Consumers’ willingness to disclose their personal data in e-commerce: A reciprocity-based social exchange perspective

While personal data is invaluable to firms, the drivers of e-commerce customers' willingness to disclose their personal data remain tenuous. Using social exchange theory, we develop a model that explores the impact of consumers' perceived benefit, and relative power, on store trust, in turn driving their willingness to disclose their personal data. We collected our empirical data using a representative online survey, with the results being analyzed by using structural equation modeling. The results corroborate that (a) consumer-perceived e-commerce store trust drives their willingness to disclose their personal data, and (b) perceived e-commerce provider reciprocity outweighs consumers’ perceived data disclosure benefit, suggesting the existence of symbolic (vs. purely instrumental) social exchange.     

Dynamics of the Market for Corporate Tax‐Avoidance Advice*

This paper addresses the debate over aggressive tax‐planning models and analyzes the role of tax consultants. It focuses on the dynamic interaction between innovation and imitation of aggressive tax‐planning products and governmental tax regulation, and it highlights the importance of the length of regulatory lag in comparison with the time it takes the tax‐consulting industry to imitate newly innovated tax‐avoidance products. It reveals an alignment of interests between highly innovative tax‐consulting firms and the governmental tax legislator/regulator. The conclusions are also relevant for the policy debate on mandatory disclosure rules about aggressive tax‐planning models.     

Perseverance and suspense in tug-of-war

We study a tug-of-war game between two players using the lottery contest success function (CSF) and a quadratic cost (of effort) function. We construct a pure strategy symmetric Markov perfect equilibrium of this game, show that it is unique, and provide closed-form solutions for equilibrium strategies and values. In stark contrast to a model of tug-of-war with an all-pay auction CSF, players exert positive efforts until the very last battle in this equilibrium. We deliver a set of empirically appealing results on effort dynamics.     

纳税信用评级结果披露与研发投入

以纳税信用评级披露作为一个天然外生冲击,并基于2013—2016年1214家A股上市公司的微观数据构造准自然实验,使用双重差分法系统评估纳税信用评级结果披露对上市公司研发投入的影响。结果发现:纳税信用评级结果披露显著增加了上市公司的研发投入。基于PSM-DID方法的估计结果与上述结论无明显差异。稳健性检验也表明上述结论的正确性。机制检验表明,纳税信用评级结果披露通过降低企业的融资约束,进而促进企业增加研发投入。此外,分样本回归发现纳税信用评级结果披露只能对中小型企业和民营企业的研发投入产生促进作用。     

Is corporate environmental disclosure associated with firm value? A multicountry study of Gulf Cooperation Council firms

Several studies have found a relationship between corporate social and environmental disclosure and firm value (FV) or accounting profitability. Where environmental disclosure has been the focus, though, only single-country studies have been published, and most of the previous research concerns the developed world. This study examines the association between corporate environmental disclosure (CED) and FV in the Gulf Cooperation Council (GCC) countries, where CED has been increasing from its previous low base. Findings from a multicountry sample of 500 firm-year observations using a 55-item unweighted environmental disclosure index suggest that CED is significantly and positively related to FV as measured by Tobin's Q (TBQ). The relationship is robust to using a weighted version of the disclosure index, individual countries and environmental disclosure subindices. Some evidence of a positive relationship between CED and return on assets is also found, but even where statistically significant, the relationship is much weaker than in the case of TBQ. For empirical and theoretical reasons, we recommend that future studies pay greater attention to market-based proxies, if possible, when investigating the value relevance of CED in both developed and developing countries. Our results suggest that both managers and policymakers in GCC countries should take a positive view of expanded CED.     

The benefits and implementation of performance transparency: The why and how of letting your customers ‘see through’ your business

While some organizations swear by the benefits of transparency and are eager to learn and implement transparency practices, many managers are still reluctant or even afraid to use them. Our research reveals that only a few innovative companies have taken steps to leverage a potentially useful form of transparency: the provision of accessible and objective information to customers (e.g., sharing unbiased benchmark data, publishing unfiltered customer comments, or providing candid product reviews that may praise but also criticize the company’s products). Our study also shows that many companies remain wary and view greater calls for transparency as a challenge to be managed rather than an opportunity to be traded upon. This is partly due to limited research into the performance benefits of giving customers access to objective information, and lack of practical guidelines on how to actually implement it. This article addresses these shortcomings. First, we investigate whether performance transparency leads to customer outcomes that can be profitable for an organization and, second, we analyze the characteristics of successful transparency initiatives in a wide range of industries. Our research shows that customers exhibit more trust and are willing to pay a premium to deal with transparent businesses. Also, it uncovers seven effective strategies to leverage transparency. This article provides convincing empirical evidence for the benefits of performance transparency and the ways in which management may implement it successfully.     

Debt Overhang and Deleveraging in the US Household Sector: Gauging the Impact on Consumption

Using a novel data set for the U.S. states, this paper examines whether household debt and the protracted debt deleveraging help explain the dismal performance of U.S. consumption since 2007 in the aftermath of the housing bubble. By separating the concepts of deleveraging and debt overhang—a flow and a stock effect—we find that excessive indebtedness exerted a meaningful drag on consumption over and beyond wealth and income effects. The overall effect, however, is modest—‐around one sixth of the slowdown in consumption between 2000–06 and 2007–12—and mostly driven by states with particularly large imbalances in their household sector. This might be indicative of non‐linearities, whereby indebtedness begins to bite only when misalignments from sustainable debt dynamics become excessive.     

Predictive regressions under asymmetric loss: Factor augmentation and model selection

This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.     

一种级联两箱通用数字预失真器及其辨识算法

提出了一种由单形规范线性分段(SCPWL)函数与记忆多项式级联的数字预失真器，并给出了复数域两步最小二乘参数辨识算法。不同于以往一种预失真器适用一种功放模型的情况，所提的预失真算法利用SCPWL函数的分段特性以及记忆多项式的非线性记忆特性，在完成参数辨识的同时自动地调整结构，可适用于传统以及强非线性新型功放模型的线性化补偿。将所提预失真器分别应用于传统记忆多项式、两箱模型以及新型包络跟踪功放。经过计算机仿真，功放输出的幅频特性和频谱曲线表明所提预失真器能够有效地补偿多种功放的非线性特性。算法仿真比较结果也表明，针对包络跟踪功放，所提复数两步最小二乘算法的邻道泄漏比(ACLR)可改善约35 dB，性能优于最小均方(LMS)类算法约30 dB。     

Do significant risk warnings in annual reports increase corporate bond credit spreads? Evidence from China

Based on listed companies issuing bonds on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2017, this study analyzes the relationship between significant risk warnings in Chinese companies’ annual reports and corporate bond credit spreads. The main findings are as follows. First, in the Chinese market, “substantial warnings of significant risks” can significantly improve corporate bond credit spreads, reflecting the risk-warning effect; second, state-owned property rights weaken this effect, which only pertains to listed companies with poor risk management and low information quality; third, significant risk warnings increase investors’ heterogeneous beliefs, also affecting credit spreads; and fourth, through textual analysis, it is found that the corporate bond credit spread is greater when the disclosed risk factors are more pessimistic and less similar to those of the previous year. The findings of this paper help to enrich the literature on credit spreads and risk disclosure.