Abstract: Advances in information technology, particularly in the e-business arena, are enabling firms to rethink their supply chain strategies and explore new avenues for inter-organizational cooperation. However, an incomplete understanding of the value of information sharing and physical flow coordination hinder these efforts. This research attempts to help fill these gaps by surveying prior research in the area, categorized in terms of information sharing and flow coordination. We conclude by highlighting gaps in the current body of knowledge and identifying promising areas for future research.

Abstract: This paper defines and operationalizes eight ERP competence constructs. We define ERP competence as a portfolio of managerial, technical and organizational skills and expertise posited as antecedents to improved business performance occurring after an ERP system is operational and functionally stable. To improve responses to changes in markets and products, manufacturers are increasingly adopting ERP systems. However, anecdotal accounts indicate that the realization of ERP's potential benefits is rare. Because of its pervasive influence on manufacturing and business performance, the need for scientifically developed and tested multi-item scales pertaining to ERP competence is highly relevant to manufacturing strategy research. We follow a two-stage normative process of scale development. First, we identify a portfolio of eight generic constructs that are hypothesized to be associated with successful ERP adoption. Each construct is then operationalized as a multi-item measurement scale by applying a manual item sorting technique iteratively to independent panels of expert judges until tentative reliability and validity is established. Second, we further refine and validate the multi-item scales using survey data from 79 North American manufacturing users of ERP systems.

Abstract: In the literature of cooperative (co-op) advertising, the focus of the research is on a relationship in which a manufacturer is the leader and retailers are followers. This relationship implies the dominance of the manufacturer over retailers. Recent market trends have shown a shift in power from manufacturers to retailers. Retailers, as a result, may now possess equal or even greater power than a manufacturer in some instances when it comes to retailing. Based on this new market phenomenon, we intend to explore the role of co-op advertising in a manufacturer-retailer supply chain through brand name investments, local advertising expenditures, and sharing rules of advertising expenses. Two co-op advertising models are developed and compared. The first co-op advertising model is based on the traditional leader-follower relationship of a manufacturer and a retailer. The second model incorporates partnership into co-op advertising coordination. Business examples and managerial implications of the models have been discussed. A cooperative bargaining technique is utilized to implement the partnership co-op advertising model.

Abstract: In recent years, the area of Supply Chain Management has generated a substantial amount of interest both by managers and researchers. This interest has also been fueled by the growth in the development and application of e-business technologies. These technologies enable the supply chain manager to make coordinated decisions by integrating the diverse and sometimes conflicting objectives of the various trading partners in a chain. The purpose of this paper is to: (a) highlight strategic and tactical issues for analyzing supply chains in an e-business setting based on papers published in this special issue; and (b) describe future research opportunities in this emerging interdisciplinary area.

Abstract: Academics and practitioners alike are focusing more attention on manufacturing strategy after having recognized the important role it plays in shaping the success of industrial firms. Even though research in this area has increased in the last decade, the focus of much of that work has been on the content rather than the process of the manufacturing strategy. Consequently, this study attempts to understand the important elements of the strategic manufacturing planning process and its effectiveness. Borrowing from the extant literature in the fields of strategic management and information systems, we propose a research model that relates strategic manufacturing planning system design to planning system success. Using structured questionnaires, empirical data is collected from over 200 manufacturing executives to test the model hypotheses. Planning process in manufacturing was found to be a bottom-up approach from a corporate or business perspective, which differs from the top-down planning process prevalent in strategic information systems planning process. Findings also indicate that greater planning system success in manufacturing is associated with a planning system that combines some “rational” elements (formality, comprehensiveness, control focus, longer horizon) with others that lend adaptability (wider participation and more intense interaction). But the strategic manufacturing planning system is more than just a collection of independent planning characteristics. Instead, it can be viewed as a gestalt planning system whereby planning characteristics move together in affecting overall planning system success.

