Cross‐Training with Imperfect Training Schemes

Cross‐training workers is one of the most efficient ways of achieving flexibility in manufacturing and service systems for increasing responsiveness to demand variability. However, it is generally the case that cross‐trained employees are not as productive on a specific task as employees who were originally trained for that task. Also, the productivity of the cross‐trained workers depends on when they are cross‐trained. In this work, we consider a two‐stage model to analyze the effects of variations in productivity levels on cross‐training policies. We define a new metric called achievable capacity and show that it plays a key role in determining the structure of the problem. If cross‐training can be done in a consistent manner, the achievable capacity is not affected when the training is done, which implies that the cross‐training decisions are independent of the opportunity cost of lost demand and are based on a trade‐off between cross‐training costs at different times. When the productivities of workers trained at different times differ, there is a three‐way trade‐off between cross‐training costs at different times and the opportunity cost of lost demand due to lost achievable capacity. We analyze the effects of variability and show that if the productivity levels of workers trained at different times are consistent, the decision maker is inclined to defer the cross‐training decisions as the variability of demand or productivity levels increases. However, when the productivities of workers trained at different times differ, an increase in the variability may make investing more in cross‐training earlier more preferable.     

Older and Wiser: How CEOs’ Time Perspective Influences Long‐Term Investments in Environmentally Responsible Technologies

Most theories of corporate governance argue that chief executive officers (CEOs) take less risk as they near the end of their career, and therefore are less likely to make major investments. This prediction is based on decisions related to firm‐specific benefits; however, it may not be generalizable to decisions that involve broad societal goals. In terms of societal investments, CEOs with a longer time perspective may be more likely, rather than less likely, to invest. In this paper, we argue that a CEO's future time perspective is fostered by shorter career horizons, longer tenures, higher organizational ownership and less short‐term compensation. We test these hypotheses on 150 observations from the US investor‐owned electric power generation sector over a three‐year unbalanced sample (64.3% of the population). We applied random‐effects generalized least squares (GLS) estimations to test our hypotheses, and found support for three out of four hypothesized relationships.     

Competitive and Collaborative Quality and Warranty Management in Supply Chains

Product quality and product warranty coverage are two important and closely related operational decisions. A longer warranty protection period can boost sales, but it may also result in dramatically increased warranty cost, if product quality is poor. To investigate how these two decisions interact with each other and influence supply chain performance, we develop a single‐period model with a supplier that provides a product to an original equipment manufacturer, which in turn sells it to customers. Customer demand is random and affected by the length of the product warranty period. Warranty costs are incurred by both the supplier and the manufacturer. We analyze two different scenarios based on which party sets the warranty period: manufacturer warranty and supplier warranty. Product quality is controlled by the supplier, and the manufacturer determines the ordering quantity. We analyze these decentralized systems and provide the structural properties of the equilibrium strategies. We also compare the results of centralized and decentralized systems and identify the conditions under which one system provides a longer warranty and better product quality than the other. Our numerical study further shows that, in decentralized settings, when the warranty period is determined by the firm sharing the larger proportion of total warranty costs, the supply chain can achieve greater system‐wide profit. Both parties can therefore benefit from properly delegating the warranty decision and sharing the resulting additional profit. We further design a supplier‐development and buy‐back contract for coordinating decentralized supply chains. Several extensions are also discussed.     

It's Only Temporary: Time Frame and the Dynamics of Creative Project Teams

The success of many knowledge‐intensive industries depends on creative projects that lie at the heart of their logic of production. The temporality of such projects, however, is an issue that is insufficiently understood. To address this, we study the perceived time frame of teams that work on creative projects and its effects on project dynamics. An experiment with 267 managers assigned to creative project teams with varying time frames demonstrates that, compared to creative project teams with a relatively longer time frame, project teams with a shorter time frame focus more on the immediate present, are less immersed in their task and utilize a more heuristic mode of information processing. Furthermore, we find that time frame moderates the negative effect of team conflict on team cohesion. These results are consistent with our theory that the temporary nature of creative projects shapes different time frames among project participants, and that it is this time frame that is an important predictor of task and team processes.     

