bluuebunny/crossref_metadata_2025_split huggingface dataset:
Success Factors in Strategic Supplier Alliances: The Buying Company Perspective*
Authors: Monczka Robert M. , Petersen Kenneth J. , Handfield Robert B. , Ragatz Gary L. 
Published: June 2007

ABSTRACTThe emerging area of supply chain alliances has received considerable attention in the academic and managerial press, yet there are many unanswered questions regarding the dynamics of such relationships. A number of such fundamental issues drive this research initiative, including how alliances are developed, their key success factors, and the specific benefits to be achieved. The study begins by establishing a definition of strategic supplier alliances, based on a comparison of both theoretical and managerial descriptions. The critical antecedents associated with the success of strategic supplier alliances are next developed, and the magnitude of the effect of these factors on partnership success is assessed. The analysis employs both qualitative and quantitative data, collected through an electronic network of over 200 companies, as part of an ongoing benchmarking initiative in supply chain management.From the perspective of the buying company in the alliance, the following attributes of supplier alliances were found to be significantly related to partnership success: trust and coordination, interdependence, information quality and participation, information sharing, joint problem solving, avoiding the use of severe conflict resolution tactics, and the existence of a formal supplier/commodity alliance selection process. Resource commitment and smoothing over problems were found to be poor predictors of alliance success. The implications of these results for managerial decision making in supplier alliance development are discussed.
The Relationship Between Information System Planning Sophistication and Information System Success: An Empirical Assessment*
Authors: Sabherwal Rajiv 
Published: June 2007

ABSTRACTLiterature on information systems (IS) planning implicitly assumes that a sophisticated IS planning process leads to greater IS success. This paper questions the exclusive reliance on this traditional belief. Instead, because IS planning requires significant organizational resources, prior IS success is essential to convince top management of the importance of IS planning sophistication. Therefore, IS success may influence IS planning sophistication. Several theoretical arguments are advanced in support of this explanation.Data from a survey of 236 academic institutions are used to empirically assess the two alternative directions of the relationship between IS planning sophistication and IS success. Four structural models including the alternative causal directions are evaluated. Two of these models are supported. Together, they imply that for a high level of IS planning sophistication, either the previous ISs should have been successful or the organization should possess advanced information technology capabilities. Thus, empirical results suggest that the explanation presented here (i.e., IS success facilitates IS planning sophistication) provides an equally good alternative to the more traditional explanation (i.e., IS planning sophistication facilitates IS success).
A Comparative Revenue Analysis of Hotel Yield Management Heuristics
Authors: Baker Timothy Kevin , Collier David A. 
Published: June 2007

ABSTRACTYield management is the dynamic pricing, overbooking, and allocation of perishable assets across market segments in an effort to maximize short‐term revenues for the firm. Numerous optimization heuristics for allocation and overbooking exist for the airline industry, whose perishable asset is the airplane seat. When an airplane departs, no revenue is gained from the empty seat(s). In the hotel industry, the perishable asset is the hotel room‐once a room is left empty for a night, that night's revenue cannot be recaptured. The literature on yield management heuristics for the hotel industry is sparse. For the hotel operating environment, no research has adequately (1) integrated overbooking with allocation, (2) modeled the phenomenon of hotel patrons extending or contracting their stay at a moment's notice, or (3) performed a realistic performance comparison of alternative heuristics.This research develops (1) two hotel‐specific algorithms that both integrate overbooking with the allocation decisions, (2) a simulation model to reproduce realistic hotel operating environments, and (3) compares the performance of five heuristics under 36 realistic hotel operating environments. Seven conclusions are reached with regard to which heuristic(s) perform best in specific operating environments. Generally, heuristic selection is very much dependent on the hotel operating environment. A counterintuitive result is that in many operating environments, the simpler heuristics work as well as the more complex ones.
Information Systems Management Issues: Reporting and Relevance*
Authors: Palvia Prashant C. , Basu Suvojit Choton 
Published: June 2007

ABSTRACTReports 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.
Empirically Testing the Relationship Between End‐User Computing Problems and Information Center Success Factors
Authors: Guimaraes Tor , Gupta Yash P. , Rainer R. Kelly 
Published: June 2007

