Impact of Social Media on Perceptions and Use of Renewable Energy Sources

Social media plays an important role in increasing knowledge, attitudes and acceptance of renewable energy. This study used modified EPPM and extended information adoption model to investigate the effect of social media on information adoption and use of renewable energy. The statistical population of the study includes Instagram users who have followed the pages related to solar energy. The questionnaire was randomly distributed among potential respondents using an online survey platform and 173 completed questionnaires were collected. The results of structural equations modeling (SEM) of modified EPPM showed that trust in information obtained from social media regarding renewable energy affects the perceived severity and susceptibility of the consequences of using conventional energy/fuels. Also, the results of SEM of the extended information adoption model indicate that the argument quality as a central path has a positive and direct effect on the perceived usefulness information. Also, the source credibility as a peripheral path indirectly affect perceived usefulness of information via changing attitudes toward information. In addition, based on the findings, perceived usefulness has both a direct impact on information adoption, as well as has indirect effect on information adoption via trust mediation. As both studies have shown; Trust in the source of information plays a key role in improving the impact of information on people's lifestyles. Therefore, it is necessary for environmental policymakers to use trusted media to lead people to do environmental behaviors

Evaluating climate change adaptation options in the agriculture sector: a PROMETHEE-GAIA analysis

Mitigating maladaptation and effectively managing climate risks are crucial components of strategic planning in agriculture amidst climate change. Evaluation serves as a pivotal element in this process, facilitating the identification of effective adaptation strategies tailored to local contexts. Consequently, it's imperative to thoroughly evaluate these strategies to ensure their success and resilience. The current study evaluated adaptation methods tailored to the local context in southwest Iran across three categories-crop, farm, and water management-employing Multi-Criteria Decision-Making (MCDM) and the PROMETHEE-GAIA. Sensitivity analysis was performed during the AHP (Analytical Hierarchy Process) stage to confirm the criteria weights and in the PROMETHEE to confirm the ranking. A set of eight criteria, including effectiveness/importance, affordability, institutional feasibility, technical feasibility, social feasibility, traditional acceptance, flexibility, and environment side effects (positive) were applied to evaluate the adaptation measures. Our results indicated the three highest rankings in each set of measures, as follows: i) crop management—relay intercropping, change of crop type, and mixed intercropping; ii) farm management—pest and disease management, weed control, and crop rotation; iii) water management—lining water canals or covering their earth floors with nylon, using pipes rather than open canals to transfer water to the field, and increasing the time intervals between irrigations to deal with water shortages. The outcomes underscore the urgency of formulating region-specific adaptation policies that align with local expertise and contextual needs. By prioritizing the identified effective strategies, policymakers can enhance resilience against water scarcity in southwest Iran. Moreover, the study highlights the importance of ongoing evaluation and adaptation, emphasizing the dynamic nature of climate challenges and the need for continuous refinement of adaptive policies

Investigating the Adoption of Precautionary Behaviors Among Young Rural Adults in South Iran During COVID-19

COVID-19 is an unprecedented challenge for public health worldwide. Reducing the incidence of the disease requires protective measures to prevent virus transmission. Understanding those factors influencing preventive behavior is the first step in preventing the spread of the disease. This study investigates factors affecting youth intention and preventive behaviors in the face of COVID-19 through the health belief model by using a cross-sectional survey collected through an online questionnaire. The sample comprises 304 rural youth in South Iran who were selected through a random sampling technique. The results reveal that perceived severity, perceived benefits, public health beliefs, perceived self-efficacy, and the cue to act positively and significantly affect preventive behaviors. The model explains 59% of variance changes in rural youth preventive behaviors during COVID-19. Cue to action is the strongest and self-efficacy was the weakest determinant of youth's preventive behavior. This study confirms that the HBM framework has appropriate predictive power and is an effective tool for investigating preventive behaviors during COVID-19. These results provide important policy implications for the development of policies that aim to avoid the further spread of COVID-19 between young citizens

Why Have Economic Incentives Failed to Convince Farmers to Adopt Drip Irrigation in Southwestern Iran?

Sustainable water usage is an important global concern and an urgent priority, especially in dryland regions such as Iran. The Iranian government is actively addressing the challenge of water scarcity by encouraging farmers to adopt new water application technology. Its main element to decrease water consumption is to encourage new irrigation systems, in particular drip irrigation. However, despite the benefits of drip irrigation technologies and the availability of generous government subsidies, adoption rates of the improved irrigation technology remain critically low among Iranian farmers. Therefore, this study seeks to determine what is limiting the uptake of improved irrigation technology in Iran. While it is well known that acceptance of new technology ultimately depends on multiple and interrelated factors, we examine those factors affecting farmers’ adoption from three theoretical perspectives in the adoption literature: farmers’ socio-economic characteristics, social capital, and technology characteristics. A cross-sectional survey was undertaken in Behbahan district in Khuzestan province in southwest Iran. The sample comprises 174 farmers who adopted drip irrigation in that region and 100 non-adopters who were located in the same region. Discriminant analysis reveals that a socio-economic approach is the strongest model to predict adoption of drip irrigation technology in the study area, followed by models of technical characteristics, and social capital. These results can help agricultural extension agents and policy-makers design appropriate and effective strategies that facilitate the adoption of drip irrigation at an increasing rate

