Search results

This paper aims to propose guidelines for public sector managers in assessing the impact of outsourcing on business continuity (BC) strategies. This paper evaluated how public managers from the state of Pernambuco, Brazil, perceive outsourcing, considering BC and how it relates to the outsourcing of services and activities.

Theoretical lenses of outsourcing and BC were used to derive the study hypotheses. A questionnaire was drawn up to collect information to test the hypotheses. To test the proposed hypotheses, binary logistic regression was used through an empirical analysis of a sample of 51 Brazilian public managers.

This study found that when the public sector suffers from negative impacts of financial restrictions, outsourced services are the first ones to receive the negative impacts. This has had an adverse impact on BC in the public sphere. On the other hand, the authors verified that the public sphere’s capacity for resilience and the existence of specific methodologies to support public managers in outsourcing decision-making can contribute to BC.

This study assists public organizations to take advantage of internal outsourced services in the best possible way, making better use of public resources, gaining social legitimacy and legitimacy also in the provision of public services. However, each public sector can present different risks of non-continuity, and this aspect could not be considered in this research as well.

This study is a pioneer in highlighting the relationships between outsourcing strategies and BC in public services in Brazil. Through the guidelines discussed in this study, public managers could develop a more effective response to the implications of post-outsourcing budget constraints. In addition, the findings of this paper add to an understanding of the importance of business strategies for public services continuity and seek to help reduce uncertainties and better inform the government decision-making process.

This study aims to develop a talent selection model for learning organizations capable of connecting two groups, candidates in a talent hiring process and managers of the hiring company, in a reliable process, promoting organizational learning and increasing employee satisfaction.

This paper integrates egalitarian principles, an artificial intelligence mechanism founded on stable matching algorithms, and evaluating critical soft skills to enhance recruitment practices within learning organizations. The authors conduct a numerical real-world application in Python to showcase the model’s effectiveness. Five candidates were evaluated for five job positions. Moreover, 26 soft skills were analyzed by the five company leaders, relating them to the requirements of each job position and by all candidates, as a self-assessment process.

The model promoted egalitarian talent management because it motivates the candidates to choose the preferred position in a company, and the employers hire the best candidate. It is satisfactory for all participants in a company’s hiring process if the parties intend to be fair and egalitarian. The benefits of the process can be considered isolated (parties’ satisfaction) or a part of a company’s effort to stimulate an egalitarian culture in organizational values.

The information generated by the model is used to refine its selection process and improve its understanding of the job requirements and candidate profiles of the company. The model supports this idea, using the concepts of indifference, stability, egalitarianism and the soft skills required and identified to be more effective and learn about themselves.

This paper discusses an egalitarian point of view in the recruitment process. It is satisfactory for all participants in a company’s hiring process if the parties intend to be fair and egalitarian. The process’s benefits can be considered part of a company’s effort to stimulate an egalitarian culture in organizational values.

This paper brings an excellent future perspective and points to the company’s development of talent retention. The model simultaneously solves the evolution of talent management processes through new technologies and soft skills emerging in the postpandemic scenario.