Deals not done: Sources of failure in the market for ideas

Using novel survey data on technology licensing, we report the first empirical evidence linking the three main sources of failure emphasized in the market design literature (lack of market thickness, congestion, lack of market safety) to deal outcomes. We disaggregate the licensing process into three stages and find that, although lack of market thickness and deal failure are correlated in the first stage, they are not in the latter stages, underscoring the bilateral monopoly conditions under which negotiations over intellectual property often occur. In contrast, market safety is only salient in the final stage. Several commonly referenced bargaining frictions (congestion) are salient, particularly in the second stage. Also, universities and firms differ in the stage during which they are most likely to experience deal failure. Copyright © 2014 John Wiley & Sons, Ltd.     

Study of kite string injuries in Western India

A prospective analysis of 104 patients (outdoor and indoor) with manja (powdered glass coated kite string) injury from January 2011 to January 2015 was carried out at Civil Hospital Ahmedabad. All patients were analysed for mode and severity of injury, site of injury, associated injuries, activity being performed when injury occurred, the clinical diagnosis and treatment required. Analysis of collected data revealed that majority of the injuries occurred while driving or in pedestrians with the neck being the most commonly affected body part. Males were more commonly affected with most of the victims in the age group of 16–45 years. Injuries sustained while driving tended to be more severe. All injuries were recorded in the month of January. No deaths were reported, but potentially fatal injuries did occur. Most of the injuries were superficial and could be prevented or mitigated by either protective clothing or by use of protective devices on vehicles, which should be implemented to reduce the morbidity of such injuries in the future. There were no ethical issues or vested interests associated with the study.     

Non-market economic valuation in developing countries: Role of participant observation method in CVM analysis

Developing countries have high proportion of black money and related corruption in the society in comparison to the developed ones. This aspect has to be kept in mind while conducting contingent valuation method (CVM) questionnaire survey (in-person) at the site whose economic valuation is being done. Participant observation method (POM) and unstructured interview schedule (UIS) are the two means, which must be used in addition to structured interview schedule during CVM studies in developing countries to arrive at a reasonable non-market economic valuation figure of an environmental amenity. It has been observed that researchers generally ignore this fact during survey for primary data collection among respondents who are quite well off, educated and belong to countries of huge parallel economy. However in the present study, we have utilized these two means during primary data collection for a CVM study and reached the conclusion that CVM has to be used with caution even among educated masses in the developing countries.     

A new multivariate count data model to study multi-category physician prescription behavior

Multivariate count models represent a natural way of accommodating data from multiple product categories when the dependent variable in each category is represented by a positive integer. In this paper, we propose a new simultaneous equation multi-category count data model–the Poisson-lognormal simultaneous equation model–that allows for the Poisson parameter in one equation to be a function of the Poisson parameters in other equations. While generally applicable to any situation where simultaneity is an issue and the dependent variables are measured as counts, such a specification is particularly useful for our empirical application where physicians prescribe drugs in multiple categories. Accounting for the endogeneity of detailing in such situations requires us to explicitly allow for pharmaceutical firms’ detailing activities in one category to be influenced by their activities in other categories. Estimation of such a system of equations using traditional maximum likelihood method is cumbersome, so we propose a simple solution based on using Markov Chain Monte Carlo methods. Our simulation study demonstrates the validity of the solution algorithm and the biases that would result if such simultaneity is ignored in the estimation process.     

Development and application of the Leadership Archetype Questionnaire

The leadership assessment questionnaire (LAQ) is a 360 degree survey instrument designed to help organizational leaders identify their own style of leadership and formulate appropriate development objectives. It is designed to provide avenues for development of an executive team in which multiple leadership archetypes are represented. The LAQ is based on eight leadership archetypes – strategist, change-catalyst, transactor, builder, innovator, processor, coach, and communicator. These archetypes are representations of ways of leading in a complex organizational environment. In this article, we discuss the development, design, and psychometric analysis of the LAQ. We detail the conceptual foundations of the questionnaire and the psychometric methods used to confirm the validity and reliability of the instrument. We conclude with avenues for future research.     

