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Managing a necessary evil: Can payment methods reduce product returns?
•Paying before delivery reduces return rates compared with paying after delivery.•Payment timing does not harm future purchase intentions.•The return-reducing effect of payment timing only holds when shipping is free.•Paying before delivery fosters psychological ownership and perceived return effort.•Retailers can encourage payment before delivery (e.g., through discounts).
Product returns represent a serious challenge for online retailers and environmental protection alike. Taking a fresh perspective on effective product return management options, the current study proposes payment methods as a potential driver of product returns. By combining field data from an online fashion and accessory retailer with a laboratory experiment, the authors show that payment before product delivery (e.g., direct debit, PayPal) reduces customers’ product returns compared with payment after delivery (e.g., invoicing, Prime Wardrobe). Psychological ownership and perceived return effort represent the underlying mechanisms that determine the effects of these payment methods on return behavior: If customers pay before they receive the product, they experience stronger feelings of psychological ownership and perceive higher effort to return it. However, this effect only occurs when retailers offer free shipping. Considering that small reductions in return rates can have considerable effects on retailers’ bottom lines and the environment, a tactical approach to managing online payment methods suggests immense potential for sustainable online retailing.
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Journal Article
Evaluating the utility of data integration with synthetic data and statistical matching
Data integration enhances dataset utility but raises privacy concerns due to increased disclosure risks. Synthetic data offers a potential solution, though its role in data integration has not been thoroughly investigated. This study assesses synthetic data integration by evaluating the impact of varying common variables during statistical matching and exploring synthetic-real dataset combinations in donor-recipient settings. We used data from the Korean Genome and Epidemiology Study (KoGES) cohort, with the full dataset as the donor and one-quarter of the subjects as the recipient. Multiple synthetic datasets were generated from both datasets, with varying sets of common variables. Statistical matching was conducted using the nearest-neighbor hotdeck method. Data utility was evaluated using confidence interval overlap measures in the hazard ratio estimates under clinical scenarios to predict diabetes onset. When both donor and recipient data were synthetic, the all-available matched data generally outperformed other matching conditions. However, clinically relevant matching variables occasionally showed equivalent performances. The synthetic data showed comparable model accuracy to real data, although further investigation is warranted to understand the performance differences. Statistically matched synthetic data offers utility comparable to real data, providing a potential approach for reducing privacy risks while maintaining data utility.
Journal Article
The role of dairy consumption in the relationship between wealth and early life physical growth in India: evidence from multiple national surveys
Introduction
Prevalence of undernutrition continues to be high in India and low household wealth is consistently associated with undernutrition. This association could be modified through improved dietary intake, including dairy consumption in young children. The beneficial effect of dairy on child growth has not been explored at a national level in India. The present analyses aimed to evaluate the direct and indirect (modifying association of household level per adult female equivalent milk and milk product consumption) associations between household wealth index on height for age (HAZ) and weight for age (WAZ) in 6-59 months old Indian children using data from of nationally representative surveys.
Methods
Two triangulated datasets of two rounds of National Family Health Survey, (NFHS-3 and 4) and food expenditure (National Sample Survey, NSS61 and 68) surveys, were produced by statistical matching of households using Non-Iterative Bayesian Approach to Statistical Matching technique. A Directed Acyclic Graph was constructed to map the pathways in the relationship of household wealth with HAZ and WAZ based on literature. The direct association of wealth index and its indirect association through per adult female equivalent dairy consumption on HAZ and WAZ were estimated using separate path models for each round of the surveys.
Results
Wealth index was directly associated with HAZ and WAZ in both the rounds, but the association decreased from NFHS-3 (β
HAZ
: 0.145; 95% CI: 0.129, 0.16) to NFHS-4 (β
HAZ
: 0.102; 95%CI: 0.093, 0.11). Adult female equivalent milk intake (increase of 10gm/day) was associated with higher HAZ (β_NFHS-3=0.001;95% CI: 0, 0.002; β_NFHS-4=0.002;95% CI: 0.002, 0.003) but had no association with WAZ. The indirect association of wealth with HAZ through dairy consumption was 2-fold higher in NFHS-4 compared to NFHS-3.
