38 resultados para Random regression models
Resumo:
Purpose When consumers buy online, they are often confronted with consumer reviews. A negative consumer review on an online shopping website may keep consumers from buying the product. Therefore, negative online consumer reviews are a serious problem for brands. This paper aims to investigate the effects of different response options to a negative consumer review. Design/methodology/approach In an online experiment of 446 participants different response options towards a negative consumer review on an online shopping website are examined. The experimental data is analysed with simple linear regression models using product purchase intentions as the outcome variable. Findings The results indicate that a positive customer review counteracts a negative consumer review more effectively than a positive brand response, whereas brand strength moderates this relationship. Including a reference to an independent, trusted source in a brand or a customer response is only a limited strategy for increasing the effectiveness of a response. Research limitations/implications Additional research in other product categories and with other subjects than students is suggested to validate the findings. In future research, multiple degrees of the phrasing’s strength of the reference could be used. Practical implications Assuming high quality products, brands should encourage their customers to write reviews. Strong brands can also reassure consumers by responding whereas weak brands cannot. Originality/value This research contributes to the online consumer reviews literature with new insights about the role of brand strength and referencing to an independent, trusted source.
Resumo:
Contagious bovine pleuropneumonia (CBPP) is an economically important disease in most of sub-Saharan Africa. A conjoint analysis and ordered probit regression models were used to measure the preferences of farmers for CBPP vaccine and vaccination attributes. This was with regard to inclusion or not of an indicator in the vaccine, vaccine safety, vaccine stability as well as frequency of vaccination, vaccine administration and the nature of vaccination. The analysis was carried out in 190 households in Narok District of Kenya between October and December 2006 using structured questionnaires, 16 attribute profiles and a five-point Likert scale. The factors affecting attribute valuation were shown through a two-way location interaction model. The study also demonstrated the relative importance (RI) of attributes and the compensation value of attribute levels. The attribute coefficient estimates showed that farmers prefer a vaccine that has an indicator, is 100% safe and is administered by the government (p<0.0001). The preferences for the vaccine attributes were consistent with expectations. Preferences for stability, frequency of vaccination and nature of vaccination differed amongst farmers (p>0.05). While inclusion of an indicator in the vaccine was the most important attribute (RI=43.6%), price was the least important (RI=0.5%). Of the 22 household factors considered, 15 affected attribute valuation. The compensation values for a change from non inclusion to inclusion of an indicator, 95-100% safety, 2h to greater than 2h stability and from compulsory to elective vaccination were positive while those for a change from annual to biannual vaccination and from government to private administration were negative. The study concluded that the farmers in Narok District had preferences for specific vaccine and vaccination attributes. These preferences were conditioned by various household characteristics and disease risk factors. On average the farmers would need to be compensated or persuaded to accept biannual and private vaccination against CBPP. There is need for consideration of farmer preferences for vaccine attribute levels during vaccine formulations and farmer preferences for vaccination attribute levels when designing delivery of vaccines.
Resumo:
The present study evaluated the effects of climate variability on maize (Zea mays L.) yield in Sri Lanka at different spatial scales. Biophysical data from the Department of Agriculture (DOA) in Sri Lanka for six major maize-growing districts (Ampara, Anuradhapura, Badulla, Hambantota, Moneragala, and Kurunegala) from 1990 to 2010 were analyzed. Simple linear regression models were fitted to observed climate data and detrended maize yield to identify significant correlations. The correlation between first differences of maize yield and climate (r) was further investigated at 0.50° grid scale using interpolated climate data. After 2003, significantly positive (p < 0.01) yield trends varied from 154 kg ha–1 yr–1 to 360 kg ha–1 yr–1. The correlations between maize yield and climate reported that five out of six districts were significant at 10% level. Rainfall had a consistent significant (p < 0.10) positive impact on maize yield in Anuradhapura, Hambantota, and Moneragala, where seasonal total rainfall together with high temperature (“hot-dry”) are the key limitations. Further, the seasonal mean temperature had a negative impact on maize yield in Moneragala (“hot-dry”), the only district that showed high temperatures. Badulla district (“cold-dry”) reported a significant (r = 0.38) positive correlation with mean seasonal temperature, indicating higher potential toward increasing temperatures. Each 1°C rise in seasonal mean temperature reduced maize yield by about 5% from 1990 to 2010. Overall, there was a reasonable correlation between district maize yield and seasonal climate in most of the districts within the maize belt of Sri Lanka.