ABSTRACTEnd‐user computing (EUC) has been a significant organizational phenomenon for more than two decades and remains critically important with the rapid introduction of new technologies (e.g., client‐server architectures, internet and intranet applications). Although EUC is a mature concept, it is apparent that end users do not become independent over time, but instead require additional resources and support. One widely employed support mechanism is the Information Center (IC).This study surveyed the internal auditor and the information systems (IS) director in each of 185 organizations. The internal auditors provided responses on the severity of EUC problems in their organizations, and the IS directors supplied information on their firms' performance on the IC critical success factors (CSFs) proposed by Magal, Carr, and Watson (1988). Results show that stronger IC performance is indeed inversely related to the severity of EUC problems encountered by the organization. Specifically, the study's findings show that to have the greatest impact on EUC problems, IC managers should concentrate on clearly defining the IC's mission; establish standards and controls; monitor, coordinate, and help users prioritize applications development; and be responsive to user requests.
Supporting Quick Response Through Scheduling of Make‐to‐Stock Production/Inventory Systems*
Authors: Johnson M. Eric , Scudder Gary 
Published: June 2007

ABSTRACTScheduling of traditional job shops in make‐to‐order systems has seen extensive research over the past three decades. In such systems, performance is often related to various job completion metrics such as average flow time, average lateness, etc. This paper examines a scheduling problem in a make‐to‐stock environment where individual job completion measures are irrelevant. In this case, customer orders are satisfied through on‐hand inventory where customer service is more closely related to the manufacturer's ability to quickly satisfy demand. We consider the role of scheduling in reducing inventories and improving customer service in the context of a manufacturer who assembles several different products on a single assembly line. We develop scheduling rules for such a system and experimentally compare their performance to those typically used in such environments. Our results indicate that rules which consider the inventory position and demand forecast outperform traditional fixed cycle rules.
Variable Royalty Rates for Improving Franchise Channel Coordination*
Authors: Tikoo Surinder , Nair Suresh K. 
Published: June 2007

ABSTRACTA business format franchisor obtains a major part of its revenues from franchise royalties, which are typically a fixed percentage of franchisee gross sales. When a fixed royalty rate is used and the marginal costs of operating the franchise are increasing, the franchisee does not have an incentive to increase sales beyond a certain “optimal” volume. We present a model that recommends the use of a variable franchise royalty rate for extending this optimal sales volume. For a general convex cost function, we show that a new lower rate can be applied to incremental sales beyond the original optimal level. We show that this new rate should be less than half of the original rate when a quadratic cost function is applicable. Adopting a variable royalty rate increases franchisor royalty revenues and franchisee profits.
Workforce‐constrained Preventive Maintenance Scheduling Using Evolution Strategies
Authors: Ahire Sanjay , Greenwood Garrison , Gupta Ajay , Terwilliger Mark 
Published: June 2007

ABSTRACTHeavy equipment overhaul facilities such as aircraft service centers and railroad yards face the challenge of minimizing the makespan for a set of preventive maintenance (PM) tasks, requiring single or multiple skills, within workforce availability constraints. In this paper, we examine the utility of evolution strategies to this problem. Comparison of the computational efforts of evolution strategies with exhaustive enumeration to reach optimal solutions for 60 small problems illustrates the ability of evolution strategies to yield optimal solutions increasingly efficiently with increasing problem size. A set of 852 large‐scale problems was solved using evolution strategies to examine the effects of task‐related problem characteristics, workforce‐related variables, and evolution strategies population size (μ) on CPU time. The results empirically supported practical utility of evolution strategies to solve large‐scale, complex preventive maintenance problems involving single‐ and multiple‐skilled workforce. Finally, comparison of evolution strategies and simulated annealing for the 852 experiments indicated much faster convergence to optimality with evolution strategies.
An Integrative Framework of the Information Systems Development Process*
Authors: Sambamurthy V. , Kirsch Laurie J. 
Published: June 2007

ABSTRACTDespite more than 25 years of research on the processes and outcomes of information systems development in organizations, deficiencies exist in our knowledge about the effective management of complex systems development processes. Although individual studies have generated a wealth of findings, there is a need for a cumulative framework that facilitates interpretation of what has been learned and what needs to be learned about the process of information systems development. This paper reviews prior research on ISD processes and identifies the different types of contributions that have been made to our growing knowledge. More important, it generates a cumulative framework for understanding the process of ISD that could provide a valuable template for future research and practice.
Multicriteria Preference Disaggregation for Classification Problems with an Application to Global Investing Risk*
Authors: Doumpos Michael , Zanakis Stelios H. , Zopounidis Constantin 
Published: June 2007

