Complementary Product Pricing and Service Cooperation Strategy in a Dual-Channel Supply Chain

Ren, Minglun; Liu, Jiqiong; Feng, Shuai; Yang, Anli; Borondo, F.

doi:10.1155/2020/2314659

Cited by 6 publications

(4 citation statements)

References 63 publications

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“…Wei et al (2013) consider five different market power structures to explore the pricing problem in two usabilitycomplementary manufacturers and a common retailer. Ren et al (2020) study how different market power structures influence price and service decisions in a dual-channel supply chain composed of two usability-complementary manufacturers and one retailer. The results show that the retailer benefits the most when the two manufacturers are on equal footing.…”

Section: Strategy Choice: Acquisition or Investmentmentioning

confidence: 99%

“…Li and Chen (2020a) consider that a manufacturer assembles n components from n suppliers into final products. However, the type of complementary products is not clear enough (Leng and Parlar, 2010; Ren et al. , 2020; Yue et al.…”

Section: Introductionmentioning

confidence: 99%

“…Usability-complementary products are independent and complete but need to be used together to show their values. Examples include toothbrushes and toothpaste (Ren et al. , 2020), printers and cartridges (Jalali et al.…”

Section: Introductionmentioning

confidence: 99%

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Acquisition or investment: a manufacturer quality improvement strategic choice

Wang

Song

Huang

et al. 2023

TQM

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PurposeThis paper explores how the manufacturer’s strategic choice (acquisition or investment) impacts product quality in a supply chain comprising two complementary suppliers and a common manufacturer.Design/methodology/approachThe manufacturer faces six strategic choices to improve product quality: acquiring or investing in the high-capable supplier, the low-capable supplier, or both. As the Stackelberg leader, the manufacturer determines which strategy is adopted, while suppliers are separately responsible for components’ quality and wholesale prices. The authors use game theory and calculate the model with Mathematica.FindingsThe authors develop analytical models to analyze how acquisition costs, investment proportions, component importance and quality improvement coefficients influence decision-makers. The results show that the highest quality may not benefit the manufacturer. Investing in or acquiring a low-capable supplier is better than a high-capable supplier under certain conditions. If the gaps between two suppliers’ quality improvement coefficients and the importance of two components are dramatic, the manufacturer should choose an investment strategy.Originality/valueThis study contributes to the complementary supply chain management by comparing two kinds of strategies-acquisition and investment, with a high-capable supplier and a low-capable supplier.

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Section: Strategy Choice: Acquisition or Investmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Acquisition or investment: a manufacturer quality improvement strategic choice

Wang

Song

Huang

et al. 2023

TQM

View full text Add to dashboard Cite

show abstract

“…They use game theory and fuzzy theory to solve these models and compare the optimal pricing decisions and profits among these models. Ren et al [14] construct a dual-channel supply chain model with two manufacturers and one retailer and investigate the pricing and cooperation problem by considering complementary products. A third stream of literature on dual-channel supply chain management focuses on supply chain coordination.…”

Section: Literature Reviewmentioning

confidence: 99%

Pricing Decision of the Dual-Channel Supply Chain with the Manufacturer’s Extended Warranty

Zhu

Liang

Liu

2023

Systems

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With the rapid development of the internet economy, many manufacturers have opened online direct sales channels and built multi-channel distribution systems. Meanwhile, both consumers and companies are paying more attention to extended warranty services. Considering a dual-channel supply chain with a manufacturer and a retailer, we assume the manufacturer provides an extended warranty in the online direct channel and investigates the decision making of the supply chain players. We develop three game models to study this problem, and they are the basic model without extended warranty (Model B), the decentralized decision model with the manufacturer’s extended warranty (Model M), and the centralized decision model with the manufacturer’s extended warranty (Model C). The Stackelberg game method is used to solve the established model, the influence of relevant parameters on the solution result is analyzed, and different models are compared. Compared with Model B, we find that the whole supply chain always be better, but the retailer would be worse in Model M. Compared with Model M, we find that the entire supply chain always performs better in Model C. Finally, we do some sensitivity analysis.

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Product pricing solutions using hybrid machine learning algorithm

Namburu¹,

Selvaraj²,

Varsha³

2022

Innovations Syst Softw Eng

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E-commerce platforms have been around for over two decades now, and their popularity among buyers and sellers alike has been increasing. With the COVID-19 pandemic, there has been a boom in online shopping, with many sellers moving their businesses towards e-commerce platforms. Product pricing is quite difficult at this increased scale of online shopping, considering the number of products being sold online. For instance, the strong seasonal pricing trends in clothes—where Brand names seem to sway the prices heavily. Electronics, on the other hand, have product specification-based pricing, which keeps fluctuating. This work aims to help business owners price their products competitively based on similar products being sold on e-commerce platforms based on the reviews, statistical and categorical features. A hybrid algorithm X-NGBoost combining extreme gradient boost (XGBoost) with natural gradient boost (NGBoost) is proposed to predict the price. The proposed model is compared with the ensemble models like XGBoost, LightBoost and CatBoost. The proposed model outperforms the existing ensemble boosting algorithms.

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Complementary Product Pricing and Service Cooperation Strategy in a Dual-Channel Supply Chain

Cited by 6 publications

References 63 publications

Acquisition or investment: a manufacturer quality improvement strategic choice

Acquisition or investment: a manufacturer quality improvement strategic choice

Pricing Decision of the Dual-Channel Supply Chain with the Manufacturer’s Extended Warranty

Product pricing solutions using hybrid machine learning algorithm

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