Department of Information Systems & Operations Management

Decision Sciences Journal

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Author(s) Title
Yariv Taran, Harry Boer, and Peter Lindgren A Business Model Innovation Typology

Abstract:

An effective business model is the core enabler of any company’s performance. Business model innovation is not only becoming more and more important due to increasing and globalizing competition, but also an enormous challenge, both theoretically and practically. Although many managers are eager to consider more disruptive changes to their business model, they often do not know how to articulate their existing or desired business model and, even less so, understand the possibilities for innovating it. One of the steps towards developing more theoretical insight and practical guidelines is the identification of types and the development of a typology of business model innovations.

Ten retrospective case studies of business model innovations undertaken by two industrial companies provide the empirical basis for this article. We analyzed the characteristics of these innovations as well as their success rates. The findings suggest that there are indeed various business model innovation types, each with its own characteristics and challenges.

Rui Sousa, Marlene Amorim, Elliot Rabinovich, and Anníbal C. Sodero Customer Use of Virtual Channels in Multichannel Services: Does Type of Activity Matter?

Abstract:

Many firms have recently adopted virtual channels, based most notably on the Internet and the phone, to complement the delivery of services to their customers by their existing physical facilities. The success of such multichannel (MC) strategies relies on the alignment of service design decisions – namely those concerning the allocation of service activities to virtual channels – with customers’ MC behavior. While prior studies have looked at the intensity with which customers use virtual channels, they have not addressed virtual channel use for different types of service activities. In our study, we investigate whether customers’ use of virtual channels for MC services varies with the type of service activities they engage in, and if so, in what way. In doing so, we address two objectives. First, we investigate the impact of accessibility to the physical channel on the degree of use of virtual channels (Internet and phone, aggregated) for different types of activities.

Second, we look at channel preferences (Internet vs. phone) for different types of activities when customers do resort to virtual channels to conduct activities.

To address our objectives, we develop and test hypotheses regarding customers’ use of virtual channels based on the match between activity attributes (complexity and volume) and channel attributes (access efficiency, interface efficiency, interface richness). Using data from a MC bank, we find that the impact of accessibility to physical channels (specifically, customer distance) on customers’ use of virtual channels, as well as the relative use of Internet versus phone, depend on the type of activities.

Zhaolin Li, Lusheng Shao, and Daewon Sun Designing Multi-Attribute Procurement Mechanisms for Assortment Planning

Abstract:

This research investigates how to design procurement mechanisms for assortment planning. We consider that a retailer buys directly from a manufacturer who possesses private information about the per-unit variable cost and per-variety setup cost. We first develop a screening model to assist the retailer in integrating assortment planning into supply chain contracting processes when only one manufacturer is available. We demonstrate that the screening mechanism is optimal among all feasible procurement strategies. When there are multiple competing manufacturers, we propose a supply contract auctioning mechanism and evaluate its performance. In this mechanism, the retailer announces a contract menu and the manufacturer that bids the highest upfront fee paid to the retailer wins the auction. The winner then chooses and executes a contract from the contract menu. We show that when the retailer uses the optimal screening contract menu as the object of the auction, it achieves the optimal procurement outcome if the screening contract menu does not pay rent to any manufacturer type. This finding sheds light on the connection between screening and auction mechanisms when there exists multi-dimensional private information.

Taesu Cheong, Mark Goh, and Sang Hwa Song Effect of Inventory Information Discrepancy in a Drop-shipping Supply Chain

Abstract:

This paper investigates the impact of information discrepancy between a drop-shipper and an online retailer on the drop-shipping supply chain performance. The inventory information misalignment between them contributes to the failure of order fulfillment and demand satisfaction, and hence the associated penalties are incurred. In this paper, we first analyze the penalties of ignoring such information discrepancy on both the drop-shipper and the online retailer. We then assess the impact of information discrepancy on both parties when the drop-shipper understands the existence of the information discrepancy but is not able to eliminate the errors. The numerical experiments indicate that both parties can have significant amount of the percentage cost reductions if the information discrepancy can be eliminated, and the potential savings are substantial especially when the errors have large variability. Furthermore, we observe that the online retailer is more vulnerable to information discrepancy than the drop-shipper, and the drop-shipper is likely to suffer from the online retailer’s underestimation of the physical inventory level more than the problem of its overestimation. Moreover, even if eliminating errors is not possible, both parties could still benefit from taking the possibility of errors into consideration in decision making.