Personal and Professional Mitigation Behavioral Intentions of Agricultural Experts to Address Climate Change

Mitigation activities, whether at the personal level relating to lifestyle or on the professional level, especially in the agriculture sector, are widely encouraged by scientists and policymakers. This research empirically analyses the association between agricultural experts’ perceptions about climate change and their intention to implement climate change mitigation. Based on survey data, individuals’ reported intention to implement personal and professional mitigation behavior is explained using a conceptual model. The structural equation modeling results suggest that the new ecological paradigm (NEP), institutional trust, and risk salience indirectly influence climate change mitigation intentions. The findings indicate that risk perception, personal efficacy, responsibility, belief in climate change occurring, and low psychological distance trigger a significantly greater intention to support personal and professional mitigation behaviors. However, the research framework is much stronger at predicting the intention to mitigate climate change in professional affairs compared to personal activities. The findings suggest that hypothetical distance factors only have a moderating effect on the relationship between higher climate change environmental values, institutional trust, risk salience, and mitigation intention. This paper analytically explores the regulating role of risk perception, hypothetical distance, personal efficacy, and responsibility between institutional trust, risk salience, and the NEP as independent concepts and intention to personal and professional mitigation behaviors as dependent variables. The findings of the study have important implications for encouraging personal and professional mitigation behaviors

Shaping farmers’ beliefs, risk perception and adaptation response through Construct Level Theory in the southwest Iran

Due to the severe effects of climate change on the agricultural sector, urgent action is required on the part of farmers and is, indeed, critical to reducing climate change impacts. However, reports globally revealed farmers' engagement in climate change adaptation is still insufficient, ambivalent, and inconsistent and farmers do not consider adaptation to be urgent. Researchers have argued that this issue is rooted in psychological biases beside other factors. Therefore, the aim of this study is to evaluate how psychological distance determines climate change beliefs, risk perception and adaptation strategies among Iranian farmers. A cross-sectional paper-based survey was conducted in the Dasht-e Azadegan county of Khuzestan province in southwest Iran. The study sample consisted of 250 farmers selected through a multi-stage random sampling process. An expert panel review and a pilot study were conducted to confirm convergent validity and reliability of the scales. The results confirm that all four dimensions of psychological distance influence water management adaptation strategies and non-farm activities. Moreover, all psychological dimensions, except the temporal dimension, affect adaptation in farming management. Thus, making climate change more proximal to decision makers could be a strategic way of encouraging individuals to take adaptive actions. This study emphasizes that concepts of psychological distance can be applied to help organizations (e.g., agriculture extension services) to understand farmers' risk perceptions and responses to climate change impacts and improve risk communication to better engage farmers in climate action

Comparison of different modern irrigation system adopters through socio-economic, innovation characteristics and social capital values

Diffusion of modern irrigation systems is one of the most important objectives of Iranian water policies targeting the sustainable use of water resources to resolve the water crisis. Despite considerable policy support, high subsidization, and a range of benefits, farmers have only minimally adopted modern irrigation systems in most parts of Iran. Therefore, the water crisis persists in almost all parts of the country. Thus, decision makers must recognize why diffusion of these systems has not been successful among farmers despite strong financial and political support. The aim of the current study was to investigate differences between adoption groups of modern irrigation systems and more critically whether the aspects affecting approval were altered by ongoing diffusion prejudiced by policy support. In other words, we explored the postponement of adoption among the early and the later adopters of modern irrigation systems and aimed to identify reasons behind different adoption behaviors. To achieve these aims, we developed a research framework of adoption that integrates multiple theories. In addition to the already established measures (human and physical capital), the current study integrated social capital and technology characteristics. A cross-sectional survey was carried out in Behbahan district in Khuzestan province southwest Iran. A total of 274 farmers were interviewed, of which 100 farmers had not and 174 farmers had adopted modern irrigation systems. A multinomial logit model was applied by using STATA14 to identify the most effective factors for farmers’ adoption decisions. We distinguished four groups; three consisted of adopters (early, middle, and late adopters) and a fourth group of non-adopters who did not accept modern irrigation technologies. The study found that farmers’ delayed adoption of drip irrigation technologies was due to the complexity of the application process and the availability of family and work social capital. Additionally, the study suggested that improved trust in institutions could increase the likelihood of earlier adoption of these technologies. The results also revealed divergent perspectives among pioneer (early adopters), follower (middle adopter), and laggard (late adopter) farmers regarding the adoption of drip irrigation technologies

