Operational Decision-Making for Reach Maximization of Incentive Programs that Influence Consumer Energy-Saving Behavior

利用信息社会影响力的环境项目最近在培养有能源意识的消费者行为方面取得了成功。通过传播家庭能源报告，将单个家庭的能源支出模式与邻居的能源支出模式进行比较，这些计划利用了这样一个事实，即人们更有可能调整自己的行为，当简单的关于其对环境的负面影响的信息之前是“社会证据”，即其他人已经开始采取环保行为。虽然利用社会影响力为社会利益服务本身就是一个突破，但需要进一步研究，以直接激励措施来提高此类计划的影响，以便能够主动控制这些计划，并以有组织的方式加速其影响。该奖项支持对随机激励计划（社会彩票）的设计和规划进行基础研究，这些计划旨在告知消费者他们的同龄人节能，同时获得奖励。所研究的规定性方法能够计算出社会影响计划或政策的“范围”的最大化，并且预计将适用于经济学、医疗保健、教育等，提高个人对社会关注问题的认识。该项目将进一步支持美国国家科学基金会的教育使命，通过参与代表性不足的学生团体，高级设计项目咨询，并进行本科生研讨会。该研究计划包括建模工作，以定量捕捉信息社会影响和随机节能激励计划的影响之间的联系;开发混合整数规划，动态规划和分散网络优化算法，以实现预算约束下的最大化;以及在有关目标异质人口的有限信息下对运营计划规划进行调查。该项目将产生新的问题类别和利用社交网络进行干预的业务规划的基本见解。它的产品将允许对社会影响力的机制进行建模，而不是像以前那样直接由扩散驱动，而是由范围驱动。开发的设计，配方和工具将根据合作能源供应商提供的数据和建议进行评估。引入研究的形式主义和算法所带来的改进将以收集理论证据为特征，在准备试点实施的途中。

Environmental programs that exploit informational social influence have recently found success in fostering energy-conscious consumer behavior. By disseminating Home Energy Reports that compare individual households' energy spending patterns to those of their neighbors, these programs capitalize on the fact that people are more likely to adjust their behavior when simple information on its negative impacts on the environment is preceded by ''social proof'' that referent others have already started to behave pro-environmentally. While exploiting the power of social influence for the societal benefit is a breakthrough in itself, further research is required to boost the impact of such programs with direct incentives, so that they can be proactively controlled and their impact accelerated in an organized manner. This award supports fundamental research into the design and planning of randomized incentive programs -- social lotteries -- that inform consumers of their peers saving energy while being rewarded for doing so. The researched prescriptive methodologies enable calculated maximization of the ''reach'' of a social influence program or policy, and are expected to be applicable in economics, healthcare, education, etc., for increasing individual awareness of issues of societal concern. This project will further support the educational mission of the NSF by involving members of underrepresented student groups, senior design project advising, and conducting undergraduate student seminars.The research plan encompasses the modeling efforts to quantitatively capture the connection between the informational social influence and the impact of the randomized energy-saving incentive program; the development of mixed-integer programming, dynamic programming and decentralized network optimization algorithms for reach maximization under budgetary constraints; and the investigations into operational program planning under limited information about a targeted heterogeneous population. This project will produce new classes of problems and fundamental insights into operational planning of interventions exploiting social networks. Its products will allow for modeling of the mechanisms of social influence driven not directly by diffusion, as previously done, but by reach. The developed designs, recipes and tools will be evaluated with the data and advice provided by a collaborating energy provider. The improvements resulting from the introduction of the researched formalisms and algorithms will be characterized by gathering theoretical evidence, en route to preparing a pilot implementation.