The Individually Responsible and Rational Decision Approach to Economic Lot Sizes for One Vendor and Many Purchasers

Banerjee's [2] joint economic lot size (JELS) model, along with related works by Monahan [12] and Lal and Staelin [10], represents one approach to minimizing the total inventory carrying and ordering costs of a vendor and his purchaser(s). Noting that JELS philosophy requires a coordinated system and that its practical implementation is problematic, we present an alternative approach to the same problem: the individually responsible and rational decision (IRRD) approach. The IRRD approach is consistent with a free enterprise system and easy to implement. In order to show that the IRRD approach is also more economical than the JELS approach, we first build a more refined JELS model for the case of one vendor and many identical purchasers. Drawing on earlier criticisms of specific JELS models, our refinement relaxes the lot-for-lot assumption commonly used by JELS scholars. To be comparable with earlier works, we retain the assumption of deterministic conditions and demonstrate the economic advantages of IRRD over JELS through a numerical example. An algebraic proof of IRRD's superiority over JELS is offered in the more general and realistic case of a vendor dealing with K nonidentical purchasers with reasonably predictable annual demand but uncertain order quantities and timings.     

Economic Production Lot Sizing with Periodic Costs and Overtime*

Traditional approaches for modeling economic production lot‐sizing problems assume that a single, fixed equipment setup cost is incurred each time a product is run, regardless of the quantity manufactured. This permits multiple days of production from one production setup. In this paper, we extend the model to consider additional fixed charges, such as cleanup or inspection costs, that are associated with each time period's production. This manufacturing cost structure is common in the food, chemical, and pharmaceutical industries, where process equipment must be sanitized between item changeovers and at the end of each day's production. We propose two mathematical problem formulations and optimization algorithms. The models' unique features include regular time production constraints, a fixed charge for each time period's production, and the availability of overtime production capacity. Experimental results indicate the conditions under which our algorithms' performance is superior to traditional approaches. We also test the procedures on a set of lot‐sizing problems facing a national food processor and document their potential economic benefit.     

Vendor Selection with Bundling: A Comment*

In a recent article by Rosenthal, Zydiak, and Chaudhry (1995), a mixed integer linear programming model was introduced to solve the vendor selection problem for the case in which the vendor can sell items individually or as part of a bundle. Each vendor offered only one type of bundle, and the buyer could purchase at most one bundle per vendor. The model employed n(m+ 1) binary variables, where n is the number of vendors and m is the number of products they sell. The existing model can lead to a purchasing paradox: it may force the buyer to pay more to receive less. We suggest a reformulation of the same problem that (i) eliminates this paradox and reveals a more cost-effective purchasing strategy; (ii) uses only n integer variables and significantly reduces the computational workload; and (iii) permits the buyer to purchase more than one bundle per vendor.     

A Game-Theoretic Approach to Quantity Discount Problems*

The traditional quantity discount problem is analyzed from the perspective of game theory, including both noncooperative and cooperative models. For the noncooperative case, the Stackelberg equilibrium is derived. For the cooperative case, the Pareto Optimality criteria are used to find a group of optimal strategies. Both scenarios are illustrated through an example which quantifies the benefits resulting from cooperation between the buyer and the seller for game-theoretic solutions using geometric programming.     

A Profit‐Maximizing Approach to Disposition Decisions for Product Returns*

Motivated by the asset recovery process at IBM, we analyze the optimal disposition decision for product returns in electronic products industries. Returns may be either remanufactured for reselling or dismantled for spare parts. Reselling a remanufactured unit typically yields higher unit margins. However, demand is uncertain. A common policy in many firms is to rank disposition alternatives by unit margins. We propose a profit‐maximization approach that considers demand uncertainty. We develop single period and multiperiod stochastic optimization models for the disposition problem. Analyzing these models, we show that the optimal allocation balances expected marginal profits across the disposition alternatives. A detailed numerical study reveals that our approach to the disposition problem outperforms the current practice of focusing exclusively on high‐margin options, and we identify conditions under which this improvement is the highest. In addition, we show that a simple myopic heuristic in the multiperiod problem performs well.     

On Extending Russell and Krajewski's Algorithm for Economic Purchase Order Quantities*

Russell and Krajewski presented an optimal purchase order quantity algorithm that considered the effect of the transportation rate structure for less-than-truckload (LTL) shipments. The authors applied the Russell and Krajewski algorithm to a variety of freight classes and lengths-of-haul. Anomalous cases were found in which the freight rate schedule, when used with the suggested algorithm, resulted in incorrect order size decisions. In this comment, the authors consider the impact of these anomalies on the optimal order quantity and associated total costs. A procedure is presented to adjust the Russell and Krajewski algorithm to arrive at the optimal purchase order quantity and the lowest total annual cost.     