Conclusions
The analysis of triangulated survey data shows that household level per- adult female equivalent dairy consumption positively modified the association between wealth index and HAZ, suggesting that regular inclusion of milk and milk products in the diets of children from households across all wealth quintiles could improve linear growth in this population.
Journal Article
Assessing the Effectiveness of Student Advice Recommender Agent (SARA): the Case of Automated Personalized Feedback
Greer and Mark’s (
2016
) paper suggested and reviewed different methods for evaluating the effectiveness of intelligent tutoring systems such as Propensity score matching. The current study aimed at assessing the effectiveness of automated personalized feedback intervention implemented via the Student Advice Recommender Agent (SARA) in a first-year biology class by means of statistical matching and by reviewing and comparing four different statistical matching methods (i.e., exact matching, nearest neighbor matching using the Mahalanobis distance, propensity score matching, and coarsened exact matching). Data from 1026 (73% female and 27% male) students who took a first-year biology course at a Western Canadian university were used. Two different measures for balance assessment of the matched data (i.e., % of balance improvement and standardized bias) were used to choose the best performing statistical matching method. Nearest neighbor matching using the Mahalanobis distance was found to be the most appropriate method for this study and results showed a statistically significant but small treatment effect for the group who received personalized feedback. Research and practical considerations were discussed and suggestions for future research are provided.
Journal Article
Applied usage and performance of statistical matching in bibliometrics: The comparison of milestone and regular papers with multiple measurements of disruptiveness as an empirical example
Controlling for confounding factors is one of the central aspects of quantitative research. Although methods such as linear regression models are common, their results can be misleading under certain conditions. We demonstrate how statistical matching can be utilized as an alternative that enables the inspection of post-matching balancing. This contribution serves as an empirical demonstration of matching in bibliometrics and discusses the advantages and potential pitfalls. We propose matching as an easy-to-use approach in bibliometrics to estimate effects and remove bias. To exemplify matching, we use data about papers published in
and a selection classified as milestone papers. We analyze whether milestone papers score higher in terms of a proposed class of indicators for measuring disruptiveness than nonmilestone papers. We consider disruption indicators DI1, DI5, DI1n, DI5n, and DEP and test which of the disruption indicators
performs best, based on the assumption that milestone papers should have higher disruption indicator values than nonmilestone papers. Four matching algorithms (propensity score matching (PSM), coarsened exact matching (CEM), entropy balancing (EB), and inverse probability weighting (IPTW)) are compared. We find that CEM and EB perform best regarding covariate balancing and DI5 and DEP performing well to evaluate disruptiveness of published papers.
Journal Article
How community forest management performs when REDD+ payments fail
The reduced emissions in deforestation and degradation (REDD+) initiative uses payments for ecosystem services as incentives for developing countries to manage and protect their forests. REDD+ initiatives also prioritize social (and environmental) co-benefits aimed at improving the livelihoods of communities that are dependent on forests. Despite the incorporation of co-benefits into REDD+ goals, carbon sequestration remains the primary metric for which countries can receive payments from REDD+, but after more than 10 years of REDD+, many site-specific programs have failed to complete the carbon verification process. Here, we examine whether the REDD+ social co-benefits alone are sufficient to have slowed deforestation in the absence of carbon payments on Pemba, Tanzania. Using satellite imagery (Landsat archive), we quantified forest cover change for the period before (2001–2010) and after (2010–2018) the launch in 2010–2011 of Pemba island’s REDD+ readiness project. We then compared rates of forest cover change between shehia (administrative units) that were part of REDD+ readiness intervention and those that were not, adjusting for confounding variables and the non-random selection of REDD+ shehia with a statistical matching procedure. Despite considerable variation in forest outcomes among shehia , the associated co-benefits with the Pemba REDD+ project had no discernible effect on forest cover change. Likewise, we did not detect an effect of socioecological covariates on forest cover change across all shehia , though island-wide human population growth since 2012 may have played a role. These findings are unsurprising given the failure to secure carbon payments on Pemba and indicate that co-benefits alone are insufficient to reduce deforestation. We conclude that better oversight of all-involved parties is needed to ensure that REDD+ interventions satisfactorily conclude the process of securing a mechanism for carbon payments, if slowing deforestation is to be achieved.
