امیرسالار ونکی

This study set out to investigate the trend of studies conducted on tourist experience using bibliometric analysis. To this end, the study analyzed 2683 articles published in the Web of Science database from 1980 to 2020 using the VOS Viewer software to visualize and analyze the results. In this regard, two analysis levels were considered. At the first level, the publication trend and the impact factor of authors, journals, and articles were examined. At the second level, the structure of the co-occurrence network of keywords and the co-authorship network of authors, institutions, and countries were analyzed. The findings of the study indicated a significantly growing trend of studies (most of which were published in 2019) conducted on tourism experience in recent years, which is expected to continue to grow in the future. On the other hand, hospitality and leisure, management, and environmental studies were found as the highly researched areas, with most articles being published on tourism experience. Moreover, social media, trust, user opinions, and competitiveness are among the emerging research areas in the relevant literature. In this regard, health tourism, culinary tourism, social experience, shared value creation, authenticity, cultural experience, destination experience, backpackers, information technology, cultural differences, cultural heritage, students’ experiences, sustainable management, and transportation are among the main topics addressed in the literature. On the other hand, the analysis of the authors' co-authorship network revealed that thirty-five research groups are currently working in this field worldwide, with the Hong Kong Polytechnic University exerting the highest influence on the international collaboration network.

National competitiveness as an important economic goal in the context of globalization has been considered by many policymakers around the world. In the Iran, national competitiveness has been considered by officials and the government of men, so that achieving Iran's top economic, scientific, and technological position among the countries, especially among the countries of Southwest Asia, is one of the most important goals in the 20-Year Vision Document. Therefore, providing a framework for identifying and prioritizing factors that help improve Iran's competitiveness can be effective in achieving this goal.

Methodolog:

This study intends to provide a new framework based on the Global Competitiveness Index to prioritize the competitiveness pillars to increase the national competitiveness of Iran and determine the benchmark countries. This framework is implemented in three stages. The countries of the world are first clustered on the basis of competitive pillars using the fuzzy c-means clustering algorithm to distinguish the countries that are more similar in terms of national competitiveness. The competitiveness pillars in each cluster are then weighted using the CCSD weighting method. The weights obtained indicate the importance and priority of competitive factors. Finally, the WASPAS method is used to rank the countries in each cluster. These rankings are used to identify benchmark countries in each cluster.

Based on the results of this study, the countries of the world were first classified into three clusters. Clusters 1, 2 and 3 represent the developing, least developed, and the developed countries, respectively. After clustering the countries, competitive pillars were weighed using the CCSD weighting method. Accordingly, the labor market in cluster 1, the product market in cluster 2, and macroeconomic stability in cluster 3 had the highest weights. The higher the weight of a pillar, the higher its importance and priority in terms of competitiveness. For the Iran, labor market, macroeconomic stability and infrastructures were the most important competitiveness factors, respectively. Finally, the countries of each cluster were ranked using the WASPAS method. Latvia, Thailand, and Cyprus in cluster 1, Namibia, Kenya, and Macedonia in cluster 2, and Singapore, United States and Switzerland were top three ranked countries. Iran, with a rank of 58, is among the last countries in cluster 1 in this ranking. Latvia, Thailand, and Cyprus, which have the highest rankings in Cluster 1, can be used as benchmark countries for Iran.

 National competitiveness has become the main focus of policymakers and governments. Therefore, in this study, a framework based on national competitiveness index was presented to determine the national competitiveness priorities as well as benchmark countries for Iran. In this framework, the countries of the world were first clustered based on competitive pillars using fuzzy c-means algorithm. Competitive columns were then weighed in each cluster using CCSD method. Finally, the countries of each cluster were ranked using the WASPAS method. Based on the proposed framework, competitive factors and priorities as well as benchmark countries for the Iran were determined.

A review of the internal audit literature over the past century reveals a significant topic variety and thematic diversity, so that a systematic review of these studies is necessary in order to gain a deeper understanding of internal audit research. This research aims to fill the gap in previous review research and in response to the recommendation of Behrend & Eulerich (2019) and aims to identify the most effective articles, journals, authors, research centers and countries; Structure of cooperation between authors (co-authorship), research centers and countries; and issues with repetitive patterns (co-occurrence) in the field of internal auditing over the last hundred years. Using the Computational Literature Review (CLR) approach, a collection of articles extracted from the WoS database (1401 articles) over a period of one hundred years from 1920 to 2021 are examined in two ways: impact analysis and structure analysis. VOSviewer is used to build and visualize Bibliometrics. Researchers, practitioners, standard setters, and regulators in the field of accounting and auditing are the target audience of this research and can, respectively, use its results to direct future research, improve the level of internal auditing in practice, and develop standards and regulations to improve oversight on internal audit processes and required competencies.

