Bargaining Process and Channel Efficiency

2020 ◽  
Vol 66 (7) ◽  
pp. 2845-2860 ◽  
Author(s):  
Ernan Haruvy ◽  
Elena Katok ◽  
Valery Pavlov
Keyword(s):  
Operations Management ◽  
Laboratory Experiments ◽  
Wholesale Price ◽  
Analytical Models ◽  
Bargaining Process ◽  
Supply Chain Contracts ◽  
Channel Efficiency ◽  
Contract Performance ◽  
Do So ◽  
Additional Channel

The behavioral literature has demonstrated that the format of supply chain contracts matters even when theoretically it should not and that contracts that in theory coordinate channels fail to do so in laboratory experiments. The existing body of experimental evidence uses an ultimatum bargaining protocol to test analytical models, but there is no reason to think that bargaining in supply chains is in the form of ultimatum offers. We investigate the effect of bargaining on contract performance by extending the bargaining protocol to allow the manufacturer to make concessions. We test coordinating contract with bargaining in the laboratory by comparing wholesale price and the two-part tariff contracts using two different bargaining protocols. We then develop and estimate a statistical model of behavior with bargaining and find that this model organizes our data well. Our main finding is that the contracts that we study are more efficient when participants are allowed to make concessions. The additional channel efficiency is owing to more efficient offers made by manufacturers. The higher channel efficiency primarily benefits the retailer—the weaker party. Our main contribution is the observation that, when testing analytical models of contracts in the laboratory, the way that the bargaining process is implemented, such as the ability to make concessions, has a critical effect on conclusions. This paper was accepted by Vishal Gaur, operations management.

RiRiShun Logistics: Home Appliance Delivery Data for the 2021 Manufacturing & Service Operations Management Data-Driven Research Challenge

2021 ◽  
Author(s):  
Xiaolong Guo ◽  
Yugang Yu ◽  
Gad Allon ◽  
Meiyan Wang ◽  
Zhentai Zhang
Keyword(s):  
Operations Management ◽  
Service Operations ◽  
Optimization Techniques ◽  
Data Driven ◽  
Analytical Models ◽  
Data Set ◽  
Service Operations Management ◽  
Level Data ◽  
Home Appliance ◽  
Research Challenge

To support the 2021 Manufacturing & Service Operations Management (MSOM) Data-Driven Research Challenge, RiRiShun Logistics (a Haier group subsidiary focusing on logistics service for home appliances) provides MSOM members with logistics operational-level data for data-driven research. This paper provides a detailed description of the data associated with over 14 million orders from 149 clients (the consigners) associated with 4.2 million end consumers (the recipients and end users of the appliances) in China, involving 18,000 stock keeping units operated at 103 warehouses. Researchers are welcomed to develop econometric models, data-driven optimization techniques, analytical models, and algorithm designs by using this data set to address questions suggested by company managers.

Sharing Demand Information with Retailer Under Upstream Competition

2021 ◽  
Author(s):  
Aditya Jain
Keyword(s):  
Information Sharing ◽  
Private Information ◽  
Operations Management ◽  
Information Acquisition ◽  
Wholesale Price ◽  
Substitutable Products ◽  
Downward Pressure ◽  
Demand Information ◽  
Intensity Of Competition ◽  
Share Information

We analyze demand information sharing collaboration between two manufacturers and a retailer under upstream competition. The manufacturers produce partially substitutable products, which are stocked by the retailer that sells them in the market characterized by random demand. The manufacturers are privately informed about uncertain demand and decide on whether to share this information with the retailer. We show that by not sharing information, a manufacturer ends up distorting its wholesale price upward to signal its private information to the retailer, and under upstream competition, this distortion is propagated to the competing manufacturer. Thus, although a manufacturer’s decision to not share information may benefit or hurt its own profit, this always benefits the competing manufacturer. Under low intensity of competition, signaling-driven distortions exacerbate double marginalization and hurt all parties, whereas under more intense competition, these distortions help manufacturers offset downward pressure on wholesale prices. Thus, in equilibrium similarly informed manufacturers share information in the former case but not in the latter case. Additionally, when manufacturers differ in their information accuracies, only the better-informed manufacturer shares information. The retailer always benefits from both manufacturers sharing information, and its benefits are larger when the better-informed manufacturer shares information. We show existence of a contracting mechanism the retailer can employ to enable information sharing. Finally, we analyze manufacturers’ information acquisition decisions and find that under competition, two manufacturers acquire minimal information so that they are better off not sharing information in the information sharing game. This paper was accepted by Vishal Gaur, operations management.