Work Design and Integration Glitches in Globally Distributed Technology Projects

In a technology project, project integration represents the pooling together of complete, interdependent task modules to form a physical product or software delivering a desired functionality. This study develops and tests a conceptual framework that examines the interrelationships between the elements of work design, project integration challenges, and project performance. We identify two distinct elements of work design in technology projects: (i) the type of project organization based on whether a technology project spans a firm boundary (Domestic‐Outsourcing) or a country boundary (Offshore‐Insourcing) or both boundaries (Offshore‐Outsourcing) or no boundaries (Domestic‐Insourcing), and (ii) the joint coordination practices among key stakeholders in a technology project—namely, Onsite Ratio and Joint‐Task Ownership. Next, we measure the effectiveness of project integration using integration glitches that capture the incompatibility among interdependent task modules during project integration. Based on analysis of data from 830 technology projects, the results highlight the differential effects of distributed project organizations on integration glitches. Specifically, we find that project organizations that span both firm and country boundaries (Offshore‐Outsourcing) experience significantly higher levels of integration glitches compared to domestic project organizations (Domestic‐Outsourcing and Domestic‐Insourcing). The results further indicate that the relationship between project organization type and integration glitches is moderated by the extent of joint coordination practices in a project. That is, managers can actively lower integration glitches by increasing the levels of onsite ratio and by promoting higher levels of joint‐task ownership, particularly in project organization types that span both firm and country boundaries (Offshore‐Outsourcing). Finally, the results demonstrate the practical significance of studying integration glitches by highlighting its significant negative effect on project performance.     

Knowing What Your Customer Wants: Improving Inventory Allocation Decisions in Online Movie Rental Systems

In Online Movie Rental Systems, customer desire to rent can often be observed before the actual consumption occurs. Desire represents uncensored (or true) demand information. Hence, the impact of inventory decisions (numbers of physical copies of different movies) can be accurately traced to the creation of desire (via Word‐of‐mouth), and then to rental. Word‐of‐Mouth (WOM) has been recognized as one of the most influential sources of information transmission, especially for experience goods. Poor inventory decisions may result in lost rentals in two ways: One is the loss of rentals because of low inventory (direct effect), and the other is the loss of the possible demand (rentals) that could have been created through WOM (indirect effect). We use data from an online DVD‐by‐mail firm to estimate the direct and indirect effects of inventory decisions, considering the circular relationship: Rental generates WOM, WOM creates Desire, and Desire turns into Rental. We find that the magnitude of indirect effects is significant, comparable to and sometimes even exceeding direct effects. The value of the empirical findings to facilitate better inventory allocation decisions is examined.     

Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.     

Mitigating Supply Uncertainty: The Interplay Between Diversification and Pricing

We consider a firm's sourcing problem from one reliable supplier and one unreliable supplier in two price‐setting scenarios. In the committed pricing scenario, the firm makes the pricing decision before the supply uncertainty is resolved. In the responsive pricing scenario, the firm's pricing decision is made after the supply uncertainty is resolved. For the committed pricing scenario, we develop a condition on supply uncertainty that guarantees the unimodality of the firm's objective function. By comparing the firm's optimal diversification decisions in the two pricing scenarios, we examine the interplay of supply diversification strategy and responsive pricing strategy in mitigating supply uncertainty. While both strategies are effective in mitigating supply uncertainty, we show that they are not necessarily substitutes. The relationship between these two strategies depends on two adverse effects caused by supply uncertainty: the lost‐revenue effect and the lost‐goodwill effect. More specifically, when the lost‐revenue effect dominates the lost‐goodwill effect, these two strategies are complements; otherwise, they are substitutes. Furthermore, we examine the impact of market size, price sensitivity, supplier reliability, and failure rebate on the interplay between these two strategies, and discuss the implications of our results. Finally, we extend our analysis to the case of two unreliable suppliers and show that the insights regarding the interplay between diversification and pricing continue to hold.     

