Real‐Time Work Schedule Adjustment Decisions: An Investigation and Evaluation

Service managers often find that available worker capacity does not match with actual demand during a given day. They then must attempt to modify the planned work schedule to improve service and increase profitability. This study, which defines such a setting as the real‐time work schedule adjustment decision, pr oposes mathematical formulations of the real‐time adjustment and develops efficient heuristic approaches for this decision. The study evaluates the relative effectiveness of these heuristics versus experienced service managers, investigates the effect of the degree of schedule adjustment on profitability, and assesses the effect of demand forecast update errors on the performance of the schedule adjustment efforts. First, the results indicate that the computer based heuristics achieve higher profit improvement than experienced managers. Second, there is a trade‐off between schedule stability and profitability so that more extensive schedule revisions (efficiency first heuristics) generally result in higher profitability. However, the incremental return on schedule changes is diminishing. Third, we find that active adjustments of work schedules are beneficial as long as the direction of demand change is accurately identified.     

Decision Making and Cognition in Multi‐Echelon Supply Chains: An Experimental Study

Supply chain performance often depends on the individual decisions of channel members. Even when individuals have access to relevant information, order variation tends to increase when moving up the supply chain, a phenomenon known as the bullwhip effect. While prior research has investigated several structural/environmental factors which can mitigate the bullwhip effect, the underlying behavioral factors contributing to it are an open question. Using a production and distribution decision‐making simulation representing a four‐stage serial supply chain, we find that the cognitive profile of decision makers contributes to the bullwhip effect. We found that the specific decision tendency to underweight the supply line is linked to an individual's level of cognitive reflection. Furthermore, performance differs for entire supply chains and for specific echelons, and holds under standard mitigation efforts. The findings have implications for supply chain design, education, and industry.     

Incentive for Peer‐to‐Peer Knowledge Sharing among Farmers in Developing Economies

This study examines the peer‐to‐Peer interactions among farmers when both knowledge learning and sharing are available. We construct a stylized model in which heterogeneous farmers are endowed with their initial production capabilities and can post questions in the platform for help. A representative expert regularly monitors the forum and provides answers to the farmers’ questions, but may be non‐responsive sometimes due to the limited capacity. A knowledgeable core user (farmer) can choose to be silent or responsive, and is allowed to strategically determine the informativeness of her answers. The farmers face the minimum quantity restriction for attracting the buyers, and must make production before the time of sales. We show that in equilibrium the core user never provides answers that are more informative than the expert's, irrespective of her ex ante knowledge level. Redesigning or restructuring the platform does not help eliminate this inefficient knowledge provision. We also find that hiring more staff to frequently monitor the forum turns out to be detrimental for the peer‐to‐peer interactions. Moreover, the competition on knowledge sharing between the platform expert and the core user features strategic complementarity sometimes but strategic substitution at other times. Third, charging for the platform usage may discourage uninformative answers, but it could also discourage the core user from sharing knowledge with other farmers.     

Adversarial Risk Analysis with Incomplete Information: A Level‐k Approach

This article proposes, develops, and illustrates the application of level‐k game theory to adversarial risk analysis. Level‐k reasoning, which assumes that players play strategically but have bounded rationality, is useful for operationalizing a Bayesian approach to adversarial risk analysis. It can be applied in a broad class of settings, including settings with asynchronous play and partial but incomplete revelation of early moves. Its computational and elicitation requirements are modest. We illustrate the approach with an application to a simple defend‐attack model in which the defender's countermeasures are revealed with a probability less than one to the attacker before he decides on how or whether to attack.     

Order Stability in Supply Chains: Coordination Risk and the Role of Coordination Stock

The bullwhip effect describes the tendency for the variance of orders in supply chains to increase as one moves upstream from consumer demand. We report on a set of laboratory experiments with a serial supply chain that tests behavioral causes of this phenomenon, in particular the possible influence of coordination risk. Coordination risk exists when individuals' decisions contribute to a collective outcome and the decision rules followed by each individual are not known with certainty, for example, where managers cannot be sure how their supply chain partners will behave. We conjecture that the existence of coordination risk may contribute to bullwhip behavior. We test this conjecture by controlling for environmental factors that lead to coordination risk and find these controls lead to a significant reduction in order oscillations and amplification. Next, we investigate a managerial intervention to reduce the bullwhip effect, inspired by our conjecture that coordination risk contributes to bullwhip behavior. Although the intervention, holding additional on‐hand inventory, does not change the existence of coordination risk, it reduces order oscillation and amplification by providing a buffer against the endogenous risk of coordination failure. We conclude that the magnitude of the bullwhip can be mitigated, but that its behavioral causes appear robust.     

