Samsul Huda

Managing food security through food waste and loss : small data to big data

Abstract This paper provides a management perspective of organisational factors that contributes to the reduction of food waste through the application of design science principles to explore causal relationships between food distribution (organisational) and consumption (societal) factors. Qualitative data were collected with an organisational perspective from commercial food consumers along with large-scale food importers, distributors, and retailers. Cause-effect models are built and “what-if” simulations are conducted through the development and application of a Fuzzy Cognitive Map (FCM) approaches to elucidate dynamic interrelationships. The simulation models developed provide a practical insight into existing and emergent food losses scenarios, suggesting the need for big data sets to allow for generalizable findings to be extrapolated from a more detailed quantitative exercise. This research offers itself as evidence to support policy makers in the development of policies that facilitate interventions to reduce food losses. It also contributes to the literature through sustaining, impacting and potentially improving levels of food security, underpinned by empirically constructed policy models that identify potential behavioural changes. It is the extension of these simulation models set against a backdrop of a proposed big data framework for food security, where this study sets avenues for future research for others to design and construct big data research in food supply chains. This research has therefore sought to provide policymakers with a means to evaluate new and existing policies, whilst also offering a practical basis through which food chains can be made more resilient through the consideration of management practices and policy decisions.

Farm decision making using climate information : characterizing the decision profiles of southern Indian crop farmers

The appropriate use of seasonal climate information in agricultural management requires systematic analysis of decision makers (farmers) characteristics, needs and perceptions. An attempt has been made to characterize the decision-making approach and factors affecting them amongst 240 selected crop farmers in southern India (Coimbatore region). Farmers perceptions about the importance of farm decisions in relation to seasonal climate information and their knowledge level were also analysed. About 39% of the farmers made decisions ‘alone’, indicating monopolization of decisions by one decision maker. However, other decision-making approaches, including the participation of family members (31.7%) and other farmers (14.6%), are still very common. Factor analysis indicated that those farmers with higher education and greater occupational status tended to decide themselves. More than 70% of the farmers perceived that the strategic decisions made before the start of the rainy season were more important than in-season tactical decisions. Decisions on sowing season and selection of crops and varieties are most important and will have considerable weight with associated seasonal climate information. However, the knowledge levels of farmers on those decisions were ‘poor’. The factor analysis grouped all the farmers (n = 240) into two dimensions representing ‘poor’ or ‘moderate’ levels of knowledge on decision making. Knowledge level was directly related to innovativeness (r = 0.373), which could be improved through enhancing change-agency contact and extension participation. Therefore, it is important to design ‘climate educational programmes’ based on the decision-making approaches, farmers requirements (relevance of decisions) and their knowledge level on decision making using climate information.