We examine how, why and which consumers infer company mask policies to be politically motivated, impacting their purchase interest. Five studies (N = 3,438) demonstrate that consumers use a company’s mask policy as a proxy for its underlying political ideology but interpret the political...

With the rapid growth of omnichannel retailing, digitally native retailers are increasingly opening physical stores. A critical issue for many digitally native retailers is to estimate the causal effect of a new store opening on their online sales. To assess the causal effect, a randomized...

This is the first large-scale academic study evaluating the impact of COVID-19 on the accounting profession. We find that physical restrictions and economic hardships resulting from COVID-19 impeded accountants’ productivity, ability to perform their work, ability to maintain relationships...

As COVID-19 ravaged the US in the first quarter of 2020, the US lacked a uniform mandatory policy for containing its spread. Governors facing enormous opposing pressures from businesses and medical professionals adopted various policies, especially lockdowns. The authors statistically analyze...

We study the impact of Zillow’s Zestimate on housing market outcomes and how the impact differs across socio-economic segments. Zestimate is produced by a Machine Learning algorithm using large amounts of data and aims to predict a home’s market value at any time. Zestimate can potentially...

This paper is a theoretical review of the impact of recession to the marketing performance of the companies across the global market. The impact is determined qualitatively thru the examination of published papers. In the succeeding pages, the significant role of marketing is deliberately...

In empirical regression analysis, the existence of high multicollinearity suggests that predictors may provide redundant information and cause a reduction in statistics power. Meanwhile, dropping correlated variables may result in mis-specified models with biased parameters. Unlike previous...

We develop a testing methodology that can be used to predict the performance of email marketing campaigns in real time. We propose a split-hazard model that makes use of a time transformation (a concept we call virtual time) that allows for the estimation of straightforward parametric hazard...