bluuebunny/crossref_metadata_2025_split huggingface dataset:
Group Support Systems, Power, and Influence in an Organization: A Field Study
Authors: Williams Susan Rebstock , Wilson Rick L. 
Published: June 2007

ABSTRACTEmerging group technologies are attracting attention from researchers and practitioners for the benefits they potentially offer in terms of communications, productivity, and decision‐making capabilities within an organization. To date, research in this area has focused on process or outcome variables, substantively ignoring organizational context issues. This paper reports on a field study that investigated users' perceptions of the impact of group support systems on power and influence within the organization. The study was conducted within a division of a major U.S. software company specializing in the development of business software tools for desktop PCs. Fifteen purposively selected managers and nonmanagers, spanning diverse functional areas, were extensively interviewed for this study. Evidence gathered suggested that group support systems are perceived to exert an equalizing force on power and influence by (1) increasing participation in the decision‐making process, (2) improving access to information, (3) improving access to persons, (4) reducing the “power distance” to key individuals, and (5) providing increased opportunities to influence the opinions of others. These results provide a basis for future studies that will attempt to clarify the relationships between organizational context and group technology usage.
Virtual Teams versus Face‐to‐Face Teams: An Exploratory Study of a Web‐based Conference System*
Authors: Warkentin Merrill E. , Sayeed Lutfus , Hightower Ross 
Published: June 2007

ABSTRACTMany organizations are forming “virtual teams” of geographically distributed knowledge workers to collaborate on a variety of workplace tasks. But how effective are these virtual teams compared to traditional face‐to‐face groups? Do they create similar teamwork and is information exchanged as effectively? An exploratory study of a World Wide Web‐based asynchronous computer conference system known as Meeting Web™ is presented and discussed. It was found that teams using this computer‐mediated communication system (CMCS) could not outperform traditional (face‐to‐face) teams under otherwise comparable circumstances. Further, relational links among team members were found to be a significant contributor to the effectiveness of information exchange. Though virtual and face‐to‐face teams exhibit similar levels of communication effectiveness, face‐to‐face team members report higher levels of satisfaction. Therefore, the paper presents steps that can be taken to improve the interaction experience of virtual teams. Finally, guidelines for creating and managing virtual teams are suggested, based on the findings of this research and other authoritative sources.
Fostering Risk Taking in Research and Development: The Importance of a Project's Terminal Value
Authors: Case Randolph H. , Shane Scott 
Published: June 2007

ABSTRACTLarge firms face a conflict in managing a portfolio of high‐risk projects. When an ongoing project is thought to have a low likelihood of success, project team members take risks to improve its chances of success. However, upper‐level managers who allocate resources tend to withhold resources from a project with a low likelihood of success in favor of others in the portfolio that look more promising. Because this paucity of resources influences project team members to avoid risk, the total effect of success likelihood on risk taking is conflicted. The influence on risk taking of a project's terminal value—defined as the value that remains in the firm in the event of project failure—is unequivocally positive, because both senior management resource allocation and project team risk‐taking propensity are encouraged by terminal value. Thus, firms can override the ambivalent effect of likelihood of success on project decision making by focusing attention on a project's terminal value.
An Instrument for Assessing the Organizational Benefits of IS Projects
Authors: Mirani Rajesh , Lederer Albert L. 
Published: June 2007

ABSTRACTThis paper reports the development of an instrument to measure the organizational benefits of IS projects. The basis for this instrument was a published framework that suggests three categories of such benefits: strategic, informational, and transactional. In a cross‐sectional study of 178 IS projects proposed and approved for development, this framework was operationalized and empirically tested using the measurement model of LISREL. The analysis culminated in the validation and refinement of the these categories. The final instrument offers items under three separate subdimensions of strategic benefits: competitive advantage, alignment, and customer relations. Informational benefits are similarly comprised of information access, information quality, and information flexibility. Finally, transactional benefits are also shown to be of three types: communications efficiency, systems development efficiency, and business efficiency. Implications of this multidimensional instrument for IS practitioners and researchers are discussed.
On Inventory Abatement via Manufacturing Randomness Reductions*
Authors: Arreola‐Risa Antonio 
Published: June 2007

ABSTRACTUnder a continuous improvement framework, the policy of abating inventory via reductions in manufacturing randomness is considered. To explore this policy, a model of a real‐world production‐inventory system is developed, tested, and studied. The results suggest that manufacturing randomness reductions, even substantial ones, may not necessarily lead to inventory abatement, and paradoxically may lead sometimes to an inventory increase. In these cases, however, manufacturing randomness reductions will translate into higher customer service levels.
Setting Tolerable Misstatements When Auditing Aggregated Accounts*
Authors: Barron Orie , Groomer S. Michael , Swink Morgan 
Published: June 2007

