Browsing by Author "Nault, Barrie R."

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    Balancing openness and prioritization in a two-tier Internet
    (2018-10-03) Nault, Barrie R.; Zimmermann, Steffen
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    Benefits and Drawbacks of Digital Platforms with Policy Analysis
    (2023-08-25) Fereidouni, Meysam; Nault, Barrie R.; Patterson, Raymond; Dao, Duy; Parker, Geoffrey; Bijvank, Marco
    Digital platforms offer numerous advantages to consumers and businesses. Our first stream of research examines the role of shared platforms that are characterized by offering exclusive services to customers, also known as member-only services. Such services mitigate customers' disutility of online purchasing and enable shared platforms to reduce the risk of losing customers to competitors. Using analytical modelling methodologies, our first research chapter aims to understand the economic and social implications of shared platforms. Our finding in this chapter shows that shared platforms maximize their profits by subsidizing the customer-side of the market. Although digital platforms have enlarged contestability in many markets by allowing small firms to develop innovative solutions to compete with monopolies, they have brought new challenges. The second research stream uses analytical modelling methodologies to study two important challenges of digital platforms: biased intermediation and digital piracy. As digital platforms have grown in size and influence, there are concerns about their engagement in anti-competitive behavior, such as having incentives to offer matches that are more profitable to themselves rather than the most relevant ones to users. This conduct is called biased intermediation. Our first research chapter in this stream quantifies the economic and social impacts of biased intermediation and examines whether imposing taxes on digital platforms' revenue can mitigate the potentially harmful effects of biased intermediation. With the rise of digital platforms, it has become easier for individuals to access and share copyrighted material without permission. This has had a significant impact on the revenues of the entertainment industry, with losses estimated to be in the billions of dollars annually. Thus, policymakers must understand the new market realities of digital platforms and reinterpret traditional regulatory approaches accordingly. The second research chapter in the second stream studies how a policymaker can mitigate the harmful effects of digital piracy by imposing fines on pirates, subsidizing legal purchases, and supporting the publisher through restitution within a balanced budget.
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    A Classification of Supply Chain Problems
    (Canadian Centre of Science Education, 2012-11) Nault, Barrie R.; Osborn, Beverly E.
    Supply chain problems referenced in peer-reviewed journals and selected management magazines were collected, with information about the journal, the resource affected, the cause of the problem, the solution(s) applied, and the firm(s) involved. Keywords were used to group these problems into naturally occurring categories. Nine types of supply chain problems were identified: conflict, delays, demand fluctuations, excess/unused resources, inaccuracy, insufficient resources, long tail, pricing, and security. These categories together present a comprehensive view of problems that typically affect different resources within the supply chain, and can be used to diagnose problems and to evaluate solutions.
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    Discrete Choice-based Equilibrium Modeling of Supply Chain Network with Conflicting Objectives and Demand Uncertainty
    (2021-01-05) Ma, Jun; Tu, Yiliu; Nault, Barrie R.; Patterson, Raymond A.; Li, Simon; Ma, Yongsheng
    This PhD thesis discusses several equilibrium problems in supply chain network integration and specifically concentrates on the importance of collaboration under conflicting objective decision-making and uncertainty management in a supply chain network. In particular, discrete choice models are introduced into supply chain equilibrium models to bridge the conflicting objective decision-making in supply chains and customer preference. Furthermore, numerical examples are provided for model illustration, managerial insights, and algorithm performance. Finally, it attempts to explore the tradeoffs between the operation costs, service level, and time issues in a supply chain, considering customer preference and demand uncertainty. Two conventional assumptions used in both the supply chain network equilibrium model and the newsvendor model are generalized and relaxed in order to obtain more general solutions and methods. First, this PhD thesis adopts Sheffi’s equilibrium condition assumption rather than Wardrop’s network equilibrium condition assumption. Discrete choice models are introduced into supply chain equilibrium models. A probabilistic fashion is used to describe customer choice behavior, because all factors affecting customer choice behavior cannot be observed completely. It assumes equilibrium will be reached when no customer believes that his utility can be improved by unilaterally changing products (or services) provided by supply chains. This assumption is not easy to use in practice, except it can be characterized and formulated as equilibrium conditions mathematically. Next, the equilibrium conditions are formulated as multinomial logit- and newsvendor model-based variational inequalities. Second, the assumption in the newsvendor model that unmet demand is lost implies that customers are stockout neutral. This study assumes the customers are stockout aversion. This work generalizes the implied assumption in the newsvendor model and introduces it into the supply chain equilibrium model. This PhD thesis has several contributions to the supply chain network integration with a focus on the collaboration under conflicting objective decision-making and uncertainty management in a supply chain network. First, discrete choice models are incorporated into supply chain equilibrium models to bridge the conflicting objective decision-making in supply chains and customer preference. It brings several technical problems. A variety of corollaries, theorems, and propositions are provided to illustrate the models and problems. Hence, the model can optimize supply chain profits without multi-objective conversion at the firm level. Second, heterogeneous customers’ discrete choice behaviors are considered in the model. Most existing supply chain network equilibrium models are capable of providing equilibrium solutions in a supply chain network, only under the assumption that customers are homogeneous. This assumption can be extended to heterogeneous customers by using a supply chain network economic or equilibrium models integrated with the multinomial logit model and data at the level of the customer individual. Third, this work assumes that customers are stockout aversion and introduce the newsvendor model to solve the issue that uncertain demand depends on both price and service level in a supply chain network for joint products. The newsvendor model-based variational inequality problems are given to formulate the equilibrium conditions.
