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Purpose – Marketers are under increasing pressure to demonstrate the financial return associated with marketing expenditures. Concurrently, more attempts at measuring return on investment from marketing as well as achieving other long-term goals such as building brand equity and increasing shareholder value have been made. As a result of this emphasis, the degree to which advertising budgets are spent efficiently and the impact of these expenditures on the bottom line are an important topic to study.

Methodology/approach – This study applies data envelopment analysis (DEA) to a group of large firms to assess the degree to which companies spend advertising dollars efficiently and to examine the impact of advertising efficiency on investor behavior and, ultimately, stock prices.

Findings – The analysis reveals that firms that advertise more efficiently are rewarded by investors by positive stock returns.

Research limitations/implications (if applicable) – The study is limited to large enterprises with strong brands within a time frame of only four years.

Practical implications (if applicable) – The results imply that it is advisable for marketing managers not to limit their focus to increasing market-based assets at any cost. The efficiency of their efforts can send a positive signal to investors and contribute to shareholder value enhancement.

Originality/value of the chapter – The chapter finds investors to pay attention not only to the effectiveness of advertising activities but also to their efficiency. The study also demonstrates how DEA and stock return response modeling can be combined to investigate the link between advertising efficiency and investor behavior.

With the goal of helping consumers bounce back from the financial challenges they faced as a result of the COVID-19 pandemic, many firms developed and announced consumer-targeted resiliency programs (e.g. Walgreens waived delivery fees, Associated Bank allowed deferred mortgage payments). However, there is a paucity of research examining the unique features of these programs, and whether firms' investors (the first external stakeholder group to provide them with feedback regarding their strategies) were receptive to these programs during a period of time in which firms themselves were suffering financially. Drawing on resilience theory and stakeholder theory, the present research incorporates an event study of consumer-targeted resiliency program announcements to understand their financial implications for firms, and to learn whether firms witnessed different financial effects as a result of firm- and program-specific factors.

This study referred to business news publications and newswire services to collect a comprehensive list of consumer-targeted resiliency programs announced by publicly traded U.S. firms during the pandemic. The resulting dataset consisted of 145 announcements made during the period of February–June 2020. An event study was conducted in order to precisely measure the main effect of consumer-targeted resiliency programs on firm value, as manifested through abnormal stock returns. Finally, a moderation analysis (regression) was conducted to uncover whether firm characteristics or specific features of firms' consumer-targeted resiliency programs lead certain firms to witness stronger financial effects than others.

The main effect of consumer-targeted resiliency programs on firm value was found to be positive – a 1.9% increase on average. The moderation analysis finds that non-financial firms were rewarded more positively than financial firms (e.g. banks and credit card companies). In addition, financial aid (i.e. allowing customers to defer their payments to a firm for its products/services, versus a reduction in the price of a product/service or offering it for free or giving cash back to customers) and temporal characteristics (i.e. an offer being framed as limited-time, vs being indefinite or for the foreseeable future) are not found to have a moderating effect.

This theory-driven empirical study uncovers practical implications for managers of firms interested in whether investing in corporate social responsibility during times of crisis is a wise allocation of resources. Any form of financial aid for consumers, regardless of temporal limitations, is received positively by investors.

The aim of this study is to examine the relationship between customer satisfaction, earnings and firm value.

A model borrowed from the accounting literature – the Ohlson model – is used to consider the impact of customer satisfaction on Tobin's q – a capital market‐based measure of firm performance widely used in marketing research. Data on firm performance is drawn from COMPUSTAT and integrated with data on customer satisfaction from the American Customer Satisfaction Index (ACSI).

Results show that customer satisfaction has a positive impact on firm value. Critically, the authors find that this impact is over and above the impact that earnings has on firm value. They also find that customer satisfaction positively and significantly moderates the earnings‐firm value relationship.

Findings are limited to firms covered by the American Customer Satisfaction Index and subject to the assumptions underpinning the Ohlson model.

This study's demonstration of the complementary relationship between earnings and customer satisfaction in determining firm value should encourage managers to engage with satisfaction as a driver of business performance and value.

Findings extend recent studies on the impact of customer satisfaction on business performance. While prior studies either ignore earnings or focus on the relationship between satisfaction and stock returns, the authors show the impact of satisfaction on firm value, in a model that includes earnings. Importantly, they also extend prior studies by showing that the interaction between customer satisfaction and earnings is central to understanding the impact of both satisfaction and earnings on firm value. In addition, they demonstrate the usefulness of an earnings‐based valuation model, to explore the relationship between a marketing metric and firm value. The authors' approach may be adopted to consider the impact of other measures of marketing performance. Thus, they hope that this study helps to further bridge the gap between marketing and the financial disciplines.

