Department of Information Systems & Operations Management

Decision Sciences Journal

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Forthcoming

(Issues 44-4 and later)

Author(s) Title
Gang Peng, Jifeng Mu, and C. Anthony Di Benedetto (contact) Learning and Open Source Software License Choice

Abstract:

Licensing is the defining characteristic of open source software (OSS) and often has tremendous impact on the success of OSS projects. However, OSS licenses are very different from those for proprietary software, and our understanding of the choice of OSS licenses is very limited. In this study, we explore this important decision from a learning perspective. We build collaboration networks and trace paths through which potential learning and knowledge flow across projects occur using a dataset derived from SourceForge. We identify that both experiential learning and vicarious learning have significant influence on OSS license choice. We provide reasons why experiential learning and vicarious learning affect decision-making regarding OSS license choice, and explore important contingencies under which the two modes of learning are more effective. We find that leadership roles on prior projects and similarities between projects significantly moderate these two modes of learning respectively. More importantly, we argue and empirically illustrate that experiential learning is more powerful than vicarious learning in influencing OSS license choice. Our research sheds new light on our understanding of license choice for OSS projects and provides practical guidelines for future OSS development.
Shamir, Noam Asymmetric Forecast Information and the Value of Demand Observation in Repeated Procurement

Abstract:

In many supply chain relationships that continue over multiple periods, information about the hidden properties of the supply chain partners can be revealed throughout the course of the relationship. This paper examines how the availability of such information affects the contracting scheme between a supplier and his manufacturer in a relationship that persists over several selling seasons. At the beginning of the first selling season, the manufacturer observes private information about the demand distribution, whereas the supplier who is less familiar with the market is endowed only with a prior belief about the market condition. When the supplier cannot observe the demand realization during the first selling period, she offers a contract that induces the manufacturer to reveal the market condition in the first selling season. However, the opportunity for the supplier to observe demand realization can result in the supplier offering the manufacturer a simple contract that does not induce the manufacturer to reveal his private information during the first selling season. In the latter case, the supplier observes the demand realization and designs the second period contract based on this information. We show that when the supplier chooses to offer such a contract, the manufacturer becomes worse-off, and it has an ambiguous effect on the performance of the supply chain.
Michael Galbreth, Bikram Ghosh, and Guangzhi Shang The Competitive Impact of Targeted Television Advertisements Using DVR Technology

Abstract:

The Digital Video Recorders (DVR) is an emerging technology that is fundamentally changing the competitive landscape in industries that advertise on television. Perhaps the most familiar impact of DVR technology is that it enables consumers to avoid advertisements by fast forwarding through them. However, this "zipping" of ads is only one aspect of the impact of DVR technology. DVRs also collect a wealth of information at the consumer level that can be used by firms to target their advertisements more effectively. We examine how this targeting capability moderates the impact of ad avoidance in a competitive setting. Insights are provided on how best to manage this emerging technology in terms of the key managerial decisions of product pricing and advertising efforts, as well as its impact on profits in a competitive (duopoly) marketplace.
Suzuki, Yoshinori and Jing Dai Decision Support System of Truck Routing and Refueling: A Dual-Objective Approach

Abstract:

The variable-route vehicle-refueling problem (VRVRP) is a variant of the network-flow problem which seeks, for a vehicle traveling from origin s to destination d, both the route and the refueling policy (sequence of fuel stations to use between s and d) that jointly minimize the fuel cost of operating the vehicle. Commercial-grade decision support systems that solve the VRVRP are widely used by motor carriers, but they provide heuristic solutions only. Exact methods are available from the academic side, but because they focus on minimizing costs, they tend to cut fuel costs in exchange for increased vehicle miles (which can increase fuel consumptions and pollutants emission). We propose a new approach to the VRVRP that allows carriers to jointly seek the two possibly conflicting goals; minimizing fuel cost and vehicle miles. Computational testing shows that our approach: (i) outperforms the commercial software products in both goals, and (ii) finds solutions that require significantly less vehicle miles than those given by the exact method proposed in the academic literature, without incurring unacceptable increases in fuel cost.
W.C. Benton and Toyin Clottey Guidelines for Improving the Power Values of Statistical Tests for Non-Response Bias Assessment in OM Research