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    A dynamic pricing strategy for a 3PL provider with heterogeneous customers
    (2015-06-08) Zhang, Jian; Nault, Barrie R.; Tu, Paul Yiliu L.
    We study the pricing problem for a third-party-logistics (3PL) provider that provides ware-housing and transportation services. When customers arrive at the 3PL provider, they specify the delivery dates for their freight, and before the specified delivery dates, their freight is stocked in the 3PL provider’s warehouse. We propose a dynamic pricing strategy (DPS) and develop a stochastic-nonlinear-programming (SNLP) model which computes the optimal freight rates for different delivery dates incorporating the 3PL provider’s current holding cost and available transportation capacity for each route. As customers are heterogeneous in their valuations and price sensitivities for delivery dates, and the distributions of the customers’ delivery date preferences are unknown to the 3PL provider, we modify the standard multinomial logit (MNL) function to predict customer choices. Through a simulation experiment, we show that the proposed MNL function can be a good replacement for the mixed MNL function when the mixed MNL function is not applicable. Through simulation we also compare the proposed DPS with a static pricing strategy. We show that with our DPS both the 3PL provider and its customers are better off, and the 3PL provider has different investment incentives for increasing transportation capacity. Our results can be also applied in similar settings that feature holding costs, limited production capacity and delivery-date-sensitive customers. Keywords: dynamic pricing, multinomial logit, third-party logistics, stochastic programming
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    Essays on Content Moderation, Misinformation, and Fraud
    (2024-07-29) Hojati, Afrouz; Patterson, Raymond A.; Nault, Barrie R.; Hidaji, Hooman; Vijairaghavan, Vaarun; Hue, Jinhee; Fan, Ming
    In the digital age, ensuring online safety has become paramount. This dissertation explores three crucial dimensions of this challenge: fraud detection, misinformation management, and the control of harmful and extreme content. First, we introduce a novel framework for detecting fraudulent websites by analyzing the interactions between websites and third-party vendors. This approach transcends the limitations of traditional content-based methods, offering a more robust and adaptable solution that leverages the underlying infrastructure of websites. Our findings demonstrate that the structure of third-party requests can effectively differentiate between fraudulent and legitimate websites across diverse categories, enhancing the accuracy and efficiency of online fraud detection. Second, we empirically investigate the indirect effects of content moderation policies on social media platforms, specifically examining the unintended consequences of a policy change on Reddit designed to prevent misinformation. Through a natural experiment, we uncover that even seemingly minor policy adjustments can have far-reaching effects on user behavior, content sentiment, and overall platform dynamics. This study underscores the need for a nuanced understanding of the indirect effects of moderation policies and their broader implications for social media platforms, users, and regulators. Finally, we develop a theoretical model to investigate the economic incentives and welfare implications of different content moderation strategies, with a particular emphasis on shadowbanning. We compare shadowbanning with content removal, the most prevalent moderation strategy, to illuminate the economic motivations behind platform choices and their impact on consumer surplus and social welfare. Our analysis reveals that shadowbanning can be economically advantageous for platforms under certain conditions, but it also raises concerns about potential negative consequences for users and overall social welfare.
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    Information technology substitution revisited
    (2014-12-26) Zhang, Dawei; Cheng, Zhuo (June); Mohammad, Hasan A. Qurban H.; Nault, Barrie R.