Reinforcement‐based vs. Belief‐based Learning Models in Experimental Asymmetric‐information Games

This paper examines the abilities of learning models to describe subject behavior in experiments. A new experiment involving multistage asymmetric‐information games is conducted, and the experimental data are compared with the predictions of Nash equilibrium and two types of learning model: a reinforcement‐based model similar to that used by Roth and Erev (1995), and belief‐based models similar to the ‘cautious fictitious play’ of Fudenberg and Levine (1995, 1998) These models make predictions that are qualitatively similar cycling around the Nash equilibrium that is much more apparent than movement toward it. While subject behavior is not adequately described by Nash equilibrium, it is consistent with the qualitative predictions of the learning models. We examine several criteria for quantitatively comparing the predictions of alternative models. According to almost all of these criteria, both types of learning model outperform Nash equilibrium. According to some criteria, the reinforcement‐based model performs better than any version of the belief‐based model; according to others, there exist versions of the belief‐based model that outperform the reinforcement‐based model. The abilities of these models are further tested with respect to the results of other published experiments. The relative performance of the two learning models depends on the experiment, and varies according to which criterion of success is used. Again, both models perform better than equilibrium in most cases.     

Distributional and Peer‐Induced Fairness in Supply Chain Contract Design

Members of a supply chain often make profit comparisons. A retailer exhibits peer‐induced fairness concerns when his own profit is behind that of a peer retailer interacting with the same supplier. In addition, a retailer exhibits distributional fairness when his supplier's share of total profit is larger than his own. While existing research focuses exclusively on distributional fairness concerns, this study investigates how both types of fairness might interact and influence economic outcomes in a supply chain. We consider a one‐supplier and two‐retailer supply chain setting, and we show that (i) in the presence of distributional fairness alone, the wholesale price offer is lower than the standard wholesale price offer; (ii) in the presence of both types of fairness, the second wholesale price is higher than the first wholesale price; and (iii) in the presence of both types of fairness, the second retailer makes a lower profit and has a lower share of the total supply chain profit than the first retailer. We run controlled experiments with subjects motivated by substantial monetary incentives and show that subject behaviors are consistent with the model predictions. Structural estimation on the data suggests that peer‐induced fairness is more salient than distributional fairness.     

Supplier Behavior in Capacity Investment Competition: An Experimental Study

Many manufacturers ensure supply capacity by using more than one supplier and sharing their capacity investment costs via supplier development programs. Their suppliers face competitive pressure from peers despite the reduced capacity investment cost. Although standard game theory makes clear prediction that cost sharing increases the suppliers' capacity choice and supply chain profit, the complex decision environment of capacity competition makes it interesting to test whether the theory predictions are robust and, if not, whether systematic deviations occur. We present a laboratory experiment study. The experiment data show that supplier subjects invested in higher capacities than what our theoretical analysis predicted, resulting in profit loss for the supply chain. Our econometric analysis indicates that the subjects are bounded rational and their concern for relative standing may be the potential driver of capacity over‐investment. Based on the experimental findings, we study a modified cost‐sharing mechanism that adapts to the behavioral biases. Its performance is validated in a second experiment.     

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent‐Based Simulation

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent‐based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg “leader follower” game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent‐based simulation. The evolutionary agent‐based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent‐based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent‐based approach results in a greater percentage of defender victories than does the PRA‐based approach.     

Real‐Time Delay Estimation Based on Delay History in Many‐Server Service Systems with Time‐Varying Arrivals

Motivated by interest in making delay announcements in service systems, we study real‐time delay estimators in many‐server service systems, both with and without customer abandonment. Our main contribution here is to consider the realistic feature of time‐varying arrival rates. We focus especially on delay estimators exploiting recent customer delay history. We show that time‐varying arrival rates can introduce significant estimation bias in delay‐history‐based delay estimators when the system experiences alternating periods of overload and underload. We then introduce refined delay‐history estimators that effectively cope with time‐varying arrival rates together with non‐exponential service‐time and abandonment‐time distributions, which are often observed in practice. We use computer simulation to verify that our proposed estimators outperform several natural alternatives.     

Profit Seeking vs. Survival Seeking: An Analytical Study of Supplier's Behavior and Buyer's Subsidy Strategy

Supplier default is common in emerging markets. Suppliers under the threat of default have different objectives from profit‐seeking companies. This paper analytically tests how profit‐seeking or survival‐seeking behavior, single‐period or two‐period consideration, and buyer's subsidy influence the supplier's and buyer's final utilities. The results show that under single‐period consideration, the supplier's survival‐seeking strategy in fact drives more start‐ups or small suppliers out of business when the competition becomes severe; under two‐period consideration, no matter which strategy (profit‐seeking or survival‐seeking) the supplier selects, the second‐period price and profit are always higher than those of the first period. Furthermore, we find that providing subsidy is an effective way for buyer to keep suppliers’ competition at a certain level on the behalf of buyer's interest. By numerically estimating the benefits associated with the cost of subsidy, we provide a basis for understanding the cost–benefit analysis of buyer's subsidy strategy.     

