Which farmers adopt solar energy? A regression analysis to explain adoption decisions over time

[1]  Nathan Tetteh,et al.  Determinants of Rooftop Solar PV adoption among Urban Households in Ghana , 2022, Renewable Energy Focus.

[2]  J. K. Nayak,et al.  A Meta-Analysis of TPB Model in Predicting Green Energy Behavior: The Moderating Role of Cross-Cultural Factors , 2022, Journal of International Consumer Marketing.

[3]  C. Yamu,et al.  Regionalization of a national integrated energy system model: A case study of the northern Netherlands , 2022, Applied Energy.

[4]  T. Bruckner,et al.  A meta-analysis of residential PV adoption: the important role of perceived benefits, intentions and antecedents in solar energy acceptance , 2021, Energy Research & Social Science.

[5]  Oz Sahin,et al.  Residential solar photovoltaic adoption behaviour: End-to-end review of theories, methods and approaches , 2021, Renewable Energy.

[6]  P. van Beukering,et al.  Determinants of energy efficiency in the Dutch dairy sector: dilemmas for sustainability , 2021 .

[7]  Jieqiong Wang,et al.  Key factors affecting the adoption willingness, behavior, and willingness-behavior consistency of farmers regarding photovoltaic agriculture in China , 2021 .

[8]  Lu Wang,et al.  Gap between words and actions: Empirical study on consistency of residents supporting renewable energy development in China , 2021 .

[9]  T. Filatova,et al.  Growing community energy initiatives from the bottom up: Simulating the role of behavioural attitudes and leadership in the Netherlands , 2020, Energy Research & Social Science.

[10]  Shahzad Alvi,et al.  How does one motivate climate mitigation? Examining energy conservation, climate change, and personal perceptions in Bangladesh and Pakistan , 2020 .

[11]  A. Palm Early adopters and their motives: Differences between earlier and later adopters of residential solar photovoltaics , 2020 .

[12]  Boqiang Lin,et al.  Slow diffusion of renewable energy technologies in China: An empirical analysis from the perspective of innovation system , 2020 .

[13]  Patrick Baur When farmers are pulled in too many directions: comparing institutional drivers of food safety and environmental sustainability in California agriculture , 2020, Agriculture and Human Values.

[14]  F. Verheij,et al.  Effect afbouw salderingsregeling op de terugverdientijd van investeringen in zonnepanelen , 2020 .

[15]  P. van Beukering,et al.  A new approach to explain farmers’ adoption of climate change mitigation measures , 2019, Climatic Change.

[16]  Bo Xing,et al.  Quantifying the rebound effects of residential solar panel adoption , 2019, Journal of Environmental Economics and Management.

[17]  H. Boudet,et al.  Public perceptions of and responses to new energy technologies , 2019, Nature Energy.

[18]  Omkar Aphale,et al.  A clean energy assessment of early adopters in electric vehicle and solar photovoltaic technology: Geospatial, political and socio-demographic trends in New York , 2019, Journal of Cleaner Production.

[19]  Fan Yang,et al.  An empirical analysis of county-level residential PV adoption in California , 2019, Technological Forecasting and Social Change.

[20]  Jiafan Yu,et al.  DeepSolar: A Machine Learning Framework to Efficiently Construct a Solar Deployment Database in the United States , 2018, Joule.

[21]  Noriatsu Matsui,et al.  Do determinants of adopting solar home systems differ between households and micro-enterprises? Evidence from rural Bangladesh , 2018, Renewable Energy.

[22]  Masoud Yazdanpanah,et al.  Cleaner and greener livestock production: Appraising producers' perceptions regarding renewable energy in Iran , 2018, Journal of Cleaner Production.

[23]  Lucia Baur,et al.  Diffusion of photovoltaic technology in Germany: A sustainable success or an illusion driven by guaranteed feed-in tariffs? , 2018 .

[24]  M. Pasqualetti,et al.  Dual use of agricultural land: Introducing ‘agrivoltaics’ in Phoenix Metropolitan Statistical Area, USA , 2018 .