Social media plays an important role in many aspects of tourism, especially in information retrieval, decision making, tourism promotion, and customer interaction. Due to the growing number of published researches in the field of social media and tourism, the purpose of this research is to analyze the publication trend and conduct a bibliometric analysis of the research published in this field. For this purpose, the information of 1054 articles published in the Web of Science from 2009 to 2020 is analyzed. In this research, two levels of analysis are discussed. At the first level, the publication trend and the impact of authors, journals, and articles are examined. At the second level, the structure of co-occurrence network of keywords and co-authorship network of authors, institutions, and countries are analyzed. The results of this study show that the use of social media in various sectors of tourism has increased in recent years.

According to the variety and diversity of research conducted in the field of internal auditing, the purpose of this research is to gain a deeper understanding of the topic by conducting a systematic review of existing studies to classify topics and outline some potential future research directions.

In order to achieve our purpose and to more efficiently examine a large number of articles, the "Computational Literature Review (CLR)" approach is used, and through this, the content of abstracts is analyzed automatically to provide a set of research topics within internal audit literature (Topic Modeling). The required information is collected from the Thomson Reuters Web of Science (WoS) database for 1401 articles over almost one hundred years (1920 to 2021).

The results of Topic Modeling show the focus of seven areas in internal audit research as follows: internal audit in the healthcare industry; internal audit in the areas of risk management, fraud, and internal controls; competence and training and internal audit quality; and the relationship between the external auditor and the internal auditor. A separate review of each of these identified issues related to internal audit reveals the most critical research conducted in this area and identifies some avenues for future research.

The results of this study indicate that throughout the evolution of internal auditing during its history (almost 100 years), its philosophy has evolved from ensuring the accuracy of financial statements and accounts and preventing the misuse of corporate funds or assets by helping to create and add value to companies. Internal auditing services have been upgraded from assuring financial statements and responding to its limited stakeholders (i.e., senior managers), giving assurance, consulting, forecasting risk, and being accountable to all stakeholders. Also, the change in the accountability direction of internal audit and its greater cooperation with external auditors, and the growth of technology and increasing the complexity of organizations have led to changes in competencies and skills required and improving and promoting its independence and objectivity; also engaging internal auditors in other areas of expertise (other than accounting and auditing), then it is expected that the trend will continue in the future.

Multi-criteria decision making methods have been of the most popular and practical areas in recent years. Among these methods, the AHP method has been considered by many researchers due to its unique features and has been used in numerous studies. This method facilitates decision-making for the decision-maker by allowing pairwise comparison between alternatives using language expressions. But this feature causes inconsistency in the decision matrix. One of the sources of inconsistency is the use of a predetermined scale to convert linguistic variables into quantitative values due to the different intellectual background of experts and their information about the problem. Therefore, the purpose of this study is to provide a customized scale for converting linguistic variables using the granularization of linguistic variables, which is in line with expert opinions and reduces the inconsistency. The unique feature of this framework is that the distribution of cut-off points is not known in advance and is determined according to expert opinions. To optimize the proposed model, a particle swarm optimization metaheuristic algorithm is used, which is modified to adapt to the specific characteristics of the problem. The results show the good performance of the proposed framework in reducing incompatibility.

With the advent of digital marketing and the subsequent emergence of social networks such as Facebook and Instagram, as well as the emergence of entities called influencers on these networks, numerous subcategories have arisen to optimize marketing activities with the purpose of having a larger, more effective, more targeted audience aiming at lowering the cost of advertising for businesses and obtaining greater efficiency. Influencer marketing is a branch of marketing that identifies and focuses on a specific person or a particular style of society and then observes potential audiences to lead other marketerschr('39') activities such as defining methods and markets, selecting the right target influencers, how to properly convey the message and attract the target audience in order to reach more efficiency and increase in the value of brands, businesses and products / services. The purpose of this study was to present a decision making model for selecting the most effective influencer(s) out of the existing influencer community in the  case study, Instagram social network, for the product / service being marketed. The criteria for identifying influencers in the present study were obtained by collecting those criteria that were studied sporadically in other studies previously. The data collection tool was a standard Likert 5point scale questionnaire in which these criteria were purposefully examined through distribution among100 experts in the relevant areas of the research subject, and were analyzed through Fuzzy Delphi Method.
Content validity was used to verify its validity and Cronbachchr('39')s alpha coefficient was used to measure the reliability of the questionnaire. The reliability of the questionnaire was higher than 0.8 which is scientifically accepted.
The weights of the final criteria were then determined for each of the five proposed products/services by SWARA Method. Finally, with those measurements, each criteria was individually assessed for 14 persons out of the community Instagram influencers using Multi-Criteria Decision Making (MCDM). The analysis showed a positive and significant relationship between the selected influencers and the proposed product / service.

