bluuebunny/crossref_metadata_2025_split huggingface dataset:
Are Risk-Attitudes Related Across Domains and Response Modes?
Authors: Schoemaker Paul J. H. 
Published: November 2008

This paper examines experimentally the nature of people's risk-attitudes across different payoff domains and response modes. Only simple gambles are examined, entailing just two monetary outcomes. The main issue of interest is to what extent risk-preferences in one domain or response mode predict anything (beyond chance) about risk-preferences in another domain or mode. Three domains are examined: gain, mixed and loss. The three response modes used are certainty equivalence (CE), probability equivalence (PE) and outcome equivalence (OE) judgments. In general, weak associations were found among ordinal risk-preferences within-subjects across domains, especially with respect to losses. To make the parametric responses (i.e., the CE, PE and OE judgments) comparable across domains and subjects, linear as well as utility-based risk-measures were examined. In the gain and loss domains, the linear risk-premia measures exhibited higher CE-PE correlations (within domain) than the utility-based measures. Using a multitrait-multimethod comparison, the highest correlations were found within domains across response modes. The main findings are (1) strong risk-aversion for gain and mixed gambles, (2) risk-seeking for symmetric loss gambles, although less pronounced, (3) low correlation of risk-preferences within subjects across domains, (4) high convergent validity of response methods within domain, and (5) increased risk-aversion for loss (but not gain) gambles when using real payoffs.
A Simulation Analysis of Factors Influencing the Attractiveness of Group Technology Cellular Layouts
Authors: Morris John S. , Tersine Richard J. 
Published: November 2008

Group Technology (GT) is a multi-faceted approach to batch production that includes the reconfiguration of plant equipment from a functional layout to a series of product-oriented layouts that are referred to as manufacturing cells. The cells are dedicated to process families of parts that have similar machine operations. The purported benefits of GT over traditional functional layouts range from reduced work-in-process inventory and throughput times to increased worker satisfaction and productivity. However, recent simulation studies challenge some of these claims of superior performance for cellular layouts. This research examines the influence that factors in a firm's operating environment have on the performance of cellular layouts. A simulation model using hypothetical shop data is used to compare a process layout to a cellular layout using mean throughput time and mean level of work-in-process inventory as performance measures. The operating variables analyzed are (1) the ratio of setup to process time, (2) transfer time of material between work centers, (3) demand stability, and (4) the flow of work within cells. None of the individual changes in levels of operating variables produced a clear advantage for cellular layouts. However, the results from these experiments were used to postulate an “ideal” environment for cellular layouts. This environment is characterized as having a high ratio of setup to process time, stable demand, unidirectional flow of work within a cell, and a substantial level of material movement times between process departments. When all of these conditions are present, the cellular layout outperforms the process layout on both performance measures.
Conflicting Interests in the Timing of Jobs
Authors: Ackere Ann Van 
Published: November 2008

We study a situation where jobs of unknown duration (e.g., surgical procedures) are performed sequentially in a single facility (e.g., a hospital operating room). This facility can be any resource (material or human) that is in limited supply. Due to the uncertain duration of jobs, the time at which the facility will be available for the next job is unknown. Given the existing schedule, a starting time is selected for the next job. The scheduler's task is complicated because a job necessitates the presence of (at least) one individual (e.g., the surgeon), called the agent. We model this situation as a game between the scheduler and the agent. The scheduler trades off the cost associated with keeping the facility idle between jobs against the cost of keeping the agent waiting. The agent trades off his waiting cost against his lateness cost. We determine the conditions under which it is necessary for the scheduler to take the agent's behavior into account. We introduce moral hazard by assuming that the agent's arrival time is random and compare this to the case where the agent selects a deterministic arrival time.
Nondeterministic Polling Systems
Authors: Srinivasan Mandyam M. 
Published: November 2008

A nondeterministic polling system is considered in which a single server serves a number of stations. The service discipline at each station is, consistently, either nonexhaustive, semiexhaustive, gated, or exhaustive. If the server polls a station i which uses either the nonexhaustive or the semiexhaustive service discipline, then the next station polled is station j with probability pij if there was service at station i. The service time at station i is a random variable which may depend on the station polled next. If no service is performed at station i, then the next station polled is station j with probability eij. The time to switch between stations i and j is a random variable which may depend on whether service was performed at station i or not. If the server polls a station i that follows either the exhaustive service discipline or the gated service discipline, then the next station polled is station j with probability pij regardless of whether there was service at station i or not. Cycle times and stability conditions are derived for this system, and Conservation Laws are obtained which express a weighted sum of the mean waiting times in terms of known data parameters. For systems with a mix of exhaustive and gated service stations, we show how the individual mean waiting times can be obtained.
Dispersive Equity and Social Risk
Authors: Fishburn Peter C. , Sarin Rakesh K. 
Published: November 2008

