Indexing and Stock Price Efficiency

Indexing has experienced substantial growth over the last two decades because it is an effective way of holding a diversified portfolio while minimizing trading costs and taxes. In this article, we focus on one negative externality of indexing: the effect on the efficiency of stock prices. Based on a sample of large and liquid US stocks, we find that greater indexing leads to less efficient stock prices, as indicated by stronger post‐earnings‐announcement drift and greater deviations of stock prices from the random walk. We conjecture that reduced incentives for information acquisition and arbitrage induced by indexing and passive trading are probably the main causes for degradation in price efficiency.     

An Approach for Determining Optimal Product Sampling for the Diffusion of a New Product

Free samples are an effective means for introducing and promoting a new product. However, product sampling is also expensive. As a result, careful consideration must be given to the question of how many samples should be distributed. To encourage product adoption in any target market, a company needs to determine the “right” amount of sampling. In other words, a firm needs to determine the optimal number of samples that must be available for trial by the innovators, early adopters, and other key consumers who influence the adoption rate of the new product. With too few samples, the product might not reach enough of these key consumers to generate the word-of-mouth recommendations necessary for market success. On the other hand, offering too many free samples is a waste of a company's resources. Dipak Jain, Vijay Mahajan, and Eitan Muller propose a framework for determining the optimal levels of product sampling. In addition to identifying the upper bounds for the sampling levels of both durable and nondurable products, their model identifies the optimal size of product sampling based on such parameters as the coefficients of innovation and imitation, market potential, discount rate, and gross margin. Several observations are made regarding the relationships between the optimal sampling level and the various parameters used in the model. For example, a high sampling level is not appropriate for a product with a high coefficient of innovation. On the other hand, if a product has a high coefficient of imitation, the sampling level should be high because a significant number of trials are necessary for word of mouth to be effective. High sampling levels are also indicated by a high discount rate or gross margin. For durable goods, the optimal level of neutral sampling (i.e., sampling that does not specifically target innovators and early adopters) rarely exceeds 5%, and the maximum level is 7%. The optimal target sampling level is always higher than the corresponding neutral case, but, in most cases, only marginally so. For the parameter ranges chosen in this article, the maximum level for target sampling is approximately 9%. However, it is important to note that the theoretical upper bounds are no more than benchmarks for the maximum possible level of sampling. In practical situations, the optimal level may be considerably lower than these upper bounds. In such cases, the actual values will depend on the values for the various parameters used in the model.     

Agility and flexibility in international business research: A comprehensive review and future research directions

This study explores 134 articles on agility and flexibility research published in the top-nine international business (IB) journals. Accordingly, we critically analyze, map and structure flexibility and agility research in IB, and synthesize the findings into an integrative framework. The paper identifies a wide range of definitions of the concept and a lot of work on its conceptualization. However, studies at the individual and institutional levels of analyses are scarce, and the concept is under-theorized, as there is a dearth of real theoretical underpinnings in this research stream. Thus, in addressing this gap, more qualitative and interdisciplinary research is needed.     

Understanding the quality–quantity conundrum of customer referral programs: effects of contribution margin,extraversion, and opinion leadership

Firms can substantially profit from customer referrals, but they must understand the different stages of the referral process to determine what drives the number of referrals (first stage), conversion (second stage), and average contribution margin per referral (third stage). Applying a framework that integrates perceptual and behavioral drivers, this study uses a financial services company’s customer survey and transaction data to investigate how the effect of contribution margins of referring customers at all three stages depends on their perceived extraversion and opinion leadership. Extreme extraversion and opinion leadership diminish the positive effect of the contribution margins of referring customers on the number of referrals; their effect on the number of successful referrals is insignificant. In terms of the contribution margin of successful referrals, extraversion has a negative and opinion leadership a positive moderating effect.     

Risky short positions and investor sentiment: Evidence from the weekend effect in futures markets

This paper examines the weekend effect in futures markets and presents rational and behavioral reasons for its existence. Specifically, we document a weekend effect (Friday's return minus the following Monday's return) in futures markets. The weekend effect occurs partly because of asymmetric risk between long and short positions around weekends; the weekend effect increases when short positions are relatively more risky. In addition, we find that both lagged and contemporaneous changes in investor sentiment are related to the weekend effect. These results are consistent with the investor sentiment literature that finds that mood improves on Fridays but deteriorates on Mondays.     

Environmental performance and bank lending: Evidence from unlisted firms

Growing public concerns about sustainability and adopting environmentally responsible practices increase risks as well as opportunities for firms and banks. It is unclear whether being environmentally responsible matters for unlisted firms, which are significant contributors to the degradation of the environment but which are not under strict scrutiny like public listed firms. Using a sample of 3915 firms from developing economies, we investigate whether the superior environmental performance of unlisted firms leads them to better loan conditions. After controlling for endogeneity and sample selection bias, we find that firms with better environmental performance received approximately 6.4% higher loans (as a ratio of total sales) and that this effect is more prominent in small and medium firms. This finding supports an information asymmetry view of agency costs. Our results, however, show that environmental performance does not affect loan duration and collateral requirement, indicating no spillover economic effect of corporate environmental performance on loan conditions. This partially supports a new perspective of legitimacy theory in relation to the ‘greenwash strategy’. Overall, our study shows that strategically engaged environmental activities that are integrated with core business objectives represent an important business strategy for firms to enhance credit access.     

Restructuring in Telecommunications and its Market Impacts: An Event-Study Analysis

This study presents an assessment of the changes in the telecommunications industry and their impact on market returns. Events were identified from a sample of global telecom companies and assessed in terms of their favorable or unfavorable impacts. Based on event-study analysis with generalized autoregressive conditionally heteroskedastic specification, the impact was tested after incorporating dummy variables of different lengths. The results show interesting patterns in how the market views restructuring in the business model of telecom companies, organizational structure, alliances and mergers, and technological platform changes. Countries differ in how they view telecoms restructuring and what changes are considered beneficial by investors.     

Business analytics: Why now and what next?

Business analytics is a revolution that is impossible to miss. At its core, business analytics is about leveraging value from data. Instead of being referred to as the ‘sludge of the information age,’ data has recently been deemed ‘the new oil.’ While data can be employed for purposes such as detecting new opportunities, identifying market niches, and developing new products and services, it is also notoriously amorphous and hard to extract value from. In this Guest Editors’ Perspective, we first present a structural framework for deriving value from business analytics. Extracting value from data requires aligning strategy and desirable behaviors to business performance management in conjunction with analytic tasks and capabilities. We then introduce three special articles that provide in-depth insights regarding how business analytics is being employed in the management of healthcare, accounting, and supply chains.     

The information content of stock splits

We develop a new methodology that controls for both the timing of annual earnings news (Asquith et al., 1989) and the performance prior to split announcements (Barber and Lyon, 1996) to evaluate the information content of stock splits. In contrast to existing evidence, we find that stock splits in aggregate are followed by positive abnormal future earnings growth, suggesting that stock splits contain information about future, rather than past, operating performance. When we use changes in breadth of institutional ownership as a new metric of information content to corroborate our findings, we find that splits with the greatest increase in breadth experience positive post-split abnormal returns and positive abnormal earnings growth. Together, our results suggest that some splits contain positive information about future performance, and that sophisticated market participants such as institutional investors are able to select these splits.