International Journal Of Nonlinear Analysis And Applications
Volume:15 Issue: 9, Sep 2024

Fractional derivatives are suitable for describing several physical phenomena. The construction of efficient analytical and numerical methods for the solutions of ordinary and partial fractional differential equations is an active research area and it is of great interest to the researchers. The Caputo fractional derivative is of great use in the modelling and simulation of phenomena where consideration is given to the interactions within the past and problems with nonlocal properties. This study considers the use of a hybrid of the Sumudu Transform method for constructing the solution of nonlinear equations that describe the processes in the functional and structural materials. This study considers the models that are given by the integer-order derivatives, Caputo derivatives of fractional variable orders and Caputo derivatives of fractional variable orders that are associated with delays. The study applies a hybrid of Sumudu Transform to present solutions for each considered model and makes use of graphs to show the correlation among the models. The study is of great importance in the numerical and experimental characterization of the decay properties of functional and structural materials.

The purpose of this paper is to analyze the solvability of a class of stochastic functional integral equations by utilizing the measure of non-compactness with Petryshyn’s fixed point theorem in a Banach space. The results obtained in this paper cover numerous existing results concluded under some weaker conditions by many authors. An example is given to support our main theorem.

The current research is based on the explanation of the optimal model for predicting the performance of companies using data mining techniques. The method of this research is of the applied type, in terms of the way of doing the work, it is of the descriptive-causal research type, and in terms of the time dimension, it is of the post-event research type. In the first step, by referring to databases such as theses, articles and similar researches, the required literature was collected in order to write the theoretical foundations and background of the research. In the following, the information of the investigated companies selected as a statistical sample, whose information is available in the form of data banks on CDs and is under the supervision and review of the responsible institutions, was audited by referring to the financial statements and New implementation software was compiled. The mentioned information included the financial data of the companies admitted to the Tehran Stock Exchange for a period of 10 years from the beginning of 2011 to the end of 2014. Finally, the findings showed that the firefly algorithm, genetic algorithm and evolutionary algorithm were effective in predicting the ratio of QTobins, return on equity and return on equity, and the firefly algorithm had a higher power to predict the ratio of QTobins, return on equity and return. has shares

In the present day, we are observing many contests within organizations, particularly educational ones. These competitions are causing a great deal of tension for the employees of these organizations. Organizational spirituality has had a notable impact on the morale and social interactions of employees who are under pressure and can be an effective means of coping with this pressure. Integrating spirituality into an organization's structure can imbue work with a sense of purpose, and employees who prioritize their inner values tend to approach their work with diligence and ethics. This study aimed to assess and analyze the impact of spirituality within work environments on social behavior in Iran's education sector, with a particular focus on the mediating role of organizational moral climate. The research was conducted with a statistical population of 270 education workers, from whom 159 individuals were chosen randomly using Morgan's table. To gather data, three standardized questionnaires were utilized: Milliman et al.'s  [21] "spirituality in the workplace" questionnaire consisting of 13 questions, Duffy et al.'s [7] "social behavior" questionnaire with 14 questions, and Cullen, Victor and Bronson's [5] "ethical climate" questionnaire comprising of 18 questions. All questions were rated on a five-point Likert scale that ranged from "very little" to "very much." After ensuring the questionnaire's validity and reliability through face validity and Cronbach's alpha, research hypotheses were analyzed and evaluated using SMART PLS software. The analysis demonstrated that spirituality within the work environment has a positive and significant influence on an organization's moral climate and social behavior. Moreover, it was revealed that the moral climate fully mediates the effect of organizational spirituality on social behavior.

