Yahel Giat

Investment Under Uncertainty, Heterogeneous Beliefs and Agency Conflicts

We develop a structural model to investigate the effects of asymmetric beliefs and agency conflicts on dynamic principal--agent relationships. Optimism has a first-order effect on incentives, investments, and output, which could reconcile the private equity puzzle. Asymmetric beliefs cause optimal contracts to have features consistent with observed venture capital and research and development (R&D) contracts. We derive testable implications for the effects of project characteristics on contractual features. We calibrate our model to data on pharmaceutical R&D projects and show that optimism indeed significantly influences project values. Permanent and transitory components of risk have opposing effects on project values and durations. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Optimal spares allocation to an exchangeable-item repair system with tolerable wait

In a multi-location, exchangeable-item repair system with stochastic demand, the expected waiting time and the fill rate measures are oftentimes used as the optimization criteria for the spares allocation problem. These measures, however, do not take into account that customers will tolerate a reasonable delay and therefore, a firm does not incur reputation costs if customers wait less than their tolerable wait. Accordingly, we generalize the expected waiting time and fill rate measures to reflect customer patience. These generalized measures are termed the truncated waiting time and the window fill rate, respectively. We develop efficient algorithms to solve the problem for each of the criteria and demonstrate how incorporating customer patience provides considerable savings and profoundly affects the optimal spares allocation.

Asynchronous learning sources in a high‐tech organization

Purpose – The purpose of this study is to characterize learning from asynchronous sources among research and development (RD extent of source usage; employee satisfaction with these sources and the effect of the sources on the workplace.Design/methodology/approach – A total of 120 R&D employees of a high‐tech firm were administered questionnaires consisting of open‐ended and close‐ended questions regarding different features of asynchronous learning.Findings – The study finds that a synchronous sources are highly utilized by employees and are used both for general‐purpose learning and solving specific problems. Despite the high usage and satisfaction from these sources, we do not find evidence to support the creation of an expert community of practice.Research limitations/implications – The research is limited to a single, albeit large, firm. Possibly, in different organizational, cu...

Optimizing Spare Battery Allocation in an Electric Vehicle Battery Swapping System

Electric vehicle battery swapping stations are suggested as an alternative to vehicle owners recharging their batteries themselves. To maximize the network’s performance spare batteries must be optimally allocated in these stations. In this paper, we consider the battery allocation problem where the criterion for optimality is the window fill rate, i.e., the probability that a customer that enters the swapping station will exit it within a certain time window. This time is set as the customer’s tolerable wait in the swapping station. In our derivation of the window fill rate formulae, we differ from previous research in that we assume that the swapping time itself is not negligible. We numerically analyse the battery allocation problem for a hypothetical countrywide application in Israel and demonstrate the importance of estimating correctly customers’ tolerable wait, the value of reducing battery swapping time and the unique features of the optimal battery allocation.

A computational analysis of R&D support programs

We compare two common government R&D support programs, R&D tax credits and direct R&D grants. To study their effectiveness and the extent to which their design matters, we analyze these programs within a dynamic equilibrium model of imperfectly competitive industries. Adopting comprehensive welfare measures that take into account government, producer and consumer surpluses, we find that both schemes exhibit positive social returns. Mid-range R&D-intensive sectors exhibit higher social returns than either high or low R&D-intensive sectors. Both incentive schemes generate positive measures of R&D input additionality of magnitudes consistent with empirical R&D research. However, R&D grants that require firms to allocate subsidy funds to R&D spur less R&D than a more flexible R&D tax credit. Subsidy schemes can even induce competing firms to over-spend on R&D, generating negative producer surplus and possibly negative social returns.We compare two common government R&D support programs, R&D tax credits and direct R&D grants. To study their effectiveness and the extent to which their design matters, we analyze these programs within a dynamic equilibrium model of imperfectly competitive industries. Adopting comprehensive welfare measures that take into account government, producer and consumer surpluses, we find that both schemes exhibit positive social returns. Mid-range R&D-intensive sectors exhibit higher social returns than either high or low R&D-intensive sectors. Both incentive schemes generate positive measures of R&D input additionality of magnitudes consistent with empirical R&D research. However, R&D grants that require firms to allocate subsidy funds to R&D spur less R&D than a more flexible R&D tax credit. Subsidy schemes can even induce competing firms to over-spend on R&D, generating negative producer surplus and possibly negative social returns.

