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“慧学（114）：精读复刻论文《数智驱动营销下企业网络平台供应链的绿色产品营销策略研究》协调性分析（2）”。
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Dear, this is the LearningYard Academy!
Today, the editor brings the
“Hui Xue (114): Intensive reading of the replicated article ‘Research on Green Product Marketing Strategy of Enterprise Network Platform Supply Chain under Data-driven Marketing’ coordination analysis (2)”.
Welcome to visit!
本期推文小编将从思维导图、精读内容、知识补充三个方面为大家介绍期刊论文《数智驱动营销下企业网络平台供应链的绿色产品营销策略研究》的协调性分析（2）。
In this issue, the editor will introduce the coordination analysis (2) of the journal article “Research on Green Product Marketing Strategy of Enterprise Network Platform Supply Chain under Data-driven Marketing” from three aspects: mind mapping, intensive reading content, and knowledge supplement.
一、思维导图（Mind mapping）
二、精读内容（Intensive reading content）
1、提高需求敏感度参数的稳健性分析（Robustness analysis of improving demand sensitivity parameters）
为进一步检验模型结论在不同市场敏感度水平下的稳定性，构建数据集2：α = β = k = l = 0.75。相较数据集1，该组参数意味着消费者对绿色投入与营销努力的响应程度更高，市场放大效应更强。将数据集2代入各模式均衡表达式后发现，各利润函数依然满足存在内部最优解的条件，需求与利润均为正值，未出现异常波动或发散现象，表明模型在较高敏感度水平下仍然保持结构稳定性。
To further test the stability of the model's conclusions under different market sensitivity levels, dataset 2 was constructed: α = β = k = l = 0.75. Compared to dataset 1, this set of parameters indicates that consumers respond more strongly to green investments and marketing efforts, and the market amplification effect is stronger. Substituting dataset 2 into the equilibrium expressions of each model, it was found that each profit function still satisfies the condition of having an internal optimum, with both demand and profit being positive, and no abnormal fluctuations or divergence were observed, indicating that the model maintains structural stability at higher sensitivity levels.
2、基准模式与代售模式的方向一致性验证（Verification of the directional consistency between the benchmark model and the agency model）
在数据集2下，转售模式中平台零售价上升至1.28571，制造商利润上升至0.285714，整体利润水平明显提高，体现出需求敏感度增强带来的市场扩张效应。代售模式中，随着η增加，制造商利润依然呈下降趋势，而平台利润整体上升，变化方向与数据集1完全一致。这说明结论5关于佣金比例影响利润分配方向的结论并不依赖于特定参数水平，具有较强的稳健性。
In Dataset 2, the platform retail price in the resale model rises to 1.28571, and the manufacturer's profit rises to 0.285714, indicating a significant increase in overall profit levels and reflecting the market expansion effect brought about by increased demand sensitivity. In the consignment model, as η increases, the manufacturer's profit continues to decline, while the platform's profit increases overall, with the direction of change completely consistent with Dataset 1. This demonstrates that Conclusion 5 regarding the impact of commission rates on profit distribution direction does not depend on specific parameter levels and exhibits strong robustness.
3、成本共担机制的区间稳定性检验（Interval stability test of cost-sharing mechanism）
在RC与AC模式下，当θ提高时，制造商利润依然下降，而平台利润在一定区间内存在改善效应。即便在高敏感度参数水平下，利润函数仍然存在有效区间，未出现分母为零或负需求问题，说明结论6关于成本共担比例可行区间的理论结论具有参数稳健性。数值结果显示，无论在中等敏感度还是高敏感度市场环境下，成本共担机制均能在合理区间内改善平台收益结构，验证了模型推导的稳定性。
Under both RC and AC models, as θ increases, manufacturer profits still decrease, while platform profits show an improvement effect within a certain range. Even at high sensitivity parameter levels, the profit function still has an efficient range, without issues of zero denominator or negative demand, indicating that Conclusion 6 regarding the feasible range of cost-sharing ratios has parameter robustness. Numerical results show that, regardless of whether the market environment is moderately or highly sensitive, the cost-sharing mechanism can improve the platform's revenue structure within a reasonable range, verifying the stability of the model derivation.
三、知识补充（Knowledge supplementation）
1、稳健性分析（Robustness analysis）
稳健性分析是指在改变关键参数或市场环境设定的情况下，检验模型结论是否仍然成立的一种验证方法。其目的不是追求数值大小的一致，而是检验趋势方向是否稳定。如果核心结论在不同参数组合下依然保持一致，说明结果并非偶然，而是源于模型结构本身。在供应链研究中，稳健性验证意味着结论具有更强的普适性，而不仅仅适用于某一特定市场情形。
Robustness analysis is a verification method that examines whether a model's conclusions still hold true when key parameters or market environment settings are changed. Its purpose is not to pursue consistency in numerical values, but rather to verify the stability of the trend direction. If the core conclusions remain consistent under different parameter combinations, it indicates that the results are not accidental, but rather stem from the model structure itself. In supply chain research, robustness verification means that the conclusions have greater universality, rather than being applicable only to a specific market situation.
2、机制稳定性（Mechanism stability）
如果在不同参数环境下，成本共担仍然能够提升整体投入水平，说明该契约机制具有内在激励稳定性。这意味着成本共担并非依赖某个特殊数值才有效，而是在更广泛的市场条件下都能发挥调节作用。这种机制稳定性，是评价契约有效性的关键标准。
If cost-sharing can still improve the overall investment level under different parameter environments, it indicates that the contract mechanism has inherent incentive stability. This means that cost-sharing is not effective only when it depends on a specific value, but can play a regulatory role under broader market conditions. This mechanism stability is a key criterion for evaluating the effectiveness of a contract.
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翻译：Google翻译
参考资料：百度、Chatgpt
参考文献：陈翼, 孙晓曼, 张宁等. 数智驱动营销下企业网络平台供应链的绿色产品营销策略研究 [J]. 中国管理科学, 2024, 32(5): 81-92.
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