Search Results (35)

In recent years, scientific and technological development has made trade-in programs for innovative electronic products more and more popular. Many of these innovative companies that continue to launch new products offer trade-in and cash-out sales strategies to stimulate purchase. This paper studies when a company launches these two sales strategies and how to ensure optimal pricing that maximizes profits, while taking into account the degree of the consumer’s strategy, the degree of the new product’s innovation, the residual value of the old products, and the cost. We construct a two-period dynamic pricing joint optimization model with four core decision variables and derive the closed-form optimal solution through strict mathematical derivation including Hessian matrix analysis and KKT condition verification. We have adopted a dynamic pricing strategy that conforms to the actual market. The results show that this study provides new mathematical insights for dynamic pricing research, and reveals the substantive rule that companies are more likely to gain greater benefits when the degree of product innovation is not high and the consumer’s strategy degree is moderate. Statistics show that companies are more likely to gain greater benefits when the degree of product innovation is not high and the consumer’s strategy degree is moderate. Full article

As an effective approach to boosting consumption and facilitating the recycling of consumer goods, trade-in programs have been widely adopted by branders and e-commerce platforms. A platform supply chain system comprising e-commerce platforms and branders is investigated in this paper for this purpose. We construct a two-stage dynamic game model encompassing eight scenarios, discussing the provision of trade-in programs and product recycling issues under the resale and agency selling modes. Below are the key findings: (1) Trade-In Programs: In the resale mode, both branders and platforms prefer to adopt self-recycling when market potential is large, while opting for recycling undertaken by the other party when market potential is small. In the agency selling mode, branders prefer to adopt self-recycling (B-II) when fixed costs are high and the salvage value of used products is high, while platforms choose platform-led recycling (P-II) when fixed costs are low and the salvage value of used products is high. (2) Product Recycling: In the resale mode, branders should opt for self-recycling when facing high fixed costs, small market potential, and high salvage values, while outsourcing is more appropriate when salvage values are low. When the market potential is low, the platform ought to prefer self-recycling if the salvage value is either sufficiently high or sufficiently low; otherwise, outsourcing is preferable. In the agency selling mode, when the salvage value of used products is relatively high, platforms tend to have a free-riding mentality. When platforms provide trade-in programs, they will prioritize self-recycling if the salvage value is higher. In contrast, branders consistently achieve maximum profits when platforms adopt self-recycling. (3) Selection of Selling Mode: Branders always prefer the agency selling mode, while platforms’ mode selection depends on the trade-off between salvage value and commission rate. This study provides strategic insights for platform-based supply chain decisions. Full article

This study investigates trade-in channel selection in a closed-loop supply chain under a hybrid carbon policy framework that integrates cap-and-trade and carbon taxation. Game-theoretic models are developed for three manufacturer-led channels: manufacturer trade-in (M-CX), retailer trade-in (R-CX), and third-party trade-in (T-CX). The analysis examines pricing strategies, profitability, and carbon emission reductions across these channels. The key findings are as follows: (1) Carbon tax consistently compresses manufacturer profits, whereas cap-and-trade mechanisms exhibit a non-linear U-shaped effect. Manufacturer profits remain highest under the M-CX channel, irrespective of policy intensity. (2) Retail prices are most sensitive to carbon policies under the T-CX channel, where trade-in rebates increase with carbon intensity. The R-CX channel sustains higher retail prices and rebates than M-CX, while T-CX surpasses both under conditions of high carbon intensity. (3) Carbon emission reductions decline sharply under M-CX and R-CX as policy stringency increases. In contrast, the T-CX channel establishes a buffering mechanism through rising rebates, exhibiting the slowest rate of decline. At low carbon intensity, T-CX yields the lowest reduction levels; however, under high intensity, it overtakes the other channels to achieve the highest reduction. This study offers insights for manufacturers’ channel selection and government policy coordination under hybrid carbon regulation regimes. Full article

The trade-in service can enhance product sales and increase consumer loyalty; however, heterogeneity in consumer quality preferences significantly influences the provision and implementation of trade-in activities. By constructing a dynamic dual-supply chain model, this study examines the optimal choices for trade-in providers and the impact of consumer quality preferences on mode selection. The findings indicate that the decision of who should provide the trade-in service largely depends on the product’s quality decay rate. When the quality decay rate is low, collaboration between the manufacturer and the retail platform favors manufacturer-led trade-in service. Conversely, when the quality decay rate is high, both parties tend to fall into a prisoner’s dilemma, each preferring to dominate the trade-in process independently. Notably, as the share of pragmatic consumers increases, both sides of the supply chain are more inclined to prefer the manufacturer offering trade-in service. In our extended research, we found that the influence of government subsidies on mode selection primarily depends on the price discounts provided by the dominant party in trade-in arrangements within each mode. We also considered scenarios with asymmetric net residual values of recovered products, and the results robustly validate the stability of our core findings. Full article

