کلاه برداری شرکت و ارزش اعتبار در بازار محصول

We examine the consequences of a damaged reputation for fraud firms in the context of product markets. We generate three direct measures of reputational damage and find evidence that customers impose significant reputational sanctions on fraud firms. Using yearly transactional data to track the business dealings of fraud firms with large customers, we show that customer reputational sanctions result in a decline in the firm's operating performance through increased selling costs, as suggested by previous studies of corporate reputation. We further find that reputational losses estimated from an event study approach reflect the actual decrease in the revenue of a fraud firm, which suggests that the event study approach yields a reliable measure of reputational losses. Finally, we document that these findings are the result of a damaged reputation following the detection of fraud rather than an effect of adverse information revealed upon fraud detection.

The consequences of a damaged reputation that results from corporate misconduct have been investigated extensively in previous studies (Alexander, 1999, Gande and Lewis, 2009, Karpoff and Lott, 1993, Karpoff et al., 2008a and Karpoff et al., 2008b). The existence of reputational losses associated with financial stakeholders, such as lenders and investors, is also well documented in the literature (Graham et al., 2008 and Murphy et al., 2009). However, there is limited evidence of the imposition of significant reputational losses from financial misconduct by outside stakeholders of the firm apart from lenders and investors.1 Several theoretical studies predict that a damaged reputation has real consequences for fraud firms in the context of the product market. For instance, financial misconduct should have a large effect on the firm's contracting with customers (Klein and Leffler, 1981). Customers may be apprehensive in dealing with a firm that has dishonest management, thus, reducing their demand for the fraud firm's products. Hereafter, we refer to this unfavorable change in customer behavior as a customer reputational sanction.2 This argument leads to the following questions that we will subsequently examine in this paper: Does financial misconduct cause the firm's customers to re-evaluate their business relationships with the firm, leading the fraud firm to lose sales and bear the costs of building new customer relationships? Are these costs significant enough to become economically meaningful for fraud firms? Previous studies provide incomplete answers to these questions. Most evidence about reputational losses comes from the event study approach that is implicit in Peltzman (1981) and Jarrell and Peltzman (1985), and explicit in Karpoff and Lott (1993). These studies estimate reputational losses as the change in firm value when a fraud is first revealed minus the legal penalties from the fraud.3 However, there is limited direct evidence on whether the reputational losses imposed by customers and estimated from the event study approach reflect actual increases in the firm's costs or decreases in its revenues. The investigation of possible reputational sanctions imposed by customers is empirically challenging because these sanctions coincide with the normal business exchange between a firm and its customers. Thus, when customers of fraud firms impose less favorable terms of trade on their fraud firm suppliers (Karpoff, 2010), these changes are typically hard to detect from the outside. Ideally, researchers need access to detailed transaction-level data about a series of business exchanges between the fraud firm and its customer around the time of fraud detection. To overcome this empirical hurdle, we take a novel approach, which allows us to quantitatively measure the intensity of customer reputational sanctions based on the extensive data on the customer–supplier bilateral trading history. For this purpose, we utilize the COMPUSTAT segment level database, which contains comprehensive information about trading between a firm and its large customers. FAS No. 131 disclosure rules require firms to reveal all the customers that are responsible for over 10% of their annual revenues. The COMPUSTAT segment level database contains detailed supplier–customer data gleaned from these disclosures filed with the Securities and Exchange Commission (SEC), including information on customers that account for more than 10% of sales, along with data on the actual sales to the large customers.4 This database is extensively used in previous studies, including Fee and Thomas (2004), Fee et al. (2006), and Hertzel et al. (2008).5 Based on previous studies examining corporate reputations, including Klein and Leffler (1981), we construct three measures of the intensity of customer reputational sanctions on fraud firms. Our first measure is the likelihood of a break-up in the business relationship between the fraud firm and its large customer after the detection of fraud. We examine this likelihood using a Hazard model to analyze the duration of the relationship as obtained from the firm-large customer match obtained from the COMPUSTAT segment level database.6 Our second measure is from the perspective of the fraud firm, namely, decreases in fraud firm's sales dependency on its large customers. Our third measure is from the perspective of the customer, namely, decreases in the large customer's cost of goods sold (COGS) attributed to a fraud firm. Throughout the paper, we repeat our analysis using these three measures to ensure robustness of our results. Our empirical strategy is to calculate these three measures each year and keep track of them over time after the first revelation of the firm's financial misconduct, while searching for any significant changes in customer purchasing policy associated with the fraudulent suppliers' damaged reputation. We are particularly interested in showing that this change in customer behavior is the direct cause of substantial declines in the fraud firm's wealth as found in prior studies. For instance, in our sample of fraud firms, the likelihood of termination of the relationship increases by 5.95% in the year after the detection of fraud and the relationship length is