Does Size Matter? A Study of Risk Perceptions of Global Population Growth

The global human population now exceeds 7 billion and is projected to reach 10 billion around 2060. While population growth has been associated with certain benefits (e.g., economies of scale, technological advancements), theoretical models, probabilistic projections, and empirical evidence also indicate that this growth could increase the likelihood of many adverse events (e.g., climate change, resource shortages) and the impact of these events, as more people are exposed to the outcomes. While concerns about these issues are well‐documented in the academic literature, there is little evidence concerning the public's perceptions of the risks associated with global population growth (GPG) and how these perceptions are likely to influence related decisions. To address these issues, we conducted a U.K.‐based study that examined respondents’ risk perceptions of GPG, their willingness to embrace mitigation/precautionary behaviors, and reasons for variations in these two factors. We found that GPG is perceived as a moderate‐to‐high risk, with concerns about the increased likelihood of resource shortages, ecological damage, and violent conflict being foremost. Respondents believed that the worst effects of GPG would arrive around 2050 and would be experienced by the world's poorest people. Respondents who perceived greater levels of risk from GPG were generally those who indicated a greater willingness to embrace mitigation behaviors (e.g., reduce resource consumption) and preventative actions (e.g., support political action to limit growth). We discuss how our findings might be utilized to better manage the potential challenges associated with GPG and we suggest several directions for further research.     

Interruption and Forgetting in Knowledge‐Intensive Service Environments

An increasing barrier to productivity in knowledge‐intensive work environments is interruptions. Interruptions stop the current job and can induce forgetting in the worker. The induced forgetting can cause re‐work; to complete the interrupted job, additional effort and time is required to return to the same level of job‐specific knowledge the worker had attained prior to the interruption. This research employs primary observational and process data gathered from a hospital radiology department as inputs into a discrete‐event simulation model to estimate the effect of interruptions, forgetting, and re‐work. To help mitigate the effects of interruption‐induced re‐work, we introduce and test the operational policy of sequestering, where some service resources are protected from interruptions. We find that sequestering can improve the overall productivity and cost performance of the system under certain circumstances. We conclude that research examining knowledge‐intensive operations should explicitly consider interruptions and the forgetting rate of the system's human workers or models will overestimate the system's productivity and underestimate its costs.     

The Dynamics of Domestic Gray Markets and Its Impact on Supply Chains

Gray markets are created by unauthorized retailers selling manufacturer's branded products. Similar to international gray markets, domestic gray markets are a growing phenomenon whose impact on supply chains is not clear. We consider a supply chain with one manufacturer and several authorized retailers who face a newsvendor problem and a domestic gray market. While a gray market provides an opportunity for retailers to clear their excess inventory (inventory‐correction effect), it also can be a threat to their demand (demand‐cannibalization effect). We first characterize the emerging equilibrium by assuming an MSRP environment. Comparing a decentralized and centralized system, we show that a wholesale pricing contract is quite efficient in a gray market environment; we explain the underlying mechanism and note some of the operational decisions that could hurt that efficiency. We show that the gray market price determines the degree of both the negative effects of demand‐cannibalization and the positive effects of inventory correction, which in turn determines the net impact of gray markets on the retailer's stocking choice and, ultimately, the manufacturer's profit. We then study the authorized retailers' problem as a price‐setting newsvendor. We observe that the gray market creates price competition between the authorized and unauthorized retailers, causing a drop in the primary market price. However, this price competition can be counteracted by the authorized retailers' stocking decision. Finally, we extend our model to consider the cases where the demand can be correlated across retailers.     

Are Patients Patient? The Role of Time to Appointment in Patient Flow

The current state of outpatient healthcare delivery is characterized by capacity shortages and long waits for appointments, yet a substantial fraction of valuable doctors’ capacity is wasted due to no‐shows. In this study, we examine the effect of wait to appointment on patient flow, specifically on a patient's decision to schedule an appointment and to subsequently arrive to it. These two decisions may be dependent, as appointments are more likely to be scheduled by patients who are more patient and are thereby more likely to show up. To estimate the effect of wait on these two decisions, we introduce the willingness to wait (WTW), an unobservable variable that affects both bookings and arrivals for appointments. Using data from a large healthcare system, we estimate WTW with a state‐of‐the‐art non‐parametric method. The WTW, in turn, allows us to estimate the effect of wait on no‐shows. We observe that the effect of increased wait on the likelihood of no‐shows is disproportionately greater among patients with low WTW. Thus, although reducing the wait to an appointment will enable a provider to capture more patient bookings, the effects of wait time on capacity utilization can be non‐monotone. Our counterfactual analysis suggests that increasing wait times can sometimes be beneficial for reducing no‐shows.     

