bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quality Improvement and Learning in Productive Systems
Authors: Fine Charles H. 
Published: November 2008

Recent interest in product quality suggests that effort devoted to improving the quality of manufactured products may reduce unit costs. This conjecture—that improving quality can lower costs—challenges the traditional assumption that unit costs increase with increased quality assurance activities and has significant implications for quality management. By introducing the idea of a quality-based learning curve, this paper links the previously disjoint literatures of quality control and learning curves to explain why high quality and low costs need not be inconsistent. When costs are affected by a quality-based learning curve, product quality favorably influences the rate of cost reduction due to learning. Thus, costs decline more rapidly with the experience of producing higher quality products. Two formulations of the quality-based learning phenomenon are presented. The first assumes that quality-based experience affects direct manufacturing costs. For this formulation, the optimal quality level is decreasing over time, but is always larger than the optimal base-case quality level. The optimal production quantity is constant if the interest rate is zero and increasing in time when the interest rate is positive. The second formulation assumes that quality-based experience affects quality control costs. In this case, the optimal quality level is always increasing over time. The optimal quantity behavior is qualitatively similar to the first formulation. A key feature of the second quality-based model is that it resolves the controversy between the economic conformance level model of Juran, which asserts that one should use cost-tradeoff analysis to find the optimal quality level, and the claims of Deming and Crosby, that zero defects is always the optimal quality level. For certain parameter values, the optimal quality policy in the second model conforms to the economic conformance level model but the dynamics of the model demonstrates the optimality of always pushing towards zero defects.
The Decision-Making Paradigm of Organizational Design
Authors: Huber George P. , McDaniel Reuben R. 
Published: November 2008

This paper introduces and explicates the decision-making paradigm of organizational design. We argue that the domains of existing design paradigms are declining in scope, and that the nature of current and future organizational environments requires use of a design paradigm that responds to the increasing frequency and criticality of the decision-making process. In particular, we argue that the decision-making paradigm is applicable when the organizational environments are hostile, complex, and turbulent. The focal concept of the decision-making paradigm is that organizations should be designed primarily to facilitate the making of organizational decisions. The paper sets forth the paradigm's six major concepts and discusses the principal domains of its application. The paper also examines the relationships between the decision-making paradigm and the literatures on (1) organizational decision making, (2) the information processing view of organizations, and (3) the need for compatibility between the organization's design and the design of its technologically supported information systems. The paper concludes by identifying ten organizational design guidelines that follow from the decision-making paradigm.
Kanban, MRP, and Shaping the Manufacturing Environment
Authors: Krajewski Lee J. , King Barry E. , Ritzman Larry P. , Wong Danny S. 
Published: November 2008

There has been a great deal of interest recently in the Japanese approach to manufacturing, growing out of a concern for finding ways to reduce inventories and increase productivity. At this project's inception, its objective was to assess whether the kanban system could perform well in the manufacturing environments found in this country. Based on observations from managers visiting Japan, the project was enlarged to also assess which factors in a production environment have the biggest impact on performance—regardless of the system in use. Guided by a panel of production and inventory managers from diverse plant environments, a comprehensive list of factors thought most important to manufacturing effectiveness was constructed. The panel established low and high values for each one. These settings were considered representative of the range experienced in U.S. plant environments. The factor settings allowed a variety of representative plants to be tested with a large scale simulator. Results show that kanban, when implemented in certain environmental settings, does indeed perform exceptionally well. However, so do the more traditional systems used in the United States. Conversely, there are other plant environments in which all systems perform much worse. This suggests that the factors themselves are the keys to major improvement. Simultaneously reducing setup times and lot sizes is found to be the single most effective way to cut inventory levels and improve customer service. Shop factors of particular importance are yield rates and worker flexibility. Degree of product standardization and the product structure are also high impact factors. Less crucial than earlier believed, at least over the factor settings simulated, are inventory record inaccuracy, equipment failures, and vendor reliability. Such results suggest that the selection of a production/inventory system can be of less importance than the improvement of the manufacturing environment itself.
Lottery Dependent Utility
Authors: Becker Joao L. , Sarin Rakesh K. 
Published: November 2008

