Integration of process planning and production planning and control in cellular manufacturing

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.     

Framework for making resource use decisions: An application to subdivision development

Resource use decisions such as those involving subdivision development often have been made with limited consideration of socioeconomic and physical resource impacts. Indeed, many social and environmental difficulties have stemmed from the narrow confines of decision criteria which have centered on immediate production costs with a lesser regard for physical and biological effects and social costs. How, then, do we incorporate total resource assessment into the decision making process?To date, many have suggested what must be done. Yet, few have attempted to illustrate with specific examples. The authors of this article in suggesting two major dimensions to traditional benefit cost analysis have attempted to consolidate various concepts currently developing from regional efforts in techniques for land use planning.     

NEW PRODUCT SCREENING VIA THE INTENTION-TO-BUY SCALE*

Data obtained from the intention-to-buy scale often are used for early product screening. The authors discuss current procedures to evaluate these data and indicate the minor rote that risk assessment has played. Evaluation rules that incorporate the risk factor are presented, and their usefulness for product selection is discussed.     

Managing Delphi Surveys Using Nonparametric Statistical Techniques*

Information systems researchers have often turned to a variant of the Delphi survey technique to support their research of key issues in their field. Two particular weaknesses of past studies using this approach have been a lack of a definitive method for conducting the research and a lack of statistical support for the conclusions drawn by the researchers. In this paper, the author presents a method, based on nonparametric statistical techniques, to conduct ranking-type Delphi surveys, perform analysis, and report results. The author takes this one step further by illustrating an actual analysis of a Delphi survey. The analysis is compared to results that were presented without the benefit of the author's approach. This paper shows that use of the advocated approach can streamline and strengthen studies, improve the validity of results, and thus better serve the consumers of the research findings. Since the ranking-type Delphi is so popular among information systems researchers, a consistent method is needed to apply to their data collection, analysis, and reporting of results. This paper provides such a method in concise form and illustrates the use of the method in a manner affording comparison between it and previous practice.     

The SAM Framework: Modeling the Effects of Management Factors on Human Behavior in Risk Analysis

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.     

Utility‐consistent Brand Demand Systems with Endogenous Category Consumption: Principles and Marketing Applications*

This paper introduces the design and implementation of utility‐consistent, brand, and category demand systems. It extends formal demand analysis to the area of brand and category demand, which directly concerns marketing researchers and managers. The proposed brand demand system is a set of interrelated demand functions that are derived explicitly from a utility function describing consumer preferences. The model generalizes by the integration of category expenditures, which are determined endogenously. The theoretical plausibility of the proposed demand model is demonstrated first and, subsequently, brand and category level systems are derived. Econometric methods for estimating the systems are also developed and illustrated in empirical data. The results yield empirically determined, quantitative insights into the structure of consumer demand for brands and product categories. The proposed approach has the attractive feature of structuring the interdependencies of consumer decisions and ensuring an explicit role for theory in applied research.     

Late season low inventory assortment effects in the newsvendor problem

The assumption of the newsvendor being able to satisfy demand as long as on-hand inventory is positive does not hold for a non-homogenous product. Consumers who do not find a unit of the product which satisfies their secondary features preferences may not purchase the product even though the newsvendor has positive on-hand inventory. This is likely to occur late in the season as inventory level declines. We solve a newsvendor problem in which the probability of purchase by consumers is increasing in on-hand inventory for any inventory level below that which is needed to have a complete assortment. We identify the sufficient optimality condition for the order quantity. We show that, unlike the case of inventory-dependent demand models in the literature, the optimal order quantity may decrease due to the assortment effect. We investigate two types of pre-end of season discounts, immediate all-units and delayed, as ways to mitigate the late season assortment effect and show that in some cases, they can increase the newsvendor׳s profit and free up the shelf space for other products.     

Social forecasting: An integral part of corporate planning?

The increasing need for business to monitor the social dimensions of its environment and, hopefully make some forecasts of future trends has met with some constructive response from academics and consultants although not as yet on a very liberal scale. The published literature does not indicate to what extent companies in general attemp social forecasting and, where they do, the degree of integration which exists within their corporate planning systems. The authors, therefore, decided to survey a sample of British organizations to see if they could shed some light on these issues and thereby add some information to the excellent accounts of individual cases of social forecasting in, they suspect, the more advanced and atypical companies. The survey suggests a general picture of: awareness of the value of social forecasting; fairly widespread ignorance of the techniques which do exist, primitive though these may largely be; successful integration of social forecasting into the corporate planning systems of a substantial number of organizations but not in the majority.     

