Evaluating corporate high performance work systems via an intelligent model using complex T spherical fuzzy CoCoSo method

利用复杂T球面模糊CoCoSo方法,通过智能模型评估企业高绩效工作系统

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Abstract

High-performance work systems (HPWS) have become a key element for enhancing the performance and competitiveness of organizations in the corporate sector. Due to the complexity of HPWS, an effective and intelligent way of measuring its performance must be capable of handling uncertainty, interrelationships, and subjective expert judgments. This paper introduces a method that combines a high-quality multiple-criteria decision-making (MCDM) model operating under ambiguous and imprecise conditions, using the complex t-spherical fuzzy combined compromise solution (CTSF-CoCoSo) model to assess the features of HPWS. The seven criteria of evaluation in the current study are also determined by a thorough discussion of the HPWS literature and further adjusted by the experts to maintain construct validity and the applicability of the concept to corporate HR practices. An example involving three decision-makers, seven clearly defined evaluation criteria, and ten alternatives is presented to validate the model. In assessing alternatives, it was discovered that Alternative-2 is the best strategy to adopt in HPWS. The ranking stability and sensitivity of the proposed approach are greater than those of the current MCDM techniques. The implications of the findings are both theoretical and practical as they shed some light on the critical aspects of performance, as well as serving as a way of supporting strategy-based human resource decision-making. This model provides a dynamic and extensible model and is therefore not restricted to complex organizational evaluation situations.

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