中国科学院行为科学重点实验室知识库

在移动互联网和大数据时代,通过定制化信息推动家庭能源消费行为变革是一个亟待解决的前沿科学课题。本研究通过对固定样本组被试进行长期的行为观察、深度访谈、焦点小组、个案研究和单被试设计,基于扎根理论技术考察定制化信息的即期和远期作用,探索定制化信息影响节能行为决策过程的路径和机制。整合横断设计和纵向设计两者特点,本研究拟采用聚合交叉设计对6个实验组被试进行18个月的追踪实验,运用方差分析检验同一实验组被试不同时期的节能心理和行为决策差异,比较不同实验组被试在特定时点截面的横向(静态)差异;运用多层线性模型检验不同实验组节能行为及其决策过程变动趋势之间的(动态)差异,分析特定维度定制化信息框架的边际效应。在此基础上,设计并论证定制化信息的优化路径、实施策略和组合应用构想。本研究拟构建定制化信息对节能行为决策过程作用机制的理论模型(信息呈现-心理机制-节能行为决策模型),为探究定制化信息影响节能行为决策过程的作用机制黑箱提供理论支持和实验证据。

Abstract: During mobile internet era and the age of big data, how to promote the revolution of household energy conservation through tailored information is one of the advanced researches. Based on grounded theory techniques, this study plans to use long-term observation, in-depth interviews, case studies and single-subject design technology to explore the short-run and long-run effects of tailored information on energy conservation psychology and decision-making process. In other words, the mode and mechanism for the influence of tailored information on household energy conservation behavior can be explored. In order to achieve the above objectives, a series of studies which integrates the cross-sectional design and longitudinal design will be implemented. That is, 18 months-long panel experiments consisted of 6 groups will be conducted based on cross-sequential design experimental ideas. In the process of data analysis, the differences among conservation psychology and decision-making of separated stages will be analyzed through analysis of variance (ANOVA), trend curve differences (dynamic differences) of energy conservation and decision-making process among different experimental groups will be tested by hierarchical linear model (HLM). And HLM will also be used to analyze the marginal effects of specific tailored information frame on energy conservation decision-making process. Furthermore, the overall blue print, implementation path and combination strategies of tailored information will be designed and tested accordingly. This study will develop tailored intervention theories on household energy conservation and open the “black box” of how tailored information impacts household energy conservation decision-making process by providing theoretical supports and empirical evidences.