In this paper we propose a model for decision making under risk that is capable of predicting empirically observed preference patterns that have been found to be incompatible with the expected utility model. The model departs from the classical expected utility model by allowing utilities to depend on the lottery. The dependence of utilities on the lottery being evaluated is achieved by restricting the utility measure to a convenient parametric family of functions. The idea then is to use each lottery to determine a specific parameter value thus characterizing the utility function for each particular lottery. The expected value of this lottery dependent utility function provides the overall measure of preference. The model retains the properties of transitivity, stochastic dominance, and continuity. It also permits types of analyses, such as exploitation of basic attitudes toward risk through risk aversion properties, that have been found useful in decision theory. The primary use of our model is in descriptive or predictive research and applications. For some decision makers who wish to retain the preference patterns that are incompatible with the substitution principle, even after the implications of their choices are made transparent, our model could be of prescriptive use as well.
Comparing Hierarchical and Nonhierarchical Weighting Methods for Eliciting Multiattribute Value Models
Authors: Stillwell William G. , von Winterfeldt Detlof , John Richard S. 
Published: November 2008

A value tree relating general values and concerns to specific value relevant attributes was constructed to compare three energy options: nuclear, coal, and a combined geothermal and conservation package. Thirty-seven nonexpert subjects provided judgments of the relative importance of attributes in the tree using both hierarchical and nonhierarchical weighting procedures, and they rated the energy options on all attributes and all levels of the tree. From these importance weights and ratings several additive multiattribute value models were constructed and compared with holistic rankings and ratings of the three options. The experiment had three basic findings: First, hierarchical weights were steeper (higher weight ratios) than nonhierarchical weights. Second, groups that differed in their holistic first choice nevertheless showed substantial agreement in their assessment of attribute weights. Third, attribute level ratings of the relative desirability of energy options also agreed rather well across groups, although there was a tendency for each group to favor their holistic first choice. This convergence of multiattribute value model parameters resulted in a “common model” that was most consistent with holistic evaluations of the pro-conservation group, and generally inconsistent with those of the pro-nuclear group. This third finding of differential consistency between model composites and holistic evaluations is interpreted as a result of weight parameter distortions due to social desirability and/or a neglect to consider attribute value ranges when making weight judgments.
Diffusion and Advertising: The German Telephone Campaign
Authors: Simon Hermann , Sebastian Karl-Heinz 
Published: November 2008

The goal of the present paper is to investigate the influence of advertising on the diffusion of new telephones in West Germany. Several alternative ways of integrating advertising into the well-known Bass-diffusion-model are suggested and empirically tested. The econometric investigation yields results which are consistent with the behavioral assumption. A model which assumes that advertising mainly influenced the demand of imitators is accepted as the most valid representation of reality. The lag structure of advertising response was best captured by a Nerlove-Arrow-model. Advertising attained its maximum effect after several months. A cumulative measure of the total advertising effect is suggested and quantified. Directions for potential generalizations are discussed.
A Sequential Model of R&D Investment Over an Unbounded Time Horizon
Authors: Hopp Wallace J. 
Published: November 2008

A Markov model of sequential R&D investment, where successful firms are assumed to have an advantage in related follow-on R&D, is formulated and a solution approach is given. Under this assumption, profit maximizing firms must consider the effect of R&D investments on their future market position as well as the direct monetary returns from innovation. Under certain conditions, free entry is shown to lead to excessive competition and overinvestment by the firms. This market failure can be corrected through a three-part policy of restricted patent lives, subsidies to firms for consecutive successes, and entry taxes. In addition to these policy conclusions, the modeling and solution approaches presented here provide a framework for further research efforts to incorporate market position into project selection and budget allocation models.
Performance Evaluation of State-Owned Enterprises in Theory and Practice
Authors: Ramamurti Ravi 
Published: November 2008