Classifying capital projects for top management decision-making

This paper is an attempt to redress a perceived imbalance in the research and literature of capital project analysis. There is a plethora of work on the quantitative aspects of project analysis, yet empirical surveys show limited use of such techniques. There is limited work on the organizational processes of project selection, but there appears to be little or no work taking place on formal organizational systems for project selection.The more quantitative literature generally takes a deductive approach using a model developed from microeconomics based on the assumption that the objective of the firm is the maximization of owners' wealth. In this paper it is argued that there is a need to take an inductive approach and place the capital investment decision in its organizational setting. This paper looks at the formal capital budgeting system within the corporate setting.It is suggested that the specific capital investment decision takes place against the background of a set of policies and constraints, which are more or less explicit.The selection of corporate projects is a complex issue, but to provide some structure so that the problems can be processed by the organization, a capital budgeting system is designed. Part of this system is the classification of projects according to some criteria. It would therefore appear that the purpose of this classification system is to aid capital project selection within an organizational context.A consideration of classification systems for capital projects is undertaken, this is followed by a survey of the classification systems which have been proposed in the capital investment literature. Finally a classification system based upon specific criteria is proposed.     

An investigation of company product decision making

This article is concerned with an investigation of the approaches taken by companies in making product decisions. The first part is concerned with a review of the range of product decisions as presented within the literature. This range is established within the context of corporate planning, with a major split between long term strategic planning product decisions, and short term operational planning product decisions. The second part of the article is concerned with the results of a survey that was designed to investigate the criteria that companies use within their product decision making. These criteria included those applicable to strategic planning, but also incorporated a range of criteria applicable to short term operational planning, as proposed in a recent article by Greenley [8]. The overall conclusion to the survey results was that a common and universal approach to product decision making cannot be identified within this sample of companies. A low level of agreement as to the relative degree of importance of the criteria was evident, and, little attention to differentiating product decisions with time was also evident. The results also challenge the importance given by the literature to the concepts of product life cycle, portfolio analysis and synergy. Finally, the author suggests two implications as a consequence of these results.     

Using Cognitive Mapping in Management Research: Decisions about Technical Innovation

Case studies of firms attempting to adopt a particular type of technological innovation have demonstrated that the process of technological innovation may be mediated by decision-makers' access to knowledge and by their cognitions—reflected in belief systems. This paper highlights the importance of cognitions in decisions about technological innovation. However, cognitive processes have been under emphasized in empirical work on technological innovation and part of the problem may have been lack of availability of research tools and techniques with which to explore cognitions. Cognitive mapping methodologies are reviewed in terms of their potential to fill this gap in the research into technological innovation. The paper discusses these methodologies, evaluates their limitations and argues that a distinction should be made between cognitive maps and the output of mapping techniques. This paper concludes that cognitive mapping may provide a useful addition to existing management research tools provided researchers are clear about what is revealed by the particular methodology used.     

An integrated survey of deterministic project scheduling

There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application.     

Understanding Organizational Safety Using Value-Focused Thinking

Decision analysis is recognized as the right way to make risk management decisions, using probabilistic techniques to assess the accident risk. It is also accepted that the decisions that individuals in the organization make affect the likelihood of an accident and thus managerial and organizational factors should be included in the risk modeling process. However, decision analytic techniques have not been used to understand the decisions that are made by these individuals. The initial domain for this research is marine transportation. We use the framework of value-focused thinking in order to understand safety decisions made within our research partner organization, a major domestic oil tanker operator. We describe the results of interviews held with managers and employees from this organization. Through these interviews, we sought to understand the values these experts apply in their roles within the organization and the objectives they seek to achieve to contribute to its overall safety performance. The end result is a framework that not only portrays the fundamental objectives of safe operations for various roles in the organization, but also interconnects these different decision contexts. We believe that this approach is fundamentally different from those used in previous work and that this is an interesting application of value-focused thinking.     

Games and Mechanism Design in Machine Scheduling—An Introduction

We survey different models, techniques, and some recent results to tackle machine scheduling problems within a distributed setting. In traditional optimization, a central authority is asked to solve a (computationally hard) optimization problem. In contrast, in distributed settings there are several agents, possibly equipped with private information that is not publicly known, and these agents must interact to derive a solution to the problem. Usually the agents have their individual preferences, which induces them to behave strategically to manipulate the resulting solution. Nevertheless, one is often interested in the global performance of such systems. The analysis of such distributed settings requires techniques from classical optimization, game theory, and economic theory. The paper therefore briefly introduces the most important of the underlying concepts and gives a selection of typical research questions and recent results, focusing on applications to machine scheduling problems. This includes the study of the so‐called price of anarchy for settings where the agents do not possess private information, as well as the design and analysis of (truthful) mechanisms in settings where the agents do possess private information.     