Decision Processes for Developing Strategic Applications of Information Systems: A Contingency Approach*

Strategic applications of information systems (IS) are considered by IS researchers to be determined by contextual factors such as environmental uncertainty, and influenced by attributes of the processes preceding them, such as planning and top management support. For better management of the process leading to these applications, it is essential to understand the relationship between process attributes and contextual factors. Utilizing a contingency approach, this article takes a step toward such an understanding. Based on successful strategic IS applications from 81 large companies, it examines the relationship between the context of these applications and the decision-making process leading to them. The results indicate that the external environment is related to whether a rational or political decision-making process is used. The IS function seems to influence the use of the decision process implied by IS researchers, one in which the top management champions the strategic application, while the IS managers contribute by conducting in-depth analysis. However, the organization structure was not related to any decision process attribute. The implications of these findings for future research and practice are also discussed.     

The Selection of Computer-Aided Software Engineering Tools: A Multi-Criteria Decision Making Approach

The selection of the appropriate computer-aided software engineering (CASE) tools to suit the needs of an organization requires the systematic application of the multi-criteria decision methodology (MCDM). In order to make a case for the use of MCDM, the application of the ELECTRE I method to the selection of CASE tools from a possible set of six alternatives is demonstrated. The demonstration helps in gaining a grasp of the MCDM approach and the ELECTRE I method. There is potential for the application of the MCDM approach in other software engineering decisions, especially in the feasibility analysis of the systems life cycle.     

A Computerized Approach to Decision Process Tracing for Decision Support System Design*

We propose the use of computerized process tracing (CPT) tools as an appropriate approach for monitoring the information acquisition and evaluation phase of specific decision processes. CPT tools are unobtrusive and seem particularly relevant for evaluating certain decision tasks that may be supported by decision support systems (DSS). CPT tools can be an important component of DSS development. An information systems research taxonomy developed by previous researchers [29] [36] is used to position research work involving the methodology of CPT. Using a critique suggested by Libby [28], CPT tools are evaluated and compared to alternative process tracing tools. A brief empirical example using CPT is provided, and future uses relative to DSS are suggested. The appendix includes an example of a specific CPT tool.     

A Purchasing Framework for B2B Pricing Decisions and Risk‐sharing in Supply Chains*

This paper presents a common modelling structure for (i) the implementation of operational policies by individual purchasing managers of risk‐sharing agreements among supply‐chain partners, and (ii) the integration of brick and click purchasing policies in a B2B. The problem of price uncertainty created within these two environments is modelled as a stochastic repetitive‐sales problem, applicable to any probability distribution. The model identifies sufficient conditions for regenerative ordering cycles, which allows for the use of the renewal reward theorem. The end result is a two‐price purchasing policy, which may substantially ease implementation problems across a global corporation's purchasing managers world‐wide and across B2B markets.     

The Economic Circumstances Surrounding the Decision to Capitalize Brands—A Comment

The paper offers a reappraisal of the empirical study by Mather and Peasnell (1991) of 13 UK brand-capitalizing companies. It argues that the findings of this study can be questioned on a variety of grounds including: method appropriateness, indirectness, timing and data issues. Specifically, it is suggested that their use of market reaction testing on this topic fails to capture the wide variety of economic consequences that may flow from brand capitalization.     

Assigning Students to Groups: A Multi-Criteria Decision Support System Approach*

MCADSS is a multi-criteria allocation decision support system for assisting in the task of allocating students to groups. Based on multiple criteria, MCADSS's goal is to maximize the diversity of members within groups, while minimizing the average differences between groups. The project may be viewed from several perspectives: as a multi-criteria decision-making problem, as a “reverse'’clustering problem, or as a personnel assignment problem. The system is currently being used to allocate M.B.A. students into sections and study teams at The European Institute of Business Administration (INSEAD). This paper describes the rationale for MCADSS, design criteria, system methodology, and application results. It also suggests how this approach could be used for further applications.     

A Modeling Framework for Supply Chain Simulation: Opportunities for Improved Decision Making*

Owing to its inherent modeling flexibility, simulation is often regarded as the proper means for supporting decision making on supply chain design. The ultimate success of supply chain simulation, however, is determined by a combination of the analyst's skills, the chain members' involvement, and the modeling capabilities of the simulation tool. This combination should provide the basis for a realistic simulation model, which is both transparent and complete. The need for transparency is especially strong for supply chains as they involve (semi)autonomous parties each having their own objectives. Mutual trust and model effectiveness are strongly influenced by the degree of completeness of each party's insight into the key decision variables. Ideally, visual interactive simulation models present an important communicative means for realizing the required overview and insight. Unfortunately, most models strongly focus on physical transactions, leaving key decision variables implicit for some or all of the parties involved. This especially applies to control structures, that is, the managers or systems responsible for control, their activities and their mutual attuning of these activities. Control elements are, for example, dispersed over the model, are not visualized, or form part of the time‐indexed scheduling of events. In this article, we propose an alternative approach that explicitly addresses the modeling of control structures. First, we will conduct a literature survey with the aim of listing simulation model qualities essential for supporting successful decision making on supply chain design. Next, we use this insight to define an object‐oriented modeling framework that facilitates supply chain simulation in a more realistic manner. This framework is meant to contribute to improved decision making in terms of recognizing and understanding opportunities for improved supply chain design. Finally, the use of the framework is illustrated by a case example concerning a supply chain for chilled salads.     

