Suchergebnisse

PurposeBusinesses need to make quick decisions and adjustments to fulfill the growing online demand. Previous studies examined various factors affecting the online sales performance of products such as books, electronics and movies; however, they paid limited attention toward the local brand clothing products. The current study investigates the importance of different kinds of seller-generated and consumer-generated signals such as price, discount, product ratings, review volume, review sentiment, number of questions and interaction between some of these factors for predicting the sales performance of clothing products.Design/methodology/approachThe multiple linear regressions has been employed to investigate the influence of various predictor variables on sales performance. The study also examines the importance of these predictor variables by using different machine learning models, including random forest (RF), neural networks and support vector regression (SVR).FindingsThe findings of the study emphasize the importance of price and discount rates offered on the product. The quantitative characteristics of reviews, such as review volume and average rating, have been found to be more important predictors than sentiment strengths. However, the sentiment strength of reviews with higher helpfulness scores plays a significant role in predicting sales performance.Originality/valueThe study highlights the varying importance of seller-based and consumer-based signals in predicting sales performance. It also investigates the interaction effect of these two kinds of signals. The consumer-generated signals have been further divided into two components based on social influence theory, and the interaction effects of these components have also been examined.

BackgroundPrimary congenital glaucoma (PCG), occurs due to the developmental defects in the trabecular meshwork and anterior chamber angle in children. PCG exhibits genetic heterogeneity and the CYP1B1 gene has been widely implicated worldwide. Despite the diverse mutation spectra, the clinical implications of these mutations are yet unclear. the present study attempted to delineate the clinical profile of PCG in the background of CYP1B1 mutations from a large cohort of 901 subjects from India (n=601) and Brazil (n=300).MethodsGenotype-phenotype correlations was undertaken on clinically well characterized PCG cases from India (n=301) and Brazil (n=150) to assess the contributions of CYP1B1 mutation on a set of demographic and clinical parameters. the demographic (gender, and history of consanguinity) and quantitative clinical (presenting intraocular pressure [IOP] and corneal diameter [CD]) parameters were considered as binary and continuous variables, respectively, for PCG patients in the background of the overall mutation spectra and also with respect to the prevalent mutations in India (R368H) and Brazil (4340delG). All these variables were fitted in a multivariate logistic regression model using the Akaike Information Criterion (AIC) to estimate the adjusted odds ratio (OR) using the R software (version 2.14.1).ResultsThe overall mutation spectrum were similar across the Indian and Brazilian PCG cases, despite significantly higher number of homozygous mutations in the former (p=0.024) and compound heterozygous mutations in the later (p=0.012). A wide allelic heterogeneity was observed and only 6 mutations were infrequently shared between these two populations. the adjusted ORs for the binary (demographic) and continuous (clinical) variables did not indicate any susceptibility to the observed mutations (p>0.05).ConclusionsThe present study demonstrated a lack of genotype-phenotype correlation of the demographic and clinical traits to CYP1B1 mutations in PCG at presentation. However, the susceptibility of these mutations to the long-term progression of these traits are yet to be deciphered. ; Department of Science and Technology, Government of India ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Univ Estadual Campinas, Ctr Mol Biol & Genet Engn, Campinas, SP, Brazil ; LV Prasad Eye Inst, Jasti V Ramanamma Childrens Eye Care Ctr, Hyderabad, Andhra Pradesh, India ; Universidade Federal de São Paulo, Dept Ophthalmol, São Paulo, SP, Brazil ; LV Prasad Eye Inst, Ctr Clin Epidemiol & Biostat, Hyderabad, Andhra Pradesh, India ; LV Prasad Eye Inst, Kallam Anji Reddy Mol Genet Lab, Hyderabad, Andhra Pradesh, India ; Univ Estadual Campinas, Fac Med Sci, Dept Ophthalmol, Campinas, SP, Brazil ; Univ São Paulo, Sch Med, Dept Ophthalmol, São Paulo, SP, Brazil ; Univ São Paulo, Ribeirao Preto Med Sch, Dept Ophthalmol, BR-14049 Ribeirao Preto, SP, Brazil ; Univ Connecticut, Ctr Hlth, Dept Surg, Surg Res Ctr,Mol Ophthalm Genet Lab, Farmington, CT USA ; Irmandade Santa Casa de Misericordia São Paulo, Sch Med Sci, Dept Ophthalmol, São Paulo, SP, Brazil ; Univ São Paulo, Ribeirao Preto Med Sch, Dept Genet, Ribeirao Preto, SP, Brazil ; Universidade Federal de São Paulo, Dept Ophthalmol, São Paulo, SP, Brazil ; Department of Science and Technology, Government of India: DST/INT/BRAZIL/RPO-01/2008 ; CNPq: EU475687/20094 ; Web of Science