954 resultados para customer needs identification


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Peak electricity demand requires substantial investment to update transmission, distribution and generation infrastructure. A successful community peak demand reduction project was examined to identify residential consumer motivational and contextual factors involved in their decision to adopt/not adopt interventions. Energy professionals actively worked to achieve community 'peer' membership and by becoming a trusted information source, facilitated voluntary home energy assessment requests from over 80% of the residential community. By combining and tailoring interventions to the specific needs and motivations of individual householders and the community, interventions promoting energy conservation and efficiency can be effective in achieving sustained reduction in peak demand.

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Purpose The purpose of this paper is to explore what the attitudes of small firm owner-managers are to developing the skills of their key resources and then examine how these and other factors affect owner-managers’ preferences for training these employees. Design/methodology/approach This study of training in small road transport firms in West Australia is cast in light of the literature on human resource management in small firms underpinned by insights drawn using the resource based view of the firm. Small firms (less than 20 people) dominate this industry, while the increasing freight task, and extreme distances between West Australian ports, towns and mines highlight this sectors’ importance. Survey results from 39 small road transport firms and interviews with nine owner-managers are analysed. Findings Legislative, regulatory and licensing requirements were shown to be a key determinant of skills development. Employers ensured that basic standards for employee certification and qualification were met, as the penalty for not doing so would be too high. Regulations drove the need for certain types of training – licenses, fatigue management, occupational health and safety, handling dangerous goods, the Maritime Security Identification Card card, forklift license, mine site inductions – while owner-managers knew where to get the training their staff needed. Although regulation appeared most visible in prescribing what happened in relation to training for drivers, the relevance of owner-managers’ attitudes could not be ignored, nor could conditions in the firms external environment as this shaped how these requirements were met. Research limitations/implications The RBV is useful in showing how skill development enabled similarity in skills across firms, while the attitudes owner-managers and economic and social conditions meant what happened in firms around skill development varied. The importance of small firm owner-managers’ attitudes are clearly highlighted and shown to influence organizational decisions and choices around training, but these were not independent of the regulatory framework and the economic and social conditions within which the firm operated. The small firms in this study did engage workers in formal training when necessary but it was put in the context of the idiosyncratic approach of the owner-manager and the day-to-day needs of the firm. “Training” was essentially about ensuring certain types of skills were held by employees and then passing on knowledge to ensure the behavior of employees was consistent with the owner-manager’s vision for the firm in its current environment. Originality/value Ways industry and government can encourage training activity that goes beyond the day-to-day firm needs are suggested.

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Timely access to effective technical information is a key ingredient of profitable strawberry production. Through the Better Berries Program, a joint RD&E initiative of government and industry, a number of information products and services have been provided in recent years to Australia's subtropical strawberry industry, centred in southern Queensland. However, there is a lack of knowledge of how well these are meeting the information needs of growers, both in content and delivery. To better understand grower information use and needs, a stratified sample of 25 growers was interviewed on-farm during the 2004 season. Growers were asked about how they currently accessed information, what they thought of a range of information products and ideas on show, and what advice they would provide for information development in the future. Results indicated that information sought by growers and the style in which it is best presented, varied considerably with grower experience, but little with farm size. New growers had a wide range of needs while the needs of experienced growers were focused mainly on problem identification and new production development. Interestingly, the overwhelming majority across all sectors still preferred paper-based information products despite their extensive use of computers for business purposes. The findings were used to develop a strategy for an improved range of technical information products and services that are more accessible, easier to use, more timely, and more relevant to the needs of growers.

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As a first step to better targeting the activities of a project for improving management of western flower thrips, Frankliniella occidentialis, (WFT) in field grown vegetable crops, we surveyed growers, consultants and other agribusiness personnel in two regions of Queensland. Using face-to-face interviews, we collected data on key pests and measures used to manage them, the importance of WFT and associated viral diseases, sources of pest management information and additional skills and knowledge needed by growers and industry. Responses were similar in the two regions. While capsicum growers in one northern Queensland district had suffered serious losses from WFT damage in 2002, in general the pest was not seen as a major problem. In cucurbit crops, the silverleaf whitefly (Bemisia tabaci biotype B) was considered the most difficult insect pest to manage. Pest control tactics were largely based on pesticides although many respondents mentioned non-chemical methods such as good farm hygiene practices, control of weed hosts and regular crop monitoring, particularly when prompted. Respondents wanted to know more about pest identification, biology and damage, spray application and the best use of insecticides. Natural enemies were mentioned infrequently. Keeping up to date with available pesticide options, availability of new chemicals and options for a district-wide approach to managing pests emerged as key issues. Growers identified agricultural distributors, consultants, Queensland Department of Primary Industries staff, other growers and their own experience as important sources of information. Field days, workshops and seminars did not rank highly. Busy vegetable growers wanted these activities to be short and relevant, and preferred to be contacted by post and facsimile rather than email. In response to these results, we are focusing on three core, interrelated project extension strategies: (i) short workshops, seminars and farm walks to provide opportunities for discussion, training and information sharing with growers and their agribusiness advisors; (ii) communication via newsletters and information leaflets; (iii) support for commercialisation of services.

