بازاریابی

With the increasing development of technologies and communication methods, the use of digital marketing to advertise and promote services and products has become very important. One of the industries that benefit from these methods is the medical tourism industry. Also, considering the ever-increasing growth of technology and the widespread use of the Internet in different societies, the use of artificial intelligence and related technologies is very important. Therefore, the aim of the current research is to identify the effective factors on digital marketing in medical tourism with an emphasis on artificial intelligence (case study: Tehran). This research is a survey in terms of practical purpose and in terms of data collection. The statistical population of the research included 53 medical tourists from Tehran, who were selected to participate in building the model. For this purpose, the conceptual framework of the specific model and the data were analyzed using tools and techniques of fuzzy cognitive mapping and social network analysis. The results showed that several factors are involved in digital marketing in medical tourism with an emphasis on artificial intelligence (case study: Tehran city), including site optimization and branding factors in search engines, marketing targeting, better evaluation of marketing campaigns and better feedback from Audiences were the most important in order; Because they were more central.

 The purpose of this research is to analyze the impact of effectiveness of media (Seda-va-Sima) advertisement on the extent of consumers’ urge to consume national commodities. In case of its goal, this research is an applied research, and is a descriptive-survey research, which has been conducted as a field work. Statistical population of the research is the population of Mashhad city. Using Cochran formula, 384 people were selected as the statistical sample. In order to gather data, a researcher-made questionnaire with 61 questions was used. Content validity of the questionnaire was approved by 15 academic and practitioner experts in the field of advertisement and media. The reliability of the questionnaire according to Cronbach's alpha was 0.824. Also, SPSS and SPLS applications were used to analyze data. Results of the research indicate that effectiveness of media advertisement positively and in a meaningful manner affects consumers’ urge to consume national commodities.

The purpose of this research is to investigate the identification of effective factors on the distribution strategy in the food industry from the point of view of marketing and online sales. This research is in terms of applied-developmental purpose, in terms of the method of collecting data in a qualitative form, and in terms of the research implementation method, it is a meta-composite approach. The statistical population of the research includes 12 university professors who are experts in the field of marketing management and distribution channels and have books or articles in this field, as well as theorists and researchers who have specialized studies in this field. This research was analyzed using the scientific method of metasynthesis (metasynthesis) and by reviewing the published articles, and based on 23 selected articles, 85 indicators were extracted. Finally, 16 components were evaluated and identified, and finally the final framework was created by applying the total opinions of experts on the components of human factors, creating value for the customer, paying attention to the competence of managers, internal factors, external factors, management factors, opinion mining, digital marketing, Environmental factors, content marketing, business strategies, complete knowledge of the internal and external environment, direct marketing, visual features, optimization, competitive performance were confirmed and identified.

Green influencer marketing is considered one of the new approaches in today's world in purchasing tourism services. Influencers, people with a large number of followers in social networks, play an important role in promoting products and services by influencing the attitudes and behaviors of customers. The tourism industry has also used this potential. The purpose of this research is to design a green influencer marketing model in purchasing tourism services. The research method is qualitative and the research strategy is based on foundational data theorizing. The participants include university professors, researchers and experts active in the field of tourism and marketing, 12 people have been selected by the judgmental sampling method of the snowball type according to theoretical saturation. To collect data, in-depth interviews and A semi-structured interview was used. To calculate the reliability of the model, the method of percentage agreement coefficient or Cohen's kappa coefficient was used, the value of which was calculated to be 0.85. The research findings included 6 categories. Causal conditions include social media developments and technological developments. The core category of the core category (green influencer marketing) includes the sharing of experience from the tourist destination and the mental representation of the destination brand. The strategies include the strategy of creating a mental road map, the strategy of creating unique content, and the strategy of online tourism services. Consequences include improving tourist performance, improving tourism industry performance. Intervenors include individual characteristics of influencers, macro environmental factors. Areas include personal branding and infrastructure.

This research was conducted with the aim of analyzing the gap in the deployment of artificial intelligence in advertising and marketing companies in Iran.

the multi-criteria decision-making study method was chosen using Super Decision. The methods of information collection, according to the background of the research, library methods were used, and the field method was used to collect information to answer the research questions. The tool used to collect information in this research is through a questionnaire designed by the researcher in order to identify challenges. In the next step, using experts' opinions, they were modified and then analyzed using the combined approach of ANP and DEMATEL.

