The Impact of Cause-Related Marketing on Millennials’ Product Attitudes and Purchase Intentions

This study, using scenarios, examined the impact of two kinds of cause-related marketing (CRM) efforts (a traditional donation of a portion of sales to a related cause and a more strategic one-for-one donation of donating a product to a related cause when that product was purchased) on millennials’ (those born between 1982 and 2000) attitudes and purchase intentions for four different consumer product categories. The four different consumer product categories selected included a specialty good (laptop), a shopping good (hat), a convenience good (bottled water), and a service (food restaurant). Given the importance of social media to millennials, this research also examined the role of social media on CRM awareness. While millennials had relatively low awareness of CRM campaigns, there was a positive correlation between social media use and CRM awareness. Additionally, CRM efforts may not work for all products as there was no impact on attitude or purchase intention for the product category of laptops. Additionally, the positive attitudes created by marketers’ CRM efforts will not always translate to increased purchase intentions. The use of a strategic one-for-one CRM effort though had a greater impact, specifically for products that deal with needed fundamentals, such as food and water.     

Household Income, Termination Risk and Mortgage Pricing

The premium embedded in home mortgage loans to compensate investors for their exposure to prepayment risk is a significant component of the cost of home mortgage lending. Moreover, there is some reason to believe that prepayment risk may be lower for loans to lower-income housing borrowers, especially those that are first-time home owners. If so, investor recognition of this advantage should facilitate greater willingness to acquire portfolios of lower-income housing loans, and encourage more competitive pricing in this segment of the market. This study investigates the possibility of differential mortgage prepayment behavior between lower-income home owners and non-low income home owners. The investigation relies on samples of the American Housing Survey spanning ten years of experience from 1985 to 1995. We find no significant difference between the termination or refinancing behavior of non-low income and low-income households. This result is robust to a number of alternative specifications such as restricting the low-income test group to non-moving households and to first-time owners. The same conclusions are derived from both aggregate prepayment rates and from analysis of individual household prepayment behavior.     

The effect of uncertainty and instability on dynamic economic models with an application to cournot oligopoly

Consider a dynamic discrete-time economic model in which a state-dependent payoff is earned during each period. We give conditions which ensure that a mean preserving increase in the riskiness of the model's parameters increases (or decreases) the expected payoff earned during n periods.     

Linkages between Regulated and Unregulated Markets: the Case of Milk Supply in Kenya

Linkages between the regulated and unregulated dairy markets in Kenya were examined using an econometric model of the fluid milk intake for eight processing plants. Counter-intuitive results were obtained: an increase in the regulated price was significant in decreasing intake in the regulated market, indicating that a price increase in the regulated market also increased price and quantity supplied in the unregulated market. Lagged rainfall was a proxy for available feed and was highly significant in explaining milk intake in the regulated market.     

A customized market response model: Development,estimation, and empirical testing

A customized, stepwise, log-linear, distributed lag, restricted market response model is proposed to estimate the effects of various elements of promotion expenditures on sales in the presence of potentially significant effects due to trend and/or seasonality when using time-series data. As distinct from standardized software packages, the customization offers management several benefits: (a) an (optional) imposition of prior restrictions on the directions of the coefficient variables; (b) an empirical determination of the lag structure for selected variables; (c) the detrending of the data to allow for the assessment of incremental marketing mix effects above trend; and (d) a simplified sensitivity analysis. The model is empirically tested and validated using sales data for a brand where the impact of several marketing mix variables is estimated and investigated via policy simulations. A comparison of these results with those obtained from a corresponding unrestricted model illustrates the advantages of this approach. Finally, the limitations of this procedure and directions for future research are discussed.