Effects of IoT technology on gray market: An analysis based on traceability system design

Ding, Long; Hu, Bin; Ke, Changying; Wang, Tingting; Chang, Shan

doi:10.1016/j.cie.2019.06.038

Cited by 18 publications

(4 citation statements)

References 45 publications

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“…a) Trust challenges. There are many nodes involved in an system composed of various intelligent devices and transmission protocols (Ding, Hu, Ke, Wang, & Chang, 2019;Zhang, Wang, Li, & Su, 2018). When a single node in the IoT network is attacked, it is easy to cause paralysis of the IoT system.…”

Section: Challenges and Discussionmentioning

confidence: 99%

The evolution of the Internet of Things (IoT) over the past 20 years

Wang

Lim

Wang

et al. 2021

Computers & Industrial Engineering

178

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Section: Challenges and Discussionmentioning

confidence: 99%

The evolution of the Internet of Things (IoT) over the past 20 years

Wang

Lim

Wang

et al. 2021

Computers & Industrial Engineering

178

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“…If one or more authorized sellers accept the offer, the dealer sets its retail price

p_{{D}}

. The unauthorized dealer often has less pricing power in the market, especially for high‐end and specialty brands, thus the unauthorized dealer is commonly modeled as the Stackelberg follower (Autrey et al., 2014; Ding et al., 2019; Shavandi et al., 2015). If both authorized sellers reject the offer, the unauthorized dealer does not participate in the market.…”

Section: Modelmentioning

confidence: 99%

“…Diversion's impacts are often vague and can have unexpected effects (Chen, 2009;Mitchell, 1998). Bandyopadhyay (2010), Chen (2009), Ding et al (2019), Gallini and Hollis (1999), Myers andGriffith (1999), andHintz (1993) focused on manufacturers and their profit loss from diversion. Myers (1999), Assmus and Wiese (1995), and Autrey and Bova (2012) pointed out that multinational companies not only suffer from detrimental profit decrease but also lose incentives to innovate, which imposes potential long-term costs to consumers and the society.…”

Section: Production and Operations Managementmentioning

confidence: 99%

Product diversion by vertically differentiated firms

Smith

Shulman

2022

Production and Operations Management

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Retail sellers authorized to sell a branded product may divert some units to an unauthorized dealer thus enabling the dealer to become a direct competitor. Because these sellers vary in quality, it is often unclear what type of seller is more motivated to participate in diversion. We develop an analytical model to demonstrate how vertically differentiated sellers make diversion decisions responding to an unauthorized dealer under unique circumstances not considered by previous research. The model demonstrates that when diversion occurs, the low‐quality seller can actually earn a greater profit than the high‐quality seller. Furthermore, a higher quality differential can lead to an overall profit loss for the high‐quality seller when both sellers divert. The sellers will divert products to the competing dealer if and only if they are sufficiently similar to each other. The low‐quality seller has an incentive to divert more units in general, and is motivated to divert alone when the quality differential is not too high. Additionally, changes in vertical differentiation have nonmonotonic effects on the sellers. Overall, the results establish seller vertical differentiation as a new key variable in analyzing product diversion and demonstrate its unique consequences for the authorized sellers and the unauthorized dealer.

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“…In terms of comprehensive practices between manufacturers and distributors, supply chain managers should be aware of value creation of Information Technology (IT) in supply chain planning (Fuchs and Otto, 2015), and information technology (IT) investments should be wisely thought given that huge and impudent IT investments may damage overall organizational performance (Panda and Rath, 2016). Nevertheless, on the positive side, a cloud-based management system enhancing supply chain responsiveness (Giannakis et al , 2019; Jede and Teuteberg, 2015) could enhance rapid detection and reactions to changes coming from gray market speculators, or the Internet of Things (IoT) technology enabling the manufacturer to track gray-product distribution and monitor gray market activity (Ding et al , 2019). Otherwise, as indicated by Ruel et al (2019), a lack of knowledge management practices between supply chain members may lead to supply chain vulnerability.…”

Section: Managerial Implicationsmentioning

confidence: 99%

Arbitrage in gray markets and its impact on supply chain decisions

Yao

Foropon

Wang

et al. 2020

JEIM

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PurposeThe purpose of this paper is to investigate the impacts of different gray markets’ structures on both supply chain decisions and associated profits.Design/methodology/approachWithin the context of gray markets, using game theory approach in this paper, supply chains have been considered as assets of manufacturers, distributors and speculators, within which manufacturers sell products to distinctive markets either directly or through authorized distributors, while speculators buy products from a lower price market and then sell them in a higher price market. Our study has examined different decision variables within such a framework.FindingsConsidering a situation where one manufacturer sells its products either directly in one market (Market 1) or through its authorized distributor (Market 2), due to different products prices in both markets, results have shown that, when market elasticity is less than its critical value, a speculator can sell a gray market product arbitrage in market 2, whereas when the market elasticity is greater than its critical value, a speculator can sell a gray market product arbitrage in market 1. In addition, manufacturers—as leaders of Stackelberg game—are always the most profitable stakeholders within a gray market supply chain.Practical implicationsIn this study, equilibrium results for each market have been obtained, optimal results have been compared, and accordingly, valuable insights have been developed. Such results would help managers to take better managerial decisions, as well as strategizing policies in gray markets.Originality/valueIn this paper, we have considered a gray market where both distributors and speculators exist and act as parallel channels. To the best of our knowledge, the extant literature focuses either on distributors or speculators, but never concurrently on both. In fact, the coexistence of one distributor and one speculator in a gray market will impact their own decisions, as well as both decisions and profits of other stakeholders, and hence, will exert an impact on the manufacturer side.

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Effects of IoT technology on gray market: An analysis based on traceability system design

Cited by 18 publications

References 45 publications

The evolution of the Internet of Things (IoT) over the past 20 years

The evolution of the Internet of Things (IoT) over the past 20 years

Product diversion by vertically differentiated firms

Arbitrage in gray markets and its impact on supply chain decisions

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