scholarly journals Supply Chain Competition: A Market Game Approach

2020 ◽  
Vol 66 (12) ◽  
pp. 5648-5664 ◽  
Author(s):  
C. Gizem Korpeoglu ◽  
Ersin Körpeoğlu ◽  
Soo-Haeng Cho
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Operations Management ◽  
Wholesale Price ◽  
Market Price ◽  
Market Game ◽  
Wholesale Market ◽  
Supply Chain Competition ◽  
Local Supply ◽  
Buyer Power

We study supply chains where multiple suppliers sell to multiple retailers through a wholesale market. In practice, we often observe that both suppliers and retailers tend to influence the wholesale market price that retailers pay to suppliers. However, existing models of supply chain competition do not capture retailers’ influence on the wholesale price (i.e., buyer power) and show that the wholesale price and the order quantity per retailer do not change with the number of retailers. To overcome this limitation, we develop a competition model based on the market game mechanism in which the wholesale price is determined based on both suppliers’ and retailers’ decisions. When taking into account retailers’ buyer power, we obtain the result that is consistent with the observed practice: As the number of retailers increases, each retailer’s buyer power decreases, and each retailer is willing to pay more for her order, so the wholesale price increases. In this case, supply chain expansion to include more retailers (or suppliers) turns out to be more beneficial in terms of supply chain efficiency than what the prior literature shows without considering buyer power. Finally, we analyze the integration of two local supply chains and show that although the profit of the integrated supply chain is greater than the sum of total profits of local supply chains, integration may reduce the total profit of firms in a retailer-oriented supply chain that has more retailers than suppliers. This paper was accepted by Charles Corbett, operations management.

Making the Most of Your Regret: Workers’ Relocation Decisions in On-Demand Platforms

2020 ◽  
Author(s):  
Zhong-Zhong Jiang ◽  
Guangwen Kong ◽  
Yinghao Zhang
Keyword(s):  
System Performance ◽  
Financial Incentives ◽  
Laboratory Experiments ◽  
Policy Design ◽  
Working Hours ◽  
Problem Definition ◽  
Analytical Models ◽  
Behavioral Biases ◽  
On Demand ◽  
Regret Aversion

Problem definition: We have witnessed a rapid rise of on-demand platforms, such as Uber, in the past few years. Although these platforms allow workers to choose their own working hours, they have limited leverage in maintaining availability of workers within a region. As such, platforms often implement various policies, including offering financial incentives and/or communicating customer demand to workers in order to direct more workers to regions with shortage in supply. This research examines how behavioral biases such as regret aversion may influence workers’ relocation decisions and ultimately the system performance. Academic/practical relevance: Studies on on-demand platforms often assume that workers are rational agents who make optimal decisions. Our research investigates workers’ relocation decisions from a behavioral perspective. A deeper understanding of workers’ behavioral biases and their causes will help on-demand platforms design appropriate policies to increase their own profit, worker surplus, and the overall efficiency of matching supply with demand. Methodology: We use a combination of behavioral modeling and controlled laboratory experiments. We develop analytical models that incorporate regret aversion to produce theoretical predictions, which are then tested and verified via a series of controlled laboratory experiments. Results: We find that regret aversion plays an important role in workers’ relocation decisions. Regret-averse workers are more willing to relocate to the supply-shortage zone than rational workers. This increased relocation behavior, however, is not sufficient to translate to a better system performance. Platform interventions, such as demand information sharing and dynamic wage bonus, can help further improve the system. We find that workers’ regret-aversion behavior may lead to an increased profit for the platform, a higher surplus for the workers, and an improved demand-supply matching efficiency, thus benefiting the entire on-demand system. Managerial implications: Our research emphasizes the importance and necessity of incorporating workers’ behavioral biases such as regret aversion into the policy design of on-demand platforms. Policies without considering the behavioral aspect of workers’ decision may lead to lost profit for the platform and reduced welfare for workers and customers, which may ultimately hurt the on-demand business.

