bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mathematical Programming Formulations for the Discriminant Problem: An Old Dog Does New Tricks*
Authors: Ragsdale Cliff T. , Stam Antonie 
Published: June 2007

ABSTRACTIn recent years, much research has been done on the application of mathematical programming (MP) techniques to the discriminant problem. While promising results have been obtained, many of these techniques are plagued by a number of problems associated with the model formulation including unbounded, improper, and unacceptable solutions as well as solution instability under linear transformation of the data. In attempting to solve these problems, numerous formulations have been proposec involving additional variables and/or normalization constraints. While effective, these models can also become quite complex. In this paper we demonstrate that a simple, well‐known special case of Hand's [13] original formulation provides an implicit normalization which avoids the problems for which various complicated remedies have been devised. While other researchers have made use of this formulation, its properties have not previously been fully recognized.
A Comprehensive Model for Measuring the Potential Impact of Information Technology on Organizational Strategic Variables*
Authors: Mahmood Mo Adam , Soon Siew Khim 
Published: June 2007

ABSTRACTThe existing literature on the impact of information technology (IT) does not include rigorous theory building or empirical studies. This research seems to be the first comprehensive investigation towards the development of an empirically validated comprehensive model for understanding the potential impact of IT on organizational strategic variables. More specifically, organizational and industrial variables that appeared to be affected by IT are identified, measured, and operationalized in the form of a comprehensive model. This study is based on structured interviews with a carefully selected sample of 31 strategic managers who had experience using IT for strategic decisions. In addition, the variables included in the model are well grounded in the information systems literature. The variables are then empirically validated and their reliabilities critically tested. A comprehensive model is derived from these validated variables. The model is a first step towards measuring the overall potential impact of IT on an organization. The model can also be used to gauge IT's potential impact on individual strategic variables. A set of hypotheses is also presented for future research. The hypotheses primarily relate to the impact of IT on organizational strategic performance. The model provides an empirically validated foundation for testing of such hypotheses.
An Improved Heuristic for Multilevel Lot Sizing in Material Requirements Planning
Authors: Coleman B. Jay , McKnew Mark A. 
Published: June 2007

Improvement on existing techniques for multilevel lot sizing in material requirements planning was sought by developing a theoretical and mathematical basis for the problem. Such a foundation was employed to design a heuristic which was superior in both cost performance and computational efficiency, and provided consistent results regardless of designated environmental factors. This represents a significant advantage over other algorithms tested here and within the literature, in that their performances are dependent upon various lot‐sizing environmental factors.The heuristic is based on the technique for order placement and sizing (TOPS), a single‐item technique, and utilizes a mechanism for linking interdependent lot‐sizing decisions. The inputs are applied in a sequential manner to constitute sequential TOPS with incremental look‐down (STIL). A two‐phase experimental design was employed to evaluate the performance of STIL against optimality and other heuristics. Results from the initial phase of simplified problems revealed practical indifference from optimality for the new algorithm. Phase 2 emphasized the relative strength and consistency of the proposed heuristic versus all other rules tested over more difficult examples. The final stage also indentified environments in which STIL performed particularly well. These were more descriptive of common industrial settings than were cases in which existing methods have been shown to be effective.
A Comparison of Three Joint Ordering Inventory Policies*
Authors: Pantumsinchai Pricha 
Published: June 2007

ABSTRACTThis paper evaluates the performance of a joint ordering inventory policy which was first suggested and characterized by Renberg and Planche [14]. This paper shows that the policy is easily characterized for Poisson demands. This policy is then compared with two other joint ordering policies—the well‐known (S, c, s) or can‐order policy of Balintfy [3] and the recent periodic policies suggested by Atkins and lyogun [2]. For a continuous review operating environment, the Renberg and Planche policy utilizes a group reorder point and a combined order quantity (Q), with each item maintaining an order‐up‐to level (S). For the can‐order policy, each item in the product group has a must‐order point (s), a can‐order point (c) and an order‐up‐to level (S). The periodic policies require that item orders be grouped at some fixed scheduled intervals. Using long‐run total average costs as the basis, it is shown that no one policy is superior to the others in all the examples tested. In some cases, the Renberg and Planche policy performs surprisingly well.
A New Multiperiod Multiple Traveling Salesman Problem with Heuristic and Application to a Scheduling Problem
Authors: Gilbert Kenneth C. , Hofstra Ruth B. 
Published: June 2007