Abstract: Make-to-order firms use different approaches for managing their lead-times and pricing in the face of changing market conditions. A particular firm's approach may be largely dictated by environmental constraints. For example, it makes little sense to carefully manage lead-time if its effect on demand is muted, as it can be in situations where leadtime is difficult for the market to gauge or requires investment to estimate. Similarly, it can be impractical to change capacity and price. However, environmental constraints are likely to become less of an issue in the future with the expanding e-business infrastructure, and this trend raises questions into how to manage effectively the marketing mix of price and lead-time in a more “friction-free” setting. We study a simple model of a make-to-order firm, and we examine policies for adjusting price and capacity in response to periodic and unpredictable shifts in how the market values price and lead-time. Our analysis suggests that maintaining a fixed capacity while using lead-time and/or price to absorb changes in the market will be most attractive when stability in throughput and profit are highly valued, but in volatile markets, this stability comes at a cost of low profits. From a pure profit maximization perspective, it is best to strive for a short and consistent lead-times by adjusting both capacity and price in response to market changes.

Abstract: This 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.

Abstract: This paper proposes a decision rule to rank actions under strict uncertainty, the available information being limited to the states of nature, the set of alternative rows, and the consequence of choosing every row if a given state occurs. This rule is suitable to moderately pessimistic individuals and social groups, these agents being neither maximax nor maximin decision makers but people who assume that the best outcome from the action will not occur. For these decision makers the paper shows the existence of a consistent weight system in which one and only one weight is attached to each state of the world under plausible conditions of domination. Most of the traditional axioms are satisfied by the proposed ranking approach. In the frame of disappointment (measured by ranges of column dispersion), the meaning of some controversial postulates used in the literature is explained. The proposed criterion is a departure from Laplace’s (1 825) rule and from the remaining standard criteria. Only in the special case of equal column dispersion do both Laplace’s rule and the proposed weights lead to the same solution. Subject Areas: Decision Analysis, Disappointment, Domination, and Unce&n& INTRODUCTION According to certain common definitions, strict uncertainty means almost complete lack of knowledge about an outcome. Regarding this type of uncertainty, the authors distinguish between complete and partial ignorance (Arrow & Hurwicz, 1972). Under complete ignorance the probabilities are totally unknown while under partial ignorance they are virtually but not totally unknown. More precisely, in the case of partial ignorance, the individual’s vague beliefs about them are sufficient to assign superior positions to some states of the world with respect to the remaining states. However, “complete ignorance” might be an inappropriate terminology, as the decision maker (DM) has sufficient information on the states of the world (with exception of their probabilities), and he can predict the consequence xij *Thanks are given to the reviewers for their helpful suggestions which have greatly improved the presentation and accuracy of the paper. The English editing by Dr. Keith Stuart is appreciated.

Abstract: A supply chain consisting of a single supplier distributing two independent products through multiple retailers is analyzed in this paper. The supplier needs to incentivize its retailers to adopt stocking policies that are mutually advantageous and that result in the optimal level of market coverage. The focus is on determining the optimal stocking policies for retailers and the resulting distribution strategy given that the supplier has either unlimited or limited capacity. The results provide insights on the optimal distribution strategy and stocking policies for the supply chain. In general, the paper shows that it is optimal for the supplier to use an intensive distribution strategy (i.e., the products are stocked by all retailers). Selective or exclusive strategies are optimal only when retailers are risk averse, stocking synergies exist, and there are differences in demand or supply uncertainties across products. The analysis also shows that retailers hold larger stocks of a product which generates higher supplier margins but only when the supplier has unlimited capacity. If the supplier has limited capacity, then their margins have no effect on retailers' stocking decisions. Contrary to conventional wisdom, retailers hold larger stocks of a product that has less demand uncertainty as compared to one that has more demand uncertainty.

Abstract: Revenue Management Systems (RMS) are commonly used in the hotel industry to maximize revenues in the short term. The forecasting-allocation module is a key tactical component of a hotel RMS. Forecasting involves estimating demand for service packages across all stayover nights in a planning horizon. A service package is a unique combination of physical room, amenities, room price, and advance purchase restrictions. Allocation involves parsing the room inventory among these service packages to maximize revenues. Previous research and existing revenue management systems assume the demand for a service package to be independent of which service packages are available for sale. We develop a new forecasting-allocation approach that explicitly accounts for this dependence. We compare the performance of the new approach against a baseline approach using a realistic hotel RMS simulation. The baseline approach reflects previous research and existing industry practice. The new approach produces an average revenue increase of at least 16% across scenarios that reflect existing industry conditions.

