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Abstract:
Prior research hypothesizes managers use 'real actions,' including the reduction of discretionary expenditures, to manage earnings to meet or beat key benchmarks. This paper examines this hypothesis by testing how different types of marketing expenditures are used to boost earnings for a durable commodity consumer product which can be easily stockpiled by end-consumers as well as who, within the firm, is responsible for these actions.

Combining supermarket scanner data with firm-level financial data, we find evidence that differs from prior literature. Instead of reducing expenditures to boost earnings, soup manufacturers roughly double the frequency of marketing promotions (price discounts, feature advertisements and aisle displays) at the fiscal year-end. Firms also engage in similar behavior following periods of poor financial performance.

Furthermore, our results confirm managers' stated willingness to sacrifice long-term value in order to smooth earnings (Graham, Harvey and Rajgopal, 2005) and use real actions to boost earnings to meet earnings benchmarks. We estimate that marketing actions can be used to boost quarterly net income by up to 5% depending on the depth and duration of promotion. However, there is a price to pay, with the cost in the following period being approximately 7.5% of quarterly net income.

Finally, a unique aspect of the research setting allows tests of who is responsible for the earnings management. While firms appear unable to increase the frequency of aisle display promotions in the short run, they can reallocate these promotions within their portfolio of brands. Results show firms shifting display promotions away from smaller revenue brands toward larger ones following periods of poor financial performance. This indicates the behavior is determined by parties above brand managers in the firm.

These findings are consistent with firms engaging in real earnings management and suggest the effects on subsequent reporting periods and competitor behavior are greater than previously documented.

Earnings Management, Marketing Promotions

Abstract:
This paper empirically explores the contingencies that drive cannibalizing and complementary effects across channels to provide sales forecasting, promotion planning, and customer relationship management guidance to multichannel managers. We investigate three contingencies in a sales analysis of a leading U.S. retailer who adds a new retail store channel to existing catalog and online channels. We show that the emergence and strength of cannibalizing and complementary effects varies over time, across type of channel, and by type of customer, and provide insight into when and where managers can expect these effects to dominate and how to counter cannibalization and promote complementarity across channels.

We find that opening retail stores cannibalizes sales in the catalog and online channels in the short term, but produces complementary effects in both channels in the long term; cannibalization is magnified in the catalog channel, while complementarity is magnified in the online channel. Customer analysis suggests that opening retail stores paves the way for higher rates of customer acquisition and higher rates of repeat purchasing among existing customers in the direct channels in the long term.

Channels of Distribution, Multichannel Retailing, Direct Marketing, E-commerce, Channel Management

Abstract:
This article addresses the question of whether lump-sum bonuses motivate salespeople to work harder to attain incremental orders or whether they induce salespeople to play timing games (behaviors that increase incentive payments without providing incremental benefits to the firm) with their order submissions. We find that lump-sum bonuses primarily motivate salespeople to work harder - a result that is consistent with the widespread use of bonuses in practice, but that contradicts earlier empirical work in academics.

compensation methods, salesforce

Abstract:
This article introduces a newly discovered property of discrete-choice models, which I call the Invariant Proportion of Substitution (IPS). Like the Independence from Irrelevant Alternatives (IIA) property, IPS implies individual behavior that is counterintuitive in the context of choice among similar alternatives. But models that alleviate the concerns raised by IIA, such as generalized extreme value and covariance probit models, do not necessarily alleviate the concerns raised by IPS. I explore the implications of the IPS property on individual behavior in several choice contexts and discuss some models that alleviate the concerns raised by IPS.

discrete-choice models, econometric models, individual choice behavior, IIA

Abstract:
The purpose of this paper is to show that allowing for taste heterogeneity does not address the similarity critique of discrete-choice models. Although IIA may technically be broken in aggregate, the mixed logit model allows neither a given individual nor the population as a whole to behave with perfect substitution when facing perfect substitutes. Thus, the mixed logit model implies that individuals behave inconsistently across choice sets.

Estimating the mixed logit on data in which individuals do behave consistently can result in biased parameter estimates, with the individuals' tastes for desirable attributes being systemically undervalued.

Heterogeneity, Mixed logit, Independence from Irrelevant Alternatives, IIA, Similarity Critique, Ecological Fallacy

Abstract:
This paper establishes the following: Random Utility Models (RUMs) that assume consistent preferences result in inconsistent and therefore irrational choice behavior. Paradoxically, it is possible to create RUMs that result in consistent choice behavior, but these models assume inconsistent preferences.

random utility models, RUM, independence from irrelevant alternatives, IIA, rationality, choice theory, similarity critique

Abstract:
Using data on individual level sales force performance over a 3 year period at a Fortune 500 firm, we propose and estimate a dynamic structural model of sales force response to a bonus based compensation plan. We combine Arcidiacono and Miller's new EM algorithm approach within a two step conditional choice probability (CCP) estimator to allow for sales force response heterogeneity, while preserving the computational advantage of the CCP estimators. Further, in contrast to typical dynamic choice applications estimated using real world data, where discount factors cannot be non-parametrically identified, our bonus-based compensation structure enables us to identify discount factors in a hyperbolic discounting model.

We find evidence of present bias consistent with hyperbolic discounting. Further, bonuses enhance sales productivity. Overachievement commission rates help maintain the productivity of the high performance sales force and quarterly bonuses serve as pacers to keep the sales force on track to achieve their annual sales quotas.

