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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.

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.

Automotive industry particularly, commercial automotive industry, ranks as a key industry in the economic growth. The necessity of investigating the research & development(R & D) activities of digital marketing and innovation in the form of a dynamic system in automotive industry based on the 3 variables: empowerment of supply network, of product innovation, and of digital marketing is quite undisputed. The present research has been done with a view to identifying and evaluating the cause-and-effect interdependent relations governing the variables of R & D of digital marketing and innovation in commercial automotive industry. The research is typically applied, and has been done using the descriptive-survey method. The research community consisted of 50 experts; all with acceptable academic backgrounds and years of experience as executive managers and marketeers in the R & D of automotive industry. To analyze the data, the views of some elected experts on automotive industry, along with Delphi fuzzy and Dematel method were applied. Our findings showed that the variable “Intensity of R & D of digital marketing and innovation” has the most effect on the other variables. The variable “Empowerment of supply network” with the score of 3,25 has the largest amount of interaction with the other variables. Also, the variable “ Empowerment of R & D in digital marketing and innovation” with the score of 1,08 has the smallest amount of interaction with the other variables.

This research has evaluated the innovation components in information technology startups with a focus on Industry 4.0. The approach of the current research is of a qualitative type and was implemented based on the meta-composite approach. On this basis, all articles published in ISI magazines, books and internal and external theses related to the topic of innovation in the field of startups and in the period of 2015 to 2021 were examined. According to the SIP model, the researchers identified 17 concepts and 96 codes for each of the 4 categories of substrate (background), input (input), the main category of process and output (output), which were paid attention to in internal and external studies. The results of this research will help researchers and practitioners in the field of innovation in information technology startups to know what variables and components should be included in the four sectors of the platform for a comprehensive understanding of the innovation development of startups based on the 0.4 industry. Pay attention to the main category of process and output. The present study contributes to the literature on startup technology innovation in information technology and its practices and outlines desirable practices for future researchers.