Yann B. Ferrand, Michael J. Magazine, and Uday S. Rao Partially Flexible Operating Rooms for Elective and Emergency Surgeries

Abstract:

In hospitals, the management of operating rooms faces a trade-off between the need to be responsive to emergency surgeries and to conduct scheduled elective surgeries efficiently. Operating rooms can be configured as flexible and handle both electives and emergencies, or as dedicated to focus on either electives or emergencies. With flexible rooms, the prioritization of emergencies over scheduled electives can lead to schedule disruptions. Focused rooms can lead to imbalances between capacity and surgery workload. Whereas hospital administrators typically handle this trade-off by employing either flexible rooms (complete flexibility) or dedicated rooms (complete focus), we investigate whether a combination of flexible and dedicated rooms (partial flexibility) could be a preferable alternative. The ensuing question is what is the right combination of flexible and dedicated rooms? A versatile simulation model is developed to evaluate different resource allocation policies under various environmental parameters and performance metrics, including patient wait time, staff overtime, and operating room utilization. The main result is that partial flexibility configurations outperform both complete flexibility and complete focus policies by providing solutions with improved values of expected wait time for both emergency and elective patients.

Pankaj Setia and Cheri Speier-Pero Reverse Auctions to Innovate Procurement Processes: Effects of Bid Information Presentation Design on a Supplier’s Bidding Outcome

Abstract:

Information technologies (ITs) are being used to innovate various procurement processes. This research study focuses on the supplier-side effects of IT design choices to conduct reverse auctions, which are increasingly used to procure a wide range of products and services. IT-enabled reverse auctions enhance supplier participation across geographical boundaries, leading to more efficient pricing. However, there are growing concerns about the adverse effects of IT-enabled reverse auctions on a supplier’s performance. Supplier-side issues are gaining prominence in the reverse auction literature and are critical for the long-term success of reverse auctions. Therefore, we focus on suppliers’ bidding outcomes and assess how the design of an IT-enabled reverse auction facilitates the auction bidding outcomes of participating suppliers. Specifically, we examine the effects of two types of bid information presentation design–full price visibility (FPV) and partial price visibility (PPV)–on supplier’s auction bidding outcomes, across auctions with different cost certainty and suppliers bargaining power vis-à-vis the buyer. The results of this study contribute new knowledge about the ways to use IT for creating effective auction designs and innovating procurement through auctions to enhance both the buyer’s and suppliers’ performance. We present the detailed theoretical contributions of our study and discuss the managerial implications for designers of reverse auctions.

Shailesh S. Kulkarni, Uday M. Apte, and Nicholas E. Evangelopoulos The Use of Latent Semantic Analysis in Operations Management Research

Abstract:

In this paper, we introduce the use of Latent Semantic Analysis (LSA) as a technique for uncovering the intellectual structure of a discipline. LSA is an emerging quantitative method for con-tent analysis that combines rigorous statistical techniques and scholarly judgment as it proceeds to extract and decipher key latent factors. We provide a step-wise explanation and illustration for implementing LSA. To demonstrate LSA’s ability to uncover the intellectual structure of a discipline, we present a study of the field of Operations Management. We also discuss a number of potential applications of LSA to show how it can be used in empirical Operations Management research, specifically in areas that can benefit from analyzing large volumes of unstructured textual data.