ABSTRACTGenerally accepted auditing standards require auditors to plan audits of clients' account balances. If accounts are to be sampled, then part of this planning must include setting the tolerable misstatement for each account or class of transactions to be sampled. Although classical sampling approaches provide certain advantages, they have not been widely used because they are viewed as complex and difficult to implement. We present a remedy to these difficulties in an efficient, easily implemented optimal solution method for the problem of setting tolerable misstatements given constraints on tolerable misstatements for individual account balances as well as the overall audit. Further, our method suggests when the materialities of certain accounts or the materiality of the overall audit are irrelevant to the problem. Several example auditing problems demonstrate both our solution approach and the settings in which our approach provides a more effective or more efficient sampling plan than that provided by monetary unit sampling.
Effect of Level of Disaggregation on Conjoint Cross Validations: Some Comparative Findings*
Authors: Krieger Abba M. , Green Paul E. , Umesh U. N. 
Published: June 2007

ABSTRACTEarly formulations of conjoint models focused on part‐worth estimation at the individual level. As the methodology's popularity grew so did industry demands for increasingly larger numbers of attributes and levels. In response to these demands, new approaches, based on partial or full data aggregation (such as clusterwise/latent class conjoint and choice‐based conjoint), have appeared. This paper suggests that pooled‐data models will often be successful in predicting market shares when researchers employ monotonic attributes. In these cases more of a good attribute (or less of a bad attribute) is always more preferred. In the more realistic case, in which some of the attributes may be nonmonotonic, we find that data aggregation does not predict holdout sample preferences as well as individual part‐worth models.
A Simulation Metamodel for Response‐Time Planning*
Authors: Watson Edward F. , Chawda Prabhulal P. , McCarthy Brad , Drevna Michael J. , Sadowski Randy P. 
Published: June 2007

ABSTRACTField service management continues to be a major challenge for many service organizations as companies are required to provide more service with less resources. Especially in information intense environments, short response times for service calls are essential to avoid disruptions to a business office or production facility. Managers must regularly assess their manpower needs, and ensure that their allocation and operational decisions lead to the best service at the lowest cost.Xerox Corporation provides copiers, duplicators, and printing systems to an international market. Xerox operates a service network consisting of over 30,000 trained service personnel, each allocated to service regions by the service planning staff. Response‐time planning involves many challenging problems: requirements planning at the national level, allocation planning at the district level, and operational planning at the team level. Customer service is critical and is commonly measured by response time—the time that elapses from when a service call is placed to when a service engineer begins service. This paper discusses how Xerox Corporation has used simulation models and metamodels to improve response‐time planning and field service operations.
Process Mean Determination with Quantity Discounts in Raw Material Cost*
Authors: Gong Linguo , Roan Jinshyang , Tang Kwei 
Published: June 2007

ABSTRACTSetting the mean (target value) for a container‐filling process is an important decision for a producer when the material cost is a significant portion of the production cost. Because the process mean determines the process conforming rate, it affects other production decisions, including, in particular, the production setup and raw material procurement policies. In this paper, we consider the situation in which quantity discounts exist in the raw material acquisition cost, and incorporate the quantity‐discount issue into an existing model that was developed for simultaneously determining the process mean, production setup, and raw material procurement policies for a container‐filling process. The product of interest is assumed to have a lower specification limit, and the items that do not conform to the specification limit are scrapped with no salvage value. The production cost of an item is proportional to the amount of the raw material used in producing the item. A two‐echelon model is formulated for a single‐product production process, and an algorithm is developed for finding the optimal solution. A sensitivity analysis is performed to study the effects of the model parameters on the optimal solution.
Causal Linkages in Supply Chain Management: An Exploratory Study of North American Manufacturing Firms
Authors: Narasimhan Ram , Jayaram Jayanth 
Published: June 2007

ABSTRACTIn this paper we investigate the key causal linkages in supply chain management. We propose a conceptual framework and test this framework on data from 215 North American manufacturing firms using structural equation modeling techniques. Three major research issues are addressed in this study: Do sourcing decisions affect the degree to which firms achieve manufacturing goals of cost, flexibility, dependability, and quality? Does the degree of manufacturing goal achievement lead to higher customer responsiveness? Does the degree of manufacturing goal achievement lead to higher internal manufacturing performance? The study examines the relationship among sourcing decisions, manufacturing goals, customer responsiveness, and manufacturing performance. The results support the notion that an integrated supply chain involves aligning sourcing decisions to achieve manufacturing goals that are set to respond favorably to the needs of customers.
Modeling Supply Chain Dynamics: A Multiagent Approach*
Authors: Swaminathan Jayashankar M. , Smith Stephen F. , Sadeh Norman M. 
Published: June 2007