The findings of the research showed that in the technical subject of security factor, in the subject of culture the leadership and organizational support factor, in the organizational-human factor of organizational strategy and in the social-environmental topic organizational culture had the most importance from the experts' point of view.

The research results also stated that artificial intelligence will transform the business world, increase innovation and productivity, and help advertising and marketing companies to think bigger. Lack of current knowledge and experience in using this technology is definitely one of the main obstacles that prevent organizations from using artificial intelligence in marketing. But the way and the only answer to this is education. It is worth noting that another factor investigated in the research was the constantly changing trends, which is another major obstacle that we see in the field of artificial intelligence. This is inevitable as the technology is still developing. However, there is no way to solve this problem except for it to constantly present itself. Organizations can use artificial intelligence to improve their products, processes and decision making. The impact of artificial intelligence is felt in all industries, especially marketing. With the help of AI, companies are better equipped to combat crisis by using AI decision-making algorithms, identifying anomalies and predicting future behavior.

The‏ aim‏ of‏ this‏ research‏ is‏ to‏ design‏ a‏ digital‏ marketing‏ model‏ in‏ small‏ and‏ medium-sized‏ industries‏ in‏ Iran‏ using‏ the‏ meta-synthesis‏ method.‏ The‏ present‏ research‏ was‏ conducted‏ as‏ a‏ qualitative‏ research.‏ Accordingly,‏ in‏ order‏ to‏ design‏ a‏ comprehensive‏ model‏ of‏ digital‏ marketing,‏ the‏ meta-synthesis‏ qualitative‏ research‏ method‏ of‏ Sandelowski‏ and‏ Barroso‏ (2007)‏ was‏ used.‏ Thus,‏ after‏ identifying‏ the‏ categories,‏ concepts‏ and‏ codes‏ of‏ digital‏ marketing‏ and‏ evaluating‏ its‏ validity‏ and‏ reliability,‏ the‏ conceptual‏ model‏ of‏ the‏ research‏ was‏ formed. Finally,‏ the‏ present‏ research‏ model‏ consists‏ of‏ 6‏ categories,‏ 18‏ components‏ and‏ 54‏ indicators‏ that‏ can‏ represent‏ the‏ digital‏ marketing‏ model‏ in‏ small‏ and‏ medium-sized‏ industries‏ in‏ Iran.‏ The‏ results‏ of‏ the‏ research‏ show‏ that‏ all‏ six‏ categories;‏ 1.‏ Marketing‏ strategy,‏ 2.‏ Reaching‏ and‏ interacting‏ with‏ target‏ customers,‏ 3.‏ Converting‏ visitors‏ into‏ customers,‏ 4.‏ Engaging‏ customers,‏ 5.‏ Appropriate‏ digital‏ tools,‏ and‏ 6.‏ Digital‏ content‏ marketing‏ play‏ a‏ significant‏ role‏ in‏ the‏ "digital‏ marketing"‏ model‏ for‏ Iranian‏ small‏ and‏ medium-sized‏ industries,‏ and‏ the‏ designed‏ model‏ is‏ the‏ most‏ appropriate‏ digital‏ marketing‏ model‏ in‏ terms‏ of‏ the‏ cultural,‏ organizational,‏ and‏ structural‏ conditions‏ existing‏ in‏ Iranian‏ small‏ and‏ medium-sized‏ industries.

Personalized Digital Marketing is one of the key and thriving trends in the world of digital marketing, developed with the aim of delivering unique and tailored experiences to each customer. In this approach, marketers strive to understand the needs, preferences, and behaviors of users by collecting and analyzing their data. Based on these insights, they design marketing content, advertisements, and offers that align specifically with each individual. The goal of this research is to identify the dimensions and components of personalized digital marketing through a recommendation engine using a thematic analysis approach. To achieve this, after reviewing the literature and research background, basic and organizing themes were identified. Then, through surveys and interviews with 25 experts and university professors familiar with the concepts of personalized digital marketing, a conceptual model of the research was introduced. In conclusion, practical suggestions were provided to IT and marketing managers in online stores, including Digikala.

Considering the importance of marketing and public relations in libraries and the lack of an official position on the one hand and the compilation of the new standard of public libraries in Iran on the other hand, the aim of this research was to investigate the view of public library managers of Isfahan province about the feasibility of implementing the Standard of Marketing and Public Relations of Iranian Public Libraries (2020).

