The Role of the Mangement Sciences in Research on Personalization

We present a review of research studies that deal with personalization. We synthesize current knowledge about these areas, and identify issues that we envision will be of interest to researchers working in the management sciences. We take an interdisciplinary approach that spans the areas of economics, marketing, information technology, and operations. We present an overarching framework for personalization that allows us to identify key players in the personalization process, as well as, the key stages of personalization. The framework enables us to examine the strategic role of personalization in the interactions between a firm and other key players in the firm's value system. We review extant literature in the strategic behavior of firms, and discuss opportunities for analytical and empirical research in this regard. Next, we examine how a firm can learn a customer's preferences, which is one of the key components of the personalization process. We use a utility-based approach to formalize such preference functions, and to understand how these preference functions could be learnt based on a customer's interactions with a firm. We identify well-established techniques in management sciences that can be gainfully employed in future research on personalization.CRM, Persoanlization, Marketing, e-commerce,

Context Effects as Customer Reaction on Delisting of Brands

The delisting of brands is frequently used by retailers to strengthen their negotiating position with the manufacturers and suppliers of their product assortment. However, retailers and manufacturers have to consider the risk of potential reactions when customers are faced with a reduced or modified assortment and thus, different choice. In this paper, two studies are presented which investigate customers` switching behavior if a (sub-)brand is unavailable and key determinants of the resulting behavior are discussed. Various conditions are tested by taking into account context theory. The results reveal that customer responses depend significantly on the context. A real-life quasi-experiment suggests that manufacturers may encounter substantially larger losses than retailers. Managerial implications for both parties can be derived and recommendations for further research are developed.Consumer decisions, delisting, context effects, switching behavior, retailing, logistic regression

Sequential Design for Optimal Stopping Problems

We propose a new approach to solve optimal stopping problems via simulation. Working within the backward dynamic programming/Snell envelope framework, we augment the methodology of Longstaff-Schwartz that focuses on approximating the stopping strategy. Namely, we introduce adaptive generation of the stochastic grids anchoring the simulated sample paths of the underlying state process. This allows for active learning of the classifiers partitioning the state space into the continuation and stopping regions. To this end, we examine sequential design schemes that adaptively place new design points close to the stopping boundaries. We then discuss dynamic regression algorithms that can implement such recursive estimation and local refinement of the classifiers. The new algorithm is illustrated with a variety of numerical experiments, showing that an order of magnitude savings in terms of design size can be achieved. We also compare with existing benchmarks in the context of pricing multi-dimensional Bermudan options.Comment: 24 page

Regime-switching Vector Error Correction Model (VECM) analysis of UK meat consumption

The asymptotic distributions of cointegration tests are approximated using the Gamma distribution. The tests considered are for the I(1), the conditional I(1), as well as the I(2) model. Formulae for the parameters of the Gamma distributions are derived from response surfaces. The resulting approximation is flexible, easy to implement and more accurate than the standard tables previously published

Regime-switching Vector Error Correction Model (VECM) analysis of UK meat consumption

The standard Vector Error Correction Model (VECM) approach to investigating the underlying dynamics of economic variables assumes a constant co-integration space. This paper relaxes this assumption by implementing a regime switching VECM that allows for shifts in both the drift and the long-run equilibrium. Applying this more flexible formulation to a study of UK meat consumption, we can clearly identify several shifts in meat consumption. These can be explained by significant shocks in consumer confidence in meat safety, such as BSE. Although it is possible to model these explicitly, since the approach adopted models the regime shift in terms of an unobserved state variable, it can be useful in identifying such shifts, thus allowing them to be modeled in subsequent steps.Markov switching, vector autoregression, error correction model

Intergenerational Transmission of Inflation Aversion: Theory and Evidence

We study the evolution of inflation aversion preferences across generations. In the theoretical part of the paper, we analyze the dynamics of such preferences in an overlapping-generations model with heterogenous mature agents characterized by different degrees of inflation aversion. We show how the stability of a society’s degree of inflation aversion depends on the strength and speed of changes in the structure of the population. The empirical part then proposes two applications in support of the theoretical results. We first link demographic structures to inflation aversion, and then proceed by looking at the relations between income (in)equality and measures of inflation aversion.Intergenerational transmission, evolving preferences, inflation aversion, central bank independence, demographic change, income inequality

STOCHASTIC PRODUCTION AND HETEROGENEOUS RISK PREFERENCES: COMMERCIAL FISHERS' GEAR CHOICE

As long as total effort cannot be completely controlled, a more thorough understanding of fishers' supply response decisions will be beneficial for fisheries managers. In this paper, we present a model of fishers' gear choice, which is empirically estimated on a panel of Swedish demersal trawlers. The approach allows for heterogeneity both in production technology and in risk preferences. Stochastic revenue functions with fixed effects are estimated and used to predict expected revenue and standard deviation for each trip. We employ a linear utility function in the mean-standard deviation framework and then analyze the gear choices, using the predicted values together with vessel capacity and lagged variables for the previous trip in a random parameters- logit model, which allow for heterogeneous preferences. The results indicate that fishers have a strong tendency to choose the same gear used on the previous trip, while in general they react to changes in economic and biological conditions by responding positively to increases in expected landing and negatively to increases in the variability of the expected landing values, indicating risk aversion.Risk and Uncertainty,

Measuring changes in preferences and perception due to the entry of a new brand with choice data

Context effects can have a major influence on brand choice behavior after the introduction of a new product. Based on behavioral literature, several hypotheses about the effects of a new brand on perception, preferences and choice behavior can be derived, but studies with real choice data are still lacking. We employ an internal market structure analysis to measure context effects caused by a new product in scanner panel data, and to discriminate between alternative theoretical explanations. An empirical investigation reveals strong support for categorization effects and changes in perception, which affect customers in two out of five segments.context effects, categorization, brand choice models, new brand introduction

Self-Selection and Subjective Well-Being: Copula Models with an Application to Public and Private Sector Work

We discuss a new approach to specifying and estimating ordered probit models with endogenous switching, or with binary endogenous regressor, based on copula functions. These models provide a framework of analysis for self-selection in economic well-being equations, where assigment of regressors may be choice based, resulting from well-being maximization, rather than random. In an application to public and private sector job satisfaction, and using data on male workers from the German Socio-Economic Panel, we find that a model based on Frank's copula is preferred over two alternative models with independence and normal copula, respectively. The results suggest that public sector workers are negatively selected.Ordered probit, switching regression, Frank copula, job satisfaction, German Socio-Economic Panel