Conservation technology adoption decisions and the theory of planned behavior

This study of water saving technology adoption and technology investment behavior for Florida strawberry farmers represents an application of the Theory of Planned Behavior. It is compared with the Theory of Reasoned Action, and the Theory of Derived Demand. The focus is on perceived control in the decisions, first, to become an adopter of conservation technology, and, second, to invest more capital in the technology. The results lend credence to the Planned Behavior Theory but also support Derived Demand Theory, in that actual financial capability (actual control) is found important. To predict technology adoption we may need to account for both perceived and actual control. Unfettered government control of farmer technology decisions could be counterproductive, suggesting technology policy may need to include a mix of moral suasion and incentives with more modest controls.     

Crea-Space — eine Methode zur Entwicklung des kreativen Potenzials in Teams und größeren Gruppen

Crea-space — a method to develop the creative potentials in teams and larger groups Crea-Space is a kind of group-intervention, suitable for mid-size groups. The technique is derived from Open Space and offers an instrument to generate creativity in the process of elaborating future-visions. The technique consists of five steps, step one to four provide a frame for opening up the creative potential of the group, the fifth is a commitment for the next steps towards realization of the creative ideas.     

Strengthening Local Governance in Developing Countries: Partnership as an Alternative Approach

One of the major current concerns in administrative science is the scarcity of partnership-based administration in developing countries, where the capacity of local government is generally weak. Due to the impact of globalisation, the growth of information technology and the rise of third sector organisations, public administration has adopted a new paradigm but given it different names i.e., partnership, public-private partnership, networking, sound governance, good governance etc. As a result, the notion of partnership has emerged as one of the key approaches to meeting the governance challenges of the new millennium focusing, in particular, on building and strengthening the capacity of local governance. As a model, the sustainability of a social system based solely on state capacity has failed in most developing countries. As such, this paper intends to analyse the prospects for partnership based local governance in the developing countries. We argue that there is no alternative to building partnerships at the local government level between the state, private and civil society in order to improve the capacity of local government, enabling it to better attain sustainability, ensure good governance and promote participation in an attempt to mitigate the problems of social exclusion and fragmentation in the delivery of services and products.     

Probabilistic Modeling of Flood Hazard and its Risk Assessment for Eastern Region of India

This article models flood occurrence probabilistically and its risk assessment. It incorporates atmospheric parameters to forecast rainfall in an area. This measure of precipitation, together with river and ground parameters, serve as parameters in the model to predict runoff and subsequently inundation depth of an area. The inundation depth acts as a guide for predicting flood proneness and associated hazard. The vulnerability owing to flood has been analyzed as social vulnerability $(V_S)$, vulnerability to property $(V_P)$, and vulnerability to the location in terms of awareness $(V_A)$. The associated risk has been estimated for each area. The distribution of risk values can be used to classify every area into one of the six risk zones—namely, very low risk, low risk, moderately low risk, medium risk, high risk, and very high risk. The prioritization regarding preparedness, evacuation planning, or distribution of relief items should be guided by the range on the risk scale within which the area under study falls. The flood risk assessment model framework has been tested on a real‐life case study. The flood risk indices for each of the municipalities in the area under study have been calculated. The risk indices and hence the flood risk zone under which a municipality is expected to lie would alter every day. The appropriate authorities can then plan ahead in terms of preparedness to combat the impending flood situation in the most critical and vulnerable areas.     

Measurement of the sexual health and wellbeing of women who have undergone female genital mutilation/Cutting: A scoping review

Objective: We conducted a scoping review to identify and assess instruments used to measure sexual health and wellbeing in women who have undergone female genital mutilation/cutting (FGM/C). Method: We retrieved and assessed 10 validated instruments using an 18-item checklist derived from the Consensus-based Standards for the Selection of Health Status Measurement Instruments (COSMIN) checklist. Results: All instruments were developed and initially validated among literate, predominantly Caucasian participants in North America and Europe. Only 1 validation study was conducted among women living with FGM/C. Conclusion: Most instruments only measured sexual functioning. Findings underscore the need to validate instruments appropriate for use among FGM/C survivors.     

