Human tacit signals at organization performance development

Marko Kesti, Antti Syväjärvi

Tutkimustuotokset: Kirjoitus lehdessä tai erikoisnumeron toimittaminenArtikkeliTieteellinenvertaisarvioitu

9 Sitaatiot (Scopus)


Purpose - The purpose of this paper is to deal with tacit signals and organization performance development. Tacit signals are personal guiding beliefs that arise from tacit knowledge. The paper describes theoretical hypotheses how tacit signal method is utilized in competence measurement and organization performance improvement. Theories are evaluated by empirically grounded study. Design/methodology/approach - The tacit signal approach is linked to human pressure-performance theory of inverted U-curve, known as Yerkes-Dodson law. Moreover, a new mental model of five interrelated competences is used in order to understand the pluralistic nature of organization development. These five competences are management, leadership, culture, skills, and processes. The paper describes how competences can be studied by tacit signals, offering positive elements for both management and performance. The case study is done in Finnish commercial business enterprise of approximately 1,000 employees. Findings - Empirically grounded case study supports the theoretical approach, showing that tacit signals are in correlation to organization performance. Tacit signals help working groups identifying their collective dissonance in a way that will help them to increase emotional intelligence and performance. In the case, company significant improvement in profitability is found. Originality/value - The paper connects researcher innovation of tacit signals to organization competence measurement. This paper supports hypotheses that persons have tacit knowledge of personal situation at pressure-performance curve. This situation can be measured for each competence by tacit signal inquiry which guides to optimal improvement which strengthens the group emotional intelligence and increases performance. The described tacit signal method and system intelligence model gives additional value to further scientific studies.

JulkaisuIndustrial Management and Data Systems
DOI - pysyväislinkit
TilaJulkaistu - 1 tammik. 2010
OKM-julkaisutyyppiA1 Vertaisarvioitu alkuperäisartikkeli


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