Abstract:

The assessment of non-response bias in survey based empirical studies plays an important role in establishing the credibility of research results. Statistical methods which involve the comparison of responses from two groups (e.g., early vs. late respondents) on multiple characteristics, which are relevant to the study, are frequently utilized in the assessment of non-response bias. We consider the concepts of individual and complete statistical power used for multiple testing and show their relevance for determining the number of statistical tests to perform when assessing non-response bias. Our analysis of factors that influence both individual and complete power levels, yielded recommendations that can be used by OM empirical researchers to improve their assessment of non-response bias. A power analysis of 61 survey-based research papers published in three prestigious academic OM journals, over the last decade, showed the occurrence of very low (<0.4) power levels in some of the statistical tests used for assessing non-response bias. Such low power levels can lead to erroneous conclusions about non-response bias, and are indicators of the need for more rigor in the assessment of non-response bias in OM research.
Hubert Pun Channel Structure Design for Complementary Products under a Co-opetitive Environment

Abstract:

In the high-tech industry, firms can be partners in one respect (e.g., resellers) and competitors in another. In this paper, we investigate the channel structure problem for two firms – each selling competing products in two complementary markets – who are deciding whether to sell their products to customers directly or distribute one of them through a competitor. The customers are heterogeneous and both firms have products that are horizontally differentiated. When selling products directly, the firm can co-ordinate the prices of the two complementary products and avoid the inefficiency of double marginalization. However, selling (indirectly) through the competing manufacturer can mitigate competition because the competitor shares the profit of both competing products and therefore does not price its own products aggressively. One might expect that when the externality across the markets is strong, firms would prefer to sell both products directly (rather than through the competitor) in order to take advantage of the complementarity between markets and eliminate the inefficiency of double marginalization. Interestingly, we find that even though the first mover chooses to sell both products directly, the second mover forsakes the opportunity to co-ordinate the prices of its products and instead opts to distribute one of the products through the first mover.
Muge Yayla-Kullu Capacity Investment and Product Line Decisions of a Multiproduct Leader and a Focus Strategy Entrant

Abstract:

In this paper, I investigate the capacity investment cost conditions where a multiproduct market leader may respond to a focus strategy entrant by using different strategies such as changing the product mix, production volumes, quality levels, and by investing in more capacity. The products offered in the market are quality differentiated and the customer base is heterogeneous in their willingness to pay for quality. The capacity investment costs of the two firms (i.e., the leader and the entrant) may also be different. Classical Stackelberg model predicts that an incumbent does not change its position in response to entry. However, when heterogeneous customer base, product differentiation, and capacity costs are taken into consideration, I find that the leader with a low capacity cost may choose to expand its product line and increase its production. The leader with low capacity cost may introduce a product that it was holding back when the entrant has to bear the high capacity cost and cannibalization threat is relatively small. The extent of production volume strategies reduces as the capacity cost increases for the leader. I also find that when the leader has the power to set the industry standards by deciding the quality levels, as a response to a high quality focused entrant, the leader increases both levels of quality and production of the low quality product. Moreover, when the capacity investment cost is high for both the entrant and the leader, I find that market prices may increase with entry.
B. Elango, Srinivas (Sri) Talluri, and G. Tomas M. Hult Understanding Drivers of Risk-Adjusted Performance for Service Firms with International Operations

Abstract:

This paper investigates whether international operations of service firms increase performance while reducing risk. The paper draws on a longitudinal dataset of 584 internationally operating service firms from the United States. Analysis indicates that international diversification is negatively related to risk-adjusted performance. However, it is established that international diversification interacts with internationalization and positively influences risk-adjusted performance. This finding offers significant promise for firms, as it indicates that international operations (if managed well), through exposure to varied foreign markets coupled with adequate global scope, can lead to firms’ increased risk-adjusted performance. The results provide a mechanism for decision-makers to better understand international operations of service firms and present a strategy for achieving success in international markets by effectively managing two important levers, i.e., internationalization and international market diversification.
Pankaj C. Patel, Arash Azadegan, and Lisa M. Ellram The Effects of Strategic and Structural Supply Chain Orientation on Operational and Customer-Focused Performance

