Adoption and Diffusion of Nature-Based Solutions by Property Owners in Urban Areas: The Case of Green Roofs in Eindhoven, The Netherlands

Abstract

This article explores general concepts related to the diffusion of innovations theory (DoI) and its use regarding the adoption of nature-based solutions, specifically green roofs, in urban areas by private house/property owners in the city of Eindhoven (Netherlands). Given the gap in knowledge on the potential for the adoption of green roofs by private house/property owners as well as barriers and enablers to their implementation from the DoI perspective, we used a model for predicting the adoption of innovations (ADOPT). Results show that the predicted peak adoption level is 3% and that the time to peak adoption level is 17 years. However, the level of adoption can be significantly enhanced by increasing profit benefit (i.e., cost savings) in the years that they are used (+19 percent points adoption), reducing risk exposure (+17 percent points adoption), and improving ease and convenience (+15 percent points adoption), while the time to peak adoption level can be reduced by enhancing relevant and existing skills and knowledge (−3 years), simplifying trialability and innovation complexity (−2 years), and increasing observability (−1 year). Hence, key factors affecting the adoption of green roofs by private house/property owners have been identified, contributing to the formulation of urban climate change adoption strategies.

Promoting the Diffusion of Sustainable Innovations through Customer Education—A Case of the Cosmetic Industry

“…The study that relates the most to ours is [28]. Using the Adoption and Diffusion Outcome Prediction Tool (ADOPT), the relative advantages as well as the learnability of the diffusing innovation and the potential adopters were analyzed to predict the diffusion of a solar photovoltaic system [29] and green roofs [28]. However, the factors identified as the barriers in those cases are general (i.e., profit benefits, risk exposure, ease, and convenience of use) and applicable to non-sustainable innovations as well.…”

“…The key behavior changes that signal the crossing from "awareness" to "interest" and then to the "evaluation" stage are that potential adopters seek more important information about the product by checking ingredients [18], a decision to avoid non-sustainable products, an adoption intention for a sustainable product, increased trust in certified sustainable products, and an adoption intention for certified sustainable innovation. The factors used to measure the relative advantage in the ADOPT model [28,29] were grouped into four, as shown in Figure 1. Among them, three factors-quality/effectiveness, cost (price), and sustainability (being sustainable)-were used directly in the survey and presented to the participants.…”

“…Policies that encourage the new and destabilize the old are suggested to be included in the policy mix to facilitate sustainable transitions [12]. The study that relates the most to ours is [28]. Using the Adoption and Diffusion Outcome Prediction Tool (ADOPT), the relative advantages as well as the learnability of the diffusing innovation and the potential adopters were analyzed to predict the diffusion of a solar photovoltaic system [29] and green roofs [28].…”

Prediction of the Spatial and Temporal Adoption of an Energy Management System in Automated Dairy Cattle Barns in Bavaria—“CowEnergySystem”

“…The focus here is on both targetgroup-oriented and region-adapted advertising of the on-farm energy management system and the appropriate variable assignment in the tool. (5) Although ADOPT was originally designed purely for the agricultural sector, it is already being used for analyses outside the agricultural sector [28,29]. In comparisons, good correlations have already been established between the forecast results of ADOPT and practical figures, for example for automatic steering systems and direct sowing [26].…”

“…In practical comparisons, good correlations have already been found between the ADOPT forecast results and the practical figures for automatic steering systems and no-till farming, for example [26]. Although ADOPT was originally designed purely for the agricultural sector, it is already being used for analyses outside of agriculture [28,29]. For example, the ADOPT tool is also used to evaluate factors influencing the introduction of photovoltaic systems for water extraction in Australian sugar cane irrigation [30].…”