    Taking advantage of the opportunities created by the price adjusted performance improvement in IT depends in part on the ability of IT capital to substitute for other inputs in production. Studies in the IS literature as well as most economics training that examine substitution of IT capital for other inputs use the Allen elasticity of substitution (AES). We present a less-well-known measure for the elasticity of substitution, the Morishima Elasticity of Substitution (MES). In contrast to the AES which is misleading when there are three or more inputs – such as non-IT capital, labor and IT capital – the MES provides a substitution measure where the scale is meaningful, and the measure differs depending upon which price is changing. This is particularly important for IT capital as prices have been declining and there is evidence that IT capital can substitute for non-IT capital or labor in a qualitatively different way than non-IT capital and labor substitute for each other. Methodologically we also show the impact of imposing local regularity – for example, monotonicity of output from increases in inputs – that we do through Bayesian methods employed to estimate the underlying functions that are used to calculate various measures of substitution. We demonstrate the importance of the MES as an under-recognized measure of substitution and the impact of imposing local regularity using an economy-wide industry-level dataset covering 1998-2009 at the three-digit NAICS level. Our MES results show that reductions in the price of IT capital increase the quantity of IT capital in use but are unlikely to change the input share of IT capital – the value of IT capital as a proportion of the value of all inputs, in contrast to major studies using the AES. In addition, estimates for both elasticities of substitution are more stable after imposing local regularity. Both of these advances – that is, the MES and imposing local regularity – have potential to impact future work on IT productivity, IT pricing, IT cost estimation and any type of analysis that posits the substitution of IT capital for non-IT capital or labor.
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    An internet-Enabled Move to the Market in Logistics
    (2016-01-21) Gong, Fengmei; Nault, Barrie R.; Rahman, Mohammad Saifur
    Logistics outsourcing has increased with the commercialization of the Internet, implying a reduction in the corresponding transaction costs. The Internet – with its universal connectivity and open standards – radically enhanced information technology (IT) capabilities, and we hypothesize this has reduced external transaction costs relatively more than internal governance costs. Using transaction cost theory as a lens, we examine whether the commercialization of the Internet coincided with a move to the market in logistics – one of the most connected industries in the economy. We estimate the relationship between IT and outsourced logistics in a production function based on two datasets from 1987 to 2008. We find that the effects of IT on outsourced logistics have changed in the post-Internet era. After the commercialization of the Internet, an industry’s own IT investment and outsourced logistics became complements whereas they were not before. It suggests that because of the unique characteristics of the Internet as an enabler, IT reduced external transaction costs relatively more than internal governance costs. Consequently, industries favored the market form of the provision of logistics. We also find similar impacts of customers’ IT investments on a focal industry’s outsourced logistics. Previous studies argued that IT led to the shift from hierarchies to markets, or provided indirect evidence through measures of firm size or integration. Using a production theory model our study provides systematic empirical evidence to support that the Internet enabled a move to the market in the provision of logistics.
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    Operating room scheduling and adaptive control using a priority first fit decreasing heuristic
    (2015-06) Li, Wei; Mitchell, Victoria L.; Nault, Barrie R.; Brind, Denise
    Operating room (OR) scheduling is a critical factor affecting overall hospital performance. We examine OR scheduling from two perspectives. In the first perspective we propose a scheme for OR block scheduling that uses a heuristic developed for a three-machine flow shop where the three phases of the peri-operative process (pre-op, OR, and post-op) correspond to the three-machine flow shop. This approach facilitates a hospital-as-a-system perspective. The second perspective used to examine OR scheduling is adaptive control of the OR slate. Recognizing that there are many factors affecting OR throughput performance, especially preemptions from emergent and urgent cases, adaptive control of the OR slate is necessary. To realistically improve performance, adaptive control of the OR slate should incorporate constraints on how surgeries can be rescheduled. We examine the benefits from adaptive control of the OR slate that uses a priority first fit decreasing (PFFD) heuristic while incorporating constraints on OR slate rescheduling. The PFFD heuristic is a priority-driven variation of the classic FFD heuristic used in bin packing problems. We develop a scheme for OR block scheduling and our PFFD heuristic. We then demonstrate our PFFD heuristic in a simulation-based case study, and subsequently run a simulation using 1000 instances to test the performance of our PFFD heuristic in OR slate scheduling and OR slate adaptive control showing improvements in performance relative to the frequently used first-come-first-served rule.
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    Pricing in C2C sharing platforms
    (2017-07-23) Angerer, Peter; Provin, Daniel; Zimmermann, Steffen; Nault, Barrie R.
    Sharing platforms such as Zilok.com enable the sharing of durable goods among consumers, and seek to maximize profits by charging transaction-based platform fees. We develop a model where consumers that are heterogeneous in their need to use a durable good decide whether to purchase and share (i.e., be a lender) or borrow (i.e., be a borrower), and a monopoly sharing platform decides on the platform fees. We find first that consumers with a greater need to use a durable good purchase and share, and that consumers with a lesser need borrow. Second, sharing platforms maximize profits only if the supply of a durable good matches demand – that is, the market must clear for platform fees to be profit maximizing. Third, the market-clearing condition requires that lender and borrower fees are classic strategic complements. Fourth, to maintain the market-clearing condition, sharing platforms have to increase their lender fee or decrease their borrower fee in response to increases in the sharing price, increases in usage capacity, and decreases in the purchase price of a durable good, and vice versa. These findings indicate that commonly applied one-sided pricing models in sharing platforms can be improved.