A competitive pharmaceutical supply chain under the marketing mix strategies and product life cycle with a fuzzy stochastic demand

Shakouhi, Farzaneh; Tavakkoli–Moghaddam, Reza; Baboli, Armand; Bozorgi-Amiri, Ali

doi:10.1007/s10479-021-04073-5

Cited by 12 publications

(7 citation statements)

References 40 publications

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“…2021) [7]. Taking targeted supervision measures and setting up a reasonable government reward and punishment mechanism (Zhu LL, et al 2021[8]; Ozawa S, et al 2022 [9]) can urge the main participants of the pharmaceutical supply chain to ensure the level of investment in drug quality and help improve drug quality and safety (Lu BJ, et al 2022) [10].…”

Section: Drug Quality Supervisionmentioning

confidence: 99%

Drug Quality Supervision Strategy Analysis under Government Rewards and Punishments: What Role does Patient Feedback Play？

Zhang,

Zhu

2023

Preprint

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In recent years, the frequent occurrence of drug quality and safety incidents, which seriously affect economic development, social stability and public’s health, has always been one of the hot issues that are widely concerned by all over the world. Therefore, this paper constructs a differential game model of drug quality supervision, analyses the influence of government and patients’ interaction mediated by co-regulation information platform on drug quality investment decision-making of pharmaceutical enterprises and retailers, and discusses the decision-making outcomes of pharmaceutical enterprises and retailers under government rewards and punishments. Backward Induction Method is used to solve the model, and Matlab 2021b is used for simulation analysis. The results show that, firstly, when patients give positive feedback, the reward strength of government and the quality perceived utility of patients jointly determine the external positive utility of pharmaceutical enterprises and retailers. Secondly, when patients give negative feedback, the supervision effect of punishment is affected by the market demand for the drug. Furthermore, government rewards and punishments will affect the drug’s wholesale and retail price. The decision-making of pharmaceutical enterprises is affected by the government rewards and punishments for retailers; at the same time, the retailers’ decision-making is also affected by the government rewards and punishments for pharmaceutical enterprises. Finally, this paper enriches and expands the theoretical basis of drug quality supervision, and put forwards countermeasures and suggestions for how to optimize the decision-making of the main subjects of the pharmaceutical supply chain.

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Section: Drug Quality Supervisionmentioning

confidence: 99%

Drug Quality Supervision Strategy Analysis under Government Rewards and Punishments: What Role does Patient Feedback Play？

Zhang,

Zhu

2023

Preprint

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“…The pharmaceutical supply chain is complex, and there are many drugs quality risk nodes ( 2 ), and there are problems such as non-standard drugs production testing and imperfect supervision mechanisms, which have become a research hotspot. Provide a competitive pharmaceutical supply chain under the product life cycle ( 3 ), supervise activities in the supply chain ( 4 ), and avoid monopoly ( 5 ) and collusion ( 6 ) among pharmaceutical supply chain entities, so as to better provide pharmaceutical retail services. Pharmaceutical products are perishable and improving the reliability, safety, and efficiency of the supply chain is the goal of the development and research of the pharmaceutical supply chain ( 7 ).…”

Section: Relevant Literaturementioning

confidence: 99%

Drugs quality supervision strategy of different distribution channels in pharmaceutical supply chain

Zhang

Zhu

2022

Front. Public Health

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Aiming at the dual-channel pharmaceutical supply chain, which consists of two distribution channels, offline medical institutions, and online e-commerce platforms, and taking into account the impact of different strategic choices made by relevant stakeholders on the drugs quality of different distribution channels, this article constructs an evolutionary game model involving the participation of government regulator, pharmaceutical enterprises, medical institutions, and pharmaceutical e-commerce companies. The stable equilibrium points of each participant's strategic choices are solved; the stability of strategic combination is analyzed by Lyapunov's first method, and MATLAB 2020b is used for simulation to verify the influence of each decision variable on the strategic choice of different participants. The results show that, first, the purpose of punishment is to ensure the drugs quality in the pharmaceutical supply chain, but when the fine is too high, it will restrain the economic behavior of pharmaceutical enterprises, which is not conducive to the performance of social responsibilities by other relevant participants. Second, the probability that government regulator strictly supervises the pharmaceutical supply chain and the probability that pharmaceutical enterprises provide high-quality drugs are negatively related to their additional cost. Third, whether medical institutions and pharmaceutical e-commerce companies choose inspection is affected by multiple factors such as inspection cost, sales price, and sales cost. Furthermore, when the penalty for non-inspection of pharmaceutical e-commerce companies is greater than the threshold Fm0, it can ensure that it chooses an inspection strategy. Finally, this article puts forward countermeasures and suggestions on the drugs quality supervision of different distribution channels in the pharmaceutical supply chain.

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“…Cai et al [ 19 ] studied the price and warranty competition between two risk-averse retailers by assuming that the retailers’ risk-aversion levels are private information. Shalouhi et al [ 20 ] studied Nash and Stackelberg models of competition problems in two pharmaceutical supply chains in which both exclusive retailer and manufacturer are included. Sazvar et al [ 21 ] developed a scenario-based multi-objective programming model to design a sustainable closed-loop pharmaceutical supply chain, which simultaneously considers competitive market and demand uncertainties.…”

Section: Literature Reviewmentioning

confidence: 99%

“…According to the result of Eq (20) and the non-increment of x k i , we propose the iterative algorithm for solving the (GCKP) as follows:…”

Section: Ranking-based Imbedding Algorithmmentioning

confidence: 99%

Robust competitive facility location model with uncertain demand types

2022

PLoS ONE

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In competitive settings, firms locate their facilities according to customers’ behavior to maximize their market share. A common behavior is consuming from different motivations: one is for convenient demand, and the other is for quality demand. In this behavioral pattern, consumers patronize facilities within convenience for some demands, and patronize high quality facilities beyond convenience range for other demands. This behavior has never been included in competitive facility location problems. Given several other companies’ facilities in the market offering similar products or services, we study how a new entrant company can locate facilities based on this customer behavior to maximize its market share. A two-level robust model for the new entrant company is proposed to locate its facilities by taking into account the uncertainty of the types of customers’ demands. For medium size problems, we propose an equivalent mixed binary linear programming to obtain exact solutions. For large size problems, an exact algorithm (GCKP-A) for solving the inner-level model is given first by exploring the optimal solution. Then a heuristic algorithm is proposed by imbedding (GCKP-A) and 2-opt strategy into the framework of the improved ranking-based algorithm. The performance of the proposed heuristic algorithm is checked for different size problems. The sensitivity analysis of a quasi-real example shows that: (1) in most cases, the uncertainty between two types of demands does not affect the location scheme; (2) the convenience range, the quality range and the quality threshold play an important role in the market share of the new entrant company.

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A competitive pharmaceutical supply chain under the marketing mix strategies and product life cycle with a fuzzy stochastic demand

Cited by 12 publications

References 40 publications

Drug Quality Supervision Strategy Analysis under Government Rewards and Punishments: What Role does Patient Feedback Play？

Drug Quality Supervision Strategy Analysis under Government Rewards and Punishments: What Role does Patient Feedback Play？

Drugs quality supervision strategy of different distribution channels in pharmaceutical supply chain

Robust competitive facility location model with uncertain demand types

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