The Effectiveness of Graphical Presentation for Information Extraction: A Cumulative Experimental Approach*

Three laboratory experiments were conducted to assess the relative strengths and weaknesses of bar, symbol, and line graphs for performing a variety of elementary information extraction tasks using two dependent variables, time and accuracy. The findings indicate that the degree of support provided by a particular graph format for a particular data extraction task depends on the matching of format and task in terms of their anchoring characteristics. Anchoring, in this context, refers to the phenomenon that specific and diverse parts of a graph are segmented by the reader to act as salient and relevant cues, or anchors, when different classes of information are to be extracted from the graph. A data extraction task has high x-value (y-value) anchoring if the x-axis (y-axis) component is represented in the question as either a given value or an unknown value. Conversely, a task has low x-value (y-value) anchoring if the x-axis (y-axis) component is not represented in the question as either a given value or as an unknown value. Data extraction accuracy was not significantly affected by presentation format. Bars provided the best time performance for data extraction tasks having high anchoring on both axes but were not appropriate for tasks having low anchoring on either the y axis or both the x and y axes. Line graphs tended to be worse in terms of time performance for tasks having high anchoring on both axes although they were as fast or better than other representations for tasks having low anchoring on both axes. Symbol plots appeared to possess anchoring characteristics associated with both bars and line graphs. Symbols (as with bars) tended to produce a time performance superior to that of line graphs for tasks having high anchoring on both axes; and (as with line graphs) symbols allowed faster results than bar graphs for tasks having low anchoring on either the y axis or both the x and y axes.     

The Information Problems in Organizations: A Research Model for the Value of Information and Information Systems*

Growing recognition of the need for better management information system (MIS) theory and practice centers around problems with identifying the value of information and information systems in organizations. This paper addresses this issue by showing that existing theory in organizational economics and industrial organization directly relates to information problems in organizations (their nature, and their effects in terms of organization structure and performance). The paper categorizes these problems and associated theories into four distinct classes and shows that MIS research and practice can be mapped to information problems of each type. Because the economic theory pertinent to specific information problems includes the nature of the organizational response to information constraints, it also provides insight into the nature of the improvement to be realized if information constraints can be overcome. These improvements can then be interpreted as the value of the associated information systems which suggests using the resultant classification scheme to map between information problems and system value. The paper shows that this methodology provides a more appropriate level of focus than either traditional normative or business value methods, especially because many improvements have structural as well as performance consequences.     

A Goal Programming Model for Effective Segment Determination: A Comment and Application

This note presents a model for the effective market segment determination problem. The integer goal programming model was developed for a nonprofit health care organization. The approach is an alternative application of a model presented by McClure and Wells [7]. The model includes input from the organization's clients as well as the organization's decision makers. A distinctive element is the simultaneous development of market segments and the consideration of management, institutional, and resource constraints. The purpose of the model was to aid the decision makers in determining if effective market segments exist which can be reached with information and educational materials concerning infant nutrition and breastfeeding. The model was tested and found to be effective in helping the decision makers segment their clients.     

A Note on ‘An Approximate Solution to Deterministic Kanban Systems’: A Commentary and Further Insights

In a recent paper, Vemuganti, Batta, and Zhu (1996) stated that the linear programming model suggested by Moeeni and Chang (1990) could result in infeasibility. They also suggested an alternative mathematical formulation for determining the number of kanbans. The intention of this article is twofold. First, we maintain that the finding of Vemuganti et al., while valid, is based on a misplaced emphasis on the purpose of the Moeeni and Chang article. Second, we demonstrate that the Vemuganti et al. formulation is a special case of a more general model proposed by Bitran and Chang (1987).     

A Behavioral Approach to Organizational Change: Reinforcing Those Responsible for Facilitating the Climate and Hence Promoting Diversity

Despite the passage of the U.S. Civil Rights Act in 1964, cries can still be heard for a more diverse workforce. Among the difficulties are retaining often sought-after women and minorities. In this 2-year demonstration, change agents—the provost, deans, and heads of departments/schools of a large public university—were helped to deliberately and directly change the milieu of their departments and schools so as to encourage faculty to remain. Uniquely suited to organizational change, the behavioral approach identifies constructive actions for change agents and, most importantly, provides proven strategies for motivating them. Fostering a supportive climate was defined in terms of change agents’ behaviors. The Building Behaviorally Based Climate Survey was developed and validated. Recognition and feedback were provided in what is typically a feedback desert. This reinforcement model can be used to create and sustain inviting atmospheres, hence enticing all faculty, including women and minority faculty, to stay, hence enabling a diverse workforce.     

Developing Measures for Assessing the Organizational Impact of Information Technology: A Comment on Mahmood and Soon's Paper

In a recent study, Mahmood and Soon [26] identified and operationalized a set of variables that can be potentially impacted by information technology. The lack of factor analysis to verify the dimensionality of different variables is a notable omission in the study. This paper describes and employs the limited-information factor analysis approach and the minimum average partial criterion for testing the unidimensionality of different variables in the Mahmood and Soon study. While reconfirming the construct validity of eight variables, our results question the unidimensionality of two original variables. Further testimony is provided in favor of our results by citing previous research studies.