Daewon Sun, Robert Easley, Byung-Cho Kim Optimal Digital Rights Management with Uncertain Piracy

Abstract:

Many firms that sell digital copies of copyrighted materials online face a common dilemma: the use of Digital Rights Management (DRM) to impede pirates can impose restrictions on legitimate use. We introduce a two-period model in which the use of DRM in the first period affects the probability that a consumer finds a pirated copy in the second period; the threat of legal action reduces consumers’ consumption of pirated copies; and firms choose whether to sell, and at what prices, either strongly or weakly DRM-protected products, or both. Further, we incorporate the role of uncertainty concerning future levels of piracy. Using a two-period model with uncertainty, we investigate a firm’s optimal DRM strategies and present the optimal pricing strategy as well as product launch strategy under different market conditions. We find that one important characteristic of the optimal strategy is that it is optimal to maintain the same product line configuration strategy for both periods. We also characterize the conditions under which each strategy is optimal.

Marco Habermann, Jennifer Blackhurst, and Ashley Y. Metcalf Keep Your Friends Close? Supply Chain Design and Disruption Risk

Abstract:

In this paper, we evaluate the relationship between supply chain design decisions and supply chain disruption risk. We explore two supply chain design strategies: (1) the dispersion of supply chain partners to reduce supply chain disruption risk versus (2) the co-location of supply chain partners to reduce supply chain disruption risk. In addition, we assess supply chain disruption risk from three perspectives: the inbound material flow from the supplier (supply side), the internal production processes (internal), and the outbound material flow to the customer (customer side) as a disruption can occur at any of these locations. We measure disruption risk in terms of stoppages in flows, reductions in flow, close calls (disruptions that were prevented at the last minute), disruption duration (time until normal operation flow was restored), and the spread of disruptions all the way through the supply chain. We use seemingly unrelated regression (SUR) to analyze our data, finding that lead times, especially supply side lead times, are significantly associated with higher levels of supply chain disruption risk. We find co-location with suppliers appears to have beneficial effects to the reduction of disruption duration, and, overall supply side factors have a higher impact when it comes to supply chain disruption risk than comparable customer side factors.

Eren Demir A Decision Support Tool for Predicting Patients at Risk of Readmission: A Comparison of Classification Trees, Logistic Regression, Generalized Additive Models, and Multivariate Adaptive Regression Splines

Abstract:

The number of emergency (or unplanned) readmissions in the United Kingdom National Health Service (NHS) has been rising for many years. This trend, which is possibly related to poor patient care, places financial pressures on hospitals and on national healthcare budgets. As a result, clinicians and key decision makers (e.g. managers and commissioners) are interested in predicting patients at high risk of readmission. Logistic regression is the most popular method of predicting patient-specific probabilities. However, these studies have produced conflicting results with poor prediction accuracies. We compared the predictive accuracy of logistic regression with that of regression trees for predicting emergency readmissions within forty five days after been discharged from hospital. We also examined the predictive ability of two other types of data-driven models: generalized additive models (GAMs) and multivariate adaptive regression splines (MARS). We used data on 963 patients readmitted to hospitals with chronic obstructive pulmonary disease and asthma. We used repeated split-sample validation: the data were divided into derivation and validation samples. Predictive models were estimated using the derivation sample and the predictive accuracy of the resultant model was assessed using a number of performance measures, such as area under the receiver operating characteristic (ROC) curve in the validation sample. This process was repeated 1000 times—the initial data set was divided into derivation and validation samples 1000 times, and the predictive accuracy of each method was assessed each time. The mean ROC curve area for the regression tree models in the 1000 derivation samples was 0.928, while the mean ROC curve area of a logistic regression model was 0.924. Our study shows that logistic regression model and regression trees had performance comparable to that of more flexible, data-driven models such as GAMs and MARS. Given that the models have produced excellent predictive accuracies, this could be a valuable decision support tool for clinicians (health care managers, policy makers, etc.) for informed decision making in the management of diseases, which ultimately contributes to improved measures for hospital performance management.

