Search results

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.

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.

This paper aims to investigate the risk-return and volatility spillover within the Tunisian stock market during the COVID-19 pandemic analyzing both the Islamic and conventional stocks’ performance.

Both symmetric (GARCH and GARCH-M) and asymmetric (Threshold GARCH and Exponential GARCH) models are used to analyze the market returns and volatility response. Standard and Poor’s (S&P) index has been used to test both the Islamic and conventional stocks within the Tunisian stock market.

The findings suggest that both Tunisia Islamic and conventional stock markets are highly persistent; however, the conventional stock index showed a negative return spillover on the Islamic stocks during the pandemic. The conventional stock index has also shown a higher exposure to risk for a lower amount of return, and evidence of potential diversification benefit between both indexes was found during the pandemic, whereas the Islamic market showed a positive leverage effect, indicating a positive correlation between past return and future return; the conventional index implied a negative leverage effect.

The value of this paper emerges in studying three main aspects that are specific to the Tunisian stock market. This includes COVID-19 effect of return spillovers, volatility transmission across both conventional and Islamic stock market within the local financial market.

The purpose of this paper is to examine the impact of Turkish individual investor sentiment on the Istanbul Stock Exchange (ISE) and to investigate whether investor sentiment, stock return and volatility in Turkey are related.

This study used the monthly Turkish Consumer Confidence Index, published by the Turkish Statistical Institute, as a proxy for individual investor sentiments. First, Turkish market fundamentals were regressed on investor sentiments in order to capture the effects of macroeconomic risk factors on investor sentiments. Then, it used the impulse response functions (IRFs) generated from the vector autoregression (VAR) model to examine the effect of unanticipated movements in Turkish investor sentiment to both stock returns and volatility of the ISE.

The generalized IRFs from VAR shows that unexpected changes in rational and irrational investor sentiment have a significant positive impact on ISE returns. This suggests that a positive investor sentiment tends to increase ISE returns. The study also documents that unanticipated increase in the rational component of Turkish investor sentiment has a negative significant effect on ISE volatility. This might indicate that investors have optimistic expectations of the economy overall with respect to market fundamentals in Turkey. This optimism can result in creating positive expectations, reducing uncertainty, and reducing the volatility of stock market returns.

The study was applied only for the period 2004-2010 on the ISE stock returns and volatility.

Regardless, investors should know the impact of irrational investor sentiments while establishing investment strategies. The results of this study may also help policy makers stabilize investor sentiments to reduce stock market volatility and uncertainty.

This paper adds to the limited understanding of investor sentiment impact on stock return and volatility in an emerging market context.

The purpose of this paper is to investigate the dynamic relationship between 19 pandemic and government actions, such as governmental response index and economic support packages.

The authors use a panel dataset of 10 American and Latin countries for the period spanning from January 2020 to April 2021 to analyze the effect of government actions on stock market returns. The authors provide robust test results that improve the understanding of the impact of the pandemic on stock market indices through the break-up structure method and the new measure of Covid-19 extracted from Narayan et al. (2021) study.

Empirical results show the harmful effect of the corona virus on stock prices, hence the risk adverse behavior of investors. On the other hand, the quantitative approach reveals that the positive impact of government actions is degraded during Covid-19.

This article highlight that government actions may be effective in reducing new infections but could generate perverse economic impact through increasing uncertainty. The authors conclude that the adjustment of macroeconomic factors and the integration of financial news improve the forecasting performance of the model based on health news.

This paper aims to investigate the spillover effect of 14 US key macroeconomic news on the first two moments of 12 Asian stock market returns.

The authors collect market expectation and actual scheduled announcements data for 14 key US's macroeconomic announcements from January 2002 to April 2012 from Bloomberg. The dataset consists of six groups: monetary policy and general macroeconomic indicators: the Federal Reserve's target interest rates (FOMC), gross domestic product (GDP), and leading indicator (LI); price indicators: consumer price index (CPI) and producer price index (PPI); business indicator: housing starts (HS) and industrial production (IP); consumption indicators: retail sales (RS) and consumer confidence level (CONSUM); labor market indicators: non-farm payroll (NFP), unemployment level (UE), and jobless claim (JOB); and external sector indicators: current account (CA) and trade balance (TB). The authors also collect daily opening and closing data of 12 Asian stock markets. Following Dow Jones classification, the authors divide them into two groups: five developed markets (Japan, Hong Kong, Republic of Korea, Singapore and Taiwan), and seven emerging markets (China, India, Indonesia, Malaysia, Pakistan, Sri Lanka, and Thailand). The MA-EGARCH (1,1) model is used for the empirical test.

First, the authors find that stronger than expected news from the USA is associated with higher conditional mean and lower conditional variance of the Asian stock market returns, in general. Second, the Asian stock markets tend to put more weight on information relating to the US labor market than the other news as this indicator reveals much information about the underlying health of the US economy since full employment is the most important mandate for the US administration and policy makers. Third, in responding to the US news, the Asian emerging markets seem to respond stronger to the US news than the Asian developed markets both in terms of the number of responses and the magnitude of the reaction. This suggests that this could be seen as evidence that emerging markets are more dependent on the information content of the US news than the developed markets. Fourth, the US news is absorbed gradually leading to persisting volatility responses in the Asian stock markets.

The authors fill a gap in the extant literature in investigating the speeds of the news absorption across the Asia region by examining the spillover effects across three time horizons, namely daily, overnight and intraday.