Complements or Substitutes? Culture–Technology Interactions in Healthcare

The U.S. government recommends that hospitals adopt Computerized Provider Order Entry (CPOE) systems to improve the quality problems that plague U.S. hospitals. However, CPOE studies show mixed results. We hypothesize that CPOE effectiveness depends on the prevalence of patient safety culture within a hospital. Using organizational information processing theory, we describe how patient safety culture and CPOE enable healthcare organizations to better process information. Specifically, we posit that CPOE complements some aspects of patient safety culture and substitutes for others. Using ridge regression, we empirically test this proposition using data from 268 hospitals and multiple data sources. Results show that while CPOE complements the patient safety dimensions of handoffs and transitions, feedback and communication about error, and organizational learning, CPOE substitutes for the dimension of management support for safety, in the context of our dependent variable. As organizations work to implement new systems, this research can help decision‐makers understand how culture impacts such initiatives and account for culture when anticipating effects.     

A Profitability Evaluation of America's Best Hospitals, 2000–2008

Each year U.S. News and World Report evaluates more than 5,000 U.S. hospitals, of which approximately 3% are considered the best hospitals in America, and hospital profitability has emerged as a business objective for these hospitals. This study investigates the profitability performance of the best (highest quality) hospitals in the United States. A 9‐year longitudinal investigation of profitability for the best hospitals in the United States is conducted. The results offer evidence that the primary drivers of hospital profitability are the case mix index and daily bed capacity. In terms of hospital profitability, there appears to be a tradeoff between these two factors. Finally, caution must be used when ranking U.S. News and World Report Honor Roll hospitals, in terms of profitability and performance.     

Managing Supply Chain Execution: Monitoring Timeliness and Correctness via Individualized Trace Data

Improvements in information technologies provide new opportunities to control and improve business processes based on real‐time performance data. A class of data we call individualized trace data (ITD) identifies the real‐time status of individual entities as they move through execution processes, such as an individual product passing through a supply chain or a uniquely identified mortgage application going through an approval process. We develop a mathematical framework which we call the State‐Identity‐Time (SIT) Framework to represent and manipulate ITD at multiple levels of aggregation for different managerial purposes. Using this framework, we design a pair of generic quality measures—timeliness and correctness—for the progress of entities through a supply chain. The timeliness and correctness metrics provide behavioral visibility that can help managers to grasp the dynamics of supply chain behavior that is distinct from asset visibility such as inventory. We develop special quality control methods using this framework to address the issue of overreaction that is common among managers faced with a large volume of fast‐changing data. The SIT structure and its associated methods inform managers on if, when, and where to react. We illustrate our approach using simulations based on real RFID data from a Walmart RFID pilot project.     

Martin K. Starr: A Visionary Proponent for System Integration,Modular Production,and Catastrophe Avoidance

Martin K. Starr facilitated the creation of an identity for production and operations management (POM) as an academic discipline. This paper aims to summarize Starr's substantial contributions to scholarly inquiry on system integration and interfunctional coordination, modular production, and catastrophe avoidance. Even after four decades, we describe how his legacy in these areas continues to define several major drivers of operations and supply chain management research and practice. Starr has influenced several generations of students, professors, and executives with his writings, teaching, and leadership roles in the POM community that include 32 years on the faculty of the Columbia School of Business, 15 years as Editor‐in‐Chief of Management Science, and presidency of the Production and Operations Management Society.     

Linking Process Quality and Resource Usage: An Empirical Analysis

Motivated by an increasing adoption of evidence‐based medical guidelines in the delivery of medical care, we examine whether increased adherence to such guidelines (typically referred to as higher process quality) is associated with reduced resource usage in the course of patient treatment. In this study, we develop a sample of US hospitals and use cardiac care as our context to empirically examine our questions. To measure a patient's resource usage, we use the total length of stay, which includes any additional inpatient stay necessitated by unplanned readmissions within thirty days after initial hospitalization. We find evidence that higher process quality, and more specifically its clinical (as opposed to its administrative) dimensions, are associated with a reduction in resource usage. Moreover, the standardization of care that is achieved via the implementation of medical guidelines, makes this effect more pronounced in less focused environments: higher process quality is more beneficial when the cardiac department's patient population is distributed across a wider range of medical conditions. We explore the implications of these findings for process‐oriented pay‐for‐performance programs, which tie the reimbursement of hospitals to their adherence to evidence‐based medical guidelines.     

