Financing an online newsvendor with considering the impact of advertising strategy

This study examines the relationship between advertising and financing decisions in an online supply chain consisting of an e-platform and a capital-constrained retailer. The e-platform is the leader in a Stackelberg game, and the interaction is modelled in two advertising scenarios. The results indicate that advertising can reduce risk and is always beneficial, with an e-platform willing to support the retailer only when the former decides on the advertising level. When providing both advertising and financing services, the e-platform gains the ability to directly regulate the retailer's ordering decisions, thereby increasing its strategic flexibility.</p

Logistic regression models for the association between planned mode of delivery and method of feeding^a.

a<p> <i>Data shown are odds ratio (95% confidence interval) and number (percentage);</i></p>b<p> <i>Odds ratio expresses the likelihood that mothers will exclusively breastfeed their babies before discharge in the planned CDMR group compared to that in the planned VD group;</i></p>c<p> <i>Odds ratio expresses the likelihood that mothers will formula feed their babies before discharge in the planned CDMR group compared to that in the planned VD group;</i></p>d<p> <i>Adjusted for maternal age at delivery, BMI, gestation, infant birthweight, year of delivery, occupation, educational level, delivery hospital level, infant sex, mother's hospital stay before discharge, and location of residence or site of delivery or both.</i></p

Characteristics of US children and their parents.

1<p>Statistics are reported either as means with 95% Confidence Interval (CI) for continuous variables or percentages with their 95% Confidence Interval (CI) for categorical variables.</p>2<p>Chi-square tests were used to test for between-group differences for categorical variables; t-tests were used for continuous variables.</p><p>Source: Medical Expenditure Panel Survey, 2006–2007.</p

Percent agreement (%) and weighted kappa coefficients between parent and children BMI quintiles by dyad type and characteristics¹.

1<p>For children, age- and sex-specific quintiles of BMI were used. For parents, sex-specific BMI quintiles were used. Weighted kappa values can be interpreted as follows: κ<0.20 =  poor agreement, κ between 0.20–0.40 =  fair agreement, κ between 0.40–0.60 =  moderate agreement, κ between 0.60–0.80 =  good agreement, and κ≥0.80 =  very good agreement.</p>2<p>The expected percent of agreement is 20%.</p>3<p>SEM are reported in parentheses and were obtained through Fay's balanced repeated replication (BRR) method of estimation.</p>4<p>Weighted kappa coefficients were calculated using the Cicchetti-Allison weight matrix (see text). All point estimates have taken MEPS’ sampling design into account. ⁵ NH, non-Hispanic;</p>5<p>MVPA, moderate-to-vigorous physical activity.</p><p>Source: Medical Expenditure Panel Survey, 2006–2007.</p

The data processing to create the cohort of planned CDMR and planned VD.

<p>The data processing to create the cohort of planned CDMR and planned VD.</p

Logistic regression models for the association between actual route of delivery and method of breastfeeding^a.

a<p> <i>VD: vaginal delivery; CDMR: cesarean delivery on maternal request; CD: cesarean delivery;</i></p>b<p> <i>Odds ratio expresses the likelihood that mothers will exclusively breastfeed their babies before discharge compared to that in the reference group;</i></p>c<p> <i>Odds ratio expresses the likelihood that mothers will formula feed their babies before discharge compared to that in the reference group;</i></p>d<p> <i>Adjusted for maternal age at delivery, BMI, gestation, infant birthweight, year of delivery, location of residence, site of delivery, occupation, education level, delivery hospital level, infant sex, and mother's hospital stay before discharge.</i></p

Definition of planned CDMR and planned VD (adapted from the paper published by Zhang et al.) [4].

<p>Definition of planned CDMR and planned VD (adapted from the paper published by Zhang et al.) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037336#pone.0037336-Zhang1" target="_blank">[4]</a>.</p

The possible pathways of planned CDMR and planned VD.

<p>The possible pathways of planned CDMR and planned VD.</p

Association between child’s obesity and parents’ obesity status, stratified by child and parental characteristics as indicated¹.

1<p>Results are reported based on logistic regression models adjusted for child sex and age, household income, and parental age, education, race/ethnicity, and physical activity. The reference group was children whose parents were neither obese.</p>2<p>Obese was defined as BMI ≥30 kg/m².</p>3<p>The odds ratio (OR)for child obesity was 2.1, comparing children for whom only their father was obese to those whose father and mother were both not obese.</p>4<p>NH, non-Hispanic; ⁵ MVPA, moderate-to-vigorous physical activity.</p><p>Source: Medical Expenditure Panel Survey, 2006–2007.</p

Pearson partial correlation coefficients (r)¹ between parent and child BMI measures by dyad type and various socio-demographic and socioeconomic characteristics.

1<p>The r was adjusted for child's age and parent's age, ethnicity, education, household income, marital status, and physical activity. In the stratified analysis, partial correlation coefficients were calculated adjusting for the same variables except the stratification variable. For example, for the father-son correlation, we controlled for child age and father's characteristics as described above. For the father-son correlation stratified by household income, we controlled child age and father's characteristics with exception of household income.</p>2<p>SEM: standard error of measurement.</p>3–7<p>Significantly different from the reference group (p<0.05), based on the interaction terms of parent BMI standard score and the strata of interest.</p><p>NH: non-Hispanic; ref: reference group.</p><p>Source: Medical Expenditure Panel Survey, 2006–2007.</p