Statistical inference using the T index to quantify the level of comparability between accounts

The extent to which the accounts of companies are comparable is considered important to users and regulators. However, prior research has been restricted by a lack of appropriate statistical methods for testing comparability indices. This has made it difficult to assess the true level of comparability from sample data and to test research hypotheses such as whether the level of comparability (a) differs by policy, (b) differs by country, and (c) changes over time. This paper fills this gap by exploring the statistical properties of the T index. The T index generalises the H, C, I and various modifications of these indices and represents a unified framework for the measurement of the extent to which the accounts of companies are comparable. Formulae for the bias and standard error for any index under this framework are provided and proved. The bias is shown to equal zero or be negligible in most practical situations. Using historical data, the standard error is used to illustrate the accuracy with which comparability is estimated and to perform formal statistical inference using confidence intervals and p‐values. Furthermore, the sampling distribution of the T index is assessed for normality. Implications for research design and sample size determination are also discussed.     

A Cross‐Disciplinary Examination of Firm Orientations’ Performance Outcomes: The Role of Supply Chain Flexibility

Although market orientation (MO) has long been considered an important business philosophy, the examination of MO outside the firm's boundaries has been rather limited. To address this, this study explores how supply chain orientation and operational flexibility (FLX) facilitate the implementation of MO. Although the positive impact of MO on firm performance has been well established, this study highlights that such benefits are enhanced by the development of supply chain related capabilities. Results indicate that market‐oriented firms are more likely to realize the strategic importance of managing the supply chain when operating under conditions of high environmental munificence, dynamism, and complexity. This provides a better understanding of the complex relationship between the demand and supply sides of the firm. This study highlights the importance of marketing theory and concepts to supply chain management scholars, and vice versa. This further accentuates the importance of eliminating the disconnect between supply and demand‐management processes, also described as the “Great Divide” (Drucker 1973; Esper et al. 2010a,b). A number of key managerial implications are offered as well.     

The changing US–China investment relationship

The United States and China are at a turning point in their investment relationship. China’s previous investments in the United States were predominantly in government securities, while other holdings were negligible. Recently, the accumulation of treasury securities has slowed and direct investments by Chinese firms have risen steeply, with Beijing signaling greater support for portfolio investment outflows as well. This article describes the nascent shift in patterns of Chinese investment in the United States and uses the case of direct investment to examine the implications for US–China relations. We discuss current and future policy issues presented by Chinese foreign direct investment (FDI) in the United States, including national security, market access, and antitrust.     

The emergence of next generation internet users

The Internet is central to the new media, but the Internet is itself a dynamic technology that is constantly evolving as users adopt and reject new features, devices and applications and use them in ways that are often unanticipated. This article is anchored in longitudinal survey data on how Britons use the Internet, which illuminates the emergence of new patterns of accessing the Internet over multiple devices—some of which are portable—in everyday life and work. We call those who adopt this new approach ‘next generation users’. In contrast, first generation users remain anchored to one or more personal computers in the household or workplace for accessing the Internet. The analysis shows how this emerging pattern of access is reshaping the use and impact of the Internet, such as in supporting the production of user generated content. The analysis also shows how next generation access is socially distributed; creating a new digital divide that reinforces socioeconomic inequalities. Future research needs to move beyond the study of access to the Internet to track the diffusion of next generation access and its implications across a wider array of nations.     

The performance of insolvency prediction and credit risk models in the UK: A comparative study

Theoretically-driven, market-based contingent claims models have recently been applied to the field of corporate insolvency prediction in an attempt to provide the art with a theoretical methodology that has been lacking in the past. Limited studies have been carried out in order directly to compare the performance of these models with that of their accounting number-based counterparts. We use receiver operating characteristic curves to assess the efficacy of thirteen selected models using, for the first time, post-IFRS UK data; and investigate the distributional properties of model efficacy. We find that the efficacy of the models is generally less than that reported in the prior literature; but that the contingent claims models outperform models which use accounting numbers. We also obtain the counter-intuitive finding that predictions based on a single variable can be as efficient as those which are based on models which are far more complicated – in terms of variable variety and mathematical construction. Finally, we develop and test a naïve version of the down-and-out-call barrier option model for insolvency prediction and find that, despite its simple formulation, it performs favourably compared alongside other contingent claims models.     