ABSTRACTA new multiperiod variation of the M‐traveling salesman problem is introduced. The problem arises in efficient scheduling of optimal interviews among tour brokers and vendors at conventions of the tourism and travel industry. In classical traveling salesman problem vocabulary, a salesman is a tour broker at the convention and a city is a vendor's booth. In this problem, more than one salesman may be required to visit a city, but at most one salesman per time period can visit each city. The heuristic solution method presented is polynomial and is guaranteed to produce a nonconflicting set of salesmen's tours. The results of an implementation of the method for a recent convention are also reported.
Partitioning Work Centers for Group Technology: Analytical Extension and Shop‐Level Simulation Investigation*
Authors: Suresh Nallan C. 
Published: June 2007

ABSTRACTThis paper investigates the effects of partitioning job shop work centers to implement cellular manufacturing. Analytical models are utilized to show that partitioning leads to adverse effects on flow characteristics. The setup reduction introduced in partitioned systems has to overcome these adverse effects before leading to the benefits associated with cellular manufacturing. It is shown that partitioned systems with an insufficient degree of setup reduction are inferior to unpartitioned systems. Two new parameters relevant to this context, the breakeven setup reduction factor and flow ratio, are introduced for the design of viable cellular manufacturing systems. These insights are verified using a shop‐level simulation experiment, assuming non‐Markovian conditions. The experimental factors include lot size, setup reduction factor, cell size and allowance of inter‐cell movements. It is shown that the results are consistent with analytical insights in indicating the range of parameters in which cellular manufacturing may compare favorably with the best of the functional‐layout systems.
The Determinants of DSS Success: An Integrated Model*
Authors: Guimaraes Tor , Igbaria Magid , Lu Ming‐te 
Published: June 2007

ABSTRACTThe results of a field study investigating the determinants of decision support systems (DSS) success are presented. A multivariate model was developed and tested using multiple regression hierarchical analysis on responses from 118 DSS users. Several specific hypotheses are also proposed and tested. Data analyses indicate that DSS success, as measured by DSS satisfaction and perceived benefits, depends on several factors: previous user experience with DSS, user involvement, user training, top management support, information sources, the level of managerial activity, and task structure, difficulty and interdependence. Based on the research results, several suggestions are made to improve the likelihood of successful DSS implementation.
An Empirical Investigation of the Effects of Decision Aids on Problem‐Solving Processes*
Authors: Mackay Jane M. , Barr Steve H. , Kletke Marilyn G. 
Published: June 2007

ABSTRACTDespite the growing number of investigations examining decision support systems (DSS), relatively few empirical studies have evaluated the effects of DSS on problem‐solving processes. This study uses protocol analysis to investigate the impact of a specific decision aid on problem‐solving processes in a semi‐structured problem. Results indicate that decision aids influence the problem‐solving processes of decision makers. The effect of a decision aid is found to be contingent on familiarity with the decision aid, task familiarity, and the interaction of these two factors. Suggestions for incorporating interaction effects and problem‐solving processes into future examinations are proposed.
Artificial Intelligence and Generalized Qualitative‐Response Models: An Empirical Test on Two Audit Decision‐Making Domains
Authors: Hansen James V. , McDonald James B. , Stice James D. 
Published: June 2007

ABSTRACTMachine learning methods are currently the object of considerable study by the artificial intelligence community. Research on machine learning carries implications for decision making in that it seeks computational methods that mimic input‐output behaviors found in classes of decision‐making examples. At the same time, research in statistics and econometrics has resulted in the development of qualitative‐response models that can be applied to the same kind of problems addressed by machine‐learning models—particularly those that involve a classification decision. This paper presents the theoretical structure of a generalized qualitative‐response model and compares its performance to two seminal machine‐learning models in two problem domains associated with audit decision making. The results suggest that the generalized qualitative‐response model may be a useful alternative for certain problem domains.
Marketing Communication Intensity Across Industries
Authors: Zinkhan George M. , Cheng C. S. Agnes 
Published: June 2007

ABSTRACTMarketing communication intensity (i.e., the ratio of advertising and promotional expenditures to sales) has been an important topic for both business managers and academics. Here, we investigate cross‐sectional and time‐series variation of communication intensity due to: type of offering (product versus service) and type of market (consumer versus industrial). Overall, we find that both of these factors affect variation of communication intensity across industries and over time. However, the effect of market type is much more dramatic than the effect of offering type. Such knowledge about patterns in communication intensity levels helps managers make decisions about how much to spend on advertising and promotion.
Toward Computerizing a Causal Modeling Approach to Strategic Problem Framing*
Authors: Heintz Timothy J. , Acar William 
Published: June 2007