Abstract: Choice 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.

Abstract: This paper points out the need for performance measures in the context of simulation optimization and suggests six such measures. Two of the measures are indications of absolute performance, whereas the other four are useful in assessing the relative performance of various candidate metamodels. The measures assess performance on three fronts: accuracy of placing optima in the correct location, fit to the response, and fit to the character of the surface (expressed in terms of the number of optima). Examples are given providing evidence of the measures' utility—one in a limited scenario deciding which of two competing metamodels to use as simulation optimization response surfaces vary, and the other in a scenario of a researcher developing a new, sequential optimization search procedure.

Abstract: We develop a stochastic model to explore the benefits of incorporating auctions in revenue management. To the best of our knowledge the extant literature on modeling in revenue management has not considered auctions. We consider three models, namely, a traditional fixed price (non-auction) model, a pure auction model, and a hybrid auction model and evaluate their revenue performance under a variety of conditions. The hybrid approach outperforms the other two in all 24 scenarios and yields an average revenue increase of 16.1% over the next best. A surprise finding is that there is no significant difference between the performance of the fixed price and pure auction approaches. A sensitivity analysis reveals that the relative superiority of the hybrid revenue management strategy is reasonably robust.

Abstract: This 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.

Abstract: For 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.

Abstract: Job shops have long faced pressures for improvement in a challenging and volatile environment. Today's trends of global competition and shortening of product life cycles suggest that both the challenges and the intensity of market volatility will only increase. Consequently, the study of tactics for maximizing the flexibility and responsiveness of a job shop is important. Indeed, there is a significant body of literature that has produced guidelines on when and how to deploy tactics such as alternate routings for jobs and transfers of cross-trained workers between machines. In this paper we consider a different tactic by adjusting the length of workdays. Hours in excess of a 40-hour week are exchanged for compensatory time off at time and a half, and the total amount of accrued compensatory time is limited to no more than 160 hours in accordance with pending legislation. We propose several simple flexible workday policies that are based on an input/output control approach and investigate their performance in a simulated job shop. We find significant gains in performance over a fixed schedule of eight hours per day. Our results also provide insights into the selection of policy parameters.

Abstract: Moment-matching discrete distributions were developed by Miller and Rice (1983) as a method to translate continuous probability distributions into discrete distributions for use in decision and risk analysis. Using gaussian quadrature, they showed that an n-point discrete distribution can be constructed that exactly matches the first 2n - 1 moments of the underlying distribution. These moment-matching discrete distributions offer several theoretical advantages over the typical discrete approximations as shown in Smith (1993), but they also pose practical problems. In particular, how does the analyst estimate the moments given only the subjective assessments of the continuous probability distribution? Smith suggests that the moments can be estimated by fitting a distribution to the assessments. This research note shows that the quality of the moment estimates cannot be judged solely by how close the fitted distribution is to the true distribution. Examples are used to show that the relative errors in higher order moment estimates can be greater than 100%, even though the cumulative distribution function is estimated within a Kolmogorov-Smirnov distance less than 1%.

Abstract: Rationality is a fundamental concept to several models of IT planning and implementation. Though the importance of following rational processes in making strategic IT decisions is well acknowledged, there is not much understanding on why discrepancies occur in the IT decision-making process and what factors affect rationality. Drawing upon structural and resource-based perspectives of strategy, this study examines the influence of shared domain knowledge and IT unit structure on rationality in strategic IT decisions. Data were gathered from 223 senior IT executives using a survey to examine the relationships among the research constructs. The results suggest a positive impact of shared domain knowledge and formalization of IT unit structure on rationality in strategic IT decisions. Further, a highly centralized IT unit structure was found to negatively influence shared domain knowledge. On the other hand, formalization of IT structure positively influenced shared domain knowledge. The implications of the findings for research and practice are presented.

Abstract: 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.

