sales volume and limited quantity are important factors that influence consumers' purchasing decisions. Therefore, this study combines sales volume and limited quantity and adds dynamic changes in sales to explore individuals' intertemporal choices in online consumption situations. The findings of the study have significant implications for both merchants and consumers.