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The management literature has been investigating teams’ human capital resources as a predictor of their task performance. However, our knowledge regarding the precise structure of the human capital-performance relationship, as well as the resource orchestrator role managers play in this relationship, remains limited. In this study, we relax the ass...
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... fit to the data). In this study (Figure 2), we estimated the model by using (1) the teams' gross human capital resources; (2) the gross human capital resources, managers' human capital resources and the interaction term; and (3) the gross human capital resources, managers' human capital resources, the interaction term and the active human capital resources (the whole model). The second model had higher predictive validity (mean squared error = 254) than the first model (mean squared error = 298), and the third model, which included all variables, had higher predictive validity than the two other models (mean squared error = 139). ...
Citations
... Human capital management (HCM) represents a set of activities for managing the human capital (HC) of an organization. It encompasses planning, recruitment and selection, placement, development, and training, maintaining employee satisfaction, engagement, and collaborative activities to manage individual and organizational competencies [76][77][78][79][80][81][82][83]. The mentioned idea is also complemented by the European Partnership for Public Strategies (2022) [84] and Kianto et al. (2017) [85], who argue that HCM aims to manage people in such a way as to ensure greater efficiency and productivity in the enterprise. ...
... The introduction of elements, such as automation, digitalization, or robotization will cause employees to work much more efficiently than when the company did not use such elements [4,86,87]. Managers in companies should motivate employees to take a proactive approach to education [83,[88][89][90][91][92][93]. ...
Countries of the EU are trying to create a single digital market. Therefore, this article aims to evaluate the current situation in the field of readiness of economic entities in Slovakia for challenges in the field of human capital management (HCM) when implementing digital technologies in their processes and to propose recommendations regarding the implementation of digital technologies. We used basic scientific methods and calculated Cronbach’s alpha, descriptive statistics, and the chi-square test to detect dependencies between variables. This article processes data from a questionnaire survey completed by managers or owners of economic entities in Slovakia. In 2020, we received answers from 905 respondents, and in 2021, our sample consisted of 561 respondents. We found that among the most used is digitalization in the field of GDPR and not the use of a personnel information system (HRIS). The assumptions that the size of the entity and the prevailing ownership influence the use of digital technologies were also confirmed. The article’s originality lies in the topicality of the examined issue and the extensive questionnaire survey spanning two years. It follows from the findings from previous articles, which pointed to the extremely low values of Slovakia within the DESI index.
... Likewise, HC is generated at the individual level; it belongs to employees and is accumulated to form the overall HC of the organization. This process differs from one organization to another, which makes HC a unique resource (Harris and Brown, 2021;Tuncdogan et al., 2021;Munjal and Kundu, 2017;Bryant-Kutcher et al., 2009). ...
... It can not only perform efficient classification tasks on massive data of research objects, but also find a nonlinear mapping relationship from these tedious data. ese nonlinear mapping relationships are a relationship that is difficult to discover by manual methods or empirical formulas [16,17]. With the development of big data technology, it has emerging methods such as deep learning and reinforcement learning. ...
The innovative development of an enterprise is a necessary factor for its long-term development, and science and technology is a necessary driving force for its development. An effective management of human resources management will find more high-quality talent, and it will also be efficient management of the enterprise staff. The efficiency of the traditional human resource management is relatively low; the approach will produce larger errors for the enterprise. This study combines the Hadoop distributed platform and big data technology to conduct a decision recommendation research on the relevant factors of human resource management. In this study, the decision tree is used to classify the data related to human resource management. The data feature of human resource will be predicted by the neural network method, and human resource managers will refer to the prediction data from the output layer of neural network. Human resource managers will make corresponding decisions and recommendations. The research results show that Hadoop technology and big data technology have better accuracy in human resource management recommendation system, which contains ConvLSTM method and decision tree method in this study. The maximum prediction error of the ConvLSTM algorithm in predicting the relevant factors of the human resource decision-making system is only 2.67%, and this part of the error comes from the employee-job matching index. The smallest forecast is only 1.98%.
... Likewise, HC is generated at the individual level; it belongs to employees and is accumulated to form the overall HC of the organization. This process differs from one organization to another, which makes HC a unique resource (Harris and Brown, 2021;Tuncdogan et al., 2021;Munjal and Kundu, 2017;Bryant-Kutcher et al., 2009). ...