[25]  Anna Bergek,et al.  Motives to adopt renewable electricity technologies: Evidence from Sweden , 2017 .

[26]  Jinlin Xue,et al.  Photovoltaic agriculture - New opportunity for photovoltaic applications in China , 2017 .

[27]  Md. Abdul Hai,et al.  Results of intention-behaviour gap for solar energy in regular residential buildings in Finland , 2017 .

[28]  Kimberly S. Wolske,et al.  Explaining interest in adopting residential solar photovoltaic systems in the United States: Toward an integration of behavioral theories , 2017 .

[29]  Sebastian Seebauer,et al.  Money, not morale: The impact of desires and beliefs on private investment in photovoltaic citizen participation initiatives , 2017 .

[30]  Samdruk Dharshing Household dynamics of technology adoption: A spatial econometric analysis of residential solar photovoltaic (PV) systems in Germany , 2017 .

[31]  Laurie Buys,et al.  Influence of demographic variables on uptake of domestic solar photovoltaic technology , 2017 .

[32]  P. Sheeran,et al.  The Intention–Behavior Gap , 2016 .

[33]  Peter Wolfs,et al.  A review of high PV penetrations in LV distribution networks: Present status, impacts and mitigation measures , 2016 .

[34]  Christian Breyer,et al.  On the role of solar photovoltaics in global energy transition scenarios , 2016 .

[35]  Johannes Rode,et al.  Does localized imitation drive technology adoption? A case study on rooftop photovoltaic systems in Germany , 2016 .

[36]  A. Palm Local factors driving the diffusion of solar photovoltaics in Sweden: A case study of five municipalities in an early market , 2016 .

[37]  Xiaoyu Liu,et al.  More than two decades of climate change alarm: Farmers knowledge, attitudes and perceptions , 2015 .

[38]  A. Hidalgo,et al.  Motivators for adoption of photovoltaic systems at grid parity: A case study from Southern Germany , 2015 .

[39]  Ulf J. J. Hahnel,et al.  Intentions to adopt photovoltaic systems depend on homeowners' expected personal gains and behavior of peers , 2015 .

[40]  Véronique Vasseur,et al.  The adoption of PV in the Netherlands: A statistical analysis of adoption factors , 2015 .

[41]  T. Stoerk,et al.  From intention to action: Can nudges help consumers to choose renewable energy? , 2014 .

[42]  Chelsea Schelly Residential solar electricity adoption: What motivates, and what matters? A case study of early adopters , 2014 .

[43]  Antonio Hidalgo,et al.  Diffusion of eco-innovations: A review , 2014 .

[44]  Xingwu Wang,et al.  Farmers' willingness to convert traditional houses to solar houses in rural areas: A survey of 465 households in Chongqing, China , 2013 .

[45]  Alfred Posch,et al.  Photovoltaics in agriculture: A case study on decision making of farmers , 2013 .

[46]  T. Lemaire,et al.  Photovoltaic energy policy: Financial estimation and performance comparison of the public support in five representative countries , 2012 .

[47]  L. Steg,et al.  Psychological factors influencing sustainable energy technology acceptance: A review-based comprehensive framework , 2012 .

[48]  I. Ajzen The theory of planned behaviour: Reactions and reflections , 2011, Psychology & health.

[49]  J. Nolan,et al.  “An Inconvenient Truth” Increases Knowledge, Concern, and Willingness to Reduce Greenhouse Gases , 2010 .

[50]  G. Whitwell,et al.  Why Ethical Consumers Don’t Walk Their Talk: Towards a Framework for Understanding the Gap Between the Ethical Purchase Intentions and Actual Buying Behaviour of Ethically Minded Consumers , 2010 .

[51]  P. Stern New Environmental Theories: Toward a Coherent Theory of Environmentally Significant Behavior , 2000 .

[52]  Robert M. Groves,et al.  UNDERSTANDING THE DECISION TO PARTICIPATE IN A SURVEY , 1992 .

[53]  I. Ajzen The theory of planned behavior , 1991 .