Addressing the Advertising of Controversial Products in China: An Empirical Approach

China is a country that has undertaken a great transformation since the late 1970’s, and among these changes, has seen a massive growth in the advertising industry with the influx of foreign advertisers, and the development of regional and global media, such as satellite television and the Internet. This has resulted in the Chinese people of all ages having a greater opportunity of exposure to different types of advertising, including the advertising of potentially controversial products, which could clash with traditional Chinese values. Using a stakeholder theory approach, this study analyzes the responses of 630 Chinese respondents to discover who is offended by controversial advertisements and determine ways potentially offensive advertising messages can be reduced, thereby assisting marketers in being more socially responsible in their advertising messages.     

The impact of government intervention on the stabilization of domestic financial markets and on U.S. banks’ asset composition

The 2007–2009 financial crisis that evolved from various factors including the housing boom, aggressive lending activity, financial innovation, and increased access to money and capital markets prompted unprecedented U.S. government intervention in the financial sector. We examine changes in banks’ balance sheet composition associated with U.S. government intervention during the crisis. We find that the initial round of quantitative easing positively impacts bank liquidity across all bank samples. Our results show a positive impact of repurchase agreement market rates on bank liquidity for small and medium banks. We conclude that banks have become more liquid in the post-crisis period, especially the larger banks (large and money center banks). We show that real estate loan portfolio exposures have reverted to pre-crisis levels for money center banks and remained flat for all other bank samples.     

The Effects of Leader Succession and Prior Leader Experience on Postsuccession Organizational Performance

In this article we strive to reconcile equivocal findings about the effects of top leader succession and prior leadership experience on postsuccession organizational performance. In doing so, we draw on insights from theories of human capital, learning, and asymmetric information to better understand the conditions under which leaders increase or decrease postsuccession performance. Employing a sample of 119 newly appointed leaders in the English Premier League (1996–2010), we find the following results. First, relating to the succession event, outside leaders that directly move between leadership positions are associated with higher postsuccession performance while the departure of a prior leader to a leadership position in another organization has a negative effect on postsuccession performance. Second, relating to prior leadership experience, leaders with domestic top leader experience are associated with lower postsuccession performance, while leaders with foreign top leader experience are associated with higher postsuccession performance. © 2015 Wiley Periodicals, Inc.     

Co‐movements in commodity prices: a note based on network analysis

This article analyses co‐movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co‐movement of the commodity prices in our time sample, however from mid‐2008 to the end of 2009 co‐movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co‐movement during the sampled period.     

Predicting Corporate Bankruptcy: An Evaluation of Alternative Statistical Frameworks

Corporate bankruptcy prediction has attracted significant research attention from business academics, regulators and financial economists over the past five decades. However, much of this literature has relied on quite simplistic classifiers such as logistic regression and linear discriminant analysis (LDA). Based on a large sample of US corporate bankruptcies, we examine the predictive performance of 16 classifiers, ranging from the most restrictive classifiers (such as logit, probit and linear discriminant analysis) to more advanced techniques such as neural networks, support vector machines (SVMs) and “new age” statistical learning models including generalised boosting, AdaBoost and random forests. Consistent with the findings of Jones et al. ( 2015 ), we show that quite simple classifiers such as logit and LDA perform reasonably well in bankruptcy prediction. However, we recommend the use of “new age” classifiers in corporate bankruptcy modelling because: (1) they predict significantly better than all other classifiers on both the cross‐sectional and longitudinal test samples; (2) the models may have considerable practical appeal because they are relatively easy to estimate and implement (for instance, they require minimal researcher intervention for data preparation, variable selection and model architecture specification); and (3) while the underlying model structures can be very complex, we demonstrate that “new age” classifiers have a reasonably good level of interpretability through such metrics as relative variable importances (RVIs).