Ram Narasimhan, Tobias Schoenherr, Brian W. Jacobs, and Myung Kyo (M.K.) Kim The Financial Impact of FSC Certification in the United States: A Contingency Perspective

Abstract:

This paper focuses on an important and emergent standard for sustainable operations management: the Forest Stewardship Council (FSC) certification. Unlike similar certifications, its focus is on the entire upstream supply chain, reflecting the criticality of supply chain management to ensure sustainable products. We investigate the financial impact from FSC certification, offering valuable decision support for managers considering this certification. Taking a contingency perspective, we view a firm’s supply chain position and its prior certification to the ISO 14001 standard as influencing the results. Drawing on signaling theory, we suggest that firms farther downstream in the supply chain realize significantly greater abnormal financial performance benefits than firms upstream in the supply chain. We further hypothesize that firms that were not ISO 14001 certified at the time of FSC certification realize significantly greater abnormal financial performance benefits than firms that did have the ISO 14001 certification. To test these hypotheses, we utilize financial data of all publicly traded firms in the United States that have obtained the FSC certification, and assess whether FSC certification leads to abnormal performance benefits considering the above contingencies. Data collected from the FSC Certificate Database and Compustat, employed in an event study, provide support for our hypotheses. Overall, our findings contribute to research on decision making in the context of sustainable operations management, and offer a plausible explanation for contradictory results in prior studies. We highlight the applicability of signaling theory to decision sciences research, and stress the need to consider contingencies in sustainability management research.

Damien Power, Robert Klassen, Thomas Kull, and Dayna Simpson Competitive Goals and Plant Investment in Environment and Safety Practices: Moderating Effect of National Culture

Abstract:

Operations managers clearly play a critical role in targeting plant-level investments toward environment and safety practices. In principle, a “rational” response would be to align this investment with senior management’s competitive goals for operational performance. However, operations managers also are influenced by contingent factors, such as their national culture, thus creating potential tension that might bias investment away from a simple rational response. Using data from 1453 plants in 24 countries, we test the moderating influence of seven of the national cultural characteristics on investment at the plant level in environment and safety practices. Four of the seven national cultural characteristics from GLOBE (i.e., uncertainty avoidance, in-group collectivism, future orientation and performance orientation) shifted investment away from an expected “rational” response. Positive bias was evident when the national culture favoured consistency and formalized procedures and rewarded performance improvement. In contrast, managers exhibited negative bias when familial groups and local coalitions were powerful, or future outcomes – rather than current actions – were more important. Overall, this study highlights the critical importance of moving beyond a naïve expectation that plant-level investment will naturally align with corporate competitive goals for environment and safety. Instead, the national culture where the plant is located will influence these investments, and must be taken into account by senior management.

Yoon Hee Kim and Urban Wemmerlov Does a Supplier’s Operational Competence Translate into Financial Performance? An Empirical Analysis of Supplier-Customer Relationships

Abstract:

We conduct an empirical investigation of how a supplier’s operational competence, as reflected by outcomes in the areas of quality, cost, delivery, flexibility and new product development, translates into financial gains from a key customer. In contrast to previous research directed at the firm level, this study focuses on the supplier-customer relationship level. Using survey data from 158 suppliers in the manufacturing industry, we perform structural equation modeling to map out the paths from operational competence to financial performance – via dependencies and cooperative behaviors between suppliers and their customers. This study is the first scholarly attempt to examine the link between suppliers’ operational competencies and financial performance in inter-organizational relationships. It is also an early investigation into operational competence as a source of bi-lateral dependence. Our findings show that the supplier’s operational competences increase its customer’s dependence by enhancing the value of its products/services. However, the resulting increase in the supplier’s power is not leveraged to shape relationship behaviors or capture value from its customer. In contrast, the customer’s existing power as a major buyer plays an important role in shaping cooperative behaviors and affecting the supplier’s financial performance from the customer relationship.

Hong Guo, Praveen Pathak, and Kenny Cheng Estimating Social Influences from Social Networking Sites – Articulated Friendships versus Communication Interactions

Abstract:

Despite the ubiquity of social networking sites, the online social networking industry is in search of effective marketing strategies to better profit from their established user base. Social media marketing strategies build on the premise that the social network of online users can be predicted and social influences among online users can be estimated. However, the existence of various heterogeneous social interactions on social networking sites presents a challenge for social network prediction and social influence estimation. In this paper we draw upon the literatures on self-presentation on social networking sites and signaling in online social networking to categorize six heterogeneous online social interactions on social networking sites into two types – articulated friendships and communication interactions. This paper provides empirical evidence for the differences between articulated friendships and communication interactions and the corresponding articulated and communication networks. In order to compare the impacts of the social influences based on these two networks, we utilize support vector machines to build a classifier to predict virtual community membership and we further estimate the marginal effects of these social influences using a two-stage probit least squares method. We find significant explanatory power of social influences in predicting virtual community membership. Although the communication network is much sparser than the articulated network, social influences based on the communication network achieve similar performance as the articulated network. These findings provide important implications for social media marketing as well as the management of virtual communities.