This research was applied in terms of purpose and descriptive-survey in terms of method. The statistical population consisted of 196 public library managers of Isfahan province. 127 managers were selected as a statistical sample by the Krejcie and Morgan table and stratified random sampling method. The data collection tool was a researcher-made questionnaire, and SPSS V.26 statistical software was used to analyze the data.

The results showed that the average feasibility of implementing the Standard from the view of public library managers of Isfahan province is lower than the average (x=3) and the observed average difference is also significant. The average of the components of planning, evaluation and support were all lower than the hypothetical average, which shows the poor condition of the feasibility of these components in the public libraries of Isfahan province. There was also no significant difference between the view of the public library managers based on the demographic variables of gender, age, education degree, discipline, city and work experience regarding the feasibility of implementing the Standard.

Conclusions: 

So far, there has been no research on the Standard of Marketing and Public Relations of Iranian Public Libraries (2020). The results of the present research can achieve the desired situation in the field of marketing and public relations in order to attract the audience and facilitate relations with the actual and potential audience community.

Artificial intelligence has become one of the key tools for enhancing advertising strategies. By leveraging capabilities such as data analysis, machine learning, and natural language processing, AI enables transformative advancements in advertising and marketing processes. Exploring the role of AI in fostering advertising innovation, increasing audience engagement, and optimizing advertising strategies is of significant importance.The primary aim of this study is to map the knowledge structure of research on the application of AI in advertising using co-word analysis. To achieve this, 3,577 scientific articles published between 1994 and 2024 were retrieved from the Scopus database. The titles and abstracts of these articles were analyzed using VOSviewer software to generate a comprehensive map of the most frequent terms and key topics. The results revealed that the keyword “advertising” had the highest frequency, serving as a focal point for numerous studies in this field.The co-word analysis identified five main clusters: (1) prediction and optimization of advertising performance, (2) AI-driven content generation, (3) precise targeting and audience identification, (4) personalization of advertisements for enhanced engagement, and (5) the development of recommender systems to improve advertising efficiency. These clusters reflect the key trends in AI applications in advertising and marketing.This analysis provides a comprehensive and structured map of the existing knowledge on AI applications in advertising and serves as a reference for future research in this area. It also offers guidance for developing policies and strategies in the advertising industry.

This study aims to design a ritual marketing mix model based on interpretive structural modeling.

The research is exploratory in terms of its objective and qualitative in approach. In this study, 15 experts were interviewed for analysis. The snowball sampling method was used to collect data, which was then categorized and analyzed using thematic analysis. Semi-structured interviews and document analysis based on thematic analysis were employed to gather data in line with the research objectives.

Ultimately, one overarching theme, four organized themes, 11 basic themes, and 63 initial codes were identified. The organized themes included: religious advertising and promotional strategies, distribution channels and religious sales locations, religious products, and religious pricing. Based on interpretive structural modeling, the final model was developed.

The results suggest that integrating cultural and religious values into marketing strategies provides a comprehensive approach for engaging audiences in religious communities. This model can not only strengthen deeper connections with customers but also enhance social responsibility and help achieve the economic objectives of organizations. By adopting this approach, a balance is achieved between economic benefits and ethical principles.

The present study is a mixed method and a type of exploratory mixed research design, which is carried out in two consecutive qualitative-quantitative stages. In the first phase (qualitative phase), the present research conducted a qualitative study, and in this phase, by reviewing and evaluating the studies conducted in the field of the topic raised in the current research, as well as in-depth interviews with knowledgeable experts in the field of brand repositioning, the necessary information was collected. And by using the grounded theory analysis method, it has been coding and categorizing and presenting a conceptual model. The second phase (quantitative phase) of the study was quantitative and by the method of structural equation modeling, for this purpose, the data collected from the researcher-made questionnaire based on the proposed model (resulting from the qualitative phase of the study) was evaluated using Smart PLS software. Results In the qualitative part, the grounded theory results showed that the brand repositioning pattern of companies active in the electricity industry includes 71 open codes, 8 core codes, and 1 selective code. In the quantitative part, the results of structural equation modeling showed that 8 components including financial power, quality, price, delivery, service, marketing, customer satisfaction and human resource management were identified for the brand repositioning model of companies active in the electricity industry, and all 8 The component affects the repositioning of the brand of companies active in the electricity industry

