The Value of Stock Options To Non-Executive Employees

This study empirically investigates the value employees place on stock options using information from the option exercise behavior of individuals. Employees hold options for another period if the value from holding them and reserving the right to exercise them later is higher than the value of exercising them immediately and collecting a profit equal to the stock price minus the exercise price. This simple model implies the hazard describing employee exercise behavior reveals information about the value to employees of holding options another time period. We show the parameters of this model are identified with data on multiple option grants per employee and we apply this model to the disposition of options received in the 1990s by a sample of over 2000 middle-level managers from a large, established firm outside of manufacturing. Exercise behavior is modeled using a random effects probit model of monthly exercise behavior that is estimated using simulated maximum likelihood estimation methods. Our estimates show there is substantial heterogeneity (observed and unobserved) among employees in the value they place on their options. Our estimates show most employees value their options at a value greater than the option’s Black-Scholes value

New Data for Answering Old Questions Regarding Employee Stock Options

This paper is a description and summary of existing questions and sources of data on stock options with an emphasis on two issues; what are the issues surrounding stock options in the national accounts and what value do employees place on stock options? We survey many existing data sources and outline some of the ways these data can be used to answer questions about the use and impact of employee stock options. The data sources include administrative records from individual firms, survey data of employee perceptions, disclosure filings with the SEC and other government, nonprofit, and international sources. We explore ways to investigate the value of options to employees and their cost to the firms using data on employee exercise decisions. Finally, we discuss the implications of our findings for public policy, the reporting of stock options, and how options are considered in the national accounts

Employees’ Choice of Method of Pay

Who chooses what type of pay? The costs and benefits of “flexible” and “cafeteria-style” benefit plans have been discussed for some time. Additionally, many papers have considered the potential costs and benefits of certain types of pay plans (e.g. salaries versus piece rates). In this paper, we use detailed data from a specific firm that annually set the total compensation level for each of its employees but then did something extremely unusual. At the start of each pay year, the firm set an exchange rate for the dollar trade-off between cash pay and stock option pay. It then gave every employee nearly complete choice over the fraction of their pay that was contingent (stock options, bonus) versus guaranteed (salary). There are several empirical findings. There is substantial variation in the choice of contingent pay with some workers choosing almost all base pay and others choosing almost entirely stock options. Younger employees, more experienced employees, higher paid employees, and male employees are more likely to allocate a larger fraction of their total compensation to at-risk alternatives. The robustness of these results varies somewhat depending on the empirical specification and set of covariates used

The Value of Stock Options to Non-Executive Employees

This study empirically investigates the value employees place on stock options using information from the option exercise behavior of individuals. Employees hold options for another period if the value from holding them and reserving the right to exercise them later is higher than the value of exercising them immediately and collecting a profit equal to the stock price minus the exercise price. This simple model implies the hazard describing employee exercise behavior reveals information about the value to employees of holding options another time period. We show the parameters of this model are identified with data on multiple option grants per employee and we apply this model to the disposition of options received in the 1990s by a sample of over 2000 middle-level managers from a large, established firm outside of manufacturing. Exercise behavior is modeled using a random effects probit model of monthly exercise behavior that is estimated using simulated maximum likelihood estimation methods. Our estimates show there is substantial heterogeneity (observed and unobserved) among employees in the value they place on their options. Our estimates show most employees value their options at a value greater than the option's Black-Scholes value.

Jesus and the Parables: A Compelling Oral Training Tool

https://place.asburyseminary.edu/firstfruitspapers/1034/thumbnail.jp

Process Mining Concepts for Discovering User Behavioral Patterns in Instrumented Software

Process Mining is a technique for discovering “in-use” processes from traces emitted to event logs. Researchers have recently explored applying this technique to documenting processes discovered in software applications. However, the requirements for emitting events to support Process Mining against software applications have not been well documented. Furthermore, the linking of end-user intentional behavior to software quality as demonstrated in the discovered processes has not been well articulated. After evaluating the literature, this thesis suggested focusing on user goals and actual, in-use processes as an input to an Agile software development life cycle in order to improve software quality. It also provided suggestions for instrumenting software applications to support Process Mining techniques

Gas dynamics in interacting and merging galaxies.

In this dissertation I develop a three dimensional model of the dynamics of gas clouds in interacting galaxies. The gas clouds move under the combined gravitational influence of two galaxies passing close to each other. By performing a multipole expansion of the gravitational field I am able to include the effects of self-gravity within a galaxy. This also allows me to model the case in which the two galaxies merge. The gas clouds are allowed to interact with one another by colliding. They either coalesce to form a larger cloud or are disrupted, depending on their relative kinetic energy as compared to the total gravitational binding energy of the two-cloud system. Various cases are considered in this dissertation by varying such parameters as impact parameter, inclination of the gaseous disk of a galaxy to the orbital plane of the two, interacting galaxies, relative velocity of the galaxies, the mass ratio of the galaxies, and the presence of gas in the second galaxy. As the strength of the interaction increases the more disturbed the interstellar medium becomes. The clouds collide at an increased rate and with larger velocities so that the fraction of collisions which disrupt the clouds rises as the strength of the interaction increases. The region of the galaxy where increased rates of collision are induced also becomes more and more concentrated toward the center of the galaxy. Since interacting galaxies are observed to have elevated star formation rates, I conclude that the star formation induced by the interaction of two galaxies is related to the high velocity, disruptive cloud-cloud collisions. Monitoring the amount of gas mass involved in such collisions allows me to estimate the star formation rate and the luminosity produced by these stars. Considering parameters such as inclination, bound and unbound orbits, the mass of the perturbing galaxy, and the possible presence of gas in both galaxies, I find that the scatter in observations of the infrared luminosity to gas mass ratio can be explained

Discrete Data Assimilation in the Lorenz and 2D Navier--Stokes Equations

Consider a continuous dynamical system for which partial information about its current state is observed at a sequence of discrete times. Discrete data assimilation inserts these observational measurements of the reference dynamical system into an approximate solution by means of an impulsive forcing. In this way the approximating solution is coupled to the reference solution at a discrete sequence of points in time. This paper studies discrete data assimilation for the Lorenz equations and the incompressible two-dimensional Navier--Stokes equations. In both cases we obtain bounds on the time interval h between subsequent observations which guarantee the convergence of the approximating solution obtained by discrete data assimilation to the reference solution

IT-Enabled Services as Complex Adaptive Service Systems: A Co-Evolutionary View of Service Innovation

One specific type of service innovation of particular interest to IT and business professionals is IT-Enabled Services (IES). Previous studies have suggested many roles for IT in service innovations. IT has proven a useful tool in service innovation. IT is an important component of most services in many industries, including healthcare, financial services, engineering, and management consulting. However, little work has been conducted in IESs. Thus, there is considerable potential for researchers in IS, operations, marketing, and economics to make contributions to the emerging debates and challenges in IESs and service innovation. Two topics are critically important in both IES research and practice: what IESs are and how such services emerge and evolve. This research-in-progress attempts to offer a novel perspective on these two topics. Drawn upon complexity theory, we conceptualize services (IESs) as complex adaptive service systems (CASS) with such properties and behaviors as emergence, self-organization, adaptive learning, and nonlinearity, and service development or innovation as a co-evolutionary process composed of variation, selection, and retention (VSR). From this perspective, IESs produce and are reproduced by the environment (or by wide business networks). Based on this complexity theory perspective, we also provide propositions regarding what IESs are, how they emerge and evolve, and what strategies are effective for IT-enabled eservice innovation. The last section offers a research plan for a longitudinal case study of Business Analytics (BA) as an IES to qualify the proposed theoretical perspective