Andrei Neboian and Stefan Spinler Fleet Replacement, Technology Choice and the Option to Breach a Leasing Contract

Abstract:

We analyze the option to breach a leasing contract when replacing a fleet of ICVs (internal combustion engine vehicles) and EVs (electric vehicles) subject to cost uncertainty. We derive the optimal policy for technology choice and breaching ICV contracts. The decision to breach is shown to offer both cost savings resulting from reduced ICV operating costs and preemptive acquisition, but incurs additional costs arising from the need to compensate for breached vehicles and in the form of opportunity costs. We also demonstrate that the effects of breaching a leasing contract have a ripple effect across the decision horizon, thus amplifying the impact of a single breach. A numerical study based on data from La Poste, the French postal service, shows that breaching a leasing contract in this context offers measurable cost benefits.

Howard Hao-Chun Chuang, Guanyi Lu, David Xiaosong Peng, Gregory R. Heim Impact of Value-Added Service Features in e-Retailing Processes: An Econometric Analysis of Website Functions

Abstract:

We examine the impact of three classes of website functions (foundational, customer-centered, and value-added) upon e-retailer performance. Using secondary panel data for 2007-2009 on operating characteristics of over 600 e-retailers, our econometric analysis finds that only the value-added service functions are positively associated with changes in e-retail sales revenues across time. We also observe a decreasing marginal impact of deploying additional value-added service features. To account for possible alternate explanations, we control for firm- and time-specific fixed effects, merchant types, merchandise categories, and order fulfillment strategies. By further decomposing e-retail sales revenues into website traffic, conversion rate, and average order value, we find that website functions affect e-retail sales revenues mainly through their impact on website traffic. Our investigation demonstrates the empirical research usefulness of the Voss (2003) conceptual e-service sand cone model. Our results identify for managers where to focus ongoing e-retailing system development efforts, yet suggest that focusing too many retailing capabilities on exploratory and experimental value-added service features may backfire, potentially leading to worsening e-retailer performance.

Aravind Chandrasekaran and Kevin Linderman Managing Knowledge Creation in High-Tech R&D Projects: A Multi-method Study

Abstract:

R&D projects in high-tech organizations bring together diverse knowledge domains to quickly develop new products and processes. The fast paced context of high-tech organizations makes it challenging to create new knowledge and solve complex problems. Managing these R&D projects requires understanding both the mechanisms and the type of knowledge created to achieve project objectives. This research conducts a two phased multi-method study to understand knowledge creation in high-tech R&D projects. The first phase uses qualitative data to develop a theory on knowledge creation in R&D projects. The second phase involves a survey that collects data from R&D projects to test the theory. Results from the case study find that R&D projects benefit from two types of knowledge - objective and intuitive. The case analyses shows that intuitive and objective knowledge creation in high-tech organizations occurs by creating not only diverse but also psychological safe project teams. The large scale survey finds that team diversity positively influences objective knowledge creation while psychological safety affects intuitive knowledge creation. Surprisingly, the results show that team diversity negatively affects intuitive knowledge creation. A post-hoc analysis takes a more granular look at diversity and shows that different kinds of diversity have different effects on knowledge creation. This helps to better explain how to manage innovation across boundaries. Finally, the analysis shows that both objective and intuitive knowledge influence R&D project performance. Taken together these results help explain how to manage innovation across functional boundaries to create knowledge and enhance R&D project performance.