This research is applied from the perspective of purpose and descriptive-survey research from the perspective of data collection method. The statistical population included customers of sports complexes in Tehran. The samples were determined based on Cochran's formula of 384 people using cluster random sampling method. For data collection, the Internet Advertising Assessment Questionnaire, Chang and Wang (2019), respectively. Chang and Wang Electronic Word of Mouth Advertising Questionnaire (2019). Questionnaire of disapproval of the expectation of the judge and colleagues (2017). Behavioral Tendency Questionnaire from Hyun, Kim and Lee Questionnaire (2011). used. SPSS and Smart pls software were used to analyze the data. Based on the results of electronic advertising and word of mouth, it has an effect on the behavioral tendencies of customers (0.712) and (203), respectively, which is significant according to the rate of T (9.550) and (2.483). And disapproval of expectation as a mediator affects the relationship between electronic advertising and behavioral tendencies of customers, so disapproval of expectation as a mediator affects the relationship between word of mouth and customer behavioral tendencies. Therefore, with the increase of advertising, customers' behavioral inclinations will also increase and the tendency to prefer and use products and services will also increase. Therefore, it is suggested that in presenting advertisements, points such as increasing the quality of services at the time of submitting the request and need, awarding prizes, facilities and price discounts, and using new and non-repetitive techniques to advertise services should be considered.

The purpose of this study is to design a marketing development model for the Iranian Wrestling Federation. The statistical population of this study includes specialized faculty members (marketing, sports management, wrestling experts of the Islamic Republic of Iran), senior managers of the Wrestling Federation of the Islamic Republic of Iran, national and provincial coaches Higher education in sports management, wrestling experts and journalists, senior managers of the National Olympic Committee and the Ministry of Sports. Purposeful sampling was performed by snowball method. Then the primary, axial and selective codes were assigned. Findings showed that the reported regression coefficients, causal factors, contextual factors and intervening factors had the greatest impact on marketing development, respectively. In addition, the impact of interfering factors is negative. This means that as it increases, the amount of marketing development decreases. In this study, data collection and analysis were performed based on variable sequences and with multiple revisions of the same. The research in general showed that in causal conditions (managerial and technical category), intervening results, legal and legal requirements), underlying factors, (efficient manpower) and marketing development (causal conditions) are very effective. And the rest of the categories are in the next priorities.

The current research was designed and implemented with the aim of designing a marketing model for the services of women's sports clubs. The current research was mixed in terms of practical purpose, in terms of descriptive-survey data collection method and based on the research approach. The statistical population of the present research in the qualitative part includes professors who had conducted research (books, translations, research projects, conference and research articles and at least two cases) in the field of sports marketing, as well as managers of women's sports teams. Be Purposive sampling method was used to select the interviewees. This sampling continued until theoretical saturation was reached and finally 30 people were selected as a sample. Also, the statistical population in the quantitative part of the research included the same group in the qualitative part in order to participate in the Delphi process (30 people). The tools of the current research included semi-structured interviews and a Deli questionnaire (59 items and 5 dimensions) in a 9-point Likert scale. Open, axial and selective coding was used to examine the data in the qualitative part, and the fuzzy Delphi method was used in the quantitative part. The results of the present research showed that the 4 factors of operation, cultural, social, infrastructure and economic are among the most important factors affecting the marketing of women's sports club services. Considering the effect of the service marketing model on the development and improvement of Batawan sports clubs,

A successful marketing strategy is essential for driving economic dynamism within the steel and iron industry, particularly during times of economic instability and fluctuating prices. The objective of this article is to identify and prioritize the key factors influencing the marketing of the iron and steel industry amid exchange rate volatility. To achieve this, a mixed-methods approach (qualitative-quantitative) was employed. Initially, a comprehensive analysis of existing literature and documents was conducted to identify the primary factors affecting marketing in the iron and steel sector. In the subsequent quantitative phase, a survey was administered to 100 marketing experts to further explore and prioritize these factors using stepwise regression analysis. The qualitative phase involved a review of relevant articles, research reports, and theses related to industrial marketing, while the quantitative phase targeted experts and specialists in the field of marketing. A purposive sampling technique, specifically snowball sampling, was used for both phases. Data collection tools included content analysis for the qualitative phase and a researcher-developed questionnaire for the quantitative phase. Data analysis was conducted using SPSS version 23, complemented by manual analysis as needed.The results of the study revealed that the most important criteria affecting the marketing of the iron and steel industry during exchange rate fluctuations, in order of priority, are: economic factors (such as reducing production costs, utilizing up-to-date production technologies, and aligning production with supply and demand), social factors (including strategic management and identifying customers and their needs), and environmental factors (with a focus on reducing production energy consumption).

