Farming under constrained budgets: Practices of agricultural credit users in central Lombok, Indonesia

There has been a long dependency on credit by Indonesian farmers as a result of the lack of capital to apply proper farming practices. This paper describes the farming activities applied by agricultural credit users in Central Lombok, Indonesia. A survey was conducted during July 2001- March 2002 of 65 farmers making use of government or private credit in three villages within the Regency. Data from the farmers were collected using face-to-face, semi-structured interviews. Survey results indicated that on average, farmers had some 20 years experience of farming, were aged 40 years, but lacked of formal education. Their main asset was cropping land with average landholding of 0.69 ha. As a consequence of their capital constraints, farmers were commonly making use of credit to finance their farming activities, including both production of rice as the main crop and secondary crops. Farmers generally applied less than recommended amount of inputs in their farming practices, since the amount of credit they obtained was limited. As a result, their farms become less productive and their repayment capability of loans diminished. Of 65 farmers interviewed, 54 could earn extra income by engaging in a variety of non-farm activities, which contributed on average some 36% to family incomes of over Rp 5 million (A$ 1 thousand). The average credit repayment rate made by agricultural producers was 60%. The repayment made did not always reflect farm production capacity, being sometimes supported by other borrowings. The greater role of credit is not in increasing agricultural production or improving farmers’ income, but in helping them to sustain farm production and their living. Farmers need a bigger amount of credit to make an impact on their livelihood. This should be accompanied by extension services for farmers to enable better use of credit and to change their attitude towards it. As well, farmers require to be equipped with technical and market skills to run a business. Interdisciplinarity, holistic analysis, and an expansion of traditional ‘agricultural’ interests to embrace the span of interests included in rural livelihood, are each critical features of revision of the existing system.

Changes in social identity when joining a new group: The role of individual-level and group-level adaptation processes

While classic intergroup theories have specified the processes explaining situational shifts in social identification, the processes whereby social identities change more profoundly and become integrated within the self have to be proposed. To this aim, the present studies investigate the processes by which group members integrate a new social identity as they are joining a new group. Combining a social identity approach and stress and coping models, this research tests if social factors (i.e., needs satisfied by fellow group members, social support), have an impact on the adaptation strategies group members use to deal with the novelty of the situation and to fit into their new group (seeking information & adopting group norms vs. disengaging). These strategies, in turn, should predict changes in level of identification with the new social group over time, as well as enhanced psychological adjustment. These associations are tested among university students over the course of their first academic year (Study 1), and among online gamers joining a newly established online community (Study 2). Path analyses provide support for the hypothesised associations. The results are discussed in light of recent theoretical developments pertaining to intraindividual changes in social identities and their integration in the self.

When electronic management tools work - and don't work - in social-based distribution channels:a study of IT manufacturers and resellers

Electronic information tools have become increasingly popular with channel manufacturers in their efforts to manage resellers. Although these tools have been found to increase the efficiency of communications, researchers and practitioners alike have questioned their effectiveness. To investigate how top-down electronic information affects social channel relationships we consider the use of such tools in information technology distribution channels. Using electronic communications theory and channel governance theory we hypothesize that the usefulness of the tools is a function of the type of information inherent in each tool (demand creation information or supply fulfillment information) and the particular communications characteristics of this information.

The boundaries of reporting sustainable development in social housing

The Registered Social Landlord (an independent housing association in the UK) examined here was widely recognized as providing an example of good governance. The organization was using extensive internal reporting, both corporate and quasi-governmental in language, to try to accurately capture different aspects of performance. This article reveals that reporting sustainable development has boundaries to be overcome, particularly in measuring performance of environmental and community activities. © 2008 The Authors.

Group consensus in social influence:type of consensus information as a moderator of majority and minority influence

Three experiments investigated the effect of consensus information on majority and minority influence. Experiment 1 examined the effect of consensus expressed by descriptive adjectives (large vs. small) on social influence. A large source resulted in more influence than a small source, irrespective of source status (majority vs. minority). Experiment 2 showed that large sources affected attitudes heuristically, whereas only a small minority instigated systematic processing of the message. Experiment 3 manipulated the type of consensus information, either in terms of descriptive adjectives (large, small) or percentages (82%, 18%, 52%, 48%). When consensus was expressed in terms of descriptive adjectives, the findings of Experiments 1 and 2 were replicated (large sources were more influential than small sources), but when consensus was expressed in terms of percentages, the majority was more influential than the minority, irrespective of group consensus.

Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.