AbstractMathematical programming and multicriteria approaches to classification and discrimination are reviewed, with an emphasis on preference disaggregation. The latter include the UTADIS family and a new method, Multigroup Hierarchical DIScrimination (MHDIS). They are used to assess investing risk in 51 countries that have stock exchanges, according to 27 criteria. These criteria include quantitative and qualitative measures of market risk (volatility and currency fluctuations); range of investment opportunities; quantity and quality on market information; investor protection (security regulations treatment of minority shareholders); and administrative “headaches” (custody, settlement, and taxes). The model parameters are determined so that the results best match the risk level assigned to those countries by experienced international investment managers commissioned byThe Wall Street Journal.Among the six evaluation models developed, one (MHDIS) classifies correctly all countries into the appropriate groups. Thus, this model is able to reproduce consistently the evaluation of the expert investment analysts. The most significant criteria and their weights for assessing global risk investing are also presented, along with their marginal utilities, leading to identifiers of risk groups and global utilities portraying the strength of each country's risk classification. The same method, MHDIS, outperformed the other five methods in a 10‐fold validation experiment. These results are promising for the study of emerging new markets in fast‐growing regions, which present fertile areas for investment growth but also
An Approximate Bayesian Algorithm for Combining Forecasts*
Authors: Li Kim‐Hung , Wong Heung , Troutt Marvin 
Published: June 2007

AbstractIn this paper we propose a consensus forecasting method based on a convex combination of individual forecast densities. The exact Bayesian updating of the convex combination weights is very complex and practically prohibitive. We propose a simple sequential updating alternative method based on function approximation. Several examples illustrate the method.
Discrete Sequential Search with Group Activities*
Authors: Wagner Bret J. , Davis Darwin J. 
Published: June 2007

AbstractEquipment failures can have significant implications in terms of cost and customer satisfaction. Reducing the time required to find the cause of a failure can provide large cost savings and help preserve customer goodwill. Single‐item discrete sequential search models can be used to sequence the tasks in diagnostic search to minimize the expected time required to find the cause of the failure. We increase the utility of the single‐item discrete sequential search model by developing a formulation that includes simple precedence relationships as well as sequence dependent relationships defined by group activities. This formulation can be applied to a number of other problems including determining the sequence for multiple quality control tests on an item, scheduling oil well workovers to maximize the expected increase in oil production, and sequencing tasks in a research project where there is a technological risk associated with each task.
New Product Development Decision‐Making Effectiveness: Comparing Individuals, Face‐To‐Face Teams, and Virtual Teams*
Authors: Schmidt Jeffrey B. , Montoya‐Weiss Mitzi M. , Massey Anne P. 
Published: June 2007

AbstractA total of 411 subjects participated in two decision‐making experiments in order to examine the effectiveness of new product development project continuation decisions. Using escalation of commitment theory, in Study 1, individual versus face‐to‐face team decision‐making effectiveness was compared. Study 2, an extension of Study 1, compared the new product development decision‐making effectiveness of individuals, face‐to‐face teams, and virtual teams. A virtual team is a geographically and temporally dispersed and electronically communicating work group. In Study 2, the virtual teams communicated asynchronously via groupware technology. Our findings suggest that teams make more effective decisions than individuals, and virtual teams make the most effective decisions.
Investigating the Level of End‐User Development and Involvement Among Time‐Based Competitors
Authors: Rondeau Patrick J. , Vonderembse Mark A. , Ragu‐Nathan T. S. 
Published: June 2007

ABSTRACTAs global markets and technology change, time‐based competitors create product development and manufacturing practices that reduce response time and enhance customization capabilities. These practices require an information‐rich internal environment that is capable of flexible resource deployment and direct and continuous feedback. To build this environment, time‐based competitors are developing end‐user capabilities and involving them in information systems (IS) activities. Data collected from 265 manufacturers were used to determine if firms with high levels of time‐based product development and time‐based manufacturing practices also have high levels of end‐user involvement in IS‐related activities, end‐user training effectiveness, and end‐user computing skills. The results of this study support that contention.
Shop Performance Implications of Using Cells, Partial Cells, and Remainder Cells*
Authors: Kher Hemant V. , Jensen John B. 
Published: June 2007