The impact of tourism and finance on women empowerment

The Goal-5 of United Nations Development Agenda for gender equality and women empowerment through equalizing the ratio of girls and boys enrolment in primary education remains suffered in almost every part of the globalized world, which does not even violate the basic human rights while it is the mandatory foundation for global peace and prosperity. The contribution of international tourism development to empower women is the key initiative of the developed world to provide an equal opportunity to the women to sustain their livelihoods. This study focused on the role of international tourism development on women empowerment through mediating a number of financial factors in a panel of 24 selected European countries, over a period of 1990–2015. The results show that financial intermediaries act as a catalyst to empower women through international tourism. More specifically, tourism and financial factors promote (i) gender parity in tertiary enrollment, (ii) gender parity in primary and secondary school enrollment, (iii) female employment, and (iv) women’s share in non-agriculture wage employment, while the results further support the (i) growth-led tourism, (ii) finance-led growth, (iii) growth stimulate women empowerment, and (iv) tourism-induced women’s empowerment hypothesis across countries.     

Variable selection for model-based clustering using the integrated complete-data likelihood

Variable selection in cluster analysis is important yet challenging. It can be achieved by regularization methods, which realize a trade-off between the clustering accuracy and the number of selected variables by using a lasso-type penalty. However, the calibration of the penalty term can suffer from criticisms. Model selection methods are an efficient alternative, yet they require a difficult optimization of an information criterion which involves combinatorial problems. First, most of these optimization algorithms are based on a suboptimal procedure (e.g. stepwise method). Second, the algorithms are often computationally expensive because they need multiple calls of EM algorithms. Here we propose to use a new information criterion based on the integrated complete-data likelihood. It does not require the maximum likelihood estimate and its maximization appears to be simple and computationally efficient. The original contribution of our approach is to perform the model selection without requiring any parameter estimation. Then, parameter inference is needed only for the unique selected model. This approach is used for the variable selection of a Gaussian mixture model with conditional independence assumed. The numerical experiments on simulated and benchmark datasets show that the proposed method often outperforms two classical approaches for variable selection. The proposed approach is implemented in the R package VarSelLCM available on CRAN.     

Health care providers' readiness to screen for intimate partner violence in Northern Nigeria

Research on screening for intimate partner violence (IPV) within health care in a sub-Saharan African context is rare. This paper assessed factors associated with the readiness to screen for IPV among care providers (HCP, n = 274) at Kano hospital, Nigeria. Readiness was measured using the Domestic Violence Health Care Providers' survey instrument, which measures grade of perceived self-efficacy in screening for IPV, fear for victim/provider safety, access to system support to refer IPV victims, professional roles resistant/ fear of offending clients, and blaming the victim for being abused victim. Social workers perceived a higher self-efficacy and better access to system support networks to refer victims than peers in other occupation categories. Female care providers and doctors were less likely to blame the victim than males and social workers, respectively. Younger care providers of Yoruba ethnicity and social workers were less likely to perceive conflicting professional roles related to screening than older providers of Hausa ethnicity and doctors, respectively. Implications of our findings for interventions and further research are discussed.     

Textual data transformations using natural language processing for risk assessment

Underlying information about failure, including observations made in free text, can be a good source for understanding, analyzing, and extracting meaningful information for determining causation. The unstructured nature of natural language expression demands advanced methodology to identify its underlying features. There is no available solution to utilize unstructured data for risk assessment purposes. Due to the scarcity of relevant data, textual data can be a vital learning source for developing a risk assessment methodology. This work addresses the knowledge gap in extracting relevant features from textual data to develop cause–effect scenarios with minimal manual interpretation. This study applies natural language processing and text-mining techniques to extract features from past accident reports. The extracted features are transformed into parametric form with the help of fuzzy set theory and utilized in Bayesian networks as prior probabilities for risk assessment. An application of the proposed methodology is shown in microbiologically influenced corrosion-related incident reports available from the Pipeline and Hazardous Material Safety Administration database. In addition, the trained named entity recognition (NER) model is verified on eight incidents, showing a promising preliminary result for identifying all relevant features from textual data and demonstrating the robustness and applicability of the NER method. The proposed methodology can be used in domain-specific risk assessment to analyze, predict, and prevent future mishaps, ameliorating overall process safety.