Sales Force Compensation, Productivity, Structural Dynamic Model

Abstract:
Nanosolar is a start-up company in the clean tech sector. It expects to be one of the first manufacturers to produce thin-film solar panels using copper indium gallium (di)selenide (CIGS) technology. Although this technology is less efficient in producing electricity than polysilicone, it is much less costly too. As it is about to enter the market, Nanosolar is facing the decision on which market to enter. Should it attempt to go into the European market which has established feed-in tariffs? Or should it enter the nascent, but growing US market?

Abstract:
Brent Constantz, founder, CEO, and president of Calera Corporation, felt a surge of optimism as he gazed at the recently commissioned prototype flue gas processing line at Calera's R&D facility in Moss Landing, California. It was late May 2009, and Calera was an early-stage venture-backed company headquartered in Los Gatos, California with a promising vision to reverse global warming and ocean acidification by adapting one of nature's oldest processes: carbonate mineralization.

Abstract:
As with many national non-profits, Planned Parenthood is organized as 100 separate 501(c)3 organizations. What is the best structure for Planned Parenthood to fulfill its mission?

Abstract:
This case introduces the concept of inbound marketing, pulling customer prospects toward a business through the use of Web 2.0 tools and applications like blogging, search engine optimization, and social media. Students follow the growth of HubSpot, an entrepreneurial venture which, in its quest for growth, faces significant challenges including: developing market segmentation and targeting strategies to decide which customer to serve and which to turn away, configuring pricing strategies to align with the value delivery stream customers experience, and determining whether inbound marketing programs can generate enough scale or whether traditional outbound marketing methods need to be employed to accelerate growth.

Abstract:
Verne Global, a pioneering startup created to build the first large-scale data center in Iceland, faces critical challenges regarding its green strategy. Verne Co-Founder Isaac Kato is tasked with evaluating how the company can most successfully market and sell the green components of its service offering. Using only renewable energy in its data center facility, Verne can drastically reduce customers' carbon emissions, enabling customers to meet emerging government regulations and to capture the financial benefit of public goodwill arising from green initiatives. But how valuable are Verne's green benefits, and are they sufficient to compel customers to pay a premium for Verne services? Further, how can Verne best integrate its green strategy into its marketing and sales message? Finally, will Verne's green benefits enable the company to overcome obstacles in the sales process, or will they alternatively overcomplicate an already complex sales message? Kato's decision allows discussion of the emerging role of green marketing and sales and to help to identify how a product or service which is good for the environment can also be good for the bottom line.

Abstract:
Companies spend billions of dollars every year on marketing because it is essential to organic growth. Given these large investments, marketing managers have the responsibility to optimally allocate resources and to demonstrate that their investments generate appropriate returns for the firm. In this chapter, we highlight a two-stage process for marketing resource allocation. In stage one, a model of demand is estimated. This model empirically assesses the impact of marketing actions on consumer demand for a company's product. In stage two, estimates from the demand model are used as input in an optimization model that attempts to maximize profits. This stage takes into account costs as well as firm's objectives and constraints (e.g., minimum market share requirement). Over the last several decades, marketing researchers and practitioners have adopted various methods and approaches that explicitly or implicitly follow these two stages. We have categorized these approaches into a 3x3 matrix, which suggests three different approaches for stage-one demand estimation (decision calculus, experiments and econometric methods), and three different methods for stage-two economic impact analysis (descriptive, what-if and formal optimization approach). We discuss pros and cons of these approaches and illustrate them through applications and case studies.

market research, demand estimation, economic impact analysis

Abstract:
We introduce the idea of a massively categorical variable, a variable such as zip code that takes on too many values to treat in the standard manner. We show how to use a massively categorical variable directly as an explanatory variable. As an application of this concept, we explore several of the issues that analysts confront when trying to develop a direct marketing campaign. We begin by pointing out that the data contained in many of the common sources are masked through aggregation in order to protect consumer privacy. This creates some difficulty when trying to construct models of individual level behavior. We show how to take full advantage of such data through a hierarchical Bayesian variance components (HBVC) model. The flexibility of our approach allows us to combine several sources of information, some of which may not be aggregated, in a coherent manner. We show that the conventional modeling practice understates the uncertainty with regard to its parameter values. We explore an array of financial considerations, including ones in which the marginal benefit is non-linear, to make robust model comparisons. To implement the decision rules that determine the optimal number of prospects to contact, we develop an algorithm based on the Monte Carlo Markov chain output from parameter estimation. We conclude the analysis by demonstrating how to determine an organization's willingness to pay for additional data.

direct marketing, categorical variables, decision theory

Abstract:
In this article, I discuss three methods of decomposing the elasticity of own-good demand. One of the methods, the decision-based decomposition (Gupta, 1988), is useful in determining the influence of changes in consumers' decisions on the growth in own-good demand. The other two methods, the unit-based decomposition (van Heerde et al., 2003) and the share-based decomposition (Berndt et al., 1997), are useful in determining whether the growth in own-good demand has been stolen from competing goods.

The objective of this article is to provide a clear and accurate method that attributes the growth in own-good demand to changes in: (1) consumers' decisions, (2) competitive demand, and (3) competitive market share. I will accomplish this by settling some confusion about what the decision- and share-based decompositions mean, by discussing how each of the decompositions relate to the others, and by discussing the research questions that each of the decompositions can answer.

elasticity decompositions, demand models