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The purpose of the study is to examine how utilizing volunteered data influences the response and unsubscribe rates of e-mail marketing to consumers.

In three longitudinal field experiments conducted among 1,864 applicants of a higher education institution, the study compares customized marketing e-mails based on volunteered consumer data to e-mails that are personalized based on observed consumer data and to control e-mails that are not tailored by the marketer at all.

The results indicate that marketers should make consumers active participants in the communication process, as response rates are higher in those e-mails where volunteered data are utilized. However, the unsubscribe rate is the highest in customized e-mails.

The authors demonstrate that e-mails displaying empowering aspects influence consumers' behaviors and lead to outcomes that mostly outperform non-empowered e-mails.

Compared to other forms of interactive marketing, e-mail has lagged behind in both popularity and customer-friendly implementation. However, it has the potential to succeed if marketers pay more attention to consumer empowerment. As over 306 billion e-mails are sent worldwide daily and 75% of marketers use e-mail when contacting customers, the increase in response rates can have a significant influence on their returns.

Unlike prior research the focus was on the process of tailoring, this perspective supports customer advocacy and emphasizes consumers' important role in creating engaging, empowering e-mail marketing communication.

This study aims to analyse the consumption inequality between farm and non-farm households in rural Vietnam, using the data from the 2016 Vietnam household living standards survey.

The present paper applies the “recentered influence functions (RIF)” in “Oaxaca-Blinder (OB)” type decomposition as proposed by Firpo et al. (2018) to allow for the flexible distribution of the outcome variables and the non-randomness of non-farm employment that violates the classical linearity assumption.

Non-farm households have significantly higher per capita consumption expenditure than farm households for the entire distribution. The gap in expenditure is large at low percentiles and narrowing with higher percentiles. At 10th percentile, the gap is estimated at 27.1%, but it is decreasing to 11.1% at 90th percentile. Most of the gaps are explained by the differences in the observed characteristics between farm and non-farm households such as ethnicity, education, income, internal transmittances and household composition. Non-farm households are endowed with more productive factors that result in higher per capita consumption expenditure.

Gaps in ethnicity and education are found to be key predictors of the inequality in consumption expenditures between farm and non-farm households, then, government policies that are aimed at increasing access to non-farm employment and education for ethnic minorities and for rural poor households are pathways to improve rural household welfare and hence reduce inequality.