Risk,Process Maturity,and Project Performance: An Empirical Analysis of US Federal Government Technology Projects

In recent years, there has been increasing pressure on the US federal government to reduce spending and improve the management of its technology projects. Mitigating the adverse impact of risks on the performance of these projects presents a significant challenge for its stakeholders. Our research examines this challenge in two steps. First, we identify and define a set of salient risks in federal technology projects—specifically, complexity risk and contracting risk in the planning process, and execution risk in the execution process. Next, we investigate whether higher levels of process maturity, assessed by the Capability Maturity Model Integration (CMMI) framework, mitigate the negative effect of project risks on project performance. The analysis of time‐series data collected from 82 federal technology projects across 519 quarterly time periods indicates that each of the three types of risks has a significant negative effect on project performance. This finding highlights the practical significance of managing these risks in the federal technology project context. Further, we find that increasing levels of process maturity attenuate the negative effect of project risks on the performance of federal technology projects. However, the attenuation effects are consequential only at high levels of project risks; at low levels of project risk, increasing levels of process maturity can adversely affect project performance. To demonstrate the financial implications of increasing process maturity levels in federal technology projects, we examine the magnitude of project cost savings (and overruns) across different levels of CMMI and project risks. In summary, our study contributes to the sparse literature on public sector operations by addressing the understudied context of federal technology projects, and provides a nuanced examination of the implications of process maturity in managing the risk to performance relationship in such projects.     

Impact of Value‐Added Service Features in e‐Retailing Processes: An Econometric Analysis of Web Site Functions

We examine the impact of three classes of Web site 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 Web site traffic, conversion rate, and average order value, we find that Web site functions affect e‐retail sales revenues mainly through their impact on Web site traffic. Our investigation demonstrates the empirical research usefulness of the Voss 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.     

Schumpeterian Growth Theory and the Dynamics of Income Inequality

In this lecture, it is argued that Schumpeterian Growth Theory, in which growth is driven by a sequence of quality‐improving innovations, can shed light on two important puzzles raised by the recent evolution of wage inequality in developed economies. The first puzzle concerns wage inequality between educational groups, which has substantially risen in the US and the UK during the past two decades following a sharp increase in the supply of educated labor. The second puzzle concerns wage inequality within educational groups, which accounts for a large fraction of the observed increase in wage inequality, although in contrast to between‐group wage inequality it has mainly affected the temporary component of income.     

Dedicated Transportation Subnetworks: Design,Analysis, and Insights

A dedicated subnetwork (DSN) refers to a subset of lanes, with associated loads, in a shipper's transportation network, for which resources—trucks, drivers, and other equipment—are exclusively assigned to accomplish shipping requirements. The resources assigned to a DSN are not shared with the rest of the shipper's network. Thus, a DSN is an autonomously operated subnetwork and, hence, can be subcontracted. We address a novel problem of extracting a DSN for outsourcing to one or more subcontractors, with the objective of maximizing the shipper's savings. In their pure form, the defining conditions of a DSN are often too restrictive to enable the extraction of a sizable subnetwork. We consider two notions—deadheading and lane‐sharing—that aid in improving the size of the DSN. We show that all the optimization problems involved are both strongly NP‐hard and APX‐hard, and demonstrate several polynomially solvable special cases arising from topological properties of the network and parametric relationships. Next, we develop a network‐flow‐based heuristic that provides near‐optimal solutions to practical instances in reasonable time. Finally, using a test bed based on data obtained from a national 3PL company, we demonstrate the substantial monetary impact of subcontracting a DSN and offer useful managerial insights.     