Tolga Akcura, Zafer Ozdemir, and Mohammad Rahman Online Intermediary as a Channel for Selling Quality Differentiated Services

Abstract:

When deciding whether to utilize an online intermediary in addition to their own distribution channels, quality differentiated service providers face the trade-off between the benefit of extended reach and the threat of increased competition. Using an analytical framework, we analyze when and how service providers may utilize an online intermediary to their advantage in the presence of advance selling (i.e., selling a service at an early date for future consumption). In general, when an online intermediary is used, the competition effect dominates the reach effect and leads to a falling price trend. Interestingly, we find that the negative effect of increased competition on profits, due to intermediary usage, can be reversed by committing to self-imposed participation limits (i.e., selling only a predetermined amount of services through the online intermediary). This ensures that the service provider is better off selling through both its own site and the online intermediary, rather than selling exclusively using either channel.

Landon Kleis, Barrie Nault, and Albert Dexter Producing Synergy: Innovation, IT and Productivity

Abstract:

Bringing innovations to market is critical to industrial progress and economic growth. We explore the potential for IT to enable innovations, and thus improve productivity. We hypothesize that a knowledge stock of process-oriented R&D increases total factor productivity growth by leveraging traditional forms of capital and labor, and further enhances the ability of IT capital to increase productivity. We estimate these relationships using two broad panels of US industries covering the periods 1987–1998 and 1998–2005. The results indicate qualified support for a synergistic effect of R&D and IT investment in both periods.

Layth Alwan, Minghui Xu, Dongqing Yao, and Xiaohang Yue The Dynamic Newsvendor Model with Correlated Demand

Abstract:

The classic newsvendor model was developed under the assumption that period-to-period demand is independent over time. In real-life applications, the notion of independent demand is often challenged. In this paper, we examine the newsvendor model in the presence of correlated demands. Specifically under a stationary AR(1) demand, we study the performance of the traditional newsvendor implementation versus a dynamic forecast-based implementation. We demonstrate theoretically that implementing a minimum mean square error (MSE) forecast model will always have improved performance relative to the traditional implementation in terms of cost savings. In light of the widespread usage of all-purpose models like the moving-average method and exponential smoothing method, we compare the performance of these popular alternative forecasting methods against both the MSE-optimal implementation and the traditional newsvendor implementation. If only alternative forecasting methods are being considered, we find that under certain conditions it is best to ignore the correlation and opt out of forecasting and to simply implement the traditional newsvendor model.

Öznur Özdemir-Akyıldırım, Meltem Denizel, and Mark Ferguson Allocation of Returned Products among Different Recovery Options through an Opportunity Cost based Dynamic Approach

Abstract:

In a make-to-order product recovery environment, we consider the disposition decision under stochastic demand of a firm with three options: refurbishing to resell, parts harvesting, and recycling. We formulate the problem as a multi-period Markov Decision Process (MDP) and present a Linear Programming approximation which provides an upper bound on the optimal objective function value of the MDP model. We then present two solution approaches to the MDP using the LP solution: a static approach which uses the LP solution directly and, a dynamic approach which adopts a revenue management perspective and employs bid-price controls technique where the LP is resolved after each demand arrival. We calculate the bid prices based on the shadow price interpretation of the dual variables for the inventory constraints and accept a demand if the marginal value is higher than the bid price. Since the need for solving the LP at each demand arrival requires a very efficient solution procedure, we present a transportation problem formulation of the LP via variable redefinitions and develop a one-pass optimal solution procedure for it. We carry out an extensive numerical analysis to compare the two approaches and find that the dynamic approach provides better performance in all of the tested scenarios. Furthermore the solutions obtained are within 2% of the upper bound on the optimal objective function value of the MDP model.

Stanley E. Griffis, Chad W. Autry, LaDonna M. Thornton, and Anis ben Brik Assessing Antecedents of Socially Responsible Supplier Selection in Three Global Supply Chain Contexts

Abstract:

A number of highly publicized, controversial lapses in social responsibility (SR) within global supply chains have forced managers and scholars to reexamine long-held perspectives on supplier selection. Extending Carter and Jennings’ (2004) department-level study of purchasing social responsibility, our research assesses the role of supply managers’ ethical intentions and three key antecedents that drive socially responsible supplier selection. Comparing evidence from firms operating in China, the U.S., and the U.A.E., we identify three key drivers of supply managers’ ethical intentions and examine both their direct and indirect impacts on socially responsible supplier selection. We find differential support for the predictor relationships on supply manager ethical intentions across national contexts and mediated versus non-mediated models. These observations bear important implications for firms conducting global supply management.