In the durable goods industry, trade-in programs have assumed a pivotal role, yet the fundamental principles governing firms’ choices of trade-in models under market segmentation remain underexplored. This study introduces a loyalty-driven market segmentation framework, categorizing consumers into replacement groups (loyal consumers and indifferent consumers) and new consumers. By constructing an optimization model for a monopolistic firm, we analyze three trade-in models, trade-in for new, trade-in for cash, and hybrid trade-in, examining pricing, rebate, model selection strategies, and consumer surplus. The research reveals that the firm offers the most generous rebates under the trade-in for new model when the proportion of loyal consumers is extremely low. As this proportion increases, the hybrid trade-in model provides higher rebate intensity. When the proportion of loyal consumers is extremely high, the rebate intensity under the trade-in for cash model exceeds that of the other two models. The choice of trade-in model hinges on the threshold proportion of loyal consumers and replacement consumers: in high-loyalty markets, hybrid trade-in model achieves optimal performance. Conversely, in low-loyalty markets, trade-in for cash model prevails when the proportion of replacement consumers exceeds a specific threshold. Trade-in for new model becomes preferable when the proportion of replacement consumers is low. Hybrid trade-in model consistently maximizes the consumer surplus of indifferent consumers due to its flexibility, while loyal consumers benefit more from the trade-in for new model when their market share is dominant. Full article

Trade-in programs have become a vital mechanism for promoting sustainable consumption and reducing negative impacts on the environment, gaining substantial support from branders, e-platforms, and consumers in recent years. Concurrently, the emergence of professional recyclers has provided firms with viable alternatives for the outsourcing of recycling processes. To investigate the optimal leadership and recycling model with respect to trade-in operations, this study examines the strategy selection in a platform-based supply chain under a resale model. A two-period game-theoretic framework is developed, encompassing four models: self-recycling and outsourcing models under the leadership of the brander or platform. The main findings are as follows: (1) In markets characterized by a low consumer price sensitivity, both branders and platforms tend to choose the self-recycling model to capture the closed-loop value. In contrast, in highly price-sensitive markets, both parties exhibit a preference for “free-riding” strategies. (2) Once the recycling leader is determined, adopting a self-recycling model can lead to a relative win–win outcome in high price sensitivity contexts. (3) With a short product iteration cycle, both the brander and platform should strategically lower their prices in the first period, sacrificing short-term profits to enhance trade-in incentives and maximize long-term gains. (4) When the brander leads the recycling process, they should consider reusing the resources derived from old products; however, in platform-led models, the brander can only consider reusing the recycled resources in a low price sensitivity market. This study provides strategic insights for the sustainable development of the supply chain through the analysis of a game between a brander and an e-commerce platform, enriching the literature on CLSCs through integrating trade-in leadership selection and the choice to outsource, offering theoretical support for dynamic pricing strategies over multi-period product lifecycles. Full article

In the context of increasing environmental awareness and resource scarcity, trade-in and remanufacturing have emerged as important strategies for sustainable product management. This study constructs decision-making models for a monopolistic manufacturer operating in a two-period market. The manufacturer produces new products in Period 1, recycles used products via trade-in for remanufacturing, and sells both new and remanufactured products in Period 2. Depending on whether the remanufactured product price is pre-committed, two models (no price commitment and price commitment) are established. The model optimization reveals that, regardless of the price commitment, four recycling and remanufacturing strategies emerge when the manufacturer engages in remanufacturing. The choice of strategy is jointly influenced by the unit residual value of the used product ($s$) and the unit cost of the remanufactured one ($c_r$). The theoretical findings for a special case ($c_r=s=0$) demonstrate that pre-committing the price of remanufactured products compels the manufacturer to simultaneously lower the price of new products and reduce trade-in subsidy while elevating the remanufactured product price. This pricing realignment reduces combined sales volumes across both periods, ultimately diminishing the total profit over two periods. Moreover, price commitment does not boost the remanufacturing rate. This study provides theoretical guidance and managerial insights for manufacturers in terms of pricing strategies and the reuse of used products. Full article