ABSTRACTThis paper considers the application of cellular manufacturing (CM) to batch production by exploring the shop floor performance trade‐offs associated with shops employing different levels of CM. The literature has alluded to a continuum that exists between the purely departmentalized job shop and the completely cellular shop. However, the vast majority of CM research exists at the extremes of this continuum. Here, we intend to probe performance relationships by comparing shops that exist at different stages of CM adoption. Specifically, we begin with a hypothetical departmentalized shop found in the CM literature, and in a stepwise fashion, form independent cells. At each stage, flow time and tardiness performance is recorded. Modeling results indicate that, depending on shop conditions and managerial objectives, superior shop performance may be recorded by the job shop, the cell shop, or by one of the shops between these extreme points. In fact, under certain conditions, shops that contain partially formed cells perform better than shops that use completely formed cells. Additional results demonstrate that in order to achieve excellent performance, managers investigating specific layouts need to pay especially close attention to changes in machine utilization as machine groups are partitioned into cells.
Modeling the Effects of a Service Guarantee on Perceived Service Quality Using Alternating Conditional Expectations (ACE)*
Authors: Sum Chee‐Chuong , Lee Yang‐Sang , Hays Julie M. , Hill Arthur V. 
Published: June 2007

ABSTRACTThis paper addresses the dearth of empirical research on the relationship between service guarantee and perceived service quality (PSQ). In particular, we examine the moderating effects of a service guarantee on PSQ. While a recent study provided empirical evidence that service quality is affected by service guarantee and employee variables such as employee motivation/vision and learning through service failure, the nature and form of the relationships between these variables remain unclear. Knowledge of these relationships can assist service managers to allocate resources more judiciously, avoid pitfalls, and establish more realistic expectations. Data was obtained from employees and customers of a multinational hotel chain that has implemented a service guarantee program in 89 of its hotels in America and Canada. As the employee variables could affect performance in a non‐linear fashion, we relaxed the assumption of model linearity by using the Alternating Conditional Expectations (ACE) algorithm to arrive at a better‐fitting, non‐linear regression model for PSQ. Our findings indicate the existence of significant non‐linear relationships between PSQ and its determinant variables. The ACE model also revealed that service guarantee interacts with the employee variables to affect PSQ in a non‐linear fashion. The non‐linear relationships present new insights into the management of service guarantees and PSQ. Explanations and managerial implications of our results are presented and discussed.
The Critical Few Minutes in Scheduling Time‐Varying Queuing Systems
Authors: Martinich Joseph S. 
Published: June 2007

ABSTRACTFor nonstationary queuing systems where demand varies over time, an important practical issue is scheduling the number of servers to be available at various times of the day. Widely used scheduling procedures typically involve adding servers at natural time points (e.g., on the hour or at half past the hour) during peak demand periods. Scheduling is often complicated by restrictions on the minimum amount of time (human) servers must work, the earliest (or latest) time a server is available, and limits on the maximum number of servers that can be used at any one time. This paper was motivated by experience with actual queuing systems that embodied such complications. For these systems common scheduling methods that used “natural” starting times for servers resulted in needlessly long customer waits. This research demonstrates that changing the starting times of servers by only a few minutes can have dramatic impacts on customer waiting times for extended periods. In addition, the results highlight the importance of server punctuality.
Leveraging the Strengths of Choice Models and Neural Networks: A Multiproduct Comparative Analysis*
Authors: Papatla Purushottam , Zahedi Mariam (Fatemeh) , Zekic‐Susac Marijana 
Published: June 2007

ABSTRACTChoice models and neural networks are two approaches used in modeling selection decisions. Defining model performance as the out‐of‐sample prediction power of a model, we test two hypotheses: (i) choice models and neural network models are equal in performance, and (ii) hybrid models consisting of a combination of choice and neural network models perform better than each stand‐alone model. We perform statistical tests for two classes of linear and nonlinear hybrid models and compute the empirical integrated rank (EIR) indices to compare the overall performances of the models.We test the above hypotheses by using data for various brand and store choices for three consumer products. Extensive jackknifing and out‐of‐sample tests for four different model specifications are applied for increasing the external validity of the results. Our results show that using neural networks has a higher probability of resulting in a better performance. Our findings also indicate that hybrid models outperform stand‐alone models, in that using hybrid models guarantee overall results equal or better than the two stand‐alone models. The improvement is particularly significant in cases where neither of the two stand‐alone models is very accurate in prediction, indicating that the proposed hybrid models may capture aspects of predictive accuracy that neither stand‐alone model is capable of on their own. Our results are particularly important in brand management and customer relationship management, indicating that multiple technologies and mixture of technologies may yield more accurate and reliable outcomes than individual ones.