درخت حوزه‌های تخصصی

Partnership quality has been known as one of the foremost critical determinants of outsourcing victory. Since the relationship is dynamic, it is important to understand both sides of the partner. The purpose of this study is design a model for the partnership quality in outsourcing services with focus on both sides. In order to achieve this goal, mixed method (qualitative-quantitative) and grounded theory approach have been used. In the qualitative section, in order to identify the categories of the contextual model of partnership quality, a semistructured interview has been used in the service provider and client section by theoretical sampling method. The statistical population in the qualitative section included all managers and heads and expert contractors in 90 contracts during the 3 years. The total number of statistical population in the qualitative section was 176 people. In the qualitative section, grounded theory and MAXQDA software are used for analysis. Then, through the coding process in three sections, open, central and selective data of qualitative section were organized. In the quantitative research section, the statistical population included district heads, deputies, officials, supervisors on the one hand, and all their contractors and representatives on the other. The total number of statistical population in the quantitative section was 623 people. In the quantitative research section, in order to test the obtained pattern, the required data were collected by a designed questionnaire. To analyses the data collected, the partial least squares (PLS) method was used. According to the results of this research, the most important operational strategies are, empowerment, standardization and technology improvement to achieve the partnership quality in outsourcing services.

The purpose of the study is to design a new behavioral model of blockchain technology acceptance in public banks through content analysis. Therefore, based on the theoretical literature and behavioral theories of technology acceptance, the primary conceptual model was presented. Then, by interviewing experts selected by snowball method, the relevant model was finalized. Theoretical validity and interpretive validity methods were used to measure the validity of interviews. To check the reliability of interviews, the test-retest reliability method has been used. The validity of the factors was checked through the Delphi technique and with fuzzy calculations. According to the results, four main factors of the behavioral model are: people, environment, organization, and technology. Totally 10 sub-factors and 36 indicators were identified. This model can contribute to public banks to understand how these various factors interact with each other and how they can be improved to achieve higher acceptance of blockchain technology.

Nowadays, researchers and managers believe that paying attention to employees' thoughts facilitates sustainable competitive advantage in organizations. After the introduction of cognitive science into organizations, the identification of what it is, how it is formed, and the formulation of Counterfactual Thoughts (CTs) have been investigated and analyzed in the field of Human Resources (HR). In this study, a systematic review of the literature in the field of CT has been done with the aim of identifying the antecedents and key consequences of this field and analyzing them. In this research, a two-stage methodology has been considered including (i) Extraction of antecedents and consequences, (ii) Weighting of antecedents. In the first stage, using the screening of articles based on the seven-step method of Sandelowski and Barroso, the antecedents and consequences of CTs, synthesis and interpretation have also been implemented through the coding method of qualitative interpretive meta-analysis. In the second stage, the consequences extracted in the field of counterfactuals are weighted using the matrix of paired comparisons based on the opinions of experts in the field of HR and AHP, which can be used to evaluate employees' thoughts and behavior. Based on the screening of the articles, the antecedents are categorized into 4 general concepts with 12 codes, and the consequences are classified into 2 and 8 codes. The results of the AHP analysis show that the normalization of the condition related to the behavioral outcome has the greatest impact on the evaluation of employees' thoughts and behavior, while the regulation of related emotions as a result of attitude has the least impact among the codes introduced in this evaluation.