Intention to apply Artificial Intelligence using fact checking tools in disaster management

The daily dissemination of a substantial amount of information concerning to disasters and crises on social media platforms, including Facebook, Instagram and Twitter in one side, and the sensitivity of this information, on the other hand, underscores the importance of evaluating the credibility of online information in this area. Fact-checking tools employing artificial intelligence represent a novel approach to verifying the validity of online information across various fields, including disaster management. The inclination of individuals to utilize fact-checking tools in such circumstances is influenced by their perceptions. Although there is a limited studies on the impact of perceptions and information processing on the intention to employ fact-checking tools in disaster-related contexts, it is anticipated that factors like critical thinking, as a concept that involves meticulous assessment of unclear or requiring careful consideration, heuristic processing, a concept indicating acceptance of news content without filtering, and the new-source tracking a concept demonstrating openness and positivity towards social media information, play pivotal roles in predicting this intention. Consequently, a conceptual framework was formulated wherein critical thinking, aside from its direct impact on the intention to use fact-checking tools, also exerts influence through two mediators of information processing and the new source tracking variables. This study's framework was examined using data from 202 respondents across various European countries, collected through an online survey. The conceptual framework analysised utilizing AMOS software. Descriptive findings indicate a moderate level of familiarity with misinformation detection tools among respondents (M=2.65; sd=1.04). Respondents exhibited close knowledge levels regarding fact-checking tools such as Rbutr, Foller, me and Botometer, Fakespot, NewsGuard, and Greek Hoaxes Detector, ranging between approximately (1.57-1.70). Contrary to initial expectations, the study's results reveal that critical thinking, was unable to directly predict the intention to use fact-checking tools. However, the indirect effect of critical thinking was confirmed through the two mediators of new source tracking and information processing (heuristic processing). Critical thinking significantly influenced the new source tracking (β=.49; p <0.0001) and heuristic processing (β=.41; p <0.0001). Both new source tracking (β=.19; p=0.043) and heuristic information processing (β=.31; p=0.001) emerged as direct predictors of the intention to use fact-checking tools. The evidence examined in this study provides empirical support that the conceptual framework has been able to predict 22% of the changes in the intention to use fact checking tools and still a significant amount of it needs to be researched

Explaining intention to apply renewable energy in agriculture: the case of broiler farms in Southwest Iran

The government of Iran has established national targets for the deployment of renewable energy sources (RES) across various sectors in the country, including agriculture. Human factors, such as the intention and willingness to use RES, are crucial for understanding RES deployment. This paper focuses on one group of stakeholders, farmers in Iran, and investigates what factors influence their intention and willingness to use RES in the energy-intensive broiler industry. The theoretical basis of the study is the health belief model (HBM). Empirical data were collected using a survey, which was developed based on the available evidence of human factors of the energy transition. Cronbach’s alpha was used to examine the internal reliability of the items of each variable through a pilot study. All scales had acceptable to good reliabilities of about 0.67 to 0.79. Altogether, 150 broiler farm owners participated, selected from Bushehr Province in southern Iran using a random sampling procedure. Structural equation modeling showed that 67% of the variation in farmer intention to use RES can be estimated. Cue to action, self-efficacy, and general health concern, also have a significant effect on intention, whereas other variables do not. The findings showed the HBM to be an effective tool for predicting farmers’ intentions to use RES. Based on these findings, more information needs to be provided to people to encourage them to use RES. Energy policy programs should pay special attention to educational and awareness-raising programs when seeking to increase renewable energy and other environmental behaviors

Social media as a driver of the use of renewable energy: The perceptions of instagram users in Iran

Despite political drivers, available solar and wind potentials, and other driving factors, the share of renewable energy sources in Iran's energy mix remains small. Many factors are perceived as barriers to the use of renewable energy sources and therefore influence the willingness of private households in Iran to use this kind of energy. We argue that social media not only plays an increasingly important role in perceptions of various technologies but also influences people's intentions. Therefore, our aim in this study is to understand whether and how social media influences people's intentions to use renewable energy sources. The research sample includes users of Instagram who are interested in and following information being posted on renewable energy sources. The methodology includes the use of a modified version of the extended parallel process model that includes attitude, intention, and trust in social media. The results of structural equation modeling show that the perceived risk of climate change significantly affects respondents' intention to use renewable energies. Also, perceived self-efficacy has a significant impact on attitude, intention, and use of renewable energy. Government agencies can increase the likelihood that household energy consumers will use renewable energy by using trusted channels to deliver necessary messages about the harms of using traditional energy and the low cost and ease of using renewable energy