Coordinating pricing and production decisions for multiple products

We consider a dynamic problem of joint pricing and production decisions for a profit-maximizing firm that produces multiple products. We model the problem as a mixed integer nonlinear program, incorporating capacity constraints, setup costs, and dynamic demand. We assume demand functions to be convex, continuous, differentiable, and strictly decreasing in price. We present a solution approach which is more general than previous approaches that require the assumption of a specific demand function. Using real-world data from a manufacturer, we study problem instances for different demand scenarios and capacities and solve for optimal prices and production plans. We present analytical results that provide managerial insights on how the optimal prices change for different production plans and capacities. We extend some of the earlier works that consider single product problems to the case of multiple products and time variant production capacities. We also benchmark performance of proposed algorithm with a commercial solver and show that it outperforms the solver both in terms of solution quality and computational times.     

Information Systems Management Issues: Reporting and Relevance*

Reports of key information systems issues have been published over the last two decades in many journals. Leading IS journals (e.g., MIS Quarterly, Information & Management, among others) have published key IS management issue reports every three or four years over the last 15 years, and will probably continue to provide such reports in the future. Although these reports claim to provide decisional guidance to practitioners, researchers, consultants, etc., the authors in their experience have noted concerns about their usefulness. While not questioning the validity of the methods and analysis conducted in these studies, we address two important questions in this article: the manner of reporting of the key issue results (which might be misleading), and the relevance of the results (are they providing what they intended to?). We hope that our discussion will provide new perspectives in making resource allocation decisions to both readers and authors of key issue articles.     

SIMULATING FOOD SHOPPERS' ECONOMIC LOSSES AS A RESULT OF SUPERMARKET UNAVAILABILITY*

This study illustrates a methodology as a first step toward the development of a benefit/cost model for the evaluation of the Federal Trade Commission regulation of the unavailability of advertised specials in food stores. A Monte Carlo simulation was used to estimate economic losses to shoppers from unavailable advertised specials. Product unavailability in the model occurred as a result of alternative managerial decisions about purchase-order quantities for advertised specials and shelf-stocking policies combined with probabilistic purchase decisions by customers. The model generated probabilistic individual customer and management behavioral responses to unavailability during a one-year time period. As a result, the derived economic losses to customers from unavailability were based on alternative assumptions about managerial behavior in conjunction with empirically derived shopper responses to advertised specials. This study thus provides some idea of the amount of damages being caused by the excessive unavailability of advertised specials. Aggregate customer losses were found to vary primarily with respect to management's purchase-order quantity of advertised specials.     

Pitfalls in multi-national long-range planning

The authors of this article argue that too many companies are not getting the benefits which should be produced by their long-range planning systems. Of the many possible explanations for this, the authors concentrate on the major pitfalls which should be avoided in order to ensure good results. The article is based upon the results of a survey of planning pitfalls among corporations in six industrialized countries.     

Paradoxes of Online Investing: Testing the Influence of Technology on User Expectancies*

At an increasing rate, individual investors are taking personal control over their financial destinies by investing their money online. Compared to offline do‐it‐yourself approaches, evidence suggests that investors exhibit lofty expectations and perform significantly worse after going online. However, little is understood about the mechanisms fueling expectancies, the role technologies play in their formation, or how technologies shape investment decisions. Therefore, this article explores the paradoxical nature of online investing technologies, which can give rise to a heightened state of conviction in one's capability to invest successfully. Drawing on Social Cognitive Theory, the concepts of encapsulation and combination are introduced to develop a research model describing how functional and technical self‐efficacy judgments independently and collectively shape and influence outcome expectancies. The results suggest that perceptions about what one can accomplish through online investing technologies can lead investors to exaggerate their capabilities, which, in turn, produces elevated expectancies of financial payoffs and nonmonetary rewards. These findings carry important implications. In tasks requiring both computing and functional skills, the principals of encapsulation and combination highlight the importance of comprehensively capturing self‐efficacy beliefs across skill domain boundaries. Moreover, online investing represents a paradoxical case that challenges the traditional assumption that fostering a robust sense of efficacy represents a purely noble enterprise. In fact, strong self‐efficacy beliefs can prove counterproductive, leading to severe, irreversible, and unintended consequences. Going forward, these discoveries provide a solid foundation to enhance systems designs and facilitate a deeper understanding of user psychology.     

Personal values and managerial decision-making: Evidence from a developing economy

This study attempts to investigate to what extent the personal values of managers from a developing economy affect their managerial decisions. Previous studies have suggested the relationship between values and managerial behavior. The purpose of the study was to examine this relationship in the context of a developing, less industrialized economy, identify peculiar issues given the context of the study, and discuss the managerial implications of the findings. The subjects studied were Nigerian managers, using the value survey designed by England. Results showed that values do affect behavior, but more significantly, that the cultural values of the managers play a significant role in their managerial decisions.