Dispersive equity is concerned with the impact of life-threatening risks from alternative policy decisions on homogeneous groups in a population. It is not addressed to the disutility of various numbers of fatalities that might occur, but rather to how fatalities are distributed over the groups. Although dispersive equity has long been recognized as an important component of some policy decisions, it has received little formal treatment within the matrix of salient factors for such decisions. Our purpose is to advance its formal development. This is done within a formulation based on probability distributions over potential fatality sets. The formulation gives rise to four distinct but not independent equity concepts: individual risk equity, group risk equity, dispersive equity, and social outcome equity. Each of these is analyzed, but special attention is given to dispersive equity. The paper also comments on relationships between total equity and its four components, and between total equity and the disutility of various numbers of fatalities.
The Output Process of Serial Production Lines of General Machines with Finite Buffers
Authors: Hendricks Kevin B. , McClain John O. 
Published: November 2008

Little is known about the interaction among manufacturing subsystems in a factory. The output of one manufacturing subsystem is usually the input to one or more others in the plant. For example, a production line may provide input to another manufacturing stage, a shipping system, or an automated parts conveyor. In all of these examples, the characteristics of the output from the production line can affect the subsequent process. This paper examines the output process of a serial production line of N machines with general processing time distributions and finite buffer capacities. Simulation is used to examine the effects of line length, buffer capacity, and buffer placement on the inter-departure distribution and correlation structure (autocorrelation function) of the output process of the production line. Results from this analysis are useful in setting production line design parameters and in determining the extent to which buffer placement can be used to control the variability of the output process, and thereby the amount of work-in-process present in downstream subsystems. Additional insights are provided to help explain why small buffers in production lines are normally adequate and to help us better understand the effects of buffers on tightly coupled production systems. By using a variety of processing time distributions, previously unknown effects attributed to skew of processing time are revealed. Since skew can often be reduced or eliminated by operator training, these effects are of particular interest since they can help to quantify some of the benefits of training.
Direct Estimation of Synergy: A New Approach to the Diversity-Performance Debate
Authors: Davis Rachel , Thomas L. G. 
Published: November 2008

This study examines the linkages between relatedness and synergy in the context of diversification among U.S. pharmaceutical firms for the period 1960–1980. Rather than assume (as in the entropy, Herfindahl and concentric indices of diversification) that the levels of synergy generated by different related combinations of business units are identical, we estimate synergy directly using a modified version of the concentric index. In addition to estimating synergy using capital market performance of the firm as a whole, we examine the effects of nondrug diversification on the innovative productivity of firms' pharmaceutical divisions alone. Our two main findings are that production relatedness, such as that between drugs and chemicals, in fact did not imply synergy over the period of our study; and that the patterns of synergy for different types of relatedness shifted over time with the industry life cycle.
Decision Rules for Buffer Inventories
Authors: Bonini Charles P. 
Published: November 2008

This paper presents the derivation of decision rules for determining the amount of each item to produce and hold in inventory in a multi-product factory. Under certain conditions the rules are good approximations to optimal minimum cost solutions. The model assumes that production is determined for all the items at the beginning of the production period. It uses as a framework a decision rule for the determination of aggregate inventory; this aggregate rule is based upon the approximation of factory cost by a quadratic cost function. A total inventory cost function, based upon the aggregation of the individual item rules, is derived.
A Taxonomy of Manufacturing Strategies
Authors: Miller Jeffrey G. , Roth Aleda V. 
Published: November 2008