Legislative Pay and Legislator Quality

This study extends previous work by Mixon and Wilkinson (1999, Public Finance Review 27: 418–433) and Palia (2000, RAND Journal of Economics 31: 165–179) suggesting that formal human capital attainment is lower in political and managerial roles wherein expected compensation is less. The present study constructs a cumulative probability distribution function for years of education attained for both branches of the 109th US Congress and finds that the distribution of years of education attainment in the US Senate second‐order dominates that in the US House due to differences in the expected compensation levels favoring the former congressional branch. The stochastic dominance test results are supported by findings of significant differences in education attainment (favoring senators) at different quantiles of the joint education attainment distribution. Finally, goodness‐of‐fit tests also indicate that the distribution of education attainment quality in the US Senate, as measured by various academic institution quality indicators, is significantly different from that in the US House, again owing to the differences in expected compensation.     

Insurer Competition in Health Care Markets

The impact of insurer competition on welfare, negotiated provider prices, and premiums in the U.S. private health care industry is theoretically ambiguous. Reduced competition may increase the premiums charged by insurers and their payments made to hospitals. However, it may also strengthen insurers' bargaining leverage when negotiating with hospitals, thereby generating offsetting cost decreases. To understand and measure this trade‐off, we estimate a model of employer‐insurer and hospital‐insurer bargaining over premiums and reimbursements, household demand for insurance, and individual demand for hospitals using detailed California admissions, claims, and enrollment data. We simulate the removal of both large and small insurers from consumers' choice sets. Although consumer welfare decreases and premiums typically increase, we find that premiums can fall upon the removal of a small insurer if an employer imposes effective premium constraints through negotiations with the remaining insurers. We also document substantial heterogeneity in hospital price adjustments upon the removal of an insurer, with renegotiated price increases and decreases of as much as 10% across markets.     

Unpacking Team Familiarity: The Effects of Geographic Location and Hierarchical Role

Examination of team productivity finds that team familiarity, i.e., individuals' prior shared work experience, can positively impact the efficiency and quality of team output. Despite the attention given to team familiarity and its contingencies, prior work has focused on whether team members have worked together, not on which team members have worked together, and under what conditions. In this paper, I parse overall team familiarity to consider effects of geographic location and the hierarchical roles of team members. Using data on all software‐development projects completed over 3 years at a large Indian firm in the global outsourced software services industry, I find that team familiarity gained when team members work together in the same location has a significantly more positive effect on team performance compared with team familiarity gained while members were collaborating in different locations. Additionally, I find that hierarchical team familiarity (a manager's experience with front‐line team members) and horizontal team familiarity (front‐line team members' experience gained with one another) have differential effects on project team performance. These findings provide insight into the relationship between team experience and team performance.     

The Role of Operational Capabilities in Enhancing New Venture Survival: A Longitudinal Study

We investigate relationships between operational capabilities and new venture survival. On the basis of operations management and entrepreneurship literature, we develop a contingency framework of operational capabilities especially appropriate at different life phases of a new venture's evolution. We expect that in the first years of a new venture's life, entrepreneurs should emphasize high inventory turnover to preserve working capital, support customer responsiveness, and aid firm adaptability. As new ventures grow, entrepreneurs should emphasize internal working capital generation via larger gross margins to support production ramp‐up. Later, new venture entrepreneurs should emphasize employee productivity to buttress sustainable volume production. We analyze a 6‐year longitudinal sample of 812 Swedish manufacturing new ventures using a gamma frailty‐based Cox regression. The findings show that specific operational capabilities, while always supporting new venture survival, have exceptional influence in specific new venture life phases. The three hypotheses are confirmed, suggesting that higher inventory turnover, gross margin, and employee productivity further increase new venture survival likelihoods, respectively, in the venture's start‐up, growth, and stability phases. This suggests a phased‐capabilities approach to new venture survival. This study contributes to operations management and entrepreneurship theory and practice, and sets a foundation for future research on operations strategy for new ventures.     