scholarly journals Physiological tolerances account for range limits and abundance structure in an invasive slug

2009 ◽  
Vol 276 (1661) ◽  
pp. 1459-1468 ◽  
Author(s):  
Jennifer E Lee ◽  
Charlene Janion ◽  
Elrike Marais ◽  
Bettine Jansen van Vuuren ◽  
Steven L Chown
Keyword(s):  
Laboratory Experiments ◽  
Climatic Factors ◽  
Range Limits ◽  
Sensitive Species ◽  
Species Preference ◽  
Absolute Limit ◽  
Drainage Line ◽  
Physiological Tolerances ◽  
Linear Decline ◽  
Do So

Despite the importance of understanding the mechanisms underlying range limits and abundance structure, few studies have sought to do so. Here we use a terrestrial slug species, Deroceras panormitanum , that has invaded a remote, largely predator-free, Southern Ocean island as a model system to do so. Across Marion Island, slug density does not conform to an abundant centre distribution. Rather, abundance structure is characterized by patches and gaps. These are associated with this desiccation-sensitive species' preference for biotic and drainage line habitats that share few characteristics except for their high humidity below the vegetation surface. The coastal range margin has a threshold form, rapidly rising from zero to high density. Slugs do not occur where soil-exchangeable Na values are higher than 3000 mg kg −1 , and in laboratory experiments, survival is high below this value but negligible above it. Upper elevation range margins are a function of the inability of this species to survive temperatures below an absolute limit of −6.4°C, which is regularly exceeded at 200 m altitude, above which slug density declines to zero. However, the linear decline in density from the coastal peak is probably also a function of a decline in performance or time available for activity. This is probably associated with an altitudinal decline in mean annual soil temperature. These findings support previous predictions made regarding the form of density change when substrate or climatic factors set range limits.

scholarly journals Precession-driven flows in non-axisymmetric ellipsoids

2013 ◽  
Vol 737 ◽  
pp. 412-439 ◽  
Author(s):  
J. Noir ◽  
D. Cébron
Keyword(s):  
Theoretical Model ◽  
Numerical Simulations ◽  
Celestial Body ◽  
Excellent Agreement ◽  
Analytical Models ◽  
Forced Flow ◽  
Spheroidal Geometry ◽  
Strong Contrast ◽  
Do So

AbstractWe study the flow forced by precession in rigid non-axisymmetric ellipsoidal containers. To do so, we revisit the inviscid and viscous analytical models that have been previously developed for the spheroidal geometry by, respectively, Poincaré (Bull. Astronomique, vol. XXVIII, 1910, pp. 1–36) and Busse (J. Fluid Mech., vol. 33, 1968, pp. 739–751), and we report the first numerical simulations of flows in such a geometry. In strong contrast with axisymmetric spheroids, where the forced flow is systematically stationary in the precessing frame, we show that the forced flow is unsteady and periodic. Comparisons of the numerical simulations with the proposed theoretical model show excellent agreement for both axisymmetric and non-axisymmetric containers. Finally, since the studied configuration corresponds to a tidally locked celestial body such as the Earth’s Moon, we use our model to investigate the challenging but planetary-relevant limit of very small Ekman numbers and the particular case of our Moon.

Field Experiments

2004 ◽  
Vol 42 (4) ◽  
pp. 1009-1055 ◽  
Author(s):  
Glenn W Harrison ◽  
John A List
Keyword(s):  
Laboratory Experiments ◽  
Field Experiments ◽  
Trading Rules ◽  
Subject Pool ◽  
The Subject ◽  
Do So

Experimental economists are leaving the reservation. They are recruiting subjects in the field rather than in the classroom, using field goods rather than induced valuations, and using field context rather than abstract terminology in instructions. We argue that there is something methodologically fundamental behind this trend. Field experiments differ from laboratory experiments in many ways. Although it is tempting to view field experiments as simply less controlled variants of laboratory experiments, we argue that to do so would be to seriously mischaracterize them. What passes for “control” in laboratory experiments might in fact be precisely the opposite if it is artificial to the subject or context of the task. We propose six factors that can be used to determine the field context of an experiment: the nature of the subject pool, the nature of the information that the subjects bring to the task, the nature of the commodity, the nature of the task or trading rules applied, the nature of the stakes, and the environment that subjects operate in.

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