Journal Article
Generating Control Groups for Organ Impairment Studies: A Case‐Study Comparing Statistical and Population Pharmacokinetic‐Based Matching Approaches
A common challenge in conducting phase 1 studies that assess the impact of organ impairment on the pharmacokinetics of a drug is the recruitment of a demographically matched control group. The work presented here evaluated alternative approaches for generating control groups in these studies. Available phase 1 data from the upadacitinib and elagolix clinical programs were leveraged as case studies. A statistical matching approach and a population pharmacokinetic model‐based approach were evaluated retrospectively for these programs' hepatic and renal impairment clinical studies. Geometric mean ratios of logarithmically transformed Cmax and AUCinf were used to compare exposure in organ impairment groups to respective matched or virtual control groups. In the statistical matching approach, the genetic matching algorithm using Mahalanobis distance showed that external control groups were adequately demographically balanced across all impairment groups of the study except for age. A 3:1 k‐match approach minimized the prediction error between matched and reference in‐study results for both case studies, resulting in differences in geometric mean ratios ranging from −19% to 3% and −27% to 40% for upadacitinib and elagolix, respectively, compared to in‐study controls. Similarly, the population pharmacokinetic approach used models developed from phase 1 data in healthy participants and found that the results were generally comparable to the in‐study results, with differences in geometric mean ratios ranging from −30% to 17% and −24% to 41% for upadacitinib and elagolix, respectively. These analyses demonstrate that both approaches may be viable alternatives to assess the impact of organ impairment on pharmacokinetics.
Journal Article
A supervised record linkage approach for anomaly detection in insurance assets granular data
Nowadays public authorities and research organizations compile and disseminate statistics based on granular data with rapidly increasing volumes. Efficient statistical methods for data quality management are essential to ensure high quality in the produced statistics and consequently in the policy decisions. In order to guarantee smooth data quality checks, such methods need to be automatic, especially during situations of constraints on human resources. This paper deals with an issue of anomaly detection in very granular insurance data which are periodically used by central banks to produce European statistics. Since 2016, insurance corporations have been reporting granular assets data in Solvency II templates on a quarterly basis. Assets are uniquely identified by codes that by regulation must be kept stable and consistent over time; nevertheless, due to reporting errors, unexpected changes in these codes may occur, leading to inconsistencies when compiling statistics and analysing balance sheets. The current work addresses the data quality issue as a record linkage problem and proposes different supervised classification models to detect anomalies in the data. Test results for the selected random forest model provide excellent performance metrics, robust to different periods and types of assets.
Journal Article
Using an integrated social-ecological analysis to detect effects of household herding practices on indicators of rangeland resilience in Mongolia
Temperate grasslands, including those of northern Eurasia, are among the most imperiled ecosystems on Earth. Eighty percent of Mongolia's land area is rangeland, where interacting climate, land-use and changes in governance threaten the sustainability of Mongolia's rangelands and pastoral culture. Particularly concerning are the potential ecological impacts of changing pastoral grazing practices-namely declining use of grazing reserves and pastoral mobility. However, like other grazing practices globally, there have been no empirical studies to evaluate the effects of specific Mongolian grazing practices on ecological function at a management scale. We collected data on the grazing practices of 130 pastoral households across four ecological zones and sampled ecological conditions in their winter pastures. We used a novel social-ecological analysis process to (1) develop integrated, holistic indicators of ecological function using exploratory and confirmatory factor analysis, and (2) assess the effects of individual grazing practices on these indicators using statistical matching to control for confounding management and contextual factors. We identified two latent factors related to ecological and pastoral resilience: Factor 1 represents resource retention and soil stability and Factor 2 represents species richness and functional diversity. Using these two factors as response variables, we found that the values of both resilience factors were higher in pastures where households made fall or winter otor migrations or set aside grazing reserves. This study provides the first management-scale empirical test of the ecological response to specific grazing practices in Mongolia, using an approach that can be applied in other rangeland systems. Our findings highlight the importance to ecological and pastoral resilience of supporting traditional pastoral practices of mobility and grazing reserves, while also controlling stocking densities, increasing rangeland monitoring, and ensuring equitable access to state-designated emergency grazing reserves at local, regional, and national levels.
Journal Article