CAREER: Product-line Design Optimization with Strategic Differentiation: Empirical Evidence and Modeling
CAREER: Product-line Design Optimization with Strategic Differentiation: Empirical Evidence and Modeling
批准号:
1943438
负责人:
Kate Whitefoot
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-08-01 至 2025-07-31
中文摘要
这项学院早期职业发展计划(Career)补助金将使用最优战略“差异化”来推进产品线设计的理论、定量建模和教育:就消费者认为的属性而言,产品与其他产品有多大的不同。对于制造商来说,预测产品变体之间的相互作用以更好地满足整体产品线营销和监管目标是具有挑战性的。例如,为了帮助遵守燃油经济性法规,汽车制造商已经推出了新的车辆。为了在商业上取得成功,制造商需要将它们与公司产品线上的其他车辆及其竞争对手的产品区分开来。从历史上看,当制造商未能实现差异化时,节能型汽车的销量一直低于预期,一些公司不得不为不符合燃油经济性规定而支付罚款。如果各公司能够从战略上让它们的汽车与众不同--例如,让它们的车相对更小、更快,而不是更大、更豪华的汽车,以及竞争对手更便宜、更高效的小型车,它们可能会增加销量,并避免处罚。不幸的是,工程师使用的现有产品线设计模型在支持战略差异化决策方面的能力有限,因为没有很好地理解模型的属性,没有足够的证据表明它们可以充分预测现实世界的行为,而且组织通常没有内部专业知识来使用和调整它们以适应适当的环境。研究成果将使制造商能够系统地优化产品线设计,在满足监管约束的同时达到企业目标的解决方案。为了实现本研究的目标,该工作将推导并实证检验关于市场和监管条件下的战略差异化的新假设,并确定能够代表这一行为的产品线优化模型类别。该研究方法将生产线优化建模与计量分析相结合。对行业产品线数据的新分析将解释行业中发现的战略差异化的系统性特征。项目成果将有助于开发(1)一种理论,该理论简约而可信地解释在设计决策、消费者偏好分布和监管约束的不同特征下的最佳战略差异化的基本属性;(2)经验支持的产品线设计模型,该模型优化工程设计变量,考虑对一个产品变体属性的调整将如何影响该系列中其他变体的市场和监管目标。综合研究和教育计划将加强本科教育,并建立实践者教育计划和在线门户网站,以扩大学术界、产业界和政府之间的协作学习和模式转移。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This Faculty Early Career Development Program (CAREER) grant will advance the theory, quantitative modeling, and education of product-line design using optimal strategic "differentiation": how different a product is from others in terms of attributes consumers consider. Anticipating interactions among product variants to better meet overall product-line marketing and regulatory goals is challenging for manufacturers. For example, to help comply with fuel economy regulations, automotive manufacturers have introduced new sets of vehicles. To do so in a commercially successful way, the manufacturers need to differentiate them from other vehicles in the company's product line and their competitors'. Historically, when manufacturers have failed to differentiate, the sales of fuel-efficient vehicles have been lower than expected, and some companies have had to pay penalties for not meeting the fuel economy regulations. If companies could strategically differentiate their cars--for example by making them relatively smaller, with better acceleration, than both their larger, more luxurious vehicles, as well as their competitors' cheaper and more-efficient small cars, they might have increased sales and averted the penalties. Unfortunately, existing product-line design models used by engineers are limited in their ability to support strategic differentiation decisions, because the models' properties are not well understood, there is not enough evidence that they predict real-world behavior adequately, and organizations often do not have in-house expertise to use and adapt them for the appropriate contexts. The research outcomes will enable manufacturers to systematically optimize product-line designs, reaching solutions to firm objectives while meeting regulatory constraints.To achieve the goals of this research, the work will derive and empirically test new hypotheses about strategic differentiation under sets of market and regulatory conditions and identify classes of product-line optimization models capable of representing this behavior. The research approach combines product-line optimization modeling with econometric analysis. New analyses of industry product-line data will explain systematic properties of strategic differentiation found in industry. The project outcomes will enable the development of (1) a theory that parsimoniously yet credibly explains fundamental properties of optimal strategic differentiation (e.g., clustering, fracturing, and divergent positioning) under different characteristics of design decisions, consumer preference distributions, and regulatory constraints; and (2) empirically-supported product-line design models that optimize engineering design variables considering how adjustments to one product variant's attributes will affect market and regulatory goals of other variants in the line. An integrated research and education plan will enhance undergraduate education and establish a practitioner education program and online portal to scale-up collaborative learning and model transfer between academia, industry, and government.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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会议论文
EAGER: Metrics to Evaluate Customer Preference Models for use in Engineering Design Optimization
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批准号:1630096
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项目类别:Standard Grant
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资助金额:$23.53万
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财政年份:2016
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负责人:Kate Whitefoot
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依托单位:
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批准年份:2003
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