A Risk Management Model for an Academic Institution's Information System

We develop and apply a two-step decision support model for investing in information technology security focusing on breaches that originate from system users. In the first step we map the risk level of each of the system’s components with the aim of identifying the subsystems that pose the highest risk. In the second step we determine how much to invest in various technological tools and workplace culture programs to enhance information security. We describe an application of this model to an information system in an academic institution in Israel. This system comprises ten subsystems and we identify the three that bear the most risk. We use these findings to determine the parameters of the investment allocation problem and find the optimal investment plan. The results of our application indicate that hacking for the purpose of cheating is a greater threat than other types of security issues. Additionally, we find support to the claim that information security officials tend to overinvest in security technological tools and underinvest in improving security workplace culture.

Supplier Selection and Assessment by University Procurement Officers

Supplier selection and assessment is at the core of the procurement process. This study investigates how procurement officers in Israels universities select and assess their suppliers. The authors explore which information channels officers use to assess suppliers and find that incidental and informal information sources are the most frequently used followed by official sources. The authors examine the criteria used by officers to select suppliers and identify quality and price as significantly more important than most other criteria. Finally, the authors do not find strong evidence that officers categorize suppliers to key and non-key suppliers according to the universitys goals.

Fuzzy Logic and Chaos Theory in Time Series Forecasting

This paper presents a method of time series forecasting based on the integration of fuzzy logic and chaos theory. The proposed method has two stages. On the first stage, we consider the time series as a dynamic system and using the methods of mutual information and false nearest neighbors, as a part of applied chaos theory, we reconstruct the phase portrait corresponding to the original time series. On the second stage, we are learning the neuro fuzzy network as a model of time series forecasting using the vectors points of reconstructed phase portrait. We consider all the formalisms necessary for understanding the method and present the results of two computer experiments proving the ability of fuzzy inference accuracy increasing using the selection of optimal parameters of time delay and phase portrait dimension.

Optimal allocation of spares to maximize the window fill rate in a two-echelon exchangeable-item repair system

Abstract We solve the spares allocation problem in a two-echelon, exchangeable-item repair system in which the lower echelon comprises multiple locations and the higher echelon is a single depot. We assume that customers tolerate a certain wait and therefore the optimization criterion is the window fill rate, i.e., the expected portion of customers who are served within the tolerable wait. We develop two algorithms to solve this problem. The first algorithm (FTEA) is formula-based and is suboptimal. The second algorithm (HTEA) combines simulations into the first algorithm and obtains a higher degree of accuracy at the cost of extra running time. We characterize the near-optimal solution by its degree of pooling and concentration. Pooling happens when spares are allocated to the depot and are therefore shared by all the lower-echelon locations. Concentration takes place when spares are allocated to only a few lower-echelon locations whereas the other lower-echelon locations receive no spares. We use numerical examples to compare the algorithms and to illustrate how the budget, shipment time, local repair and customer patience affect the optimal solution and degree of pooling in varying ways. Using the numerical results, we propose a third algorithm (ETEA) that obtains HTEA’s output in 30% of the time.

A location model for boycotting with an application to kosher certification

Abstract We develop a one-sided location model to predict the ethical behavior of firms in a market with consumer boycotting. Consumers’ ethical level is distributed along a line segment and they purchase only at firms that conform to their ethical consciousness. Firms maximize profits by choosing their ethical level. To capture the boycotting phenomena we make two assumptions. First, that firms are driven by profits and not ethical considerations. Second, that if consumers deem a firm to be engaged in unethical activity, then they refuse to purchase from it even products that are not the result of this unethical behavior. We develop the profit-maximization necessary conditions for equilibrium and show that when consumers are uniformly distributed then the equilibrium – if it exists – is unique. We solve the model for the uniform distribution case and show that firms will distribute symmetrically – but not uniformly – around the center location. Additionally, we demonstrate how the effectiveness of boycotts diminishes as the number of firms increases. We apply the model to the issue of restaurant kosher certification in Israel. In our application, kosher-keeping customers are boycotting non-certified restaurants since they generally refuse to dine in these restaurants even menu items that are kosher. We derive the relationship between the percent of kosher-keeping consumers and the equilibrium number of certified restaurants. Using population and restaurant data from Israel’s eight largest cities we estimate the implied cost of certification and the relative purchasing power of kosher-keeping customers.