ABSTRACTThis paper proposes an object‐oriented approach to the development of interactive software for the purpose of managerial problem solving. A prototype is being developed using CSM causal mapping to represent each manager's perceptions of the relationships between key variables of a firm's strategic situation. This paper suggests the design of GDSS that would enable a group of managers to discuss, learn from each other, and possibly develop consensus about decisions or their causes. Issues involving future development are discussed.
An Application of the AXIS Solution Framework to Multiple Objective Aggregate Production Planning
Authors: MacLeod Kenneth R. , Reeves Gary R. 
Published: June 2007

ABSTRACTThis paper provides data on the first application of a prototype of the AXIS solution framework. AXIS (algorithms combined with knowledge systems in an interactive sequence) is a framework for interactively combining structured algorithms that seek a best solution with knowledge‐based expert systems that seek expert heuristic solutions. This paper tests the framework using an interactive multiple objective integer programming algorithm combined with heuristics taken from the domain of aggregate production planning. The results indicate the AXIS framework can be successful in generating high quality solutions, in vastly reduced solution times compared to the structured algorithms, at much lower costs compared to the expert heuristics working alone.
Determining Order Quantity and Selling Price by Geometric Programming: Optimal Solution, Bounds, and Sensitivity*
Authors: Lee Won J. 
Published: June 2007

ABSTRACTThis paper presents a geometric programming (GP) approach to finding a profit‐maximizing selling price and order quantity for a retailer. Demand is treated as a nonlinear function of price with a constant elasticity. The proposed GP approach finds optimal solutions for both no‐quantity discounts and continuous quantity discounts cases. This approach is superior to the traditional approaches of solving a system of nonlinear equations. Since the profit function is not concave, the traditional approaches may require an exhaustive search, especially for the continuous discounts schedule case. By applying readily available theories in GP, we easily can find global optimal solutions for both cases. More importantly, the GP approach provides lower and upper bounds on the optimal profit level and sensitivity results which are unavailable from the traditional approaches. These bounding and sensitivity results are further utilized to provide additional important managerial implications on pricing and lot‐sizing policies.
A New Framework for Manufacturing Planning and Control Systems*
Authors: Sum Chee‐Chuong , Hill Arthur V. 
Published: June 2007

ABSTRACTThis paper presents a new framework for manufacturing planning and control systems which we call iterative manufacturing planning in continuous time (IMPICT) that appears to have several advantages over the well‐known material requirements planning (MRP) framework. IMPICT explicitly considers capacity constraints and total system cost (including tardiness) to determine order sizes, order release/due dates, and operation schedules in a deterministic, multi‐level, finite horizon, dynamic demand environment. Continuous time scheduling variables allow setups to be carried over from one period to the next.Three new heuristics built on the IMPICT framework are presented and tested in a simulation‐based, full‐factorial experiment with a wide variety of problem environments. The benchmark for the experiment was materials requirements planning with operations sequencing (MRP/OS) implemented with best‐case, fixed planned lead times. The experiment showed that all three heuristics were statistically better than MRP/OS. The total cost for the order merging (OM) heuristic was 25 percent better than the total cost for MRP/OS. Computational times for OM were substantially larger than for MRP/OS; however, the computational times in the experiment suggest that OM is still computationally viable for large‐scale batch manufacturing environments found in industry.IMPICT is superior to standard MRP systems because it explicitly considers capacity constraints and total system costs when it creates a materials plan. IMPICT is superior to linear programming‐based approaches to finite loading and scheduling found in the literature because it allows setups to be carried over from one period to another and because it is computationally viable for realistic‐sized problems.
An Investigation of Scheduling Policies in a Dual‐Constrained Manufacturing Cell*
Authors: Wirth Glen T. , Mahmoodi Farzad , Mosier Charles T. 
Published: June 2007

ABSTRACTIn previous group scheduling studies, labor has essentially been ignored by assuming that enough labor is assigned to each machine in the cell. In reality, however, management usually does not have the resources to employ a laborer at each machine in the cell (i.e., machines need to share labor). Both labor scheduling and group scheduling heuristics need to be administered to manage the cell effectively. This study develops and examines scheduling procedures for a dual‐constrained (i.e., machine and labor) manufacturing cell. Eleven decision rules are developed and tested under 16 different experimental conditions. The experimental factors used are interarrival time distribution, cell load, setup‐to‐run‐time ratio, and transfer‐to‐run‐time ratio. Results show that interarrival time distribution and cell load have the greatest impact on the performance of the cell. This suggests that effective production planning aimed at reducing job arrival variation and leveling the cell load can substantially improve cell performance. Among the experimental factors, setup and transfer‐to‐run‐time ratio factors had the strongest influence on the rankings of the decision rules. These rankings were fairly robust across all experimental conditions and performance measures. The results also indicated that the inclusion of labor as a contraint in the cell had a significant impact on the performance of several group scheduling heuristics. Finally, it was shown that the best performing decision rules consider both transfer time and subfamily setup times.
Structure of Uncertainty and Decision Making: An Experimental Investigation*
Authors: Ghosh Dipankar , Crain Terry L. 
Published: June 2007

