Knowledge, attitudes and behavioral intentions of agricultural professionals toward genetically modified (GM) foods: a case study in Southwest Iran

While there has been a number of consumers' studies looking at factors that influence individuals' attitudes and behavior toward GM foods, few studies have considered agricultural professionals' intentions in this regard. This study illuminates agricultural professionals' insights toward GM foods in Southwest Iran. A random sample of 262 respondents was studied. The results indicated that the majority of the respondents had little knowledge about GM foods. They perceived few benefits or risks of GM foods. Their perceived benefits and trust in individuals and institutions had positive impacts on the behavioral intentions of the agricultural professionals. The results also revealed that the low knowledge level of the respondents had a negative impact on the behavioral intentions toward GM foods. This state of affairs is problematic, either GM foods have serious problems or the knowledge conveyed to the Iranian agricultural experts is inappropriate. We recommend a well defined communication strategy to provide information in such a way that allows individuals to feel adequately informed about GM foods. Furthermore, the development of trust and knowledge regarding GM foods can be greater when risk analysis frameworks are transparent, risk assessment methodologies are objective, all stakeholders are engaged in the risk management process, and risk communication focuses on consumers

Agricultural water poverty index and sustainability

Water resources are declining at an alarming rate in the world. The use of water resources for agricultural production has contributed to the rapid decline in quantity and degradation of water quality. Though sustainable agriculture must be economically viable, ecologically sound and socially responsible, water scarcity has challenged the sustainability of agriculture, especially in arid and semi-arid regions. There is a relative consensus among professionals that the increasing water scarcity through excessive use of water and mismanagement of the available water resources are major concerns for agricultural sustainability. Agricultural sustainability is assessed using various indicators, but the contribution of the water factor in those indicators is limited. Therefore, we review the role of sustainable water management in achieving agricultural sustainability. We propose an agricultural water poverty index (AWPI) as an instrument to provide a holistic picture of vital issues for sustainable water management. We also distill key components of the agricultural water poverty index and discuss its applications. The agricultural water poverty index can be used to assess the agricultural water poverty among farmers and regions and to provide guidelines for sustainable water management. This article uses the case of Iran to illustrate the application of the agricultural water poverty index in analyzing agricultural water poverty and providing recommendations for sustainable water management

System dynamic simulation: A new method in social impact assessment (SIA)

Many complex social questions are difficult to address adequately with conventional methods and techniques, due to the complicated dynamics, and hard to quantify social processes. Despite these difficulties researchers and practitioners have attempted to use conventional methods not only in evaluative modes but also in predictive modes to inform decision making. The effectiveness of SIAs would be increased if they were used to support the project design processes. This requires deliberate use of lessons from retrospective assessments to inform predictive assessments. Social simulations may be a useful tool for developing a predictive SIA method. There have been limited attempts to develop computer simulations that allow social impacts to be explored and understood before implementing development projects. In light of this argument, this paper aims to introduce System Dynamic (SD) simulation as a new predictive SIA method in large development projects. We propose the potential value of the SD approach to simulate social impacts of development projects. We use data from the SIA of Gareh-Bygone floodwater spreading project to illustrate the potential of SD simulation in SIA. It was concluded that in comparison to traditional SIA methods SD simulation can integrate quantitative and qualitative inputs from different sources and methods and provides a more effective and dynamic assessment of social impacts for development projects. We recommend future research to investigate the full potential of SD in SIA in comparing different situations and scenarios

The social experience of drought in rural Iran

<p>Using qualitative social research methods at the farm family level, this paper considers the social impacts of drought on two purposefully-selected villages in Fars Province, Iran. It examines the experience of drought on different types of farm families, specifically the less vulnerable, the resource poor, and the very resource poor. Our results show that all three groups experienced economic impacts of drought, but more importantly they all suffered major social impacts as well. The less-vulnerable families sought diversified sources of income in order to cope with drought. The vulnerable families (resource poor and very resource poor) were more affected by social and emotional impacts than less-vulnerable families. The economic and social impacts that were experienced included: reduced household income; shortage of alternative income sources: increased workload; conflict of water access and water use; food insecurity, shortages and associated malnutrition: health impacts and reduced access to health services; reduced access to education; inequitable drought relief and associated stress and conflict; rural to urban migration; impoverishment and reduced quality of life: psychological and emotional impacts including depression, frustration and alienation; changed family plans such as delaying marriage; and family and community disharmony and disintegration. Recommendations and implications for drought management policy are offered to reduce the negative social impacts of drought. (C) 2012 Elsevier Ltd. All rights reserved.</p>

Social risk perception of genetically modified foods: towards a theoretical framework

peer reviewedThe debates over uncertainty about the possible undesirable impacts on human and the environmental safety of GM foods have increased. Most of these debates are rooted in different risk perceptions of various societal stakeholders. Despite growing studies on GM foods' knowledge, attitude, or behaviour, few have documented the risk perception models to assess stakeholders' risk perceptions. Therefore, this study aimed to develop a model to explain the social risk perception of GM foods. To this end, current risk perception theories and models were critically reviewed, then an attempt was made to develop an integrated and more comprehensive model called the "Comprehensive Social Risk Perception Model" (CSRPM). Addressing the theoretical and methodological weakness of conventional models, CSRPM could be a complementary model to more effectively study the social risk perception of GM foods in developed and developing countries. Furthermore, CSRPM can also be used in ex-ante and ex-post risk assessments

A framework for combining social impact assessment and risk assessment

<p>An increasing focus on integrative approaches is one of the current trends in impact assessment. There is potential to combine impact assessment with various other forms of assessment, such as risk assessment, to make impact assessment and the management of social risks more effective. We identify the common features of social impact assessment (SIA) and social risk assessment (SRA), and discuss the merits of a combined approach. A hybrid model combining SIA and SRA to form a new approach called, 'risk and social impact assessment' (RSIA) is introduced. RSIA expands the capacity of SIA to evaluate and manage the social impacts of risky projects such as nuclear energy as well as natural hazards and disasters such as droughts and floods. We outline the three stages of RSIA, namely: impact identification, impact assessment, and impact management. (C) 2013 Elsevier Inc. All rights reserved.</p>