Abstract:

Supply chain orientation (SCO), or the implementation of a supply chain management philosophy, consists of two distinct, yet interdependent elements, namely strategic SCO and structural SCO. Strategic SCO involves integrating a SCM philosophy into the firm’s strategy development, while structural SCO encompasses operational-level behaviors and actions that reflect such a philosophy. This study extends the research on SCO by developing hypotheses on the contingent effects of strategic SCO and structural SCO on a firm’s operational and customer-focused performance. Drawing on the Strategy-Structure-Performance framework, the study proposes that strategic SCO and structural SCO positively affect different dimensions of performance and that structural SCO plays a mediating role in the relationship between strategic SCO and performance. These relationships are tested using primary survey data and archival data from 183 manufacturers in the Midwestern US. Results confirm that strategic SCO is associated with both operational performance and customer-focused performance, but structural SCO is only related to operational performance. Structural SCO acts as a mediator in linking strategic SCO with operational performance and customer-focused performance and mediation effects are strengthened at higher levels of environmental dynamism.
Gilvan C. Souza Closed-Loop Supply Chains: A Critical Review, and Future Research

Abstract:

In this paper I present a review and tutorial of the literature on closed-loop supply chains, which are supply chains where, in addition to typical forward flows, there are reverse flows of used products (post consumer use) back to manufacturers. Examples include supply chains with consumer returns, leasing options, and end-of-use returns with remanufacturing. I classify the literature in terms of strategic, tactical, and operational issues, but I focus on strategic issues (such as when should an OEM remanufacture, response to take-back legislation, and network design, among others) and tactical issues (used product acquisition and disposition decisions). The paper is written in the form of a tutorial, where for each topic, I present a base model, with underlying assumptions, results, comment on extensions, and conclude with my view on needed research areas.
Kaitlin D. Wowak, Christopher W. Craighead, David J. Ketchen, Jr., and G. Tomas M. Hult Supply Chain Knowledge and Performance: A Meta-Analysis

Abstract:

Many firms make significant investments into developing and managing knowledge within their supply chains. Such investments are often prudent because studies indicate that supply chain knowledge (SCK) has a positive influence on performance. Key questions still surround the SCK-performance relationship, however. First, how big is the overall relationship between SCK and performance? Second, under what conditions is the relationship stronger or weaker? To address these questions, we applied meta-analysis to 35 studies of the SCK-performance relationship that collectively include more than 8,400 firms. Our conservative estimate is that the effect size of the overall relationship is = .39. We also find that the SCK-performance relationship is stronger when (a) examining operational performance, (b) gathering data from more than one supply chain node, (c) gathering data from multiple countries, (d) examining service industries, and (e) among more recently published studies. We also found that studies that embraced a single theory base (as opposed to using multiple ones) had a stronger SCK-performance relationship. Looking to the future, our meta-analysis highlights the need for studies to (a) include lags between the measurement of SCK and performance, (b) gather upstream data when examining innovation, (c) examine SCK within emerging economies, and (d) provide much more information relative to the nuances of the SCK examined.
Anteneh Ayanso and Brian Mokaya Efficiency Evaluation in Search Advertising

Abstract:

In this paper, we use data envelopment analysis combined with principal component analysis (PCA-DEA) to evaluate the efficiency of online retailers in search advertising. We examine various efficiency model specifications involving several resource- and performance-related variables in search advertising. Our analysis based on 200 retailers suggests different efficiency patterns for multi-channel and Web-only retailers. The results of our efficiency pattern analysis indicate that the performance metrics, impressions, online sales, click-through rate, and conversion rate together reveal differences in efficiency mainly for multichannel retailers. On the other hand, ad positions in sponsored and organic links reveal differences in efficiency for Web-only retailers. In terms of overall efficiency, we find that multichannel retailers occupy relatively most of the top positions. These results contribute to organizational level understanding of search advertising practices in online retailing and offer insights into keyword management, resource utilization, and performance metrics in search advertising campaigns.
Fujun Lai, Xiaolin Li, and Vincent Lai Transaction-Specific Investments, Relational Norms and ERP Customer Satisfaction: A Mediation Analysis