An Exploratory Study of Procurement Strategies for Multi‐Item RFQs in B2B Markets: Antecedents and Impact on Performance

This research explores procurement strategies for multi‐item requests for quotation (RFQs) in business‐to‐business (B2B) markets using responses from 825 purchasing professionals. The study first establishes procurement strategies that differ based on their level of strategic emphasis, i.e., the importance that is placed on the pursuit of four strategic objectives. Underlying objectives, which are obtained via factor analysis, include the focus on price, security of supply, internal procurement efficiencies, and bundle building. Next, cluster analysis is used to derive prototypical strategic approaches. The three cluster groups that emerge possess the same relative ranking of the four objectives, but differ based on the intensity with which these objectives are pursued. The clusters are labelled as the three strategic groups of strategists, opportunists, and responders. The research then explores, using an industrial buyer behavior lens, the impact of environmental antecedents in determining a particular strategy. Environmental variables include purchase importance, market uncertainty, supply base availability, buyer bargaining power, item experience, and supply base experience. Finally, the study tests the impact of procurement strategy on the buyer's perceived performance, suggesting that strategists, placing more emphasis on the pursuit of strategic sourcing objectives, achieve better performance than opportunists and responders.     

The [R]Evolving Relationship Between Risk Assessment and Risk Management

In Science and Decisions: Advancing Risk Assessment, the National Research Council recommends improvements in the U.S. Environmental Protection Agency's approach to risk assessment. The recommendations aim to increase the utility of these assessments, embedding them within a new risk‐based decision‐making framework. The framework involves first identifying the problem and possible options for addressing it, conducting related analyses, then reviewing the results and making the risk management decision. Experience with longstanding requirements for regulatory impact analysis provides insights into the implementation of this framework. First, neither the Science and Decisions framework nor the framework for regulatory impact analysis should be viewed as a static or linear process, where each step is completed before moving on to the next. Risk management options are best evaluated through an iterative and integrative procedure. The extent to which a hazard has been previously studied will strongly influence analysts’ ability to identify options prior to conducting formal analyses, and these options will be altered and refined as the analysis progresses. Second, experience with regulatory impact analysis suggests that legal and political constraints may limit the range of options assessed, contrary to both existing guidance for regulatory impact analysis and the Science and Decisions recommendations. Analysts will need to work creatively to broaden the range of options considered. Finally, the usefulness of regulatory impact analysis has been significantly hampered by the inability to quantify many health impacts of concern, suggesting that the scientific improvements offered within Science and Decisions will fill an crucial research gap.     

Replenishment Policies for Multi‐Product Stochastic Inventory Systems with Correlated Demand and Joint‐Replenishment Costs

This study analyzes optimal replenishment policies that minimize expected discounted cost of multi‐product stochastic inventory systems. The distinguishing feature of the multi‐product inventory system that we analyze is the existence of correlated demand and joint‐replenishment costs across multiple products. Our objective is to understand the structure of the optimal policy and use this structure to construct a heuristic method that can solve problems set in real‐world sizes/dimensions. Using an MDP formulation we first compute the optimal policy. The optimal policy can only be computed for problems with a small number of product types due to the curse of dimensionality. Hence, using the insight gained from the optimal policy, we propose a class of policies that captures the impact of demand correlation on the structure of the optimal policy. We call this class (s, c, d, S)‐policies, and also develop an algorithm to compute good policies in this class, for large multi‐product problems. Finally using an exhaustive set of computational examples we show that policies in this class very closely approximate the optimal policy and can outperform policies analyzed in prior literature which assume independent demand. We have also included examples that illustrate performance under the average cost objective.     