Jiangsu province’s forestry industry offers valuable insights for resource-poor regions in China. This study aims to determine the competitiveness of different forestry sectors in Jiangsu province and identify the industrial structural changes in this context. The shift-share method is employed to analyze the primary, secondary, and tertiary forestry industries, encompassing 17 sub-sectors, and investigate the industrial regional types. By combining location quotient values and inter-sector characteristics, the leading sectors are identified. The findings reveal that the Kuznets facts and the Engel effect in the industry structure have facilitated the process of increasing the value of ecological products; this is particularly evident between 2002 and 2018, as well as in 2021. Within the primary forestry industry, the Flower cultivation sector and the Economic forest product sector emerge as the leading sectors, outperforming the national growth effect by 7.18 and 1.02 times, respectively. In the secondary forestry industry, the Wood processing sector, the Furniture manufacturing sector, the Wood paper-making sector, and the Non-timber forest product sector mostly show the Progressive types as the leading sectors from 2006 to 2020. The tertiary industry’s regional types fluctuate from the Progressive type to the Medium type, with the Forestry tourism sector, the Ecological service sector, and the Non-forestry service sector displaying leading industry characteristics. Recommendations for enhancing inter-sector integration include fostering collaborative agglomeration, unlocking the potential value of wetland resources, and strengthening cross-industry integration through e-commerce clusters to improve the forester’s e-commerce operational capabilities. Full article

As the consumer market becomes more saturated, the e-commerce supply chain (E-SC) has introduced the trade-in program in an attempt to drive consumption. This paper considers the strategy of the E-SC to provide cash rebates for consumers participating in the trade-in program and incorporates the e-commerce platform’s trade-in service efforts into the E-SC’s decision-making system. Depending on who provides the cash rebate, we construct four decision-making models of the E-SC, i.e., the no-cash-rebate model, the manufacturer model, the platform model, and the cooperative model, where both the manufacturer and the platform jointly provide the cash rebate. We show that the platform model reduces the trade-in service level, but the manufacturer model increases the trade-in service level. In addition, since the cash rebate increases operation costs, the sale price of products is inevitably improved. Furthermore, the platform model raises product demand, but the manufacturer model lowers product demand. The cooperative model proves effective in enhancing demand only when the manufacturer contributes a minor share of the cash rebate and the trade-in service is less efficient. Cash rebates can increase the E-SC’s profits, but the degree of this increase becomes smaller as the cash rebates increase. The manufacturer and the platform always want to exploit each other’s cash rebate strategies. Consumer surplus and social welfare are highest in the platform model and lowest in the manufacturer model. Taking into account the profits, consumer surplus, and social welfare, the platform model is the most conducive to E-SC system operations. Full article

The enhancement of seed germination by using nanoparticles (NPs) holds the potential to elicit the synthesis of more desired compounds with important biomedical applications, such as preventing protein glycation, which occurs in diabetes. Here, we used 7 nm and 100 nm ZnO and 4.5 nm and 16.7 nm Fe₂O₃ NPs to treat sunflower seeds. We evaluated the effects on germination, total phenolic content, and the anti-glycation potential of extracted polyphenols. Sunflower seeds were allowed to germinate in vitro after soaking in NP solutions of different concentrations. Polyphenols were extracted, dosed, and used in serum albumin glycation experiments. The germination speed of seeds was significantly increased by the 100 nm ZnO NPs and significantly decreased by the 4.5 nm Fe₂O₃ NPs. The total phenolic content (TPC) of seeds was influenced by the type of NP, as ZnO NPs enhanced TPC, and the size of the NPs, as smaller NPs led to improved parameters. The polyphenols extracted from seeds inhibited protein glycation, especially those extracted from seeds treated with 7 nm ZnO. The usage of NPs impacted the germination speed and total polyphenol content of sunflower seeds, highlighting the importance of NP type and size in the germination process. Full article

This paper delves into optimizing the rotation of relief supplies within the relief supply chain system, concentrating on reserve quantity decisions for governments and humanitarian organizations involved in disaster response. By integrating a trade-in strategy with suppliers, it ensures a precise and timely response to the fluctuating demand for relief supplies post-disaster. Utilizing the newsvendor model, optimization theory, and supply chain coordination principles, we developed a comprehensive model that calculates optimal reserve quantities for pre-positioning demanders. It also outlines the expected profit function for suppliers and a robust supply chain coordination model. The findings highlight that optimal stockpiling decisions for relief supplies are heavily influenced by cost parameters, material characteristics, and the relationship between trade-in pricing and market resale values. Notably, higher trade-in prices generally reduce the government’s optimal reserve quantities, impacting strategic decisions within supply chain coordination. This research adds to disaster management literature by offering strategic insights into how coordination and pricing strategies can improve disaster preparedness and response efficiency and effectiveness. Full article