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Researchers and practitioners have been preoccupied with identifying ways for larger organizations to acquire and manage knowledge, however far less research attention has been directed towards these same pursuits in small and medium-sized enterprises (SMEs). This paper examines how SMEs engage in knowledge identification and acquisition; in particular how they identify knowledge needs and source this knowledge to enhance their business. The research studied six SMEs in Australia and Denmark. Contrary to prevailing assumptions, the findings suggest that SMEs engage in identification and sourcing of critical knowledge, albeit often with less than formal processes. These organizations relied on business plans to direct knowledge activities and ensure balance between long-range planning and flexibility. The results address a lack of empirical evidence about SME approaches to knowledge identification and acquisition, and demonstrate that although SMEs may approach such activities in an informal way, they are nonetheless deliberate and strategic in their knowledge activities.

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We conducted an experiment to investigate the impact of sport scandal on consumer attitudes toward a range of sport stakeholders. We examined the effects of fans’ social identity (fan of scandalized team vs. fan of rival team), scandal severity (single perpetrator vs. multiple perpetrators) and the sponsor brand’s response to the scandal (sponsorship retention vs. termination) on consumers’ attitudes toward the implicated team, the scandal perpetrators, the sport, and sponsor brand. We find evidence of differential reactions to scandal reflecting social identity, such that fans support their own team despite increased scandal severity but negatively judge a rival team’s transgressions. Results suggest that where fans are concerned, sponsors may be better served to continue with a sponsorship following scandal than to terminate, even for some forms of severe scandal. However, termination may receive more positive evaluation from rival team fans; hence continuation of sponsorship needs to accompany a tempered approach.

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The aim of this study was to identify and describe the types of errors in clinical reasoning that contribute to poor diagnostic performance at different levels of medical training and experience. Three cohorts of subjects, second- and fourth- (final) year medical students and a group of general practitioners, completed a set of clinical reasoning problems. The responses of those whose scores fell below the 25th centile were analysed to establish the stage of the clinical reasoning process - identification of relevant information, interpretation or hypothesis generation - at which most errors occurred and whether this was dependent on problem difficulty and level of medical experience. Results indicate that hypothesis errors decrease as expertise increases but that identification and interpretation errors increase. This may be due to inappropriate use of pattern recognition or to failure of the knowledge base. Furthermore, although hypothesis errors increased in line with problem difficulty, identification and interpretation errors decreased. A possible explanation is that as problem difficulty increases, subjects at all levels of expertise are less able to differentiate between relevant and irrelevant clinical features and so give equal consideration to all information contained within a case. It is concluded that the development of clinical reasoning in medical students throughout the course of their pre-clinical and clinical education may be enhanced by both an analysis of the clinical reasoning process and a specific focus on each of the stages at which errors commonly occur.

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The CGIAR Research Program on Aquatic Agricultural Systems (AAS) seeks to reduce poverty and improve food security for the millions of small-scale fishers and farmers who depend on the world’s floodplains, deltas and coasts. AAS combines more conventional approaches for introducing and scaling technical innovations, such as applied research and training, with approaches that foster innovation and promote institutional and policy change. Specifically, AAS utilizes participatory action research with communities to identify technology and policy solutions that best meet community long-term needs. One of the themes identified under AAS is the role of self-help groups in increasing livelihood resilience of agriculture and fisheries communities. As AAS establishes a hub of operations in Cambodia, AAS and Oxfam America are cooperating to investigate the potential of community-based self-help groups as a strategy for AAS implementation. As part of this cooperation, Oxfam America undertook this consultancy to analyze and describe the role, efficiency and effectiveness of the various types of self-help groups in Cambodia. This report gives an overview of this program which aims to conduct a field-based study to identify the types, main characteristics and effectiveness of self-help groups, with a particular focus on livelihood resilience of agriculture and fisheries communities.

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The article presents a two-part guideline in mangrove reforestation. The first part is zonation, which is the process of determining what species are particularly suited to plant in a particular site. While, plantation establishment is the second part, it includes guides in the identification of species, selection of planting site, preparation of the planting sites, seed collection, handling and transporting of seeds, and planting.