Resumo:
Background: Dietary intervention studies suggest that flavan-3-ol intake can improve vascular function and reduce the risk of cardiovascular diseases (CVD). However, results from prospective studies failed to show a consistent beneficial effect. Objective: To investigate associations between flavan-3-ol intake and CVD risk in the Norfolk arm of the European Prospective Investigation into Cancer and Nutrition (EPIC-Norfolk). Design: Data was available from 24,885 (11,252 men; 13,633 women) participants, recruited between 1993 and 1997 into the EPIC-Norfolk study. Flavan-3-ol intake was assessed using 7-day food diaries and the FLAVIOLA Flavanol Food Composition database. Missing data for plasma cholesterol and vitamin C were imputed using multiple imputation. Associations between flavan-3-ol intake and blood pressure at baseline were determined using linear regression models. Associations with CVD risk were estimated using Cox regression analyses. Results: Median intake of total flavan-3-ols was 1034 mg/d (range: 0 – 8531 mg/d) for men and 970 mg/d (0 – 6695 mg/d) for women, median intake of flavan-3-ol monomers was 233 mg/d (0 – 3248 mg/d) for men and 217 (0 – 2712 mg/d) for women. There were no consistent associations between flavan-3-ol monomer intake and baseline systolic and diastolic blood pressure (BP). After 286,147 person-years of follow up, there were 8463 cardio-vascular events and 1987 CVD related deaths; no consistent association between flavan-3-ol intake and CVD risk (HR 0.93, 95% CI:0.87; 1.00; Q1 vs Q5) or mortality was observed (HR 0.93, 95% CI: 0.84; 1.04). Conclusions: Flavan-3-ol intake in EPIC-Norfolk is not sufficient to achieve a statistically significant reduction in CVD risk.
Resumo:
Risk variants of the fat-mass and obesity-associated (FTO) gene have been associated with increased obesity. However, the evidence for associations between FTO genotype and macronutrients intake has not been reviewed systematically. Our aim was to evaluate potential associations between FTO genotype and intakes of total energy, fat, carbohydrate and protein. We undertook a systematic literature search in Medline, Scopus, EMBASE and Cochrane of associations between macronutrients intake and FTO genotype in adults. Beta coefficients and confidence intervals were used for per-allele comparisons. Random-effects models assessed the pooled effect sizes. We identified 56 eligible studies reporting on 213 173 adults. For each copy of the FTO risk allele, individuals reported 6.46 kcal/day (95% CI: 10.76, 2.16) lower total energy intake (P=0.003). Total fat (P=0.028) and protein (P=0.006), but not carbohydrate intakes, were higher in those carrying the FTO risk allele. After adjustment for body weight, total energy intakes remained significantly lower in individuals with the FTO risk genotype (P=0.028). The FTO risk allele is associated with a lower reported total energy intake and with altered patterns of macronutrients intake. Although significant, these differences are small and further research is needed to determine whether the associations are independent of dietary misreporting.
Resumo:
The transfer of Cd and Zn from soils amended with sewage sludge was followed through a food chain consisting of wheat, aphids and the predator Coccinella septempunctata. Multiple regression models were generated to predict the concentrations of Cd and Zn in C. septempunctata. No significant model could be generated for Cd, indicting that the concentration of this metal was maintained within relatively narrow limits. A model predicting 64% of the variability in the Zn concentration of C. septempunctata was generated from of the concentration of Zn in the diet, time and rate of Zn consumption. The results suggest that decreasing the rate of food consumption is an effective mechanism to prevent the accumulation of Zn and that the availability of Zn in the aphid prey increased with the concentration in the aphids. The results emphasise the importance of using ecologically relevant food chains and exposure pathways during ecotoxicological studies.
Resumo:
Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood functions. Several methods that permit exact, or close to exact, simulation from the posterior distribution have recently been developed. However, estimating the evidence and Bayes’ factors for these models remains challenging in general. This paper describes new random weight importance sampling and sequential Monte Carlo methods for estimating BFs that use simulation to circumvent the evaluation of the intractable likelihood, and compares them to existing methods. In some cases we observe an advantage in the use of biased weight estimates. An initial investigation into the theoretical and empirical properties of this class of methods is presented. Some support for the use of biased estimates is presented, but we advocate caution in the use of such estimates.
Resumo:
Purpose – The purpose of this paper is to investigate the effect of the crisis on the pricing of asset quality attributes. This paper uses sales transaction data to examine whether flight from risk phenomena took place in the US office market during the financial crisis of 2007-2009. Design/methodology/approach – Hedonic regression procedures are used to test the hypothesis that the spread between the pricing of low-quality and high-quality characteristics increased during the crisis period compared to the pre-crisis period. Findings – The results of the hedonic regression models suggest that the price spread between Class A and other properties grew significantly during the downturn. Research limitations/implications – Our results are consistent with the hypothesis of an increased price spread following a market downturn between Class A and non-Class A offices. The evidence suggests that the relationships between the returns on Class A and non-Class A assets changed during the period of market stress or crisis. Practical implications – These findings have implications for real estate portfolio construction. If regime switches can be predicted and/or responded to rapidly, portfolios may be rebalanced. In crisis periods, portfolios might be reweighted towards Class A properties and in positive market periods, the reweighting would be towards non-Class A assets. Social implications – The global financial crisis has demonstrated that real estate markets play a crucial role in modern economies and that negative developments in these markets have the potential to spillover and create contagion for the larger economy, thereby affecting jobs, incomes and ultimately people’s livelihoods. Originality/value – This is one of the first studies that address the flight to quality phenomenon in commercial real estate markets during periods of financial crisis and market turmoil.