Farmers’ Risk‐Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging

Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent‐based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large‐scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision‐making techniques. These results may inform continued research on such behavioral tendencies in narrower lab‐ and modeling‐based studies.     

The Economic Value of Market Information for Farmers in Developing Economies

In developing countries, farmers lack information for making informed production, manufacturing/selling decisions to improve their earnings. To alleviate poverty, various non‐governmental organizations (NGOs) and for‐profit companies have developed different ways to distribute information about market price, crop advisory and farming technique to farmers. We investigate a fundamental question: will information create economic value for farmers? We construct a stylized model in which farmers face an uncertain market price (demand) and must make production decisions before the market price is realized. Each farmer has an imprecise private signal and an imprecise public signal to estimate the actual market price. By examining the equilibrium outcomes associated with a Cournot competition game, we show that private signals do create value by improving farmers' welfare. However, this value deteriorates as the public signal becomes available (or more precise). In contrast, in the presence of private signals, the public signal does not always create value for the farmers. Nevertheless, both private and public signals will reduce price variation. We also consider two separate extensions that involve non‐identical private signal precisions and farmers' risk‐aversion, and we find that the same results continue to hold. More importantly, we find that the public signal can reduce welfare inequality when farmers have non‐identical private signal precisions. Also, risk‐aversion can dampen the value created by private or public information.     

Understanding Mechanisms Underlying Peer Effects: Evidence From a Field Experiment on Financial Decisions

Using a high‐stakes field experiment conducted with a financial brokerage, we implement a novel design to separately identify two channels of social influence in financial decisions, both widely studied theoretically. When someone purchases an asset, his peers may also want to purchase it, both because they learn from his choice (“social learning”) and because his possession of the asset directly affects others' utility of owning the same asset (“social utility”). We randomize whether one member of a peer pair who chose to purchase an asset has that choice implemented, thus randomizing his ability to possess the asset. Then, we randomize whether the second member of the pair: (i) receives no information about the first member, or (ii) is informed of the first member's desire to purchase the asset and the result of the randomization that determined possession. This allows us to estimate the effects of learning plus possession, and learning alone, relative to a (no information) control group. We find that both social learning and social utility channels have statistically and economically significant effects on investment decisions. Evidence from a follow‐up survey reveals that social learning effects are greatest when the first (second) investor is financially sophisticated (financially unsophisticated); investors report updating their beliefs about asset quality after learning about their peer's revealed preference; and, they report motivations consistent with “keeping up with the Joneses” when learning about their peer's possession of the asset. These results can help shed light on the mechanisms underlying herding behavior in financial markets and peer effects in consumption and investment decisions.     

Priority Rules for Multi‐Task Due‐Date Scheduling under Varying Processing Costs

We study the scheduling of multiple tasks under varying processing costs and derive a priority rule for optimal scheduling policies. Each task has a due date, and a non‐completion penalty cost is incurred if the task is not completely processed before its due date. We assume that the task arrival process is stochastic and the processing rate is capacitated. Our work is motivated by both traditional and emerging application domains, such as construction industry and freelance consulting industry. We establish the optimality of Shorter Slack time and Longer remaining Processing time (SSLP) principle that determines the priority among active tasks. Based on the derived structural properties, we also propose an effective cost‐balancing heuristic policy and demonstrate the efficacy of the proposed policy through extensive numerical experiments. We believe our results provide operators/managers valuable insights on how to devise effective service scheduling policies under varying costs.     