Abstract:

Integrating the perspectives of transaction cost economics (TCE), the resource-based view (RBV), and resource dependency theory (RDT), this study analyzes the institutional settings of enterprise resource planning (ERP) implementations in China. Specifically, it examines how bilateral transaction specific investments (TSIs) and relational governance mechanisms influence customer satisfaction with ERP implementations. The model is empirically tested using data from on-site interviews with 208 ERP customers in China. The results demonstrate that the effects of vendors’ and customers’ TSIs on customer satisfaction are facilitated by multiple-stage micromediational chains. The influence of TSIs on customer satisfaction is mediated by relational norms, and the impact of relational norms on customer satisfaction is bridged by perceived service quality and customer trust. Furthermore, the influence of vendors’ TSIs is stronger than the influence of customers’ TSIs. The findings contribute to business research and practice by providing valuable insights into how ERP vendors and customers should strategize transaction-specific investments to enhance relationship performance.
Lingfang Li and Anna Bargagliotti Decision Making Using Rating Systems: When Scale Meets Binary

Abstract:

This paper investigates how different decisions can be reached when decision makers consult a binary rating system and a scale rating system. Since typically decision makers use rating information to make binary decisions, it is particularly important to compare the scale system to the binary system. We show that the only N-point scale system that reports a rater's opinion consistently with the binary system is one where N is odd and N - 1 is not divisible by 4. At the aggregate level, however, we illustrate that inconsistencies persist regardless of the choice of N. In addition, we provide simple tools that can determine whether the systems lead decision makers to the same decision outcomes.
Kangkang Yu, Jack Cadeaux, and Hua Song Distribution Channel Network and Relational Performance: The Intervening Mechanism of Adaptive Distribution Flexibility

Abstract:

Network theories argue that organizations can enjoy information and control benefits from the network in which they are embedded. Focusing on distribution channel networks with strong, prominent, and central ties, this paper argues that distribution flexibility, composed of logistics and relationship flexibility, is a response to environmental uncertainty that mediates the effect of channel network embeddedness on relationship performance. Results show that logistics flexibility and relationship flexibility fully mediate the effect of channel network embeddedness on relationship satisfaction, but that only relationship flexibility mediates the effect of channel network embeddedness on long-term relationship orientation. Furthermore, not only is the effect of tie strength on logistics flexibility stronger in an uncertain environment, but relationship flexibility also decreases as the congruence between uncertainty and tie strength increases, suggesting a complex higher-order contingency model.
Tracy Jenkin, Yolande Chan, David Skillicorn, and Keith Rogers Individual Exploration, Sensemaking and Innovation: A Design for the Discovery of Novel Information

Abstract:

Discovering novel information can result in the generation of potentially valuable new ideas and therefore be beneficial to organizations interested in innovation. To be useful, novel information must have a particular relationship to existing organizational knowledge. It must be far enough away to qualify as novel, but it must be close enough that it can be understood and exploited. Therefore, a key challenge for novel-information discovery is to find concepts that have such relationships to a given starting point or focal concept of interest. Despite the potential benefits, organizations face a number of challenges discovering novel information on the Web: locating it, understanding its relevance, and making sense of it given the constraints and biases of existing mental models. In this paper, we develop an understanding of the challenges of novel information discovery and how a tool can support individuals in locating and translating novel information into novel ideas. Using a design science approach, we develop a design theory for novel-information discovery (NID). A prototype is developed and evaluated. Our findings show that an NID tool performs better than other Web search tools such as Google in terms of the perceived levels of novel information provided and radicalness of the ideas generated.
Rahul Basole and Marcus Bellamy Supply Network Structure, Visibility, and Risk Diffusion: A Computational Approach

Abstract:

