Influencing Factors on Consumers’ Willingness to Share Energy Data on Online Energy Platforms

Climate change requires an adaptation of the energy system towards an efficient use of renewable energies. For efficient control and optimization of the energy system, energy consumption and production data at household level play an essential role. Sharing platforms can enable the bundling and controlling of energy data from individual households. However, there is often a lack of acceptance among potential users to share their own data on such platforms. Therefore, this paper investigates the willingness of consumers to share their personal energy data. In particular, several factors that influence this willingness are examined. Decisive for the willingness are incentives for consumers in return for sharing their energy data. These can be offered in personal added value or collective added value. This paper shows that the factors perceived behavioral control, personal attitude and subjective norm have an influence on the willingness of private users to share energy data if a personal benefit or a collective benefit is provided. The age of users and their privacy concerns affect the willingness to share only in case personal value is added. These findings are valuable for the development and operation of online energy platforms

I shine, not burn : empirical studies on citizen participation initiatives in the field of photovoltaics

Die Notwendigkeit, das derzeit vorwiegend auf fossilen Brennstoffen basierende Energiesystem zu ändern, wird von politischen Vereinbarungen auf internationaler, europäischer und nationaler Ebene anerkannt. Neben Zielen zum Ausbau des Anteils erneuerbarer Energieträger, wird auch die Wichtigkeit von zivilem Engagement betont. Bürgerbeteiligungsinitiativen (BBI) im Bereich erneuerbarer Energien wird hier eine vielversprechende Rolle zugeschrieben. Die vorliegende Dissertation umfasst drei empirische Studien, welche die Rolle von BBIs im Bereich Photovoltaik (PV) in Österreich zu beleuchten:(1) Eine qualitative Studie analysiert marktorientierte und Graswurzelinitiativen aus dem Blickwinkel des strategischen Nischenmanagements, und zeigt auf, dass sich beide Typen von PV-BBIs derzeit in einer inter-lokalen Phase der Nischenentwicklung befinden, sowie Potenzial besitzen, sich aus einer geschützten Nische heraus weiterzuentwickeln. (2) Ein integrierter SWOT/AHP Ansatz in einer Fragebogenstudie unter GründerInnenn und EnergieexpertInnenen identifiziert wichtige Aspekte, welche die weitere Verbreitung von PV-BBIs in Österreich begünstigen oder hemmen, wie etwa staatliche Unterstützung (z.B. in Form von Einspeisetarifen, Förderungen), öffentliche Akzeptanz, und weitere Kostenreduktion von PV als Technologie. (3) Eine Umfrage unter (Nicht-)TeilnehmerInnen von zwei ausgewählten PV-BBIs in Österreich zielt darauf ab, Einfussfaktoren auf die Adoptionsentscheidung von Privatpersonen zu identifizieren. Dazu werden ‚desires‘ und ‚beliefs‘ basierend auf Hedströms DBO-Theorie neben anderen potenziellen Einflussgrößen getrennt erhoben. Die Ergebnisse von logistischen Regressionsmodellen weisen darauf hin, dass vor allem ökonomische Einflussfaktoren relevant für die Adoptionsentscheidung von Individuen sind.Fleiß EvaZusammenfassungen in Deutsch und EnglischKarl-Franzens-Universität Graz, Dissertation, 2018OeBB(VLID)276442

Social and environmental preferences : measuring how people make tradeoffs among themselves, others, and collective goods

Social preferences like social value orientation are considered a promising solution to social dilemmas, such as mitigating anthropogenic climate change. However, evidence on the relationship between social preferences and environmental concerns is mixed, possibly because these constructs have commonly been measured by distinct methods that do not facilitate direct comparisons. We address this gap by introducing an incentivized preference-based measurement approach, extending a subject’s concerns for the well-being of others to a subject’s willingness to support environmental and humanitarian endeavors, based on a simple social preferences utility function. In this measurement approach, subjects make resource allocation choices with real consequences and the design ensures comparability of different revealed preferences (i.e., people’s willingness to make tradeoffs between themselves and others via donations to NGOs supporting different environmental and social causes).We then use this measurement method in an exploratory fashion to consistently assess preferences for environmental and humanitarian concerns in a laboratory experiment. We find that social and environmental value orientations are robustly interrelated, and further that people are generally more willing to pay to benefit people in need, compared to abstract environmental causes. We conclude that interventions to nudge people towards proenvironmental behavior will have a greater impact if human suffering resulting from global climate change is made more salient