This paper describes the development and analysis of a numerical taxonomy of manufacturing strategies. The taxonomy was developed with standard methods of cluster analysis, and is based on the relative importance attached to eleven competitive capabilities defining the manufacturing task of 164 large American manufacturing business units. Three distinct clusters of manufacturing strategy groups were observed. Though there is an industry effect, all three manufacturing strategy types are observed in various industries. The two main dimensions along which the manufacturing strategy groups differ are the ability of the firms in them to differentiate themselves from competition with their products and services, and the scope of their product lines and markets. A general method for mapping manufacturing strategies on these dimensions is described. For each manufacturing group, the relationships between the competitive capabilities (which describe the manufacturing task), the business context (the business unit strategy), manufacturing activities (manufacturing strategy choices), and manufacturing performance measures are explored and compared.
The Effect of Leadtime Uncertainty in a Simple Stochastic Inventory Model
Authors: Song Jing-Sheng 
Published: November 2008

We study a basic continuous-time single-item inventory model where demands form a compound Poisson process and leadtimes are stochastic. The performance measure of interest is the long-run average cost. Order costs are linear, so a base-stock policy is optimal. We focus on the behavior of the optimal base-stock level in response to stochastically larger or more variable leadtimes. We also investigate the behavior of the corresponding long-run average costs. We show that a stochastically larger leadtime requires a higher optimal base-stock level. However, a stochastically larger leadtime may not necessarily result in a higher optimal average cost, because sometimes the variability effects may dominate. On the other hand, a more variable leadtime always leads to a higher optimal average cost. The effect of leadtime variability on optimal policies depends on the inventory cost structure: A more variable leadtime requires a higher optimal base-stock level if and only if the unit penalty (holding) cost rate is high (low). Similar results regarding the effect of leadtime demand are also discussed. In this latter case, the compound Poisson assumption is not necessary.
Solving Large-Scale Tour Scheduling Problems
Authors: Jarrah Ahmad I. Z. , Bard Jonathan F. , deSilva Anura H. 
Published: November 2008

For a given planning horizon, workforce composition and set of labor requirements, personnel scheduling often reduces to solving three problems. The first is concerned with the assignment of days off; the second involves assigning workers to shifts during the day; and the third involves the construction of weekly tours. In many manufacturing facilities, tour scheduling is easy because the start and end times of shifts are invariant, and no work takes place on the weekend. But when daily patterns vary, such as in the airlines, processing, and public service industries, and when part-timers make up a portion of the workforce, the complexity of the overall problem increases dramatically. This paper presents a new methodology for solving the combined shift and days-off scheduling problem when the labor requirements span less than 24 hours per day. We begin with an integer programming formulation and then introduce a set of aggregate variables and related cuts. When the aggregate variables are fixed the original problem decomposes into seven subproblems (one for each day of the week) that are much easier to solve. A partial enumeration scheme and a heuristic for ensuring feasibility are employed to find upper and lower bounds which converge rapidly to near-optima. The methodology is applied to tour scheduling at general mail facilities (GMFs). These facilities are located in most urban areas and process millions of mail pieces daily for local and regional distribution. The model accounts for the principal constraints in the U.S. Postal Service labor contract, including half-hour breaks, minimum full-time to part-time ratios, and variable start times. Also considered are four and five day work weeks, and the possibility of assigning workers across labor categories. A full analysis of the Providence, Rhode Island facility is presented.
The Invention of the Independence Condition for Preferences
Authors: Fishburn Peter , Wakker Peter 
Published: November 2008

This paper discusses the history and interrelations of three central ideas in preference theory: the independence condition in decision under risk, the sure-thing principle in decision under uncertainty, and conjoint independence for multiattribute decisions and consumer theory. Independence was recognized as an important component of decision under risk in the late 1940s by Jacob Marschak, John Nash, Herman Rubin, and Norman Dalkey, and first appeared in publication in Marschak (Marschak, J. 1950. Rational behavior, uncertain prospects, and measurable utility. Econometrica 18 111–141.) and Nash (Nash, J. F. 1950. The bargaining problem. Econometrica 18 155–162.). The sure-thing principle can be credited to Savage (Savage, L. J. 1953. Une Axiomatisation du Comportement Raisonnable Face à l'Incertitude. Colloq. Internal. Centre National Rech. Sci. 40 Econométrie 29–40; Savage, L. J. 1954. The Foundations of Statistics. Wiley, New York (2nd edn., Dover, New York, 1972.). Conjoint independence for consumer theory was introduced by Sono (Sono, M. 1943. The effect of price changes on the demand and supply of separable goods (in Japanese). Kokumin Keisai Zasshi 74 1–51.) and Leontief (Leontief, W. W. 1947a. A note on the interrelation of subsets of independent variables of a continuous function with continuous first derivatives. Bull. Amer. Math. Soc. 53 343–350; Leontief, W. W. 1947b. Introduction to a theory of the internal structure of functional relationships. Econometrica 51 361–373.); a form of it can also be recognized in Samuelson (Samuelson, P. A. 1947. Foundations of Economic Analysis. Harvard University Press, Cambridge, MA.), presented earlier in Samuelson (Samuelson, P. A. 1940. Foundations of analytical economics, the observational significance of economic theory. Ph.D. dissertation, Harvard University, Boston, MA.). Independence and the sure-thing principle are equivalent for decision under risk, but in a less elementary way than has sometimes been thought. The sure-thing principle for decision under uncertainty and conjoint independence are identical in a mathematical sense. The mathematics underlying our three preference conditions has an older history. The independence condition for decision under risk can be recognized in the characterization of “associative means,” and conjoint independence for multiattribute decisions in solutions to the “generalized associativity functional equation.”
Organizational Consultant: Creating a Useable Theory for Organizational Design
Authors: Baligh Helmy H. , Burton Richard M. , Obel Børge 
Published: November 2008