“Garbage in, garbage out” is a common expression that academics and practitioners use to emphasize that empirical analysis is only as good as the basis on which it relies. Although the importance of sound data and valid measures has long been acknowledged, it is nevertheless often problematic to follow required quality standards in concrete research situations. Potential sources of error are usually unknown, methods to ensure data quality are unavailable, and existing methods for scale development, index construction, data collection, and data analysis are insufficient or erroneously applied. This is especially true of international marketing research, which often makes great demands on the data and measures used, as well as on the research methodology applied. Against this background, this volume addresses issues pertaining to measurement and research methodology in an international marketing context. Thanks to the efforts of authors and reviewers, we are pleased to present nine articles that deal with cutting-edge topics such as formative measurement, response-bias in cross-cultural research, marketing efficiency measurement, and segmentation methods.

Social media have recently become an important strategic marketing tool to increase firm value. Based on an integrated theoretical framework, this study aims to examine the market reaction at the time of the creation of a Twitter platform for 312 firms from the Fortune 500 firms.

To test the hypotheses related to the effect of social media platforms on firm value, the event history analysis (EHA) was used, also known as event study, usually designed to examine the impact of a historical phenomenon for the US Fortune 500 firms that developed a Twitter platform.

A significant market reaction was found around the starting date of Twitter activities for the subsample of firms that are not contaminated by any other corporate announcements, but not for the overall sample. The market reaction is higher for firms with two-way interaction strategies rather than one-way messaging in both the uncontaminated subsample and the overall sample. It is higher in smaller firms, firms with losses and those with a family and/or a dominant shareholder. Further, firms in the contaminated subsample are likely to follow a two-way strategy after a positive revision of their earnings per share. We have run several robustness checks, including cross-validation on a holdout sample, and these findings remain consistent.

The integrated theoretical framework is another significant contribution. To our knowledge, this is the first study across disciplines that integrates the social exchange theory (SET), social representation theory (SRT), social network analysis (SNA), social identity theory (SIT), signaling theory (ST) and the impression management theory (IMT) into one framework that is built around information as a resource and social interaction.

The results suggest that Twitter can be used to add value if firms interact and reciprocate with the various stakeholders.

Firms using social media must interact and reciprocate with the various stakeholders.

This research is different than the published research on this topic in that it examines the impact on stock prices of the introduction of a specific social media platform, i.e. Twitter. The present results of the paper add to the prior research on database marketing and show that marketing “with” the customer is adding more value than marketing “to” the customer. The use of the net extends the scope of database marketing into a certain form of interaction marketing with “face-to-face” interaction within the relationships between the firm and its customers. Finally, the conditions under which social media platforms are used in an interactive manner are shown, and depicts that firms are more likely to use a two-way interactive strategy following a one-year period of positive momentum.

Product quality is a central construct in several management domains. Theoretical conceptualizations of product quality unanimously stress its multidimensional nature. Yet, no generalizable, multidimensional product quality scale exists. This study develops and validates a multidimensional Customers’ experienced product quality (CEPQ) scale, across four diverse product categories.

Based on the exploratory studies, CEPQ is conceptualized as a second-order reflective-formative construct and validated in quantitative studies with survey data collected in the USA.

Results reveal that the CEPQ scale and its underlying quality dimensions possess sound psychometric properties. In addition, CEPQ has a substantial impact on customer behavior over and above customer satisfaction. The strength of this impact is positively moderated by expertise and quality consciousness. CEPQ predicts objective quality scores from consumer reports substantially better than the existing measures of product quality.

The cross-sectional nature of the main study, as well as samples from only one country, restricts the generalizability of the findings.

Operations managers and marketers should start to measure CEPQ as an additional key metric. The formative weights of the first-order quality dimensions explain how customers define product quality in a specific product category.

A generalizable, multidimensional scale of product quality, CEPQ, is developed and validated. Materials as a new product quality dimension is identified. Once correctly measured, product quality ceases to be a mere input to satisfaction. Boundary conditions for CEPQ’s relevance were hypothesized and confirmed.