shortened by an average of 0.42 years. In addition, the percent of sales of the fraud firm to the large customer declines by a mean (median) of 4.10% (1.00%) and the percent cost of goods sold to large customers for the firm decreases by a mean (median) of 5.37% (0.03%) after a class action suit is filed. When we convert the aforementioned ratios to a dollar amount, a 1% decrease in the fraud supplier's sales dependency translates to a median loss of $1.23 million in net income. These calculations allow us to compare the estimated dollar costs resulting from these reputational sanctions with the financial penalties imposed by the SEC. Consistent with the prior literature (Karpoff et al., 2005), we find that the reputational costs are large compared to the direct sanctions of the SEC and the Department of Justice (DOJ). With the help of our three direct measures, we examine several questions related to damaged corporate reputations and customer reputational sanctions. First, we aim to establish the causal relationship between the corporate financial misconduct, customer reputational sanctions, and deteriorating operating performance of the fraud firm.7 For this purpose, we examine whether significant customer reputational sanctions follow the revelation of financial misconduct by the fraud firm and whether customer reputational sanctions cause a substantial decline in the performance of the fraud firm. Second, we examine whether customers rationally choose the intensity of reputational sanctions by considering the benefits and costs of reputational sanctions. Third, we perform our analysis from the customer's perspective to examine the impact of fraud on a firm's customers. Fourth, we examine whether the reputational losses estimated from the event study approach can be explained by the customer sanctions that result in an increase in firm costs or a decrease in firm revenues. To conduct research in this area, the previous studies have used the events of financial misconduct such as SEC sanctions, lawsuits filed by customers, and class action lawsuits. We use class action lawsuits as a useful avenue of inquiry for our investigation for the following reasons.8 The number of fraud cases involving SEC action is quite small (Kedia and Rajgopal, 2011), so by focusing on class action cases, we are able to expand the sample size substantially. In addition, the corporate misconduct in class action lawsuits runs the gamut of fraud severity, allowing us to examine, at one extreme, cases where the firm is accused of fraud, but the case is ultimately dismissed, and at the other extreme, cases where there is both a class action lawsuit and an SEC action against the firm. Our empirical results are summarized as follows. First, we find that significant customer reputational sanctions are imposed after the detection of financial misconduct in terms of our three direct measures. Namely, after the detection of a fraud, the fraud firm's trading relationship with its large customer is more likely to break up, its revenue attributable to that large customer decreases, and the large customer's COGS attributable to the fraud firm also decreases substantially. In our multivariate analysis we find that when transaction costs are higher in the fraud firm's industry, when customers can find trading alternatives to the current supplier more easily, and when there is more fraud firm information asymmetry, the customer reputational sanctions are more acute, consistent with Cremers et al. (2008). These results imply that customers rationally choose the intensity of reputational sanctions based on their comparisons between the benefits and costs of reputational sanctions. Second, we find a significant decline in operating income, net profit margin, and ROA of the fraud firms relative to a control sample. The decline in operating performance is significantly related to our measures of customer reputational sanctions.9 A fraud firm experiences a larger decline in its operating performance when the firm is particularly dependent upon the large customer and has a higher degree of information asymmetry. Third, to ensure that our results are not influenced by an omitted variables bias or reverse causality, we employ an instrumental variables approach. Our instrumental variable results strongly support the hypothesis that the decline in the relationship is responsible for at least a part of the decline in the operating performance of the fraud firm. Fourth, in addition to establishing a causal relationship between the disclosure of the fraud and decline in the operating performance of the fraud firm, we further investigate the mechanism whereby customer reputational sanctions lead to a decline in the operating performance. We find that the selling, general, and administrative costs increase substantially following the revelation of a fraud (by 10.93% in the year after the fraud), consistent with the idea that finding new customers is costly (Klein and Leffler, 1981).10 In addition, the net profit margin declines by 4.13% and the operating income/assets declines by 2.34%. Our results imply that the decline in the profit margins is the result of the tougher terms of trade by the firm's customers, requiring the fraud firms to increase selling costs to achieve the same level of sales. Fifth, we find that on the class action filing date and the event trigger date, the fraud firm has a negative and significant cumulative abnormal stock return (CAR). The announcement day return is significantly related to the decline in the fraud firm's operating performance and several measures of customer reputational sanctions, thus supporting the suggestion that reputational losses estimated from the event study approach reflect the reduction in demand for the fraud firm's products by customers. Further, firms with a higher dependence on large customers have a more negative announcement day return. Certain industry characteristics, including the market competitiveness of the fraud firm and the size of transaction costs in the fraud firm's industry are also associated with a more negative announcement day return, consistent with the previous literature (Williamson, 1985). Sixth, we find that on the class action filing and event trigger dates, the