Tao Li

Prof. Tao Li

Business School, Shandong University of Technology, Zibo, Shandong, China

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2019 in Journal of Cleaner Production
Verified
Journal Article
Closed access
TLTao Li
Tao Li
RZRong Zhang
Rong Zhang
SZSenlin Zhao
Senlin Zhao
BLBin Liu
Bin Liu

16 May 2017 in Sustainability
Verified
Journal Article
Open access
PDF file
BLBin Liu
Bin Liu
TLTao Li
Tao Li
Sang-Bing TsaiSang-Bing Tsai
Sang-Bing Tsai
This paper investigates the emission reduction performance for supply chain members in both single-channel and exclusive dual-channel cases. Two game scenarios (Manufacturer Stackelberg and Retailer Stackelberg) are examined under different channel structures. Furthermore, we introduce government subsidies as an impact factor of low-carbon strategy adoption. In the single-channel (Case 1), we mainly examine the influence of consumers’ price-sensitivity on channel members’ optimal decisions. In the dual-channel (Case 2), we focus on the joint impact of product substitutability and different channel power structures on the optimal decisions under asymmetric related channel status. The analysis suggests that the Stackelberg leaders always perform better than their corresponding followers before emission reduction, while they may not necessarily yield more benefits after emission reduction. The implementation of low-carbon strategy depends on parameters like product substitutability and channel base demand. Finally, all the supply chain members will encounter a Prisoner’s Dilemma when the product substitutability is relatively high.

1 November 2018 in Computers & Industrial Engineering
Verified
Journal Article
Closed access
TLTao Li
Tao Li
RZRong Zhang
Rong Zhang
BLBin Liu
Bin Liu

10 February 2023 in Sustainability
Verified
Journal Article
Open access
PDF file
TLTao Li
Tao Li
XXXiaotong Xu
Xiaotong Xu
WLWeirong Liu
Weirong Liu
CSChengdong Shi
Chengdong Shi
The traceability of blockchain is crucial to the quality and safety of agricultural products, primarily when bacterial contamination occurs in the agricultural supply chain. To gain a deeper understanding of the impacts on the quality and safety of agricultural products, we built a three-level agricultural supply chain model comprising one retailer, one manufacturer, and one supplier. We aimed to explore the impact of blockchain traceability and retailers’ altruistic preference on pricing decisions and channel member profit, and to then examine the motivation of enterprises to participate in blockchain technology. Our study showed that: (1) blockchain technology has the potential to improve the prices and profits of supply chain members without considering the cost of blockchain; and (2) blockchain technology has the potential to improve the retailer’s price when the unit variable cost of blockchain is higher than a certain threshold. It can also reduce the manufacturer’s price and the supplier’s output. However, the excessive cost of blockchain can also aggravate the double marginalization effect of the supply chain. When both the unit variable cost and the fixed input cost of the blockchain are low, each enterprise has the incentive to participate in the blockchain. (3) In the scenario of the altruistically-preferred retailer, when the blockchain variable cost is lower than a certain threshold, the retailer’s altruistic preferences can improve the manufacturer’s and supplier’s profit, but it will reduce the retailer’s profit.
1

10 October 2024 in Kybernetes
Verified
Journal Article
Closed access
XYXiaoxue Yu
Xiaoxue Yu
TLTao Li
Tao Li
QTQi Tan
Qi Tan
BLBin Liu
Bin Liu
HLHui Li
Hui Li
Purpose: Driven by the rapid expansion of online retail and the surge in livestream commerce, the impact of different livestream mode on brand and platform performance has become a critical issue. This paper analyzes the impact of artificial intelligence (AI) and key opinion leader (KOL) livestream on the profitability of brands and the platform, incorporating the effects of horizontal interactions to identify the optimal livestream mode. Design/methodology/approach: This paper develops a model of a platform supply chain involving two brands and a platform, where each brand independently decides whether to utilize KOL or AI livestream. Applying Stackelberg game approach, the study derives equilibria for various livestream scenarios, identifying the optimal livestream mode for both parties. Additionally, the model is extended to incorporate asymmetric market potential and network externality to evaluate their impact on a brand’s choice of livestream mode. Findings: Several interesting and important results are derived in this paper. Firstly, it is found that AI livestream enables brands to leverage network externality and mitigate the market disadvantage, thereby gaining a competitive advantage. Secondly, while KOL livestream promotes trust, the medium KOL commission rates could cause brands to be trapped in a prisoner’s dilemma, and excessively high commission rates may render them less profitable. Thirdly, the KOL commission rate, network externality intensity, horizontal interactions and market disadvantage are critical determinants influencing a brand’s choice of livestream mode. Originality/value: This study is the first to investigate the effects of horizontal interactions, asymmetric market potential and asymmetric network externality on livestream mode selection by brands within a platform supply chain. The research provides valuable insights into optimizing livestream strategies to enhance brand profitability.

21 May 2025 in Systems
Verified
Journal Article
Open access
PDF file
TLTao Li
Tao Li
Shanping 徐善萍 XuShanping 徐善萍 Xu
Shanping 徐善萍 Xu
QTQi Tan
Qi Tan
WTWenbo Teng
Wenbo Teng
As digital platforms reshape the commercial landscape, brands increasingly collaborate with these platforms to enhance product sales. Many adopt livestream as a strategic tool to attract more traffic, typically choosing between Artificial Intelligence (AI) or Key Opinion Leader (KOL) approaches. Meanwhile, platforms operate under either an agency or a resale mode. However, the relative effectiveness of these strategies remains unclear. This study investigates an e-commerce supply chain comprising a single brand and platform, examining how AI and KOL livestream influence supply chain decisions across different sales modes and identifying optimal strategies for the brand and platform. Results show that when the platform’s revenue sharing rate is low, the agency mode consistently yields a Pareto improvement over resale, regardless of the livestream scheme. Moreover, when the KOL promotion fee rate is low, KOL livestream outperforms AI livestream under both sales modes. When the revenue sharing rate is high, the brand’s optimal strategy is “resale mode and KOL livestream”, while the platform prefers “agency mode and KOL livestream”. Conversely, when the revenue sharing rate is low, the platform’s best strategy is “resale mode and KOL livestream”, while the brand favors the agency mode, with livestream preferences shaped by KOL promotion fee rate.