This study explores the goal orientation of state-owned enterprises (SOEs) with a view to develop a behavioral theory of SOEs. It is set in India, where as in many other countries the government expects SOEs to promote the “public interest” rather than maximize profits. The research design consisted in searching for patterns in the subjective evaluations of a set of Indian SOEs by critical environmental actors (senior bureaucrats and influential journalists). The study attempted to get at each respondent's “espoused theory” for performance evaluation as well as his or her “theory-in-use,” and compared both with official goals as well as the prescriptions of welfare economists. Five models of performance evaluation, varying in criteria and weighting schemes, were considered. The results showed—with surprising consistency—that commercial profitability was the most important criterion that explained bureaucrats' subjective evaluations. Lack of comprehensive information seemed to accentuate their reliance on profitability—but not by very much. For a minority of bureaucrats (Type 1), the more important explanation seemed to be their “incorrect” belief that SOEs could be judged like private firms, official policy notwithstanding. For the majority (Type 2), who espoused views consistent with official policy, the explanation seemed to be conceptual confusion or double standards. Both types also behaved as if they would like SOEs to maximize profitability rather than just break even or earn a reasonable return. Some of these findings were true for responding journalists as well. Given these results, managers of Indian SOEs can be expected to seek profits not only to reduce financial dependence on government but also to gain a measure of external legitimacy. Recognizing the importance of profitability as a criterion-in-use, they can be expected to propose strategies that would increase their firm's profitability and resist those that would reduce it, regardless of official goals. Where managers are free to act independently, profitability may prevail as the dominant decision criterion, but where they are not, the outcome may depend on more complex factors. More generally, the profit motive in SOEs may be as strong or stronger than it appeared to be in India in countries with (a) less sophisticated administrative systems or personnel; (b) an official ideology more to the right than in “socialist” India; and (c) a higher proportion of mixed enterprises. The paper concludes with the implications of these findings for the design of performance evaluation systems at the government-SOE interface.
Parallel Machine Scheduling: Processing Rates Dependent on Number of Jobs in Operation
Authors: Dror Moshe , Stern Helman I. , Lenstra Jan Karel 
Published: November 2008

We treat the class of n job − m machine scheduling problems with job processing times dependent on the number of jobs being simultaneously processed in the system at any point in time. Such systems occur when jobs are assigned to multiple parallel processors driven by a common power source. In situations typical of hydraulic and pneumatic power sources the level of power delivered to each processor is inversely proportional to the number of processors simultaneously at work. Aside from the variable processing rate assumptions, the remaining assumptions on the structure of the system conform to those of the standard identical parallel processor problem without job preemption. Although the standard n job − m machine problem is NP-hard with respect to a makespan measure, this is not the case when our seemingly complicating variable processing rate function, typical of hydraulic power sources, is included. In this case our main results are exceedingly simple. The makespan is found to be independent of the job-machine assignment, and the flowtime is minimized using one out of m processors. When other job processing rate functions or constant switch-over times are considered, then solving the problem becomes increasingly difficult, and the use of multiple processors is recommended. This paper concludes with a description of a real-world problem (scheduling the refueling of navy boats) which motivated this research.
Marketing-Production Decisions in an Industrial Channel of Distribution
Authors: Eliashberg Jehoshua , Steinberg Richard 
Published: November 2008

This paper presents a model that considers the interface between marketing and production decisions in a channel of distribution of industrial goods comprised of a manufacturer and a distributor. The key issue investigated is the nature of the coordination within the channel in light of an unstable pattern of seasonal demand. The investigation, which focuses on dynamic issues, considers production activities such as product delivery and inventory policy, and their link to marketing strategies such as pricing policies. The focus here is on the dynamic nature of the coordinational aspects of the various policies. For example, the following questions are addressed: What is the distributor's pricing strategy throughout the season? What is the nature of the contractual price in the channel? Under what conditions should the distributor carry no inventory throughout the seasonal period? Under what conditions should the manufacturer carry no inventory? What is the impact of the seasonal parameters and differing holding and processing costs upon the various policies of the distribution channel? We propose a mechanism to address these issues, and we provide explicit answers to these questions.
Determining Safety Stock in the Presence of Stochastic Lead Time and Demand
Authors: Eppen Gary D. , Martin R. Kipp 
Published: November 2008

We consider the problem of setting safety stock when both the demand in a period and the lead time are random variables. There are two cases to consider. In the first case the parameters of the demand and lead time distributions are known; in the second case they are unknown and must be estimated. For the case of known parameters a standard procedure is presented in the literature. In this paper, examples are used to show that this procedure can yield results that are far from the desired result. A correct procedure is presented. When the parameters are unknown, it is assumed that a simple exponential smoothing model is used to generate estimates of demand in each period and that a discrete distribution of the lead time can be developed from historical data. A correct procedure for setting safety stocks that is based on these two inputs is given for two popular demand models. The approach is easily generalized to other models of demand. Safety stock calculation is simplified when certain normality assumptions are valid. Simulation results in the Appendix indicate when these assumptions about normality are reasonable.
Decision Support System Effectiveness: A Review and an Empirical Test
Authors: Sharda Ramesh , Barr Steve H. , McDonnell James C. 
Published: November 2008