Designing Graphs to Communicate Risks: Understanding How the Choice of Graphical Format Influences Decision Making

Previous research suggests that the choice of graphical format for communicating risk information affects both understanding of the risk magnitude and the likelihood of acting to decrease risk. However, the mechanisms through which these effects work are poorly understood. To explore these mechanisms using a real‐world scenario, we examined the relative impact of two graphical displays for depicting the risk of exposure to unexploded ammunition during potential land redevelopment. One display depicted only the foreground information graphically (a bar graph of the number of people harmed), and a second depicted the foreground and background graphically (a stacked bar graph representing both the number harmed and at risk). We presented 296 participants with either the foreground‐only or the foreground and background graphical display and measured a broad set of outcome variables, examining (1) the graphical display effect on each of the outcome measures and (2) the pathways by which any display effects work to influence decision making. We found that the foreground‐only graphical display increased perceived likelihood and experienced fear, which produced greater worry, which in turn increased risk aversion. In addition, a positive evaluation of the communication materials increased support for policies related to land redevelopment, whether those policies were risk taking or risk mitigating. Finally, the foreground‐only graphical display decreased understanding of the risk magnitude, showing that approaches to accomplish one risk communication goal (promoting risk‐averse decisions) may do so at the expense of another goal (increasing understanding).     

Panel Size and Overbooking Decisions for Appointment‐Based Services under Patient No‐Shows

Many service systems that work with appointments, particularly those in healthcare, suffer from high no‐show rates. While there are many reasons why patients become no‐shows, empirical studies found that the probability of a patient being a no‐show typically increases with the patient's appointment delay, i.e., the time between the call for the appointment and the appointment date. This paper investigates how demand and capacity control decisions should be made while taking this relationship into account. We use stylized single server queueing models to model the appointments scheduled for a provider, and consider two different problems. In the first problem, the service capacity is fixed and the decision variable is the panel size; in the second problem, both the panel size and the service capacity (i.e., overbooking level) are decision variables. The objective in both cases is to maximize some net reward function, which reduces to system throughput for the first problem. We give partial or complete characterizations for the optimal decisions, and use these characterizations to provide insights into how optimal decisions depend on patient's no‐show behavior in regards to their appointment delay. These insights especially provide guidance to service providers who are already engaged in or considering interventions such as sending reminders in order to decrease no‐show probabilities. We find that in addition to the magnitudes of patient show‐up probabilities, patients' sensitivity to incremental delays is an important determinant of how demand and capacity decisions should be adjusted in response to anticipated changes in patients' no‐show behavior.     

Assembly Systems with Sequential Supplier Decisions and Uncertain Demand

We consider multitier push assembly systems with sequential supplier decisions and a wholesale price contract. We show that both an Original Equipment Manufacturer (OEM)–Contract Manufacturer (CM) assembly and a modular assembly with sequential supplier decisions are mathematically equivalent to the corresponding traditional assembly. We determine that, in most cases, the first mover supplier realizes a higher profit than the second mover supplier but we also identify the sufficient conditions for the reverse to occur. We provide conditions under which the order quantity, the second mover profit, total supplier profits, and the assembler profit are either higher or lower for a multitier system with sequential suppliers compared to simultaneous suppliers. We conclude that the first mover is always better off in a three‐tier sequential system while she can be either better off or worse off in a four‐tier sequential system compared to the corresponding simultaneous systems. We also analyze the impact of information asymmetry on the supplier and assembler profits in a three‐tier sequential system. Finally, we determine the profit threshold for an independent manufacturer in a three‐tier system to become a CM in a four‐tier system and vice versa.     

Re‐storying the Business,Innovation and Entrepreneurial Ecosystem Concepts: The Model‐Narrative Review Method

We propose a novel literature review method in order to systematically trace and reveal the dominant narratives of a body of literature: the model‐narrative review method. We apply this method to an ever‐growing literature on ecosystems in business studies, as it resembles a rich knowledge base with somewhat competing, overarching stories, replete with emplotted characters, systematic puzzles and embellished scientific drama. To interpret these unfolding storylines, we both separately engage with and connect seminal work on business, entrepreneurial and innovation ecosystems. Through thematic reading we map the key themes and scientific puzzles in each ecosystem type. Through enstoried reading we identify how authors construct the plot, narrative setting, emplotted characters, narrative voices and moral lessons around ecosystems. Through rhetorical reading we explicate the rhetorical devices and strategies that claim the relevance of their work. Our findings expose a number of hidden meanings and underlying assumptions, adding transparency to ecosystem rhetorics and enhancing conceptual clarity. Altogether, this method offers a systematic construction of model‐narratives to synthesize and critically reflect upon similarities and differences between related concepts and opens up space for alternative research questions.