In today’s world, the rapid development of information technology has led to the creation of vast amounts of data. Approximately 2.5 quintillion bytes of data are generated daily, and this figure is expected to rise with the advent of the Internet of Things (IoT) (Seranmadevi & Kumar, 2019). The availability of reliable data is crucial for producing and utilizing information that enables quick and accurate business decisions. The rapid technological advancements and their widespread distribution globally have created opportunities to gain a competitive advantage through new methods based on data and artificial intelligence (AI) in marketing management. This study aims to enhance the marketing process by providing a systematic and precise approach toidentifying research gaps, thereby connecting practical and research actions in the field of marketing and AI. Consequently, the primary objective of this research is to develop a marketing plan based on AI using a hybrid approach and strategy.Artificial intelligence finds applications in various business contexts. Experts and academics consider AI to be the future of our society. With technological advancements, the world has become a network of interconnected systems (Jeric et al., 2019). The implementation of technology has led to investments in AI to analyze big data and create market intelligence (Stone et al., 2020).A marketing plan primarily consists of the marketing mix, which is a combination of marketing elements. The marketing mix comprises controllable marketing tools that a company uses to implement its marketing strategy, designed to satisfy consumers (Jerk & Mazurk, 2019). It is divided into four general groups known as the 4Ps. Subsequently, the 4Cs plan was introduced to emphasize the importance of the customer’s position and the formation of effective marketing communications (Tangyananakit & Samasat, 2022).Shirmohammadi and Mohammadi (2023) conducted a study titled “Using Artificial Intelligence and Internet of Things Based on Big Data to Create Knowledge and Rational Decision Making in B2B Marketing to Improve the Performance of Smart Travel Service Offices.” Their research demonstrated that AI and IoT positively and significantly impact the creation of customer and user knowledge. Additionally, the creation of customer knowledge and user knowledge of foreign markets positively andsignificantly affects rational marketing decision-making.Shah Nazari and Sharifi (2023) conducted a study titled “Artificial Intelligence-Based Systems for Consumption in Structural Marketing: Historical Reminder, Current and Future Views.” Their research highlighted the development of conscious systems and special power points to support decision-making situations for companies, especially those with a strategic identity, where good strategic data is essential.Shaik (2023) conducted a study titled “The Effect of Artificial Intelligence on Marketing,” which demonstrated that artificial intelligence significantly impacts marketing. Nalbant and Aydin (2023) conducted research titled “Development and Transformation in Digital Marketing and Artificial Intelligence Branding: The Dynamics of Digital Technologies in the Metaverse World,” showing that artificial intelligence is effective in digital marketing. Torres et al. (2022) conducted a study titled “Artificial Intelligence and Its Impact on Brand Loyalty: Relationships and Combinations with Satisfaction and Brand Name.” They used Fuzzy Qualitative Comparative Analysis (FS/QCA) along with Structural Equation Modeling (SEM). These methods reveal subtle differences that help understand the effects of different value dimensions. While SEM results emphasize the mediating role of brand love, FS/QCA results show that brand love is a major condition for brand loyalty. Different paths can be sufficient to produce beneficial results. These findings enhance our understanding of AI performance and can guide practitioners in using game experiences to influence consumer behavior.

The primary objective of this research is to identify the antecedents, dimensions, and consequences of an AI-based marketing program. It is developmental in nature and, since the data were collected without direction and manipulation, it is classified as non-experimental (descriptive) research. This study was conducted within the pragmatism paradigm using a mixed-method approach, incorporating both quantitative and qualitative methods. The bibliometric analysis method and the four-step approach proposed by Costa et al. (2017) were used to review the systematic research background. In the qualitative approach, metacomposition and the seven-step method of Sandlowski and Barroso (2007) were employed.Bibliometric Analysis As stated, this study utilized a four-step method proposed by Costa et al. (2017) for bibliometric analysis, which includes: Selection of bibliometric databases. Defining keywords (search strategy). Refining the initial results (entry and exit criteria).  Data analysis plan.

Data were collected from the Scopus database and saved in CSV format for further analysis. A total of 115 documents related to this particular issue have been published up to the mentioned date. The authors have used 789 keywords for the mentioned period. The chart illustrates the number of articles published over different years. As shown, only one article was published in 1985 in the field of artificial intelligence and marketing. From 2010 onwards, this issue gradually gained attention from researchers, and the trend of publishing articles has been on the rise from 2010 to 2022. In 2021, 50 articles were published, and in 2022, 21 articles have been published to date.

