Object classification under ignorance using CaRBS: the case of the European barn swallow

Environ Plann C Gov Policy

Pickernell

et al. 2013

With this study we evaluate the impact of diff erent training methods (TMs) on small and medium-enterprises' (SMEs') business performances, utilising a dataset of 3521. We consider the relationship between the satisfaction SMEs have towards their employees' training needs being met by a diverse range of TMs and the levels of impact the training has had on business performance. To investigate both the interdependence and dependence of satisfaction levels of training needs met with business performance, we undertake bivariate correlations and multivariate regression-type analyses (using Regression-type Classifi cation and Ranking Belief Simplex). The results presented off er novel insights into the relationships between TMs and business performance.

Section: Introductionmentioning

confidence: 97%

Evaluating the Impact of Different Training Methods on SME Business Performance

Jones

Environ Plann C Gov Policy

Pickernell

et al. 2013

“…The non-parametric technique utilised in this study is the CaRBS technique, introduced in Beynon (2005a;2005b), see Appendix A for a technical description of the technique. Since its introduction the CaRBS technique has been applied in the areas of: public administration (Beynon and Kitchener, 2005), medicine (Beynon et al, 2006a, Beynon et al 2006b, animal biology (Beynon and Buchanan, 2004), E-learning (Jones and Beynon, 2007) and strategy (Beynon et al, 2010). In the CaRBS technique there is the allowance for an a priori considered non-certainty of the association of motivational characteristics to the student aspiration problem considered.…”

Section: See Table 1 Herementioning

confidence: 99%

Investigating the motivation for enterprise education: a CaRBS based exposition

International Journal of Entrepreneurial Behavior &Amp; Research

Jones

Packham

et al. 2014

Investigating the Motivation for Enterprise Education: A CaRBS based Exposition Purpose This study investigates student motivations for undertaking an EU funded entrepreneurship education programme in the Objective One areas of Wales and the relationships between motivation characteristics and their ultimate employment and self-employment aspirations. For both statistical and explanatory reasons a novel data mining technique (CaRBS) is used to undertake the equivalent of classification analysis. The study considers what relationships certain motivation characteristics have to students' aspirations, specifically in terms of their intention to be self-employed or employed. Design/methodology/approach The study examined enrolment data of 720 students on an entrepreneurial education programme called E-College Wales, and have known aspirations to either employment or self-employment. The Classification and Ranking Belief Simplex (CaRBS) technique is employed in the classification analyses undertaken, which offers an uncertain reasoning based visual approach to the exposition of findings, and which has particular relevance when the data is non-parametric and the considered potential relationships are non-linear. Findings The classification findings demonstrate the level of "contribution" of the different motivation characteristics to the discernment of students between self-employed and employed aspirations. The most strongly contributing characteristics were, motivations to undertake a business start-up, interest in the subject matter and intent to achieve the qualification. For these characteristics, further understanding is provided with respect to the student demographics of gender and student age (in terms of the association with aspirations towards being self-employed or employed). For example, with respect to start-up, the older the student, the increasing association with employment rather than self-employment career aspirations. Research limitations/implications The study identifies candidate motivation characteristics and the demographic profile for student's undertaking an entrepreneurial education programme. Knowing applicant aspirations should inform course design, pedagogy and its inherent flexibility, and recognise the specific needs of certain student types. Originality/value The study contributes to the literature examining the motivations for undertaking entrepreneurship education and categorising motivating factors. These findings will be of value to both education providers and researchers.

“…Drawing from DST [19,20], the aim of CaRBS [17,18] is to construct a body of evidence (BOE). This is defined as m .…”

Section: Smarter and Carbs Ranking Techniquesmentioning

confidence: 99%

“…The weights used represent the importance (influence) of the attributes to the preference problem considered. 1 This study compares two MAUT-based ranking techniques, SMARTER (Simple Multiattribute Rating Technique Exploiting Ranks [16]) and CaRBS (Classification and Ranking Belief Simplex [17,18]). The context of the study is an attempt to rank state LTC systems in terms of their balance (BalSys) using six attributes shown to be important in the research literature.…”

Section: Introductionmentioning

confidence: 99%

Ranking the ‘Balance’ of State Long-Term Care Systems: A Comparative Exposition of the SMARTER and CaRBS Techniques

Kitchener

2005

Health Care Manage Sci

The use of attribute sets to rank units of health provision (e.g., states, organizations) against policy goals is an essential task within decision-making and analysis. This paper elucidates and compares two techniques, SMARTER (Simple Multiattribute Rating Technique Exploiting Ranks) and CaRBS (Classification and Ranking Belief Simplex), within an expositional ranking of US states' long-term care (LTC) systems against the policy goal of providing a balance between (traditionally dominant) institutional care, and alternative home and community-based services (HCBS). While the (more established) SMARTER technique is used primarily for comparative purposes, greater emphasis is placed on elucidating CaRBS which is based on the Dempster-Shafer theory of evidence. It is shown that CaRBS offers four appealing features for health policy analysis: (1) the capacity to rank using either of two confidence measures (DST-related belief and plausibility values), (2) a systematic approach to managing missing data, (3) the production of stable rankings, and (4) the simplex plot method of data representation. In addition to discussing the LTC policy implications of the study findings, the issues of rank order stability and the management of missing data are discussed with respect to the two techniques employed.