This article aims to provide a framework to facilitate the decision-making process of choosing a suitable spouse. In this article, at first, the criteria for choosing a spouse were extracted from the papers. Then, these criteria were given to a number of students and counselors in this field in the form of the Borda count method. Finally, the final list of the criteria was determined. It was tried to make this process more structured by using the dynamic fuzzy gray relational analysis (GRA) as a multi-attribute decision making method. The findings of this study show that self-confidence and mental and physical health of the spouse are the most important criteria for choosing a spouse. Furthermore, being with family, having a good family background and having good financial future also have a high weight among the criteria. Since the process of choosing spouse is a personal decision,the designed process has been applied to a real-world case study. Designed process can make decision for young people in such a difficult decision situation and help them in the final decision. Applying the designed framework to other real situations can explain the extent to which the outcomes of the research are valid.

Today, sport competitions are being held under different titles around the world and have attracted many fans. Team sports like football and volleyball have turned to big businesses and huge amounts of money are involved in the transfer of team players. So, one of the important issues in sports is to search new team members to fill open positions and to enhance the quality of the teams. Single attribute decision has recently been made to select top volley ball players while experts believe that this field requires multi attribute decisions. Therefore, the aim of this study was to provide a scientific framework to rank volleyball players and to select top players to play their roles in different positions. Firstly, a list of criteria to select players in different positions was provided using literature review and meetings with experts of the field. Then, SWARA method and experts’ viewpoints were employed to prioritize and weigh the mentioned criteria. TODIM method was introduced to finally select top players from the existing options. To assure the accuracy of the research path, the designed framework was used to rank those players participating in 2015 World Cup in Japan and to form the world selected team. This study was application in terms of aims and descriptive – survey in terms of data collection.

R & D is one of the most important departments in organizations and selecting the most appropriate candidate as the team manager, can have a significant impact on its success. Despite these necessities, there has not been developed a structured framework to help identify appropriate criteria to select the R&D team manager yet. Nevertheless, this study aims to introduce a new combined approach for selection of R&D team managers. For this purpose, the required criteria are obtained from existing competency models. Afterwards, due to the variety of identified criteria and this fact that the weight of each criterion is different from the experts’ point of view, a combination of multi-attribute decision-making (MADM) methods has been used. Therefore, for the weighting of the criteria, the revised SIMOS method and for the selecting of the most appropriate candidate as the team manager, ARAS interval method was used respectively. The framework proposed in this study was used to select the most appropriate candidate for R&D project manager in Keyson Company. According to the results, the most important criteria in the selection of the managers are the individual skills (especially selecting and assigning personnel, allocating resources and having systematic viewpoints).

Given the increasing requirements of communication and the need for advanced network-based technologies, cloud computing has been suggested as a perfect strategy to achieve these objectives. Yet, despite the development of computing applications and the increased number of alternatives, it is quite a difficult task to select the exact software platform for the implementation of cloud computing arrangements. In this line, the present paper aimed to develop a scientific framework as how to select the proper software for successful cloud computing implantation at the infrastructure level. First through a review on the related literature and using experts’ opinions, the software selection criteria were extracted. Based on the framework proposed here, the interval-valued fuzzy ARAS method was then employed for weighting and prioritizing specified alternatives. This model was applied by the Faculty of New Sciences and Technologies of Tehran University in order to select proper software platforms from among five alternatives. The results revealed that the OpenStack cloud operating system has been selected as the best alternative, most probably because this platform demonstrates significant achievement for its merits such as high level of performance, reliability and security, stability, and usability.

As technological advances and environmental changes accelerate, technology-based corporations increasingly understand the need to forecast and comprehend future developments in the environment. Due to the technological conditions and desired criteria, it is not possible to use all methods of technology forecasting simultaneously. Therefore, it is necessary to select an effective and efficient method for forecasting specific technology. Considering the multiplicity of effective criteria on this choice and the difference in the importance between these criteria for choosing the appropriate technology forecasting method, the use of multi-criteria decision-making methods has been considered by the experts of this field. In this regard, this paper aims to provide a framework for selecting the appropriate technology forecasting method. For this purpose, firstly, by review the literature, the appropriate indicators for choosing the technology forecasting method were extracted. After the criteria were finalized with the help of the members of the relevant committee and using multi-criteria decision-making methods, the weight of each criterion was calculated and then the forecasting methods considered for aircraft engine were evaluated and prioritized. The results indicate that the Delphi forecasting method can be used as the best method for technology forecasting in this area.