Coordination in Games with Strategic Complementarities: An Experiment on Fixed vs. Random Matching

In this article, we study behavior in a series of two‐player supply chain game experiments. Each player simultaneously chooses a capacity before demand is realized, and sales are given by the minimum of realized demand and chosen capacities. We focus on the differences in behavior under fixed pairs and random rematching. Intuition suggests that long‐run relations should lead to more profitable outcomes. However, our results go against this intuition. While subjects' capacity choices are better aligned (i.e., closer together) under fixed pairs, average profits are more variable. Moreover, learning is slower under fixed pairs—so much so that over the last five periods, average profits are actually higher under random rematching. The underlying cause for this finding appears to be a “first‐impressions” bias, present only under fixed matching, in which the greater the misalignment in initial choices, the lower are average profits.     

Evaluating Risk Communication: Narrative vs. Technical Presentations of Information About Radon

This paper reports on an experiment to test the hypothesis that people respond better to risk communication that reflects more closely the conditions of their social and cultural lives. The experiment used the case of radon to determine whether technical or narrative forms of risk communication were more effective at drawing people's attention, imparting information, and modifying behavior. Two series of articles on radon were placed in the local newspapers of two Massachusetts communities. Homeowner attitudes, knowledge, and responses were monitored in baseline and follow-up telephone surveys. A third community was selected for comparison. The newspaper series were developed on the basis of previous research and six focus groups conducted with homeowners. The technical series presented authoritative, factual risk information, in the scientific style of the passive voice with generalized and impersonal language. The narrative series consisted of dramatized accounts of individuals making decisions about radon testing and mitigation, written in a more personal style. The findings from the focus groups confirm the results of previous studies, but the small size of the follow-up samples was a limiting factor in drawing definitive conclusions about the relative effectiveness of the two formats. The experiment demonstrates the difficulty of any risk communication effort on radon and underscores the need for good research design.(ABSTRACT TRUNCATED AT 250 WORDS)     

Impact of Information Technology Integration and Lean/Just‐In‐Time Practices on Lead‐Time Performance*

Managers seeking to improve lead‐time performance are challenged by how to balance resources and investments between process improvement achieved through lean/just‐in‐time (JIT) practices and information technology (IT) deployment. However, extant literature provides little guidance on this question. Motivated by both practical importance and lack of academic research, this article examines empirically the relationships among interfirm IT integration, intrafirm IT integration, lean/JIT practices, and lead‐time performance using data from IndustryWeek's Census of Manufacturers ( IndustryWeek, 2006 ). The results provide several new insights on the relationship between IT integration and lean/JIT practices. First, the study confirms that implementing lean/JIT practices significantly reduces lead time. Second, lean/JIT practices mediate the influence of IT integration on lead‐time performance. This suggests that process improvements that result from lean/JIT practices are important contributors to the success of IT integration. Even companies that have experienced success in reducing lead time through lean/JIT practices may benefit from IT integration practices such as those embodied in enterprise resource planning systems. The findings provide managers with empirical evidence and a theoretical framework on the balance between lean/JIT and IT for effecting improvement in lead‐time performance, thus offering practical guidance on this important question. Future research is needed to extend the lean/JIT practices in this study to supply chain practices and explore the relationship between supply chain practices and IT integration.     

On‐Shelf Availability,Retail Performance,and External Audits: A Field Experiment

A potential answer to retailer's shelf out‐of‐stocks (OOS), where the item is in the store but customers cannot find it, is to employ third‐party service providers to execute audits and corrections. However, given the nontrivial cost of executing external audits, it is still necessary to assess whether external audits are capable of reducing shelf‐OOS, whether they can be performed in an economical way, and whether the benefits from the audits translate into higher sales. In an effort to address these questions, we partnered with a product manufacturer and a retail service provider and conducted a field experiment in a national retailer's store set. We used transactional data to detect abnormal operations and respond to possible shelf‐OOS by sending auditors to correct empty shelves and incorrect inventory records. At the conclusion of the experiment, we found that Stock Keeping Units in the treatment group were less likely to have shelf‐OOS and inventory record inaccuracies, and that our intervention had a positive effect on sales. Furthermore, we found that the external audit initiative is economically viable since these improvements required low auditing efforts after a transitional period, and in steady state the cost of running the program is a small fraction of the benefits it generates. We discuss the limitations of our study and the implications of our findings for researchers and practitioners.     