Despite the increasing popularity of decision support systems (DSS), effectiveness of such systems remains unproven. Past research claiming usefulness of the DSS has relied largely on anecdotal or case data. The relatively few laboratory experiments report mixed results regarding the effects of a decision aid. This study reviews the results of prior investigations and examines the effectiveness of DSS-aided decision makers relative to decision makers without a DSS over an eight-week period. An executive decision making game was used in two sections of a business strategy course. Three-person teams in one section used a DSS while the teams in the other section played the game without such an aid. Various measures of decision quality were recorded. Overall, the groups with access to the DSS made significantly more effective decisions in the business simulation game than their non-DSS counterparts. The DSS groups took more time to make their decisions than the non-DSS groups at the beginning of the experiment. However, the decision times converged after the third week. The DSS teams reported investigating more alternatives and exhibited a higher confidence level in their decisions than the non-DSS groups, but these differences were not statistically significant.
State-Level Efforts to Transfer Manufacturing Technology: A Survey of Programs and Practices
Authors: Wyckoff Andrew W. , Tornatzky Louis G. 
Published: November 2008

This study analyzed state-level university-based efforts to increase manufacturing productivity through the transfer of technologies, such as robotics and microcomputers, to manufacturing establishments. A survey was conducted by phone interview of 15 state programs that were operating in 1985. Information was gathered on the goals, planning, budgets, marketing, staffing, organizational structure, technical focus, and evaluation practices of the programs. All of the programs were university-based, typically attached to the engineering schools of land grant public universities. Programs generally fell into three types: (1) active programs, which included activities that ranged from technology needs assessment to consultation assistance; (2) broker programs, which provided limited direct assistance, but put industrial clients in touch with people who could; and (3) passive programs, which focused on providing information services, such as data base searches. Major issues of development and operation of the programs included: conflicts with the academic context, difficulties in keeping technically up to date and problems in retaining quality staff. A significant strategic and program design issue was how to balance intensive and specialized services with the need to respond to the heterogeneous needs of a broad clientele. Few of the programs had adequate planning and evaluation, perhaps contributing to their difficulties.
Information Technology and Organizational Change: Causal Structure in Theory and Research
Authors: Markus M. Lynne , Robey Daniel 
Published: November 2008

This article concerns theories about why and how information technology affects organizational life. Good theory guides research, which, when applied, increases the likelihood that information technology will be employed with desirable consequences for users, organizations, and other interested parties. But what is a good theory? Theories are often evaluated in terms of their content—the specific concepts used and the human values served. This article examines theories in terms of their structures—theorists' assumptions about the nature and direction of causal influence. Three dimensions of causal structure are considered—causal agency, logical structure, and level of analysis. Causal agency refers to beliefs about the nature of causality: whether external forces cause change, whether people act purposefully to accomplish intended objectives, or whether changes emerge unpredictably from the interaction of people and events. Logical structure refers to the temporal aspect of theory—static versus dynamic—and to the logical relationships between the “causes” and the outcomes. Level of analysis refers to the entities about which the theory poses concepts and relationships—individuals, groups, organizations, and society. While there are many possible structures for good theory about the role of information technology in organizational change, only a few of these structures can be seen in current theorizing. Increased awareness of the options, open discussion of their advantages and disadvantages, and explicit characterization of future theoretical statements in terms of the dimensions and categories discussed here should, we believe, promote the development of better theory.
Defensive Marketing Strategies: An Equilibrium Analysis Based on Decoupled Response Function Models
Authors: Kumar K. Ravi , Sudharshan D. 
Published: November 2008

The entry of a new product (attacker) into a competitive market is likely to provoke responses from some or all of the existing products (defenders). This paper investigates the development of optimal defensive strategies based on an understanding of the possible reactions of all the defenders to an optimal attack. Following Lane (Lane, W. J. 1980. Product differentiation in a market with endogenous sequential entry. Bell J. Econom. 11(1, Spring) 237–260.) we assume that N products each enter sequentially with perfect foresight on subsequent entry. Then, based on new technology, an unanticipated attacker enters. The N defenders respond in price but not position according to Lane's model. Once this equilibrium is obtained, advertising and distribution response functions scale sales. We show that under these decoupled response function models of advertising and distribution, uniformly-distributed tastes, and nonincreasing market size, the optimal defense for all existing brands is to decrease their respective prices, advertising, and distribution. Those qualitative results are consistent with recommendations by Hauser and Shugan (Hauser, J. R., S. M. Shugan. 1983. Defensive marketing strategies. Marketing Sci. 2(4, Fall) 319–360.) who used related, but different, consumer response models and a different equilibrium assumption.