Understanding and managing supply chain risks is a critical functional competency for today’s global enterprises. A lack of this competency can have significant negative outcomes, including costly production and delivery delays, loss of future sales, and a tarnished corporate image. The ability to identify and mitigate risks, however, is complicated as supply chains are becoming increasingly global, complex, and interconnected. Drawing on the complex systems and epidemiology literature, and using a computational modeling and network analysis approach, we examine the impact of global supply network structure on risk diffusion and supply network health and demonstrate the importance of supply network visibility. Our results show a significant association between network structure and both risk diffusion and supply network health. In particular, our results indicate that small-world supply network topologies consistently outperform supply networks with scale-free characteristics. Theoretically, our study contributes to our understanding of risk management and supply networks as complex networked systems using a computational approach. Managerially, our study illustrates how decision makers can benefit from a network analytic approach to develop a more holistic understanding of system-wide risk diffusion and to guide network governance policies for more favorable health level outcomes. The paper concludes by highlighting the main findings and discussing possibilities of future research directions.
Dongli Zhang, Kevin Linderman, and Roger Schroeder Customizing Quality Management Practices: A Conceptual and Measurement Framework

Abstract:

Quality Management has often been promoted as a “universal remedy,” where organizations adopt these practices to enhance performance. However, implementation of Quality Management has led to mixed results with some high profile failures. Some suggest that customizing Quality Management practices to fit the organization’s situational context can help avoid implementation failure and improve performance. However, research has not fully investigated how organizations should go about customizing quality practices. This paper addresses this question by conceptualizing two different fundamental aspects of QM practices that have different learning objectives: quality exploitation (QEI) and quality exploration (QER). Drawing on experts and empirical data, we develop a reliable and valid set of measures for QEI and QER. Furthermore, the analysis shows the performance differences in the two sets of QM practices across different contextual settings. Specifically, the empirical results show the benefits of different QM orientations depend on the level of competition and rate of product change. This research challenges prior conceptualizations of QM, and suggests a practical framework to guide decision makers in customizing QM practices.
Srimathy Mohan, Ferdous Alam, John Fowler, Mohan Gopalakrishnan, and Antonios Printezis Capacity Planning and Allocation for Web-based Applications

Abstract:

Motivated by the technology division of a financial services firm, we study the problem of capacity planning and allocation problem for Web-based applications. The steady growth in Web traffic has affected the quality of service (QoS) as measured by response time, for numerous e-businesses. In addition, the lack of understanding of system interactions and availability of proper planning tools has impeded effective capacity management. Managers typically make decisions to add server capacity on an ad-hoc basis when systems reach critical response levels. Very often this turns out to be too late and results in extremely long response times and system crashes. We present an analytical model to understand system interactions with the goal of making better server capacity decisions based on the results. The model studies the relationships and important interactions between the various components of a Web-based application using a continuous time Markov chain embedded in a queuing network as the basic framework. We use several structured aggregation schemes to appropriately represent a complex system, and demonstrate how the model can be used to quickly predict system performance which facilitates effective capacity allocation decision making. Using simulation as a benchmark, we show that our model produces results within 5% accuracy at a fraction of the time of simulation, even at high traffic intensities. This knowledge helps managers quickly analyze the performance of the system and better plan server capacity to maintain desirable levels of QoS. We also demonstrate how to utilize a combination of dedicated and shared resources to achieve QoS using fewer servers.
Stefan Spinler and Sebastian Huber 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.
Antti Tenhiala and Fabrizio Salvador Looking Inside Glitch Mitigation Capability: The Effect of Intra-Organizational Communication Channels

Abstract:

Manufacturers can reduce the occurrence of glitches in their operations by building capabilities to prevent them, yet mitigation capabilities are also needed to contain the effects of the glitches that will still inevitably occur every now and then. We examine the glitch mitigation capability of a production process from an information-processing perspective and propose that (i) the impact of operational glitches on delivery performance is contingent on the formalization of intra-firm communication channels and (ii) this effect is stronger when formal communication channels are complemented with informal channels. We test our model in a sample of 163 make-to-order production processes and find support for the first hypothesis and partial support for the second hypothesis. The statistical analyses also reveal non-hypothesized empirical regularities, which we explore through an additional qualitative study based on 34 site visits and 30 interviews with production planners. The results have practical implications for the design of intra-organizational communication channels, and they also contribute to the research on organizational resilience and communications by showing that when coping with disruptions, the formal communication channels have advantages that are seldom discussed in the literature or recognized by practitioners.
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 bene ts (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.
Andrew Yim Failure Risk and Quality Cost Management in Single versus Multiple Sourcing Decision