Pushing low-carbon mobility: a survey experiment on the public acceptance of disruptive policy packages

Disruptive policy packages that fundamentally change the current unsustainable passenger transport structures and enable low-carbon mobility transformation are inevitable. This implies the use of more stringent and multiple restrictive (i.e. push) measures. To enable successful implementation, public acceptance is critical, but what drives this acceptance? In this study, two main hypotheses were tested using survey methods that combined a two-group framing with a conjoint experiment: (1) The acceptance of push measures decreases as disruption increases; (2) disruptive push measures are less likely to be rejected when communicated as part of a policy package that included complementary pull measures (i.e. incentives). We conducted this survey with a quota-representative sample of 1,032 respondents from Austria. Two main findings emerge: First, we find low public acceptance of push measures, but observe differences based on the level of disruption (i.e. the measures’ intensity or rapidity of implementation). The more disruptive the measure (e.g. a registration ban for fossil fuel cars or a fuel price increase), the more negatively these measures were evaluated by survey respondents. Second, our results indicate the need to communicate and implement high-impact, more restrictive push measures (e.g. car bans) as part of policy packages that include acceptance-boosting pull measures.ISSN:1752-7457ISSN:1469-306

Pushing low-carbon mobility: a survey experiment on the public acceptance of disruptive policy packages

Disruptive policy packages that fundamentally change the current unsustainable passenger transport structures and enable low-carbon mobility transformation are inevitable. This implies the use of more stringent and multiple restrictive (i.e. push) measures. To enable successful implementation, public acceptance is critical, but what drives this acceptance? In this study, two main hypotheses were tested using survey methods that combined a two-group framing with a conjoint experiment: (1) The acceptance of push measures decreases as disruption increases; (2) disruptive push measures are less likely to be rejected when communicated as part of a policy package that included complementary pull measures (i.e. incentives). We conducted this survey with a quota-representative sample of 1,032 respondents from Austria. Two main findings emerge: First, we find low public acceptance of push measures, but observe differences based on the level of disruption (i.e. the measures’ intensity or rapidity of implementation). The more disruptive the measure (e.g. a registration ban for fossil fuel cars or a fuel price increase), the more negatively these measures were evaluated by survey respondents. Second, our results indicate the need to communicate and implement high-impact, more restrictive push measures (e.g. car bans) as part of policy packages that include acceptance-boosting pull measures. Successful and acceptable mitigation policies for low-carbon mobility require multiple push measures that are communicated in policy packages together with pull measures.Acceptance levels of push measures are generally low, but acceptance differs depending on how disruptive the respective policy is, with the more disruptive policies being less well accepted.Acceptable combinations of push measures may include higher parking fees, car-free city centres, and street redesign to, e.g. prioritize non-motorized modes of transport.Responses to the presented push measures vary across society, with frequent car users showing higher levels of rejection dependent on the included policy measures, underlining the need to tailor policies for specific contexts. Successful and acceptable mitigation policies for low-carbon mobility require multiple push measures that are communicated in policy packages together with pull measures. Acceptance levels of push measures are generally low, but acceptance differs depending on how disruptive the respective policy is, with the more disruptive policies being less well accepted. Acceptable combinations of push measures may include higher parking fees, car-free city centres, and street redesign to, e.g. prioritize non-motorized modes of transport. Responses to the presented push measures vary across society, with frequent car users showing higher levels of rejection dependent on the included policy measures, underlining the need to tailor policies for specific contexts.</p

Changing behavior while having climate change in mind? An investigation of social-psychological predictors for specific pro-environmental behaviors in the energy domain

&lt;p&gt;Social scientists and psychologists who study environmental issues need to improve their measures to capture relevant pro-environmental behaviors to reduce greenhouse gas emissions &ndash; the main driver of climate change. They also need to identify meaningful predictors for these behaviors, which go beyond mere statistical significance. In this large representative study of the Austrian population (&lt;em&gt;N&lt;/em&gt; = 1,083), we aim at addressing both issues. We focus on relevant and specific energy-related behavioral intentions (traveling, electricity consumption and heating) and test a set of preregistered social-psychological predictors in path models, followed by an exploratory machine-learning approach. We show that a combination of some prominent predictors &ndash; perceived behavior control, consideration of future and immediate consequences, and willingness to sacrifice &ndash; accounts for only 20 to 30% of variance in behavioral intentions. We suggest that future studies confirm our results in other cultures and set even higher qualitative benchmarks for measures and predictors.&lt;/p&gt