An exploration of the attitudes and strategic responses of soleproprietor micro-enterprises in adopting information and communication technology

This article analyses longitudinal case-based research exploring the attitudes and strategic responses of micro-enterprise owners in adopting information and communication technology (ICT). In so doing, it contributes to the limited literature on micro-enterprise ICT adoption, with a particular focus on sole proprietors. It provides a basis for widening the theoretical base of the literature pertaining to ICT adoption on two levels. First, a framework is developed which integrates the findings to illustrate the relationships between attitudes towards ICT adoption, endogenous and exogenous influencers of these attitudes and subsequent strategic response in ICT adoption. Second, building upon this framework the article reveals the unique challenges, opportunities and implications of ICT adoption for sole-proprietor micro-enterprises. © The Author(s) 2012

Visualising Textual Knowledge about Risks to Aid Risk Communication

This paper demonstrates a potential application for latent semantic analysis and similar techniques in visualising the differences between two levels of knowledge about a risk issue. The HIV/AIDS risk issue will be examined and the semantic clusters of key words in a technical corpora derived from specific literature about HIV/AIDS will be compared with the semantic clusters of those in more general corpora. It is hoped that these comparisons will create a fast and efficient complementary approach to the articulation of mental models of risk issues that could be used to target possible inconsistencies between expert and lay mental models.

A defeasible reasoning model of inductive concept learning from examples and communication

This paper introduces a logical model of inductive generalization, and specifically of the machine learning task of inductive concept learning (ICL). We argue that some inductive processes, like ICL, can be seen as a form of defeasible reasoning. We define a consequence relation characterizing which hypotheses can be induced from given sets of examples, and study its properties, showing they correspond to a rather well-behaved non-monotonic logic. We will also show that with the addition of a preference relation on inductive theories we can characterize the inductive bias of ICL algorithms. The second part of the paper shows how this logical characterization of inductive generalization can be integrated with another form of non-monotonic reasoning (argumentation), to define a model of multiagent ICL. This integration allows two or more agents to learn, in a consistent way, both from induction and from arguments used in the communication between them. We show that the inductive theories achieved by multiagent induction plus argumentation are sound, i.e. they are precisely the same as the inductive theories built by a single agent with all data. © 2012 Elsevier B.V.

Identifying functional stakeholder clusters to maximise communication for the ecosystem approach to fisheries management

Interaction with ecological models can improve stakeholder participation in fisheries management. Problems exist in efficiently communicating outputs to stakeholders and an objective method of structuring stakeholder differences is lacking. This paper aims to inform the design of a multi-user communication interface for fisheries management by identifying functional stakeholder groups. Intuitive categorisation of stakeholders, derived from survey responses, is contrasted with an Evidence-Based method derived from analysis of stakeholder literature. Intuitive categorisation relies on interpretation and professional judgement when categorising stakeholders among conventional stakeholder groups. Evidence-Based categorisation quantitatively characterises each stakeholder with a vector of four management objective interest-strength values (Yield, Employment, Profit and Ecosystem Preservation). Survey respondents agreed little in forming intuitive groups and the groups were poorly defined and heterogeneous in interests. In contrast the Evidence-Based clusters were well defined and largely homogeneous, so more useful for identifying functional relations with model outputs. The categorisations lead to two different clusterings of stakeholders and suggest unhelpful stereotyping of stakeholders may occur with the Intuitive categorisation method. Stakeholder clusters based on literature-evidence show a high degree of common interests among clusters and is encouraging for those seeking to maximise dialogue and consensus forming. © 2013 Elsevier Ltd.