ABSTRACTA global economy and increase in customer expectations in terms of cost and services have put a premium on effective supply chain reengineering. It is essential to perform risk‐benefit analysis of reengineering alternatives before making a final decision. Simulation provides an effective pragmatic approach to detailed analysis and evaluation of supply chain design and management alternatives. However, the utility of this methodology is hampered by the time and effort required to develop models with sufficient fidelity to the actual supply chain of interest. In this paper, we describe a supply chain modeling framework designed to overcome this difficulty. Using our approach, supply chain models are composed from software components that represent types of supply chain agents (e.g., retailers, manufacturers, transporters), their constituent control elements (e.g., inventory policy), and their interaction protocols (e.g., message types). The underlying library of supply chain modeling components has been derived from analysis of several different supply chains. It provides a reusable base of domain‐specific primitives that enables rapid development of customized decision support tools.
Reconfiguring the Supply Network Using Current Performance Data
Authors: Ross Anthony , Venkataramanan M. A. , Ernstberger Kathryn W. 
Published: June 2007

ABSTRACTReconfiguration of the supply chain network from time to time is essential for businesses to retain their competitive edge. This paper presents a methodology for reconfiguration of an existing supply chain network. The methodology is characterized by two decision levels. In the first level, the current network performance is evaluated and efficient practices are identified. In the next level, a model that incorporates efficient practices is developed to reconfigure the network. This integrated methodology allows for decision maker (DM) input throughout the process. The methodology has been implemented and tested in the reconfiguration of an outbound petroleum supply chain network for CountryMark Cooperative, Inc. In this case study, Data Envelopment Analysis (DEA) is used to analyze current operations and an integer programming (IP) model that incorporates efficiency metrics is developed for selection of distribution facilities and allocation of resources to the facilities. Use of this methodology can lead to improved operations and reduced operating expenses.
Influencing a Supplier Using Delivery Windows: Its Effect on the Variance of Flow Time and On‐Time Delivery
Authors: Grout John R. 
Published: June 2007

ABSTRACTA critical outcome that buyers seek is the timely delivery of the products they purchase from suppliers. Delivery windows have been proposed as a means to achieve this goal. This paper proposes a relatively simple model that shows that delivery windows do not always improve delivery timeliness. The effect of buyer‐specified delivery windows on the supplier's flow‐time variance, inventory, expected tardiness, and probability of on‐time delivery is analyzed. The analysis shows that although using delivery windows may result in the supplier's preferred action being a reduction in the variance of flow time, actual delivery timeliness may not improve. On‐time delivery performance is analyzed for linear and hyperbolic variance cost functions. The results indicate that when the cost of maintaining lower variances grows exponentially, variance reduction does not lead to more timely deliveries.
The Efficacy of Neural Networks in Predicting Returns on Stock and Bond Indices*
Authors: Desai Vijay S. , Bharati Rakesh 
Published: June 2007

ABSTRACTThis paper uses two recently developed tests to identify neglected nonlinearity in the relationship between excess returns on four asset classes and several economic and financial variables. Having found some evidence of possible nonlinearity, it was then investigated whether the predictive power of these variables could be enhanced by using neural network models instead of linear regression or GARCH models.Some evidence of nonlinearity in the relationships between the explanatory variables and large stocks and corporate bonds was found. It was also found that the GARCH models are conditionally efficient with respect to neural network models, but the neural network models outperform GARCH models if financial performance measures are used. In resonance with the results reported for the tests for neglected nonlinearity, it was found that the neural network forecasts are conditionally efficient with respect to linear regression models for large stocks and corporate bonds, whereas the evidence is not statistically significant for small stocks and intermediate‐term government bonds. This difference persists even when financial performance measures for individual asset classes are used for comparison.
The Consequences of Role‐conferred Bias and Base‐rate Neglect*
Authors: Doerr Kenneth H. , Mitchell Terence R. 
Published: June 2007

ABSTRACTThis study examines the effect of training to reduce biases and heuristics on the consequence of judgments. We demonstrate that untrained subjects' judgments may systematically yield better consequences than judgments of subjects trained to reduce biases and heuristics. This result implies that educators should use caution when interpreting the findings of biases and heuristics research. In establishing the existence of situations in which biases and heuristics produce better consequences than an unbiased, or normative procedure, we open the larger question of the need for an elaboration of the prescriptive uses of the normative procedures.
Staffing a Multiskilled Workforce with Varying Levels of Productivity: An Analysis of Cross‐training Policies*
Authors: Brusco Michael J. , Johns Tony R. 
Published: June 2007

