A data mining framework for targeted category promotions

This research presents a new approach to derive recommendations for segment-specific, targeted marketing campaigns on the product category level. The proposed methodological framework serves as a decision support tool for customer relationship managers or direct marketers to select attractive product categories for their target marketing efforts, such as segment-specific rewards in loyalty programs, cross-merchandising activities, targeted direct mailings, customized supplements in catalogues, or customized promotions. The proposed methodology requires customers’ multi-category purchase histories as input data and proceeds in a stepwise manner. It combines various data compression techniques and integrates an optimization approach which suggests candidate product categories for segment-specific targeted marketing such that cross-category spillover effects for non-promoted categories are maximized. To demonstrate the empirical performance of our proposed procedure, we examine the transactions from a real-world loyalty program of a major grocery retailer. A simple scenario-based analysis using promotion responsiveness reported in previous empirical studies and prior experience by domain experts suggests that targeted promotions might boost profitability between 15 % and 128 % relative to an undifferentiated standard campaign.     

Cross-validating fit and predictive accuracy of nonlinear quantile regressions

The paper proposes a cross-validation method to address the question of specification search in a multiple nonlinear quantile regression framework. Linear parametric, spline-based partially linear and kernel-based fully nonparametric specifications are contrasted as competitors using cross-validated weighted L ₁-norm based goodness-of-fit and prediction error criteria. The aim is to provide a fair comparison with respect to estimation accuracy and/or predictive ability for different semi- and nonparametric specification paradigms. This is challenging as the model dimension cannot be estimated for all competitors and the meta-parameters such as kernel bandwidths, spline knot numbers and polynomial degrees are difficult to compare. General issues of specification comparability and automated data-driven meta-parameter selection are discussed. The proposed method further allows us to assess the balance between fit and model complexity. An extensive Monte Carlo study and an application to a well-known data set provide empirical illustration of the method.     

Loss prediction in a linear model under a linear constraint

Loss reserving is an important subject of actuarial mathematics. It aims at the prediction of future losses caused by claims which have incurred in the past but have not yet been closed. The problem of predicting such losses is particularly important in liability insurance. In the present paper we study conjoint prediction of paid and incurred losses in a linear model with a linear constraint which is intended to reduce the gap between the predictors of ultimate paid and incurred losses. We thus present an application to actuarial mathematics of the general result established by Kloberdanz and Schmidt (AStA Adv. Stat. Anal. 92:207–215, 2008).     

Social ties and subjective performance evaluations: an empirical investigation

We empirically investigate possible distortions in subjective performance evaluations. A key hypothesis is that evaluations are more upward biased the closer the social ties between supervisor and appraised employee. We test this hypothesis with a company data set from a call center organization which contains not only subjective assessments but also several more objective measures of performance. Controlling for these performance measures, we find strong evidence that evaluations are upwards biased in smaller teams and some evidence that supervisors give better ratings to employees they themselves have evaluated before.     

The impact of different fit dimensions on spillover effects in brand alliances

Brand alliances represent a popular business strategy in many industries, because firms hope to evoke positive consumer evaluations of both the alliance’s product and the partner brands. However, extant research offers mixed findings regarding the effects of a brand alliance on its partner brands (i.e., spillover effects). In response, this study separates spillover effects into the effects of the alliance product on the partner brands (brand alliance effects) and the effects between partner brands (brand contrast effects), while also noting the potential moderating impact of perceived attitude- and product-based fit between partner brands on resulting spillover effects. Two experimental studies consistently reveal the existence of brand contrast effects; furthermore, the partner brand’s attitude-based fit reduces undesired brand contrast effects and positively moderates spillover effects in brand alliances, whereas product-based fit does not. Therefore, a third study identifies relevant drivers of partner brand’s attitude-based fit for different brand alliances (i.e., co-branding, ingredient branding, and joint advertising). The findings have notable implications for the design and management of brand alliances.     

Do Spousal Discrepancies in Marital Quality Assessments Affect Psychological Adjustment to Widowhood?

We use prospective couple‐level data from the Changing Lives of Older Couples to assess the extent to which spouses concur in their assessments of marital quality (N = 844) and whether discrepancies in spouses' marital assessments affect the bereaved spouse's psychological adjustment 6 months after loss (n = 105). Spouses' assessments of marital quality are correlated modestly (r = .45), with women offering less positive assessments. Bereaved persons who had rated their marriages more positively than their spouse at the preloss interview reported higher levels of anger 6 months postloss. We conclude that persons who offer more positive appraisals of their marriages than their spouse may view spousal loss as a particularly unjust event. We discuss implications for understanding late life marriage and spousal bereavement.     

Organizational interventions and the creation of gendered knowledge: US universities and NSF ADVANCE

Universities are sites of both elite knowledge production and reproduction of intersecting gendered inequalities. The US National Science Foundation (NSF) ‘Increasing the Participation and Advancement of Women in Academic Science and Engineering Careers’ (ADVANCE) programme uses universities’ role as self‐reflective knowledge producers to design changes promoting gender equality. This knowledge is shaped by the institutional context of its production: NSF as a funder of scientific research; US universities as participants in highly competitive markets; managerialism as a condition of modern higher education systems; and separation of basic from applied research in the hierarchy of science. The tensions and underlying power dimensions of these contexts reveal local challenges that ADVANCE interventions navigate and the broader politics shaping what and how ADVANCE discovers. Yet, as a learning‐oriented intervention, ADVANCE changes over time to create and incorporate more gendered knowledge about inequalities, to legitimize feminist understandings of organizations, and to challenge the division between fundamental and applied knowledge.     

Issues in operationalizing and comparing leadership constructs

Numerous theories of leadership have yielded a rich array of leadership constructs, yet there has been little comparative work across theories. The authors of this letter exchange compare views around the definition of leadership and four issues related to operationalizing and comparing leadership constructs: the measurement of leadership constructs, overlaps in measures of leadership, follower's ability to differentiate among leadership constructs, and conceptualizing context in studying leadership.     

Commercialisation of Non‐timber Forest Products: A Reality Check

This article challenges the pervasive view that commercialisation of non‐timber forest products can (easily) achieve ecosystem and species conservation as well as improving livelihoods. Following a brief review of who and what is involved, it focuses on the main ecological and livelihood risks of unconsidered promotion of NTFP commercialisation, drawing on a wide range of case studies from around the world. It concludes with some recommendations, emphasising the lack of ‘magic‐bullet’ products, and the importance ‐ among other things ‐ of not ignoring national policy, taking an integrated view of the value chain, considering the implications of different production options, and improving both quality and quantity.     

The relative impact of complementary leader behaviors: Which matter most?

Despite conceptual overlap between the transformational–transactional model of leadership and the Ohio State two-factor model (i.e., Consideration and Initiating Structure), no systematic research examines correspondence among these behaviors or estimates their relative validities across a common set of outcomes. The current studies a) examine the factor structure of five key dimensions of these two models (transformational, contingent reward, laissez faire, Initiating Structure, and Consideration) and b) estimate relative validities with respect to two organizational outcomes: employee job satisfaction and perceptions of leadership effectiveness. Although results of a meta-analysis show that transformational leadership is significantly related to both Consideration (ρ = .74) and Initiating Structure (ρ = .50), results of two primary studies provide support for the independence of these leadership dimensions. Moreover, dominance analyses (Budescu, 1993) reveal that Consideration and transformational leadership are the most important predictors of employee job satisfaction and ratings of leadership effectiveness, and each had incremental validity when controlling for the effects of the other. Overall, results suggest that dimensions from both models are important predictors of employee outcomes.