Dynamic pricing and green investment in the construction supply chain with incentive and consumer reference price

Purpose The paper aims to focus on the green building industry, investigating pricing and green investment decisions of the construction supply chain under static and/or dynamic models and explore the incentive effects of different models. Design/methodology/approach The construction industry is a major greenhouse gas emitter and is compelled to reduce carbon emissions. This can only be achieved through further investment in “green technologies,” which come at great expense. Consumers, on the other hand, remain price sensitive, benchmarking purchase decisions on market “reference price.” Enterprises must adopt agile pricing strategies to accommodate changing market demands. Based on Stackelberg game theory, this paper introduces consumer reference price and incentive mechanisms into the construction supply chain and investigates both developers’ pricing and contractors’ green building investment strategies. The authors develop three models: (1) a static pricing model with incentives, (2) a static pricing model with incentives and consumer reference price and (3) a dynamic pricing model with incentives and consumer reference price. Findings The results show that under an incentive mechanism, the optimal green building rating and the optimal profits of developer and contractor all improve. Moreover, the developer can extract higher profits by adopting dynamic pricing over an extended period. The nature of the optimal dynamic pricing strategy, however, is contingent on the magnitude of the initial reference price. The results also show that contractors can reduce costs by improving the efficiency of their green building investment. Similarly, developers who partner with contractors with above-par green building investment efficiency can also expect to increase their own profitability. Originality/value The proposed approach can well analyze pricing and green investment decisions between the developer and the contractor with respect to static and dynamic situations. The analysis and results can inform decision-making for developers and contractors.