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Human Systems Management (HSM) is an interdisciplinary, international, refereed journal. It addresses the need to mentally grasp and to in-form the managerial and societally organizational impact of high technology, i.e., the technology of self-governance and self-management.
The gap or gulf is often vast between the ideas world-class business enterprises and organizations employ and what mainstream business journals address. The latter often contain discussions that practitioners pragmatically refute, a problematic situation also reflected in most business schools’ inadequate curriculæ.
To reverse this trend, HSM attempts to provide education, research and theory commensurate to the needs to today’s world-class, capable business professionals. Namely the journal’s purposefulness is to archive research that actually helps business enterprises and organizations self-develop into prosperously successful human systems.
Authors: Singer, Alan E.
Article Type: Research Article
Abstract: This paper sets out an organizing framework for the extensive contemporary literature on the ethics of entrepreneurship. It consists of (i) a set of bi-polar components (or false-choices) such as economic efficiency vs. social justice, (ii) a set of spanning-themes such as character, imagination and intention, and (iii) a set of topical themes such as poverty, property-rights and corruption that are variously associated with the ethics of entrepreneurship and with global capitalism in general. The framework particularly facilitates the placement of existing contributions relative to each other, thus consolidating progress in the area and potentially guiding future works.
Keywords: Ethics, organizing-framework, typology
DOI: 10.3233/HSM-2010-0714
Citation: Human Systems Management, vol. 29, no. 2, pp. 69-78, 2010
Authors: Goletsis, Yorgos | Exarchos, Themis P. | Katsis, Christos D.
Article Type: Research Article
Abstract: Credit scoring or credit risk assessment is a domain of major importance for financial institutions. Accurate predictions can lead to significant savings for the institutions. In the current work we evaluate the use of an Ant Colony System (ACS) in the problem of credit scoring. ACS are nature inspired algorithms that search for the optimal solution, by mimicking the functions of ants. In our application artificial ants are applied for rule extraction. The performance of ant based rule extraction is compared against six widely used classification methods. All tests are complemented with feature selection approaches, for dimensionality reduction. Our evaluation …is performed using three different datasets with credit scoring instances. The obtained results indicate that the examined ant based approach, offers high accuracy comparative to the accuracies obtained by the rest of the classifiers. Considering the fact that our approach has the ability to extract classification rules, thus offering interpretation of results, it appears as a promising alternative classification method for credit scoring. Show more
Keywords: Credit scoring, ant colony systems, classification, feature selection, rule extraction
DOI: 10.3233/HSM-2010-0715
Citation: Human Systems Management, vol. 29, no. 2, pp. 79-88, 2010
Authors: Lovric, Milan | Kaymak, Uzay | Spronk, Jaap
Article Type: Research Article
Abstract: Agent-based stock markets as bottom-up models of financial markets allow us to study the link between individual investor behavior and aggregate market phenomena, and as such are a useful tool for investigating the implications of behavioral finance and investor psychology. In this paper we want to disentangle between the effects of investor sentiment and investor overconfidence. While investor optimism or pessimism influences the expectations of future returns, overconfidence is related to the precision of those expectations and is modeled as miscalibration. In an artificial stock market based on the LLS model, we find that more optimistic investors create more pronounced …booms and crashes in the market, when compared to the unbiased efficient market believers of the original model. In the case of extreme optimism, the optimistic investors end up dominating the market, while in the case of extreme pessimism, the market reduces to the benchmark model of rational informed investors. The overconfidence of investors is found to exacerbate the effects of investor sentiment. Show more
Keywords: Artificial stock market, agent-based modeling, behavioral finance, overconfidence, investor sentiment, optimism index, fuzzy aggregation
DOI: 10.3233/HSM-2010-0718
Citation: Human Systems Management, vol. 29, no. 2, pp. 89-101, 2010
Authors: Whalen, T. | Taylor, T. | Cohen, M. | Smolarski, J.
Article Type: Research Article
Abstract: Possibility theory is applied to assessing the relative risk associated with very rare, high-consequence hazards. The probability of rare negative events has to be estimated from a few past occurrences that are spread over long exposure periods, with countermeasures added in response to each event to attempt to guard against recurrence. Traditional risk assessments based on conditional probability and statistical expected value are very sensitive to the uncertainty associated with rare events. A new measure of possibility for events whose probability is not well measurably different from zero is proposed and illustrated in the context of possible release of hazardous …material from a high containment research laboratory and in the context of large insurance company failures. Strategies for managing and reducing risk that do not depend on well-measured probabilities are discussed. Show more
Keywords: Possibility, risk management, counterfactuals, laboratory safety, auditing
DOI: 10.3233/HSM-2010-0719
Citation: Human Systems Management, vol. 29, no. 2, pp. 103-113, 2010
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