The Creation of Output and Quality in Services: A Framework to Analyze Information Technology‐Worker Systems

Information technology has profoundly impacted the operations of firms in the service industry and service environments within manufacturing. Two models are introduced that establish a conceptual framework linking firm profit to attributes of the IT‐worker system. The framework considers the impact of IT capabilities (such as functionality and ease‐of‐use) and worker skill as drivers of output volume and quality. The framework contrasts attributes of the IT‐worker systems when services are mass‐produced (flow shop) versus customized (job shop). Mathematical models are introduced to formalize the conceptual framework. Numerical examples are presented that illustrate the types of insights that can be obtained from the models.     

Equilibrium in Continuous‐Time Financial Markets: Endogenously Dynamically Complete Markets

We prove existence of equilibrium in a continuous‐time securities market in which the securities are potentially dynamically complete: the number of securities is at least one more than the number of independent sources of uncertainty. We prove that dynamic completeness of the candidate equilibrium price process follows from mild exogenous assumptions on the economic primitives of the model. Our result is universal, rather than generic: dynamic completeness of the candidate equilibrium price process and existence of equilibrium follow from the way information is revealed in a Brownian filtration, and from a mild exogenous nondegeneracy condition on the terminal security dividends. The nondegeneracy condition, which requires that finding one point at which a determinant of a Jacobian matrix of dividends is nonzero, is very easy to check. We find that the equilibrium prices, consumptions, and trading strategies are well‐behaved functions of the stochastic process describing the evolution of information. We prove that equilibria of discrete approximations converge to equilibria of the continuous‐time economy.     

Competing on Time: An Integrated Framework to Optimize Dynamic Time‐to‐Market and Production Decisions

This study develops a comprehensive framework to optimize new product introduction timing and subsequent production decisions faced by a component supplier. Prior to market entry, the supplier performs process design activities, which improve manufacturing yield and the chances of getting qualified for the customer's product. However, a long delay in market entry allows competitors to enter the market and pass the customer's qualification process before the supplier, reducing the supplier's share of the customer's business. After entering the market and if qualified, the supplier also needs to decide how much to produce for a finite planning horizon by considering several factors such as manufacturing yield and stochastic demand, both of which depend on the earlier time‐to‐market decision. To capture this dependency, we develop a sequential, nested, two‐stage decision framework to optimize the time‐to‐market and production decisions in relation to each other. We show that the supplier's optimal market entry and qualification timing decision need to be revised in real time based on the number of qualified competitors at the time of market‐entry decision. We establish the optimality of a threshold policy. Following this policy, at the beginning of each decision epoch, the supplier should optimally stop preparing for qualification and decide whether to enter the market if her order among qualified competitors exceeds a predetermined threshold. We also prove that the supplier's optimal production policy is a state‐dependent, base‐stock policy, which depends on the time‐to‐market and qualification decisions. The proposed framework also enables a firm to quantify how market conditions (such as price and competitor entry behavior) and operating conditions (such as the rate of learning and inventory/production‐related costs) affect time‐to‐market strategy and post‐entry production decisions.     

Decision Making in Cross‐Functional Teams: The Role of Decision Power*

Through a series of game‐theoretical models, this study systematically examines decision making in cross‐functional teams. It provides a framework for the design of an organization‐specific decision‐making process and for the alignment of a team's microdecision with the “optimal” decision that maximizes the firm's payoff. This study finds that even without changing the team leader, firms could change and even dictate the team's microdecision outcome via adjusting the team member's seniority, empowering team members with veto power or involving a supervisor as a threat to overrule the team decision. This finding implies that to reposition products in the marketplace, structuring cross‐functional teams’ microdecision‐making processes is essential.     

The Influence of Service Orientation on B2B e‐Service Capabilities: An Empirical Investigation

E‐Services, or the company's portfolio of service offerings available to its customers through the Internet, are an emerging area of interest to operations management. Yet little is known about the operations and capabilities needed for provision of business‐to‐business (B2B) e‐services. This paper aims to make a contribution toward closing this gap. First, we develop a new construct of B2B e‐service capability, a term that captures a generic set of five interrelated and complementary dimensions: (1) e‐service recovery, (2) e‐customization, (3) ease of navigation, (4) service portfolio comprehensiveness, and (5) information richness. These combined operational abilities are associated with B2B service delivery, including its portal design, technology architecture, and mix of product and service offerings. They are posited to be necessary for delivering effective B2B e‐services. We also argue that, both service orientation (SO) and customer receptivity to technology, influence B2B e‐service capability. We empirically test a path model using structural equation modeling on a sample of 181 businesses that have deployed B2B e‐services. We find that the influence of SO on performance is not direct but rather mediated by the e‐service capability, a finding that holds for both goods producers and service providers. We suggest that a firm's SO may mitigate industrial customers' resistance toward conducting business online.