ABSTRACTDecisions in the real world usually involve imprecise information or uncertainty about the precesses by which outcomes may be determined. This research reports the results of a laboratory experiment which examined whether the structure of uncertainty, namely, both the center and the range of the probability distribution describing the uncertainty, is an important determinant of choice. Specifically, it examines how the uncertainty of audit by the Internal Revenue Service of income tax returns affects taxpayers' decisions about intentional noncompliance. The context is relevant as almost nothing is known about how taxpayers assess detection risks using the probability information they have.The study focuses on intentional noncompliance. The factors affecting it are distinct and separate from those affecting unintentional noncompliance. Other factors that affect intentional tax noncompliance, such as risk, tax rates, and penalty rates, were controlled in the experiment. It was hypothesized that the lower the mean and the lesser the range (ambiguity) of the perceived audit probability, the greater the international noncompliance. As hypothesized, the analysis indicates that both the mean and the range of the perceived audit probability rate affect intentional noncompliance, though the effect of ambiguity is greater at a relatively higher level of mean. This result suggests that the strength of the information describing an uncertain event is captured better by both the mean and the range of the uncertainty than either of those components singly.
A Dynamic Model of Product Quality and Pricing Decisions on Sales Response
Authors: Narasimhan Ram , Ghosh Soumen , Mendez David 
Published: June 2007

ABSTRACTThis paper presents a dynamic model that examines the influence of price and customer perception of product quality on the sales rate of a firm producing durable goods. The sales rate of the firm is modeled as a function of its price, average product life, perceived quality, and market potential. Specifically, the model considers: (1) the process by which perceived quality is determined by including the effects of the average life of a product and quality weighted units in the market; (2) the time delay in the influence of actual quality on perceived quality; (3) the process by which demand (i.e., potential sales) is converted to realized sales due to the effects of price and perceived quality; and (4) the saturation effect and associated non‐linearity in the demand function. The model presented is a reformulation and extension of the model originally proposed by Bass [2]. The validity of the model is tested using historical data on For Mustang.
Scheduling in a Management Context: Uncertain Processing Times and Non‐Regular Performance Measures*
Authors: Robb David J. , Silver Edward A. 
Published: June 2007

ABSTRACTDecision makers often face scheduling problems in which processing times are not known with certainty. Non‐regular performance measures, in which both earliness and tardiness are penalized, are also becoming more common in both manufacturing and service operations. We model a managerial environment with task processing times (which include sequenceindependent set‐up times) prescribed by three‐parameter lognormal distributions. Upon completion, each task derives a reward given by a particular piecewise‐linear reward function. The objective is to select a sequence of tasks maximizing the expected total reward.The relative generality of the problem renders many enumerative methods inapplicable or computationally intractable. To overcome such difficulties we develop efficient priorityinduced construction (PIC) heuristics which build up a complete schedule by inserting tasks (singly from a list) into a partial sequence of tasks. In each partial and complete sequence a period of idle time is permitted prior to the first task. Performance on realistic‐sized problems is very encouraging, with cost penalties averaging less than one percent.
A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data
Authors: Wedel Michel , DeSarbo Wayne S. 
Published: June 2007

ABSTRACTA latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group among two alternatives in paired comparison experiments. A modest Monte Carlo analysis of algorithm performance is presented. The proposed model is illustrated with empirical data from a consumer psychology experiment that examines the determinants of perceived consumer risk. The predictive validity of the method is assessed and compared to that of several other procedures. The sensitivity of the method to (randomly) eliminate comparisons, which is important in view of reducing respondent fatigue in the task, is investigated.
Organizing for Global Competition
Authors: Jarvenpaa Sirkka L. , Ives Blake 
Published: June 2007

ABSTRACTGlobal information technology (i.e., computer hardware, software, and data communications shared across country boundaries) can support the multinational firm as it seeks to coordinate global operations, diffuse innovations worldwide, or provide integrated service to a global corporate customer. The current study uses information processing theory as the basis for examining alternative organizational designs for information technology in a globally competing firm. Mail survey data gathered from information technology managers in 109 multinationals provide evidence that multinational firms use different and distinct ways of organizing their global information technology activities. The survey data also reveal that in nearly half of the organizations, the way information technology activities are organized is inconsistent with the way the organization is reportedly structured. A follow‐up interview‐based study sought explanations for these misfits. Several contingency variables were identified that may shed some light to the misfits. These included factors from both the firm's internal and external environments.