Under extended producer responsibility (EPR) regulations, trade-in programs allow manufacturers to play a vital role in recycling. Simultaneously, third-party recyclers (TPRs) can use their recycling network to compensate for manufacturers having only a single recycling channel, which increases the competition between them. To study whether companies should authorize TPRs, we constructed and analyzed a Stackelberg game model with trade-in programs under EPR regulations by focusing on three different closed-loop supply chain (CLSC) structures and differentiating consumer categories. The analytical results showed that when the government does not act as the decision maker, the optimal product selling price of the manufacturer does not change under each strategy. Otherwise, the manufacturer’s decision is affected by the cost structure and amount of subsidy, as well as funds determined by the government under the optimal environmental benefit. Furthermore, when the residual value coefficient of the used products is high, manufacturers authorize TPRs to recycle used products. Full article

With the rapid development of electric vehicles (EVs), many EV batteries have entered the retirement stage, leading to increasing concerns about the impact of resource recycling and environmental sustainability. Some countries have successfully applied reward–penalty and deposit–refund mechanisms in similar fields, such as lead-acid and waste portable batteries. However, whether these mechanisms are conducive to collecting waste EV batteries is unclear. This study aims to comprehensively analyze the influence of reward–penalty and deposit–refund mechanisms in EV battery collection by developing a Stackelberg game theoretical model. In the model, the recycling enterprise is the leader and the EV manufacturer is the follower. Furthermore, the total social welfare is used as the indicator to select the optimal incentive mechanisms. The results show that (1) both mechanisms could improve collection rates and recycling enterprises’ profits, though the collection rate is lower under the reward–penalty mechanism than the deposit–refund mechanism unless the reward/penalty coefficient takes a very high value. (2) Regardless of government focus on increasing the sales volume of new EV batteries, collection rates, or social welfare, the boundary conditions of the choice of the two mechanisms are obtained. Additionally, the boundary conditions are related to the trade-in discount and refund coefficient. (3) Under the deposit–refund mechanism, even if the refund coefficient is less than 1, the mechanism may still lead to a higher collection rate than the reward–penalty mechanism. Full article

In the context of developing the digital platform economy, trade-in programs have become an effective strategy for e-commerce platforms to stimulate consumption. Many head e-commerce platforms have launched their own trade-in programs. However, the existing research on trade-in programs is still stuck in the traditional trade-in model. The purpose of this study is to explore whether there is a new and more beneficial trade-in program. In this paper, we construct the Stackelberg game model between a brand owner and a B2C e-commerce platform under two trade-in programs and use optimization theory to obtain the equilibrium results of the model. The results indicate that the performance improvement of the new-generation product will promote the increase in two-generation products’ price under traditional trade-in programs, the price of the new-generation product will increase, and the price of the previous-generation product will decrease under new trade-in programs. The brand owner always prefers traditional trade-in to new trade-in. However, the e-commerce platform prefers traditional trade-in to new trade-in just when the previous-generation product is durable enough and the performance improvement of a new-generation product is small enough; otherwise, it prefers new trade-in to traditional trade-in. These findings are beneficial to the operational practices of e-commerce platforms and brand owners. Full article

Mass timber products are growing in popularity as a substitute for steel and concrete, reducing embodied carbon in the built environment. This trend has raised questions about the sustainability of the U.S. timber supply. Our research addresses concerns that rising demand for mass timber products may result in unsustainable levels of harvesting in coniferous forests in the United States. Using U.S. Department of Agriculture U.S. Forest Service Forest Inventory and Analysis (FIA) data, incremental U.S. softwood (coniferous) timber harvests were projected to supply a high-volume estimate of mass timber and dimensional lumber consumption in 2035. Growth in reserve forests and riparian zones was excluded, and low confidence intervals were used for timber growth estimates, compared with high confidence intervals for harvest and consumption estimates. Results were considered for the U.S. in total and by three geographic regions (North, South, and West). In total, forest inventory growth in America exceeds timber harvests including incremental mass timber volumes. Even the most optimistic projections of mass timber growth will not exceed the lowest expected annual increases in the nation’s harvestable coniferous timber inventory. Full article