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Class Condrichthyes consist of two sub-classes: Holocehali and. Elasmobranchii, the second one are more divers and has more importance. Selachimorpha (sharkes) and Batidoidimorpha (rays and skates) are two super-order of Elasmobranchii, which they have crucial role in ecological balance in marine ecosystmes. Except few cases, most of sharks and rays (rays and skates) are not well identified, so a lot of works need to be done in this regards. The area of study is located between 49°, 35' and 52°, 33' E and between 27°, 21' and 30°, 02' N in depth of 7 to 78 in. Study were conducted diuring August 1998, September 1999. Samples were taken during 3 sea cruises from 70 bottom trawl net. All sharks and batoid fishes were identified based on biometric specifications (weight, total, length and sexuality for both group and extra biometric specifications, disc width, disc length, and tail length only for, batoid fishes). The 1140 specimens of batoid fishes identified belonged to 6 families, and 18 species. 3 new species were identified, they are Himantura sp.1 and Himantura sp.2 belonged to Dasyatidae family and Rhinobatos sp. belonged to Rhinobatidae Familiy. It needs more works and more adaquate ducuments for cl.earfing scientific names of these species. The 275 specimens of sharks identified belonged to 6 families and 10 species. Chiloscyllium sp. belonged to Hemiscylliidae, family as a new species was identified.

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This study has developed an improved subjective approach of classification in conjunction with Step wise DFA analysis to discriminate Chinese sturgeon signals from other targets. The results showed that all together 25 Chinese sturgeon echo-signals were detected in the spawning ground of Gezhouba Dam during the last 3 years, and the identification accuracy reached 90.9%. In Stepwise DFA, 24 out of 67 variables were applied in discrimination and identification. PCA combined with DFA was then used to ensure the significance of the 24 variables and detailed the identification pattern. The results indicated that we can discriminate Chinese sturgeon from other fish species and noise using certain descriptors such as the behaviour variables, echo characteristics and acoustic cross-section characteristics. However, identification of Chinese sturgeon from sediments is more difficult and needs a total of 24 variables. This is due to the limited knowledge about the acoustic-scattering properties of the substrate regions. Based on identified Chinese sturgeon individuals, 18 individuals were distributed in the region between the site of Gezhouba Dam and Miaozui reach, with a surface area of about 3.4 km(2). Seven individuals were distributed in the region between Miaozui and Yanshouba reach, with a surface area of about 13 km(2).

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Nearest neighbor search is commonly employed in face recognition but it does not scale well to large dataset sizes. A strategy to combine rejection classifiers into a cascade for face identification is proposed in this paper. A rejection classifier for a pair of classes is defined to reject at least one of the classes with high confidence. These rejection classifiers are able to share discriminants in feature space and at the same time have high confidence in the rejection decision. In the face identification problem, it is possible that a pair of known individual faces are very dissimilar. It is very unlikely that both of them are close to an unknown face in the feature space. Hence, only one of them needs to be considered. Using a cascade structure of rejection classifiers, the scope of nearest neighbor search can be reduced significantly. Experiments on Face Recognition Grand Challenge (FRGC) version 1 data demonstrate that the proposed method achieves significant speed up and an accuracy comparable with the brute force Nearest Neighbor method. In addition, a graph cut based clustering technique is employed to demonstrate that the pairwise separability of these rejection classifiers is capable of semantic grouping.

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One of the main pillars in the development of inclusive schools is the initial teacher training. Before determining if it is necessary to make changes (and of what type) in training programs or curriculum guides related to the attention to diversity and inclusive education, the attitudes of future education professionals in this area should be analyzed. This includes the identification of the relevant predictors of inclusive attitudes. The research reported in this article pursued this objective, doing so with a quantitative survey methodology based on the use of cross-sectional structured data collection and statistical analyses related to the quality of the attitude questionnaire (factor analysis and Cronbach's alpha), descriptive statistics, correlations, hypothesis tests for difference of means, and regression analysis in order to predict attitudes towards inclusion in education. Firstly, the results show that the participants held very positive attitudes toward the inclusion of students with special educational needs. Particularly, older respondents, those with a longer training and, to a lesser extent, women and those who had been in touch with disabled people stood out within this attitude. Secondly, it is evidenced that self-transcendence values ​and, more weakly, contact, function as robust predictors of attitudes of future practitioners towards the inclusion of students with special needs. Some applications for the initial professionalization of educators are suggested in the discussion.

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It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.