رضا رادفر

Purpose: Evaluation of employee performance plays an effective role in organizational productivity and effectiveness. As a result, the purpose of this study was identification the components of evaluation of employee performance smart pattern. Methodology: This study in terms of purpose was applied and in terms of implementation method was qualitative. The research population was specialist managers and experts evaluation of employee performance of the bank of industry and mine in 2020 year, which according to the principle of theoretical saturation number of 16 people was selected by purposeful sampling method. The research tool was a semi-structured interview, which whose validity was confirmed by the triangulation method and its reliability was calculated by the agreement coefficient method between the two coders 0.82. Finally, data were analyzed based on open, axial and selective coding methods. Findings: The findings showed that components of evaluation of employee performance smart pattern had 50 open codes in 12 axial codes and 3 selective codes. The selective codes included the factors of functional (with 4 axial codes of optimal function, quality of work, active and effective participation in meetings and planning, forearm and follow-up), job behavior (with 7 axial codes of observing administrative regulations and discipline, proper behavior and encounter with clients and colleagues, cooperation and accountability, analysis of issues and providing appropriate solutions, self-propulsion and innovation, increased job information and skills and information transfer) and ethical behavior (with 1 axial code of observing ethics and Islamic behavior). Finally, according to the identified components, the evaluation of employee performance smart pattern was painted. Conclusion: The results of this research have practical implications for the specialists and officials of the Bank of Industry and Mine, and they with the help of identified components for evaluation of employee performance smart pattern can provide the ground for improving the performance of the organization.

While travelers' desire to visit the world's most remote places has grown, the inefficiency of global payments indicates a significant barrier to tourism growth. As an emerging, decentralized, and borderless digital innovation, Bitcoin technology seems to have the ability to serve as a payment alternative and address such fundamental inefficiencies. On the other hand, bitcoin adoption can only happen when tourists and business owners choose to operate bitcoin simultaneously. The study has developed a novel Bitcoin Collaborative Network and Tourism Collaborative Network model to examine Bitcoin adoption factors. Then a fuzzy DEMATEL method was applied to the factors influencing the adoption domain, as identified based on an extensive literature review, in-depth interviews, and an international Delphi process. The study offered a model for the heterogeneous collaborative network of Bitcoin and Tourism (BCN and TCN), revealing that Perceived Usefulness is the most influencing criterion and the most prominent variable in Bitcoin Adoption. Bitcoin Technological Complexity, Government Regulatory, and Bitcoin Awareness are the factors that give the highest impacts. Also, Bitcoin's Technological Complexity is the most significant factor in bitcoin adoption. The findings might assist businesses in adopting a new market expansion strategy and benefiting from technological spillover, while government officials can explore new supporting legislation.

Today, business environments are fast changing and Nanotechnology-driven firms are opening up their organizational boundaries to tap into an external source for R&D activities. To reform the structure of the R&D activities in order to be successful, firms face challenges in finding a proper place in the R&D ecosystem. Therefore, this research examines the open R&D ecosystem through these key questions. Which components can form an open R&D ecosystem and how do interactions behave in a dynamic model? This research is done in 3 stages; the first stage is data collection based on the Fuzzy questionnaire, then the data analysis through the Fuzzy-DEMATEL method, and finally modeling the dynamics of the open R&D ecosystem.. This research is applied in terms of purpose and descriptive survey information in terms of collecting information. The findings suggest that Nano-tech in Iran relies on two main components that affect each other: technological innovation performance and ecosystems. the result shows that inside the ecosystem, the most share of activities is related to the human resources and governance sub-ecosystems. In addition, scientific works under the concept of technological innovation performance have the greatest impact from sub-ecosystems, and the balance between performance and ecosystem is a possibility for Nano-firms to do more R&D activities. Overall, this study provides a better understanding of open R&D by suggesting that further opening of the R&D ecosystem is necessary for nanotechnology.