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In spite of emphasis on role of organizational resource and human resources in particular, on entrepreneurship in literature of management, has not been presented an integrated pattern for Iranian organizations that measures influence of hr subsystems on entrepreneurship. By concentration of key role of human resources on entrepreneurship, present research is seeking to consider influence of different practices of human resource management on promoting of entrepreneurship in oil industry of Iran. Research methodology includes both descriptive and correlation analysis based on structural equation modeling. Data was collected by means of questionnaire that was distributed among top and middle manager of Contracting company in oil industry. Research result Indicates that human resource subsystems including human resource Acquisition, work design, development, labor relation and compensation, have influence on organizational entrepreneurship. And only training has not any impact on entrepreneurship. Furthermore, research indicates that the most impact of human resource management on entrepreneurship is indirectly and through creating supportive environment of innovation.

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Professionalism is a key concept in the sociology of work, the sociology of occupations, the sociology of professions, management, public administration, Organizational Behavior and in general, organizations and societies at large. Research evidence suggests that executives and top managers have limited attitudes toward human resource function and human resource practitioners, experts and human resource managers but today, new realities of organizations in the global level have put the emphasis on professional status of human resources around the world. Therefore, the main objective of this research is to identify influencing factors on HR professionalism and the dimensions and components of human resource professionalism in organizations. In order to achieve this goal, this research has been carried out using a qualitative method (Meta-analysis). The tool for collecting data and information in this study is the past documents in this field, which generally consists of 36 articles. The method of data analysis is based on open coding. The results indicate that the factors affecting the professionalism of human resources can be based on three general categories (environmental, organizational and individual) and identified dimensions can be analyzed on nine dimensions (governing body, ethical code, independence, certification, legal status, contribution to Society, the body of knowledge, research base, identification). Finally, based on the findings of the study, suggestions are presented.

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Employees are the most important assets of the organization and the performance of the organization depends on their performance. Achieving high performance of the workforce requires the identification of employee communication mechanisms, which is pursued in the framework of the concept of employee relationship management (ERM). Employee relationship management is a strategic tool and a kind of human resource management process that focuses on the continuity and strengthening of relationships between organizations and employees by relying on improving relationships and creating shared perspectives. This study aims to develop a practical framework for employee relationship management in the organization and is analytical-descriptive. Data collection was based on interviews with 14 senior and middle managers of Tondgooyan Oil Refining Company. Based on the data analysis, the obtained codes were classified into six main activity groups including Knowledge Management, Relationship Management, Employee Assistance Program Management, Employee Development Program Management, Employee Cognitive Program Management and Employee Involvement and finally each subgroup of activities is assigned to key and non-ley employees.

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Objective: Despite massive investments in the field of digital human resource management, the failure rate of these projects is high. One of the main reasons for the failure of these projects is the lack of a proper roadmap and methodology for digital human resources. Therefore, the purpose of this study is to provide a roadmap for digital transformation in the field of human resources.
Methodology: The present study was conducted using a meta-combined method. The data collection tool in the present study is past documents in this field, which generally includes 31 articles. The data analysis method is based on three-step coding.
Findings: The results indicate that the roadmap for digital transformation in the field of human resources includes three layers of infrastructure, processes and goals. Infrastructure layer includes: new technical and technological factors, human and cultural factors, managerial factors and organizational factors; The process layer includes three main categories: support activities, core activities and evaluation and development activities, and the objective layer includes: digital staff, digital work environment, strategic integration, improving staff experience, improving time, cost and quality of human resource services.

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The advancement of technology and its widespread applications has given rise to a new type of business, known as platform businesses. Algorithms are essential tools for platforms to manage operations and simplify tasks for business owners. However, the use of algorithms also has consequences. The primary objective of this research is to investigate and identify the functions of algorithmic management and analyze its behavioral consequences on internet taxi drivers in Iran. The research community includes internet taxi drivers in Iran, and a theoretical sampling method was used to select the research sample. This study is qualitative and descriptive in terms of its applied goal and method. To collect qualitative data, a semi-structured interview tool was employed, and thematic analysis was used to analyze the data obtained from the interviews. The analysis of findings in the two sections of algorithmic management functions and its consequences yielded 189 codes for functions and 136 codes for behavioral consequences. The functions section contains 9 topics, including easy recruitment, multi-channel recruitment, motivational job design, systemic-attitudinal (perceptual) performance evaluation, digital training, performance-based service compensation, flexible service compensation management, systematic labor relations, and conditional maintenance. The results section includes 11 sub-themes, which are categorized under two main themes: pleasant feelings and unpleasant feelings. The findings indicate that algorithmic human resource management has both positive and negative consequences. While the positive consequences are often acknowledged, the negative consequences of this concept are frequently overlooked.

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Attaining wellbeing and promoting standards of citizen's life is one of the pillars of national security of countries since a long time ago, and success of governments in achieving this goal is interpreted as one of their power elements, in a manner that guarantee of social member’s survival and achieving good and happy life is counted among major mission of governments. In present research, besides review of present literature about wellbeing, promoting national wellbeing is considered from perspective of improvement of public service qualities and good governance. Research methodology includes both descriptive and correlation analysis based on Structural Equation Modeling. Data was collected by means of documents and libraries studies. Research results indicated that improvement of good governance components result in national wellbeing promotion. Meanwhile, promoting good governance pave the way of wellbeing promotion in quantities direction such as gross domestic product, education, research, health and … and qualitative directions such as happiness. In other words, promoting good governance has dual objectives such as improvement of quantitative indexes like national product and growth of qualitative indexes such as decrease of social costs of economic growth, safeguarding resources for futur and stability of growth.

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The knowledge workers are the most important members of organizations in the 21 century. Therefore, proper management of knowledge workers is one of the successful management principles of knowledge organizations.Identifying knowledge jobs is one of the primary and fundamental steps in managing knowledge workers. The aim of this study is to provide a tool to measure and identify knowledge jobs. Positions are determined in a two-dimensional space criteria of “knowledge intensity” and “job requirements”. Mixed method approach applied using grounded theory strategy in qualitative phase and survey strategy in quantitative phase. Documents and textual data were used in the qualitative phase and a questionnaire for the quantitative phase. The study population is RIPI line jobs that have been selected by census method. Results show that developed tool is valid and it can identify and measure knowledge jobs regarding “knowledge intensity” and “job requirement”.