Clinical Capital and the Risk of Maternal Labor and Delivery Complications: Hospital Scheduling,Timing, and Cohort Turnover Effects

The establishment of interventions to maximize maternal health requires the identification of modifiable risk factors. Toward the identification of modifiable hospital‐based factors, we analyze over 2 million births from 2005 to 2010 in Texas, employing a series of quasi‐experimental tests involving hourly, daily, and monthly circumstances where medical service quality (or clinical capital) is known to vary exogenously. Motivated by a clinician's choice model, we investigate whether maternal delivery complications (1) vary by work shift, (2) increase by the hours worked within shifts, (3) increase on weekends and holidays when hospitals are typically understaffed, and (4) are higher in July when a new cohort of residents enter teaching hospitals. We find consistent evidence of a sizable statistical relationship between deliveries during nonstandard schedules and negative patient outcomes. Delivery complications are higher during night shifts (OR = 1.21, 95% CI: 1.18–1.25), and on weekends (OR = 1.09, 95% CI: 1.04–1.14) and holidays (OR = 1.29, 95% CI: 1.04–1.60), when hospitals are understaffed and less experienced doctors are more likely to work. Within shifts, we show deterioration of occupational performance per additional hour worked (OR = 1.02, 95% CI: 1.01–1.02). We observe substantial additional risk at teaching hospitals in July (OR = 1.28, 95% CI: 1.14–1.43), reflecting a cohort‐turnover effect. All results are robust to the exclusion of noninduced births and intuitively falsified with analyses of chromosomal disorders. Results from our multiple‐test strategy indicate that hospitals can meaningfully attenuate harm to maternal health through strategic scheduling of staff.     

Impact of Bias Magnification on Supply Chain Costs: The Mitigating Role of Forecast Sharing

The impact of forecast error magnification on supply chain cost has been well documented. Unlike past studies that measure forecast error in terms of forecast standard deviation, our study extends research to consider the impact of forecast bias, and the complex interaction between these variables. Simulating a two‐stage supply chain using realistic cost data we test the impact of bias magnification comparing two scenarios: one with forecast sharing between retailer and supplier, and one without. We then corroborate findings via survey data. Results show magnification of forecast bias to have a considerably greater impact on supply chain cost than magnification of forecast standard deviation. Particularly damaging is high bias in the presence of high forecast standard deviation. Forecast sharing is found to mitigate the impact of forecast error, however, primarily at higher levels of forecast standard deviation. At low levels of forecast standard deviation the benefits are not significant suggesting that engaging in such mitigation strategies may be less effective when there is little opportunity for improvement in accuracy. Furthermore, forecast sharing is found to be much less effective against high levels of bias. This is an important finding as managers often deliberately bias their forecasts and underscores the importance of exercising caution even with forecast sharing, particularly for forecasts that have inherently large errors. The findings provide a deeper understanding of the impact of forecast errors, suggest limitations of forecast sharing, and offer implications for research and practice alike.     

Improving the Milk Supply Chain in Developing Countries: Analysis,Insights, and Recommendations

Quality issues in milk—arising primarily from deliberate adulteration by producers—have been reported in several developing countries. In the milk supply chain, a station buys raw milk from a number of producers, mixes the milk and sells it to a firm (that then sells the processed milk to end consumers). We study a non‐cooperative game between a station and a population of producers. Apart from penalties on proven low‐quality producers, two types of incentives are analyzed: confessor rewards for low‐quality producers who confess and quality rewards for producers of high‐quality milk. Contrary to our expectations, whereas (small) confessor rewards can help increase both the quality of milk and the station's profit, quality rewards can be detrimental. We examine two structures based on the ordering of individual and mixed testing of milk: pre‐mixed individual testing (first test a fraction of producers individually and then [possibly] perform a mixed test on the remaining producers) and post‐mixed individual testing (first test the mixed milk from all producers and then test a fraction of producers individually). Whereas pre‐mixed individual testing can be socially harmful, a combination of post‐mixed individual testing and other incentives achieves a desirable outcome: all producers supply high‐quality milk with only one mixed test and no further testing by the station.