Investors’ fear can be rational, emanating from the natural dynamics of economic fundamentals, or it can be quasi rational and not attributable to any known risk factors. Using VIX from Chicago Board Options Exchange as a proxy for investors’ fear, the purpose of this paper is to consider the following research questions: to what extent does noise play a role in the formation of investors’ fear? To what extent is the impact of fear on S&P 500 index returns driven by rational reactions to new information vs fear induced by noise in stock market returns? To what extent do S&P 500 index returns display asymmetric behavior in response to investor’s rational and quasi rational fear?

In a two-step process, the authors first decompose investors’ fear into its rational and irrational components by generating two additional variables representing fear induced by rational expectations and fear due to noise. The authors then estimate a three-vector autoregression (VAR) model to examine their relative impact on S&P 500 returns.

Impulse responses generated from a 13-variable VAR model show that investors’ fear is driven by risk factors to some extent, and this extent is well captured by the Fama and French three-factor and the Carhart four-factor models. Specifically, investors’ fear is negatively related to the market risk premium, negatively related to the premium between value and growth stocks, and positively related to momentum. The magnitude and duration of the impact of the market risk premium is almost twice that of the impact of the premium on value stocks and the momentum of investors’ fear. However, almost 90 percent of the movement in investors’ fear is not attributable to the 12 risk factors chosen in this study and thus may be largely irrational in nature. The impulse responses suggest that both rational and irrational fear have significant negative effects on market returns. Moreover, the effects are asymmetric on S&P 500 index returns wherein irrational upturns in fear have a greater impact than downturns. In addition, the component of investors’ fear driven by irrationality or noise has more than twice the impact on market returns in terms of magnitude and duration than the impact of the rational component of investors’ fear.

The results are consistent with the view that one of the most important drivers of stock market returns is irrational fear that is not rooted in economic fundamentals.

Recent empirical studies by Antonakakis, Chatziantoniou and Filis (2013), Brogaard and Detzel (2015) and Christou et al. (2017) present evidence, which supports the notion that a rise in economic policy uncertainty (EPU) will lead to a decline in stock prices. The purpose of this paper is to examine US categorical policy uncertainty on stock returns while controlling for implied volatility and downside risk. In addition to the domestic impacts of policy uncertainty, this paper also presents evidence that changes in US policy uncertainty promptly propagates to the global stock markets.

This study uses a GED-GARCH (1, 1) model to estimate changes of uncertainties in US monetary, fiscal and trade policies on stock returns for the sample period of January 1990–December 2018. Robustness test is conducted by using different set of data and modeling techniques.

This paper contributes to the literature in several aspects. First, testing of US aggregate data while controlling for downside risk and implied volatility, consistently, shows that responses of stock prices to US policy uncertainty changes, not only display a negative effect in the current period but also have at least a one-month time-lag. The evidence supports the uncertainty premium hypothesis. Second, extending the test to global data reveals that US policy uncertainty changes have a negative impact on markets in Europe, China and Japan. Third, testing the data in sectoral stock markets mainly displays statistically significant results with a negative sign. Fourth, the evidence consistently shows that changes in policy uncertainty present an inverse relation to the stock returns, regardless of whether uncertainty is moving upward or downward.

The current research is limited to the markets in the USA, eurozone, China and Japan. This study can be extended to additional countries, such as emerging markets.

This paper provides a model that uses categorical policy uncertainty approach to explain stock price changes. The parametric estimates provide insightful information in advising investors for making portfolio decision.

The estimated coefficients of changes in monetary policy uncertainty, fiscal policy uncertainty and trade policy uncertainty are informative in assisting policymakers to formulate effective financial policies.

This study extends the existing risk premium model in several directions. First, it separates the financial risk factors from the EPU innovations; second, instead of using EPU, this study investigates the effects from monetary policy, fiscal policy and trade policy uncertainties; third, in additional to an examination of the effects of US categorical policy uncertainties on its own markets, this study also investigates the spillover effects to global major markets; fourth, besides the aggregate stock markets, this study estimates the effects of US policy uncertainty innovations on the sectoral stock returns.

The purpose of this study is to investigate the interactive relationships between oil price shocks and the Nigeria stock market.

The paper applied the multivariate vector auto‐regression that employed the generalized impulse response function and the forecast variance decomposition error.

Empirical evidence reveals that stock market returns exhibit insignificant positive response to oil price shocks but reverts to negative effects after a period of time depending on the nature of the oil price shocks. The results are similar even with the inclusion of other variables. Also, the asymmetric effect of oil price shocks on the Nigerian stock returns indices is not supported by statistical evidences.

This is the first study to examine the dynamic linkages between stock market behaviour and oil price shocks in Nigeria.