Existing studies, such as those by Avari (2018), Decamp (2020), Antons and Breidbach (2018), Chang et al. (2009), Chang et al. (2016), Liebman et al. (2019), and Gu et al. (2019), indicate that marketers can use mechanical artificial intelligence for standardization to prepare marketing plans. Intellectual artificial intelligence has a high potential for creating advertising content and personalization. For instance, authors of advertising content, websites, and social networks can facilitate the production of advertisements or post content using artificial intelligence. AI technologies enable the personalization and optimization of customer profiles in different locations and times. Content analysis can assist advertisers in creating more effective content.Based on the obtained results, the following practical suggestions can be made:Using AI for customer interaction (e.g., conversational bots to gather data related to customers’ moods and emotions).Employing AI to create music and write short stories to make advertisements more creative and memorable for customers.Utilizing mechanical AI to automate adjustments and price changes.Implementing automation by mechanical AI in the advertising media planning department.Using AI writers to produce content.Future research should consider conducting studies using experimental and longitudinal methods, as well as mixed methods. It is also suggested that future researchers address the limitation of excluding non-English language studies

The present study aims to investigate the impact of political marketing orientation on strategy implementation, considering member participation. The dimensions of political marketing orientation (internal orientation, voter orientation, competitor orientation, and external orientation) were considered based on the framework proposed by Oumard and Henneberg (2010). This research was conducted using a descriptive-survey method. The statistical population consisted of faculty members in management (marketing specialization) and political science departments in Qom province. Given the limited size of the statistical population, it was necessary to use a sampling method for limited populations. According to Morgan's table, the sample size for this study was calculated to be 90 individuals, and the required data were collected through simple random sampling. For data analysis, statistical methods such as Spearman's correlation coefficient, regression analysis, and structural equation modeling (SEM) were employed using SPSS and PLS software. The results confirmed the proposed conceptual model and indicated a significant relationship between political marketing orientation and strategy implementation, considering member participation. The structural equation modeling results also supported the hypothesis

Augmented reality technology has emerged as one of the main trends in the digital market in recent years. This innovative technology, due to its appeal and potential, has been repeatedly applied in innovative businesses. The aim of this study is to conduct a systematic and comprehensive review using a bibliometric approach on the citation data of literature related to purchase decision-making based on augmented reality technology. A pragmatic paradigm allowed the researcher to systematically collect citation data from the Scopus database and preprocess it following the standard PRISMA protocol. Ultimately, 239 studies were included in the bibliometric analysis using R Studio and Vosviewer software. The final results identified the most influential documents, authors, journals, organizations, and countries, and highlighted key points regarding buyer behavior and purchase decision-making with augmented reality in virtual businesses through interactive patterns between elements and content analysis of the data. Additionally, it is noteworthy that this concept mainly revolves around five primary areas: virtual and psychological experiences of buyers in online shopping with augmented reality; the impact of artificial intelligence on new technologies in buyer behavior; interactions of technology, perceived value, and cognition on buyer experience in retail using mobile augmented reality; the role of augmented reality technology in purchase decision-making and smart shopping in the virtual space. The influential school of thought on augmented reality technology in buyer decision-making is associated with the stimulus-organism-response theory, which forms the intellectual foundation of this field.

Pricing of goods and services is one of the important topics of Islamic economics, which has long been the focus of the thinkers of the Islamic Society. The lack of government oversight of prices is a clear violation of social rights that has detrimental consequences. Therefore, in some cases, pricing should be considered. Pricing strategies differ for each stage of the product life cycle. Although each stage of product life has its own peculiarities and challenges, the most difficult and challenging stage is setting prices for new products .

This paper is prioritized new product pricing strategies and offered appropriate solutions using multidisciplinary decision-making. In this research, to evaluate and select appropriate solutions is used a hybrid MCDM approach based on FANP-DEMATEL-FCOPRAS approaches due to a multiplicity of quantitative evaluation criteria and fuzzy nature of qualitative criteria. The statistical sample consists of 15experts and specialists of Shokouh Cellulose Materials and Paperback firm. Findings,

According to studies, the main criteria in this research are innovation, marketing, organization, customer, product, and technology, each of which in turn includes sub-criteria. The results show that the free product as if zero price in priority, combining multiple products into a single package and selling them for one price in the second priority have been.