stock price of a fraud firm's customer also has a negative and significant cumulative abnormal return (CAR). This suggests that customers may suffer a real loss due to the purchase of products from a fraudulent supplier, and the real economic decisions of the customers may be distorted by the supplier's fraud (Sadka, 2006). Furthermore, the size of the loss in customer wealth is positively related to the magnitude of reputational sanctions the customer imposes on the fraud firm. This implies that customers likely consider the losses they suffer when they determine the intensity of reputational sanctions. Consistent with this conjecture, we find that the customer's CAR is a significant determinant of the fraud firm's CAR. We find that a 0.05% more negative customer CAR results in a fraud firm's CAR that is more negative by 1%. Since the customers are much larger than the fraud firms, this means that a loss of $1 by the customer is associated with a loss of $1.15 by the fraud firm.11 As additional tests and robustness checks, we consider the possibility that our results are driven by some other factors that impair the fraud firm's reputation with other stakeholders. It may be argued that our results are driven by adverse information effects. Perhaps, the financial misconduct, when revealed, coincides with information that the firm's financials are weaker than previously believed. This new information about the fraud firm's financial health may cause customers to change the terms with which they are willing to do business with the firm. Alternatively, it may be argued that corporate fraud usually arises at the early stages of financial distress (Alexander, 1999 and Alexander, 2004). We conduct a battery of additional tests to rule out these alternative explanations. Our results suggest that it is the damaged reputation rather than adverse information revealed by fraud detection that causes our documented phenomena. Furthermore, we consider the possibility that our results are caused by an industry shock to both the fraud firm and its large customers. We find that industry-matched firms do not show signs of any such shock, implying that this is not the case. Further, we examine the possibility of our results being caused by the post-fraud adjustment effect documented in Karpoff et al. (2008b). Our results are most consistent with these accounting adjustments being proxies for fraud severity. Our study contributes to the existing literature in several significant ways. First, we establish the causal link between customer reputational sanctions and loss in the wealth of the fraud firm through an increase in selling costs and a decrease in the revenue of the fraud firm from large customers. Second, we examine the way in which individual stakeholders respond to corporate fraud and check whether these responses are consistent with the predictions in previous studies on corporate reputation. We provide evidence that customers rationally choose the intensity of reputational sanctions, considering the benefits and costs of terminating the trading relationship. Furthermore, to the best of our knowledge, this is the first study providing evidence that the reputational losses estimated by the event study approach reflect the actual deterioration in the trading relationships and increased selling costs for the fraud firms. This finding provides a justification for the large losses in wealth associated with fraud documented in the extant literature, which heavily relies on the event study approach. Finally, we identify large customers, which have direct trading relationships with fraud firms, and analyze the consequences of corporate misconduct from the perspective of the customer. The rest of the paper is organized as follows. Section 2 explains our hypothesis development. Section 3 describes our methodology and presents the main findings of our study. In Section 4, we discuss our tests for robustness and alternative explanations for our results. Finally, in Section 5, we present our conclusions.

In this paper, we examine several testable implications of customer reputational sanctions for corporate financial misconduct. Using direct measures of customer reputational sanctions and the detailed transaction data about individual customer and supplier business dealings, we find that customer reputational sanctions do exist. Further, we establish a causal relationship between financial misconduct and the decline in the operating performance of a firm that has committed fraud. In addition, we find that the decline of the firm's operating performance as an effect of the firm's financial misconduct is the result of customer reputational sanctions, as measured by our three direct measures, through an increase in the selling costs following the detection of firm's financial misconduct. These results are all consistent with the previous studies, which suggest that a customer imposes reputational sanctions by reducing demand for the fraud firm's products. We also find that several industry and fraud firm characteristics, which influence the value of continuing with the existing business relationships between the fraud firm and the customer, are significant determinants of the customer reputational sanctions and the fraud firm's announcement day returns. Our results imply that the customers rationally choose the intensity of customer reputational sanctions based on a comparison of the benefits and costs of imposing the reputational sanctions. We further show that reputational losses, which are estimated from the event study approach, reflect in large part the deterioration of fraud firm's business relationship with large customers, as is implicitly assumed in previous studies. Our study provides grounds for the use of event study approach in the corporate fraud literature. In additional tests, we find that it is the damaged reputation and not the adverse information revealed by the detection of fraud that causes these phenomena. Our findings suggest that, consistent with the previous studies of corporate reputation, the consequences of the allegations of financial misconduct and the firm's reputation may significantly influence corporate policies, including the policies related to purchase and investment.