Abstract: The focus of this study is on business-to-consumer (B2C) online auctions made possible by the advent of electronic commerce over an open-source, ubiquitous Internet Protocol (IP) computer network. This work presents an analytical model that characterizes the revenue generation process for a popular B2C online auction, namely, Yankee auctions. Such auctions sell multiple identical units of a good to multiple buyers using an ascending and open auction mechanism. The methodologies used to validate the analytical model range from empirical analysis to simulation. A key contribution of this study is the design of a partitioning scheme of the discrete valuation space of the bidders such that equilibrium points with higher revenue structures become identifiable and feasible. Our analysis indicates that the auctioneers are, most of the time, far away from the optimal choice of key control factors such as the bid increment, resulting in substantial losses in a market with already tight margins. With this in mind, we put forward a portfolio of tools, varying in their level of abstraction and information intensity requirements, which help auctioneers maximize their revenues.

Abstract: Supply chain partnership involves mutual commitments among participating firms. One example is early order commitment, wherein a retailer commits to purchase a fixed-order quantity and delivery time from a supplier before the real need takes place. This paper explores the value of practicing early order commitment in the supply chain. We investigate the complex interactions between early order commitment and forecast errors by simulating a supply chain with one capacitated supplier and multiple retailers under demand uncertainty. We found that practicing early order commitment can generate significant savings in the supply chain, but the benefits are only valid within a range of order commitment periods. Different components of forecast errors have different cost implications to the supplier and the retailers. The presence of trend in the demand increases the total supply chain cost, but makes early order commitment more appealing. The more retailers sharing the same supplier, the more valuable for the supply chain to practice early order commitment. Except in cases where little capacity cushion is available, our findings are relatively consistent in the environments where cost structure, number of retailers, capacity utilization, and capacity policy are varied.

Abstract: In this paper we extend the ELSP model to allow for linearly changing demand rates over a fixed planning horizon. This extension of the ELSP research provides a model that can be used in coordinating the production and marketing planning activities in a firm. The model allows the user to evaluate the impact of changes in product demand on production costs and customer service. We solve the model using a standard nonlinear programming package (MINOS) and show through examples based on actual production data how the model can be used to support coordinated production and marketing planning.

Abstract: As 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.

Abstract: Current opinion holds that Internet-based supply chain integration with upstream suppliers and downstream customers (called “e-integration” in this paper) is superior to traditional ways of doing business. This proposition remains untested, however, and similarly we know little about what are the upstream, internal, and downstream barriers to implementing e-integration. This paper empirically addressed these questions using data from a large single nation study, and found (1) a positive link between e-integration and performance, and (2) that internal barriers impeded e-integration more than either upstream supplier barriers or downstream customer barriers. Findings from this study contribute to our theoretical understanding of implementing change in contemporary supply chains, and have important implications for manufacturers interested in improving their supply chain's performance using the Internet.

Abstract: This article describes the results of a study assessing the psychometric properties of the expectations and perceptions-of-performance instruments and the difference-score data contained within the information systems (IS)-Adapted SERVQUAL measurement paradigm. The central claim of this study is: In order for rational inferences to be made about service expectations, service performance perceptions, or the gap between them, each of the two instruments must exhibit reasonable psychometric properties in isolation before difference-scores are taken. Analysis of data from a field study (N= 401) through structural equation modeling (SEM) techniques produces empirical evidence indicating that both of the instruments exhibit low psychometric quality and yet the difference-scores exhibit “psychometric inflation.” That is, the quality of the difference-score data is in many ways apparently superior to the raw data from both instruments. Negative conclusions are reached as to the efficacy of either individual instrument and, thus, the full IS-Adapted SERVQUAL paradigm. Questions and prospects for further research in this important area of service quality measurement/management are presented, and a potentially rich future for IS service quality is outlined. It is strongly suggested that future IS service quality research be based on development of a new instrument, grounded in attributes endemic to IS services and developed using the best available development techniques.

Abstract: As the importance of supplier networks becomes increasingly recognized as a vital factor to company performance, researchers and practitioners alike are focusing their attention on this subject. The study's main objective is to test the specific hypotheses that effective use of Information Technology (IT) and the depth of company relationships with suppliers are directly related to Supplier Network (SN) performance, and that industry clockspeed moderates these relationships. A convenience sample of 135 manufacturing organizations was used to empirically test these hypotheses. Our results indicate that clockspeed does moderate the relationship between IT use effectiveness and supplier network performance. The same is true in the case of supplier relations depth, and hence, managers are encouraged to pay attention to the items comprising network performance as a determinant of supplier network performance.