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Pricing strategies of low-carbon enterprises in the Yellow River Basin considering demand information and traceability services

Pan Liu (Henan Agricultural University, Zhengzhou, China)
Xiaoyan Cui (Henan Agricultural University, Zhengzhou, China)
Ziran Zhang (Henan Agricultural University, Zhengzhou, China)
Wenwen Zhou (Beijing University of Technology, Beijing, China)
Yue Long (Chongqing Technology and Business University, Chongqing, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 9 November 2021

Issue publication date: 17 January 2023

136

Abstract

Purpose

The purpose of this paper is to solve new pricing issues faced by low-carbon companies in the Yellow River Basin, which is caused by the change of key pricing factors in the mixed appliance background of Big Data and blockchain, such as product quality and carbon-emission reduction CER level (hereafter, CER level).

Design/methodology/approach

We choose a low-carbon supply chain with a low-carbon manufacturer and a retailer as our research object. Then, we propose that using the ineffective effect of the CER level and the quality and safety level to reflect the relationships among the CER level, the quality and safety level and the market demand is more suitable in the new environment. Based on these, we revise the demand equation. Afterwards, by using Stackelberg game, four cost-sharing situations and their pricing rules are analyzed.

Findings

Results indicated that in the four cost-sharing situations, the change trends and the magnitudes of the best retail prices were not affected by the changes of the inputs of the demand information and the traceability services costs (hereafter, DITS costs), the proportion about retailer's DITS costs undertaken by the manufacturer, the ineffective effect coefficient of the CER level and the quality and safety level and the cost optimization coefficient. However, the cost-sharing situations could affect the change magnitudes of the best revenues.

Originality/value

This paper has two main contributions. First, this paper proposes a demand function that is more suitable for the mixed appliance background of Big Data and blockchain. Secondly, this paper improves the cost-sharing model and finds that demand information sharing and traceability service sharing have different impacts on key pricing factors of low-carbon product. In addition, this research provides a theoretical reference for low-carbon supply chain members to formulate pricing strategies in the new background.

Keywords

Acknowledgements

The authors would like to thank the following research grants: Key R&D and Promotion Projects in Henan, China (Soft Science) (No. 212400410307), Key scientific research projects of higher education institutions in Henan, China (No. 21A630016), Top Talent Project of Henan Agricultural University (No. 30500681) and Creator Talent Support Plan of Henan Agricultural University (No. 30200757). Research project on Chongqing’s Social Science Planning (2020ZDSC07, 2020ZDGL07), and Research Project on Teaching Reform of Postgraduate Education in Chongqing (yjg193102), and Research Project on Joint Graduate Training Base in Chongqing (yjd193006) and Research Project on Quality Courses for Postgraduate Education in Chongqing (yyk193008).

Conflict of interest: The authors declare that there is no conflict interest.

Citation

Liu, P., Cui, X., Zhang, Z., Zhou, W. and Long, Y. (2023), "Pricing strategies of low-carbon enterprises in the Yellow River Basin considering demand information and traceability services", Kybernetes, Vol. 52 No. 1, pp. 304-327. https://doi.org/10.1108/K-06-2021-0529

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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