Abstract:

The advantage of multiple sourcing to protect against supplier failures arising from undependable products due to latent defects is examined using a model with non-linear external failure costs. Prior research has focused only on supplier failures arising from unreliable supply, such as late/insufficient/no delivery. I derive a closed-form characterization of the optimal production quota allocation for the LUX (Latent defect-Undependable product-eXternal failure) setting. The allocation determines the optimal supply base, with intuitive properties that hold under a mild requirement. The requirement includes the special case of equal procurement costs charged by suppliers but also allows unequal costs without any particular order. The key result of the paper is a necessary and sufficient condition determining whether single or multiple sourcing is optimal. Another condition is obtained to determine the exact size of the optimal supply base, provided the mild requirement holds. With minor modifications, the results also hold when a buyer-initiated procurement contract can be used to elicit private information on the suppliers’ unit variable production costs.
Agnes Lubloy, Gyula Vastag, and Gabor Benedek Churn Models at Mobile Providers: Importance of Social Embeddedness

Abstract:

This article argues the importance of social embeddedness at mobile providers by examining the effects of customers’ network topological properties on churn probability—the probability of a customer switching from one telecommunication provider to another. This article uses data from regional snowball sampling—the only practically feasible network sampling method—to identify groups with significantly different churn ratios for customers with different network topological properties. Clear evidence indicates that individual network characteristics (node-level metrics) have considerable impact on churn probabilities. The inclusion of network-related measures in the churn model allows a longer-term projection of churners and improves the predictive power of the model. With no possibility to carry out repeated sampling, sample stability was checked through simulation results. On the one hand, this article highlights the importance and effectiveness of the provider’s tailored marketing campaigns by showing that customers targeted by direct marketing campaigns are less threatened by churn than non-targeted customers. On the other, this article shows that social embeddedness blocks the impact of the very same marketing efforts. This article forwards the idea that social embeddedness, also prevalent in vendor switching, can be extended to understanding the development of professional societies threatened by membership churn.
Subhamoy Ganguly, Stephen Lawrence, and Mark Prather Emergency Department Staff Planning to Improve Patient Care and Reduce Costs

Abstract:

In the face of high staffing costs, uncertain patient arrivals, and patients unsatisfied with long wait-times, staffing of medical emergency departments (EDs) is a vexing problem. Using empirical data collected from three active EDs, we develop an analytic model to provide effective staffing schedules for EDs. Patient demand is aggregated into discrete time buckets and used to model the stochastic distribution of patient demand within these buckets, which considerably improves model tractability. This model is capable of scheduling providers with different skill-profiles who work either individually or in teams, and with patients of varying acuity-levels. We show how our model helps to balance staffing costs and patient service levels, and how it facilitates examination of important ED staffing policies.
Chih-Ping Wei, Chin-Sheng Yang, and Yu-Hsun Chiang Exploiting Technological Indicators for Effective Technology Merger and Acquisition (M&A) Predictions

Abstract:

Mergers and acquisitions (M&A) play increasingly important roles for contemporary business, especially in high-tech industries that conduct M&As to pursue complementarity from other companies and thereby preserve or extend their competitive advantages. The appropriate selection (prediction) of M&A targets for a given bidder company constitutes a critical first step for an effective technology M&A activity. Yet existing studies only employ financial and managerial indicators when constructing M&A prediction models, and select candidate target companies without considering the profile of the bidder company or its technological compatibility with candidate target companies. Such limitations greatly restrict the applicability of existing studies to supporting technology M&A predictions. To address these limitations, we propose a technology M&A prediction technique that encompasses technological indicators as independent variables and accounts for the technological profiles of both bidder and candidate target companies. Forty-three technological indicators are derived from patent documents and an ensemble learning method is developed for our proposed technology M&A prediction technique. Our evaluation results, on the basis of the M&A cases between January 1997 and May 2008 that involve companies in Japan and Taiwan, confirm the viability and applicability of the proposed technology M&A prediction technique. In addition, our evaluation also suggests that the incorporation of the technological profiles and compatibility of both bidder and candidate target companies as predictors significantly improves the effectiveness of relevant predictions.

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