Jooseop Lim

You Get What You Pay For: The Effect of Top Executives' Compensation on Advertising and R&D Spending Decisions and Stock Market Return

Although there is literature on how top executives’ compensation influences general management decisions, relatively little is known about whether and how compensation influences advertising and research-and-development (R&D) spending decisions. This study addresses two questions. First, is there an incentive effect of long- versus short-term compensation on advertising and R&D spending? Second, is there a mediation effect of advertising and R&D spending on the relationship between long- versus short-term compensation and stock market return? The authors address these questions using a combination of ExecuComp, Compustat, and Center for Research in Security Prices data on 842 firms during the 1993–2005 period. They find that an increase in the equity to bonus compensation ratio is positively associated with an increase in advertising and R&D spending as a share of sales. Advertising and R&D spending as a share of sales also mediates the effect of equity to bonus ratio on stock market return. The authors discuss implications for top management seeking to mitigate myopic management of resources by employing compensation to incentivize a longer-term orientation for advertising and R&D spending to improve stock return.

Functional Extended Redundancy Analysis.

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous and/or exogenous variables functional, varying over time, space, or other continua. Computationally, the method reduces to minimizing a penalized least-squares criterion through the adoption of a basis function expansion approach to approximating functions. We develop an alternating regularized least-squares algorithm to minimize this criterion. We apply the proposed method to real datasets to illustrate the empirical feasibility of the proposed method.

Generalized functional extended redundancy analysis.

Functional extended redundancy analysis (FERA) was recently developed to integrate data reduction into functional linear models. This technique extracts a component from each of multiple sets of predictor data in such a way that the component accounts for the maximum variance of response data. Moreover, it permits predictor and/or response data to be functional. FERA can be of use in describing overall characteristics of each set of predictor data and in summarizing the relationships between predictor and response data. In this paper, we extend FERA into the framework of generalized linear models (GLM), so that it can deal with response data generated from a variety of distributions. Specifically, the proposed method reduces each set of predictor functions to a component and uses the component for explaining exponential-family responses. As in GLM, we specify the random, systematic, and link function parts of the proposed method. We develop an iterative algorithm to maximize a penalized log-likelihood criterion that is derived in combination with a basis function expansion approach. We conduct two simulation studies to investigate the performance of the proposed method based on synthetic data. In addition, we apply the proposed method to two examples to demonstrate its empirical usefulness.

Functional fuzzy clusterwise regression analysis

We propose a functional extension of fuzzy clusterwise regression, which estimates fuzzy memberships of clusters and regression coefficient functions for each cluster simultaneously. The proposed method permits dependent and/or predictor variables to be functional, varying over time, space, and other continua. The fuzzy memberships and clusterwise regression coefficient functions are estimated by minimizing an objective function that adopts a basis function expansion approach to approximating functional data. An alternating least squares algorithm is developed to minimize the objective function. We conduct simulation studies to demonstrate the superior performance of the proposed method compared to its non-functional counterpart and to examine the performance of various cluster validity measures for selecting the optimal number of clusters. We apply the proposed method to real datasets to illustrate the empirical usefulness of the proposed method.

Marketing spending, firm visibility, and asymmetric stock returns of corporate social responsibility strengths and concerns

Purpose This paper aims to focus on the unique goal of understanding how marketing spending, a proxy for firm visibility, moderates the effects of corporate social responsibility (CSR) strengths and concerns on stock returns in the short and long terms. In contrast to the resource-based view (RBV) of the firm, the visibility theory, based on stakeholder awareness and expectations, offers asymmetric predictions on the moderation effects of marketing spending. Design/methodology/approach The predictions are tested based on data from KLD, Compustat and Center for Research in Security Prices from 2001-2010 and panel data based regression models. Findings Two results support the predictions of the visibility theory over those of the RBV. First, strengths are associated with higher stock returns, for low marketing spending firms, and only in the long term. Second, concerns are associated with lower stock returns, for high marketing spending firms, also only in the long term. A profiling analysis indicates that high marketing spending firms have high R&D spending and are more likely to operate in business-to-customer than business-to-business industries. Practical implications The two findings highlight the importance of coordination among chief marketing, sustainability and finance officers investing in CSR and marketing for stock returns, contingent on the firm’s marketing and R&D spending and industry characteristics. Originality/value This paper identifies conditions under which CSR is and is not related to stock returns, by uniquely considering three variables omitted in most past studies: marketing spending, CSR strengths and concerns and short- and long-term stock returns, all in the same study.

The Optimal Advertising-Allocation Rules For Sequentially Released Products: The Case of the Motion Picture Industry

ABSTRACT This study investigates the optimal advertising-allocation rules for sequentially released products. The authors used both analytical and empirical approaches to derive and validate the rules using theatrical prerelease, postrelease, and DVD advertising and sales data in the movie industry. Theatrical prerelease advertising increased when there was a strong prerelease advertising effect on the opening box office or a strong carryover effect on DVDs through the opening box office. The optimal allocation percentages are proposed on the basis of the estimated parameters of the empirical analysis. A simulation study proposes likely improvements in revenues for 74 percent of the titles with optimal rules.

Commitment to marketing spending through recessions: Better or worse stock market returns?

Purpose This paper aims to address two unique and important questions. First, how do recessions directly affect firms’ marketing spending decisions? Second, and more importantly, do firms which are more committed to marketing spending through past recessions achieve better stock market returns? Design/methodology/approach This study is based on a combination of National Bureau of Economic Research, COMPUSTAT and Center for Research in Security Prices data on 6,000 firms between 1982 and 2009 which are analyzed using panel data-based regression models. Findings The authors find that firms cut marketing spending during recessions. However, firms committed to marketing spending during past recessions achieve better stock market returns. The findings are found to be robust across B2B and B2C industries, different periods and US firms which vary on the proportion of their global revenue from non-US sales. Research limitations/implications Top executives cut marketing budgets during recessions; however, if they can resist the pressures, and strategically continue to make marketing investments during recessions, they will achieve higher stock market returns. Originality/value This is the first paper to establish the longer-term (not short-term) positive stock market performance of continuous (not episodic) marketing spending through past recessions, i.e. the view that marketing spending is necessary (not discretionary) for stock returns.