Hong-Bin Yan, Tieju Ma, and Van-Nam Huynh Coping with Group Behaviors in Uncertain Quality Function Deployment

Abstract:

Quality function deployment (QFD) is a planning and problem-solving tool gaining wide acceptance for translating customer needs (CNs) into technical attributes (TAs) of a product. It is a crucial step to derive the prioritization of TAs from CNs in QFD. However, it is not so straightforward to prioritize TAs due to two types of uncertainties: human subjective perception and user variability. The main focus of this paper is to propose a group decision-making approach to uncertain QFD with an application to a flexible manufacturing system design. The proposed approach performs computations solely based on the order-based semantics of linguistic labels to eliminate the burden of quantifying qualitative concepts in QFD. Moreover, it incorporates the importance weights of users and the concept of fuzzy majority into aggregations of individual fuzzy preference relations of different TAs in order to model the group behaviors in QFD. Finally, based on a quantifier-guided net flow score procedure, the proposed approach derives a priority ranking with a classification of TAs into important and unimportant ones so as to provide a better decision-support to the decision-maker. Due to the easiness in articulating preferential information, our approach can reduce the cognitive burden of QFD planning team and give a practical convenience in the process of QFD planning.

Gregory R. Heim, Xiaosong (David) Peng, and Shekhar Jayanthi Longitudinal Analysis of Inhibitors of Manufacturer Delivery Performance

Abstract:

This paper examines demand, manufacturing, and supply factors proposed to inhibit manufacturer delivery execution. Extant research proposes many factors expected to harm delivery performance. Prior cross-sectional empirical research examines such factors at the plant-level, generally finding factors arising from dynamic complexity to be significant, but factors arising from detail complexity to be insignificant. Little empirical research examines the factors using product-level operating data, which arguably makes more sense for analyzing how supply chain complexity factors inhibit delivery. For purposes of research triangulation, we use longitudinal product-level data from MRP systems to examine whether the factors inhibit internal manufacturing on-time job rates and three customer-oriented measures of delivery performance: product line item fill rates, average delivery lead times, and average tardiness. Our econometric models pool product line item data across division plants and within distinct product families, using a proprietary monthly dataset on over 100 product line items from the environmental controls manufacturing division of a Fortune 100 conglomerate. The data summarize customer ordering events of over 900 customers and supply chain activities of over 80 suppliers. The study contributes academically by finding significant detail complexity inhibitors of delivery that prior studies found insignificant. The findings demonstrate the need for empirical research using data disaggregated below the plant-level unit of analysis, as they illustrate how some factors previously found insignificant indeed are significant when considered at the product-level unit of analysis. Managers can use the findings to understand better which drivers and inhibitors of delivery performance are important.

Christopher W. Zobel Quantitatively Representing Nonlinear Disaster Recovery

Abstract:

This paper provides a new technique for quantitatively characterizing the progress of recovery operations in the aftermath of a disaster event. The approach extends previous research on measuring dynamic or adaptive disaster resilience by developing a robust approach for characterizing nonlinear disaster recovery. In doing so, it enables a more accurate mathematical representation of different categories of recovery behavior and provides support for a much broader application of existing theory. Because the new approach inherits the ability to compare the relative behavior of multiple scenarios simultaneously, it also can serve as the basis for analytically comparing the expected performance of different plans for recovery operations. Practical application of the technique is demonstrated and discussed in the context of recovering electrical power after Hurricane Sandy struck the New York metropolitan area.