Organization theory is a positive science; organizational design is a normative science “concerned with how things ought to be, with devising structures to attain goals.” The Organizational Consultant is a knowledge base expert system to help design organizations. That is, it takes facts about the environment, size, strategy, technology, ownership, and management preferences and applies the knowledge base to recommend the design structure and properties such as complexity, formalization, centralization, and span of control, among others. Organization theory is comprised of numerous positive contingency theories, which are not integrated. The main issue is to create a comprehensive and consistent knowledge base from what we know, i.e., create a useful synthesis. We utilize four fit criteria as a guide: contingency fit, design parameter fit, situation fit, and total parameter fit. Contingency fit demands that the knowledge base of “if-then” rules follow what we know from the literature. Design parameter fit requires a balance, or weighting, among the supporting and opposing design recommendations. Situation fit assures us that the situation itself is not inconsistent. Finally, total design fit requires that it is useable and helpful to recommend structure and properties to attain goals. The development of the Organizational Consultant is a continuing validation exercise. The size of an organization is an important design contingency. Yet, an operational definition of size for design purposes has been wanting. We discuss how a useful definition of size was developed for the Organizational Consultant. We describe the development of the Organizational Consultant—a knowledge-based expert system that utilizes a synthesis of the elements of organizational contingency, theory through a validation process. The four fit criteria were applied to guide the development process.
Learning in Setups: Analysis, Minimal Forecast Horizons, and Algorithms
Authors: Tzur Michal 
Published: November 2008

We analyze the dynamic lot-sizing model in which the cost of a setup depends on the number of setups that have occurred prior to it. This arises, for example, when there exist learning effects in setups. Our model is more general than most learning models in the literature since it allows the total setup cost to be a general nondecreasing (but not necessarily concave) function of the number of setups. We explore tight relationships between our model and special cases of the classical dynamic lot-sizing model. On the basis of these we find minimal forecast and planning horizons for our model, which determine the first decision when the model is solved on a rolling horizon basis. When a forecast horizon cannot be found, we provide guidelines regarding the optimal first decision. We also provide an algorithm to solve the finite horizon problem, which uses as sub-problems variations of the classical dynamic lot-sizing problem. The advantage of this approach is the ability to use the extensive literature available on the latter, to generalize the results of this paper. As many of our results are qualitative in nature, they provide insights which can be useful for other models with a similar setup cost behavior.
Delays in New Product Introductions and the Market Value of the Firm: The Consequences of Being Late to the Market
Authors: Hendricks Kevin B. , Singhal Vinod R. 
Published: November 2008

This paper empirically estimates the impact of not meeting promised new product introduction dates on the market value of the firm. We estimate the average “abnormal” change in the market value for a sample of 101 firms around the date when information about delaying the introduction of new products is publicly announced. On average, delay announcements decrease the market value of the firm by 5.25%. The average dollar change in the market value in 1991 dollars is $−119.3 million. The evidence suggests that there are significant penalties for not introducing new products on time. To provide further insight, regression analyses are used to identify factors that influence the direction and magnitude of the change in market value. We find that the competitiveness of the industry in which the firm operates, the size of the firm, and the firm's degree of diversification are statistically significant predictors for the change in the market value of firms that announce delays in the introduction of new products.