The impact of investor protection law on corporate policy and performance: Evidence from the blue sky laws

Recent studies have debated the impact of investor protection law on corporate behavior and value. I exploit the staggered passage of state securities fraud statutes (“blue sky laws”) in the United States to estimate the causal effects of investor protection law on firm financing decisions and investment activity. The statutes induce firms to increase dividends, issue equity, and grow in size. The laws also facilitate improvements in operating performance and market valuations. Overall, the evidence is strongly supportive of theoretical models that predict investor protection law has a significant impact on corporate policy and performance.     

The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks

We measure the volatility information content of stock options for individual firms using option prices for 149 US firms and the S&P 100 index. We use ARCH and regression models to compare volatility forecasts defined by historical stock returns, at-the-money implied volatilities and model-free volatility expectations for every firm. For 1-day-ahead estimation, a historical ARCH model outperforms both of the volatility estimates extracted from option prices for 36% of the firms, but the option forecasts are nearly always more informative for those firms that have the more actively traded options. When the prediction horizon extends until the expiry date of the options, the option forecasts are more informative than the historical volatility for 85% of the firms. However, at-the-money implied volatilities generally outperform the model-free volatility expectations.     

Insider trading in takeover targets

We examine open market stock trades by registered insiders in about 3700 targets of takeovers announced during 1988–2006 and in a control sample of non-targets, both during an ‘informed’ and a control period. Using difference-in-differences regressions of several insider trading measures, we find no evidence that insiders increase their purchases before takeover announcements; instead, they decrease them. But while insiders reduce their purchases below normal levels, they reduce their sales even more, thus increasing their net purchases. This ‘passive’ insider trading holds for each of the five insider groups we examine, for all three measures of net purchases, and is more pronounced in certain sub-samples with less uncertainty about takeover completion, such as friendly deals, and deals with a single bidder, domestic acquirer, or less regulated target. The magnitude of the increase in the dollar value of net purchases is quite substantial, about 50% relative to their usual levels, for targets' officers and directors in the six-month pre-announcement period. Our finding of widespread profitable passive trading by target insiders during takeover negotiations points to the limits of insider trading regulation. Finally, our finding that registered insiders of target firms largely refrain from profitable active trading before takeover announcements contrasts with prior findings that insiders engage in such trading before announcements of other important corporate events, and points to the effectiveness of private over public enforcement of insider trading regulations.     

Investigating brand preferences across social groups and consumption contexts

Using a unique dataset on U.S. beer consumption, we investigate brand preferences of consumers across various social group and context related consumption scenarios (??scenarios??). As sufficient data are not available for each scenario, understanding these preferences requires us to share information across scenarios. Our proposed modeling framework has two main building blocks. The first is a standard continuous random coefficients logit model that the framework reduces to in the absence of information on social groups and consumption contexts. The second component captures variations in mean preferences across scenarios in a parsimonious fashion by decomposing the deviations in preferences from a base scenario into a low dimensional brand map in which the brand locations are fixed across scenarios but the importance weights vary by scenario. In addition to heterogeneity in brand preferences that is reflected in the random coefficients, heterogeneity in preferences across scenarios is accounted for by allowing the brand map itself to have a discrete heterogeneity distribution across consumers. Finally, heterogeneity in preferences within a scenario is accounted for by allowing the importance weights to vary across consumers. Together, these factors allow us to parsimoniously account for preference heterogeneity across brands, consumers and scenarios. We conduct a simulation study to reassure ourselves that using the kind of data that is available to us, our proposed estimator can recover the true model parameters from those data. We find that brand preferences vary considerably across the different social groups and consumption contexts as well as across different consumer segments. Despite the sparse data on specific brand-scenario combinations, our approach facilitates such an analysis and assessment of the relative strengths of brands in each of these scenarios. This could provide useful guidance to the brand managers of the smaller brands whose overall preference level might be low but which enjoy a customer franchise in a particular segment or in a particular context or a social group setting.     

Visual representation of knowledge networks: A social network analysis of hospitality research domain

Intellectual relationships and collaboration networks are the basis for the development of a knowledge domain. The visual representation of such “knowledge networks” contributes to the overall understanding of intellectual collaborations in a particular knowledge domain. Based on the co-authorship data from recent journal publications over a period of five years, the authors applied social network analysis to explore the network structures and identify their network properties in the hospitality research domain. The analysis revealed the core and peripheral networks where the power law distribution was observed on the pattern of publishing academic papers. The overall network was further examined by nine research streams in both “global” and “contextual” views to understand a broad variety of the collaboration patterns of hospitality researchers.