Kenneth J. Klassen and Reena Yoogalingam Strategies for Appointment Policy Design with Patient Unpunctuality

Abstract:

Appointment policy design is complicated by patients who arrive earlier or later than their scheduled appointment time. This paper considers the design of scheduling rules in the presence of patient unpunctuality and how they are impacted by various environmental factors. A simulation optimization framework is used to determine how to improve performance by adjusting the schedule of appointments. Prior studies (that did not include patient unpunctuality) have found that a scheduling policy with relatively consistent appointment interval lengths in the form of a dome or plateau dome rule to perform well in a variety of clinic environments. These rules still perform reasonably well here, but it is shown that a combination of variable-length intervals and block scheduling are better at mitigating the effects of patient unpunctuality. In addition, performance improves if the use of this policy increases towards the end of the scheduling session. Survey and observational data collected at multiple outpatient clinics are used to add realism to the input parameters and develop practical guidelines for appointment policy decision making.

Sebastian Huber and Stefan Spinler Pricing of full-service repair contracts with learning, preventive maintenance, and information asymmetry

Abstract:

This paper considers the optimal pricing of full-service repair contracts by taking into account learning and maintenance efficiency effects, competition from service providers, and asymmetric information. We analyze on-call service (OS) and full service (FS) contracts in a market where customers exhibit heterogeneous risk aversion. While the customers minimize their disutility over the equipment lifetime, the service provider maximizes expected profits arising from the portfolio of OS and FS contracts. We show that the optimal FS price depends inter alia on the customer's prior cost experience and on OS repair and maintenance costs. The optimal FS price is shown to increase as fewer OS customers are lost to competition, whereas improved repair learning enabled by FS reduces the optimal price. A numerical study based on data from a manufacturer of forklifts highlights the importance of learning in maintenance operations, which constitutes the key benefit of FS contracts; 81% of the customers select the FS option and are willing to pay an insurance premium of around 1.5% of total OS cost against volatility of repair costs.

Claudia Rosales, Michael Magazine, and Uday Rao Point-of-Use Hybrid Inventory Policy for Hospitals

Abstract:

Modern point-of-use technology at hospitals has enabled new replenishment policies for medical supplies. One of these new policies, which we call the hybrid policy, is currently in use at a large US Midwest hospital. The hybrid policy combines a low-cost periodic replenishment epoch with a high-cost continuous replenishment option to avoid costly stockouts. We study this new hybrid policy under deterministic and stochastic demand. We develop a parameter search engine using simulation to optimize the long-run average cost per unit time and, via a computational study, we provide insights on the benefits (reduction in cost, inventory, and number of replenishments) that hospitals may obtain by using the hybrid policy instead of the commonly-used periodic policies. We also use the optimal hybrid policy parameters from the deterministic analysis to propose approximate expressions for the stochastic hybrid policy parameters that can be easily used by hospital management.

Babak Abbasi and S. Zahra Hosseinifard On the Issuing Policies for Perishable Items such as Red Blood Cells and Platelets in Blood Service

Abstract:

Red blood cells (RBCs) and platelets are examples of perishable items with a fixed shelf life. Recent studies show that transfusing fresh RBCs may lead to an improvement of patient outcomes. In addition, to better manage their inventory, hospitals prefer to receive fresh RBCs and platelets. Therefore, as well as minimizing outdates and shortages, reducing the average age of issue is a key performance criterion for blood banks. The issuing policy in a perishable inventory system has a substantial impact on the age of issue and outdate and shortage rates. Although several studies have compared the last in first out (LIFO) and the first in first out (FIFO) policies for perishable products, only a few studies have considered the situation of blood banks where replenishment is not controllable. In this study, we examine various issuing policies for a perishable inventory system with uncontrollable replenishment, and outline a modified FIFO policy. Our proposed modified FIFO policy partitions the inventory into two parts such that the first part holds the items with age less than a threshold. It then applies the FIFO policy in each part and the LIFO policy between the parts. We present two approximation techniques to estimate the average age of issue, the average time between successive outdates and the average time between successive shortages of the modified FIFO policy. Our analysis shows in several cases that where the objective function is a single economic function, or it is formulated as a multi-objective model, the modified FIFO policy outperforms the FIFO and LIFO policies.

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