ABSTRACTService operations that utilize cross‐trained employees face complex workforce staffing decisions that have important implications for both cost and productivity. These decisions are further complicated when cross‐trained employees have different productivity levels in multiple work activity categories. A method for policy analysis in such environments can be beneficial in determining low‐cost staffing plans with appropriate cross‐training configurations.In this paper, we present an integer linear programming model for evaluating cross‐training configurations at the policy level. The objective of the model is to minimize workforce staffing costs subject to the satisfaction of minimum labor requirements across a planning horizon of a single work shift. The model was used to evaluate eight cross‐training structures (consisting of 36 unique cross‐training configurations) across 512 labor requirement patterns. These structures, as well as the labor requirement patterns, were established based on data collected from maintenance operations at a large paper mill in the United States. The results indicate that asymmetric cross‐training structures that permit chaining of employee skill classes across work activity categories are particularly useful.
Will a Risk‐averse Decision Maker Ever Really Prefer an Unfair Gamble?*
Authors: Horowitz Ira 
Published: June 2007

ABSTRACTPrakash, Chang, Hamid, and Smyser (1996) purport to show that with sufficient preference for positive skewness, risk‐averse managers might elect to engage in unfair gambles. Their “proof'’of the impossible assumes the existence of a differentiable risk‐preference function that satisfies certain assumptions about the first three derivatives. The fundamental flaw in their argument is that no differentiable function exists for which risk aversion and the participation in an unfair gamble are compatible.
The Auditor's Going‐Concern Disclosure as a Self‐Fulfilling Prophecy: A Discrete‐Time Survival Analysis*
Authors: Louwers Timothy J. , Messina Frank M. , Richard Michael D. 
Published: June 2007

The question of how an auditor's going‐concern disclosure affects a client's future operations has long troubled the auditing profession. In an attempt to provide further understanding of this issue, we introduce Discrete‐Time Survival Analysis (DTSA) to examine the aftermath of 231 first‐time going‐concern disclosures on clients' subsequent continuance. DTSA represents a significant refinement over traditional ordinary least squares (OLS) and logistic (LOGIT) regression in that it provides not only a probability estimate, but also an estimate of the timing of the event occurrence. The addition of this extra dimension (event timing) aids decision makers by providing more complete information about event probabilities.Consistent with the “self‐fulfilling prophecy effect,” the risk profiles developed from DTSA indicate that the first year subsequent to the initial going‐concern disclosure was the most dangerous in terms of risk of bankruptcy. However, after the first year, the incidence of bankruptcy decreases significantly. Thus, DTSA is able to provide a richer perspective on this perplexing issue than previously considered.
Limits to Concurrency*
Authors: Hoedemaker Geert M. , Blackburn Joseph D. , Van Wassenhove Luk N. 
Published: June 2007

ABSTRACTIn the global race to bring new products to market, many firms have adopted concurrent engineering as a technique to shrink development lead time. Due to the many concurrent engineering success stories in the business and engineering literature, a common misconception has grown that more concurrency is always better. The major contribution of this paper is a rigorous demonstration that limits to concurrency exist even in the simplified situation in which concurrency is modeled as the number of design modules to be executed in parallel. As complexities such as communication linkages between modules are layered onto our basic model, we show that the expected project completion time is minimized at a finite number of modules, a number that decreases with increasing problem complexity. In general, the more complex the project, the stricter the limits to concurrency. This strongly suggests that project managers should be cognizant of the potentially adverse effects of pushing concurrency too far.
The Effects of Learning, Forgetting, and Relearning on Decision Rule Performance in Multiproject Scheduling
Authors: Ash Robert , Smith‐Daniels Dwight E. 
Published: June 2007

ABSTRACTProduct development occurs in multiproject environments where preemption is often allowed so that critical projects can be addressed immediately. Because product development is characterized by time‐based competition, there is pressure to make decisions quickly using heuristics methods that yield fast project completion. Preemption heuristics are needed both to choose activities for preemption and then to determine which resources to use to restart preempted activities. Past research involving preemption has ignored any completion time penalty due to the forgetting experienced by project personnel during preemption and the resulting relearning time required to regain lost proficiency. The purpose of this research is to determine the impact of learning, forgetting, and relearning (LFR) on project completion time when preemption is allowed. We present a model for the LFR cycle in multiproject development environments. We test a number of priority rules for activity scheduling, activity preemption, and resource assignment subsequent to preemption, subject to the existence of the LFR cycle, for which a single type of knowledge worker resource is assigned among multiple projects. The results of the simulation experiments clearly demonstrate that LFR effects are significant. The tests of different scheduling, preemption, and resource reassignment rules show that the choice of rule is crucial in mitigating the completion time penalty effects of the LFR cycle, while maintaining high levels of resource utilization. Specifically, the worst performing rules tested for each performance measure are those that attempt to maintain high resource utilization. The best performing rules are based on activity criticality and resource learning.