The Covid-19 outbreak has created a situation in which most businesses now think of survival as a return. With the end of this crisis, they will not necessarily return to the pre-crisis period. The present study designs a strategy model to cope with industrial crises caused by the outbreak of common viruses. The meta-synthesis method was used to obtain a comprehensive combination of the factors of the strategy model to cope with the industrial crises caused by the outbreak of common viruses. To use this research method, Sandelowski, and Barroso's seven-step method was used. The primary question of the present study is "What are the criteria of the strategy model to cope with the industrial crises caused by the outbreak of common viruses?" Also, based on the previous studies, the present study performs an in-depth analysis of these factors in the international and national spaces and presents a classification of them. The research process is implemented as follows. The tests were categorized and coded using MAXQDA software. According to the literature and the background of the study and the results obtained, the factors of the strategy model to cope with the industrial crises caused by the outbreak of common viruses include organizational environmental factors, organizational crisis management, organizational resource management, organizational marketing, and customer-related strategies, organizational business model, organizational capabilities, organization human resource management, and organizational information management. In this regard, the category of environmental factors was ranked first, the category of organizational crisis management was ranked second, and the category of marketing was ranked third.

The purpose of this research is to develop the outsourcing model of the bank's electronic banking services using game theory to identify the equilibrium and win-win strategies between the bank and the applicant companies. For this purpose, an interview was held with bank and company experts. After qualitative data analysis,16 strategies were identified for the parties. According to the compatibility of the identified strategies with the marketing mix, the results were grouped into 4 product groups, price, distribution and promotion. Since the identified strategies did not have the same value for the parties, to identify the weight of the strategies. A pairwise comparison questionnaire was used and the opinions of experts from each side were collected separately. The analytical Hierarchy process was used to obtain the weight of each index and the Inconsistency Ratio index was used to check the reliability of the obtained results. After identifying the weight of the strategies, the game environment was implemented and according to the 16 identified strategies, 65536 scenarios were implemented for each side. After performing calculations, 8 scenarios with the same outcomes were identified as equilibrium scenarios or Nash Equilibrium games. The scenario that had the most consequences for the parties was introduced as the result of the game.

Nowadays, product recovery and waste recycling are receiving more attention in order to reduce environmental pollution and production costs in the form of a closed-loop and sustainable supply chain. Also, designing a supply chain by considering resilience approaches can protect buyers against disruptions such as natural, human or technological disasters. On the other hand, efficient and effective financial supply chain management (FSCM) way is known as one of the main structures in line with the continuity and stability of the chain's performance, and budget restrictions are of great importance considering the issue of scarcity of resources in the economy. This study has presented a multi-objective mixed integer linear programming (MOMILP) model of a single-period, multi-product and multi-level closed-loop supply chain, taking into account the dimensions of sustainability and resilience, emphasizing the balance between the initial budget and the cost of establishing facilities under uncertainty. subsequently, to eliminate the uncertainty of the demand parameters and costs, its robust counterpart was presented based on Pishvaee’s robust possibilistic programming (RPP) model. The augmented Epsilon Constraint method (AEC) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were used to solve and evaluate it.

Recent studies show two important factors in the nonlinear behavior of cost and profit. The first factor is cost stickiness, which expresses economic asymmetry in the reaction of cost to increase and decrease in sales. The second factor is related to accounting conservatism, which indicates the asymmetry of financial reporting in identifying good news versus bad news. Although conservatism and cost stickiness are conceptually based on two different and separate phenomena, but they create two similar patterns in the temporal asymmetry of profits. This study examines the relationship between cost stickiness, levels of conservatism and firm life cycle. In this research, by using the combined data technique and by using three models of non-operating accrual items, Basu's model and market value model, and with a sample consisting of 113 companies admitted in the Tehran Stock Exchange during the years 2010-2019, this goal has been investigated.The research results indicate that the stickiness of costs is related to conservatism in all three models. The findings of the research show that in the growth stage between cost stickiness and conservatism of companies, there is a significant negative relationship in all three models, of which Basu's model has more explanatory power. In the maturity stage, there is a negative and significant relationship between the stickiness of costs and the conservatism of companies in the Basu's model and non-operating accruals, but no significant relationship has been observed in the market value model. In the recession stage, the effect of cost stickiness on the reduction of conservatism is significant only based on the market value model. Finally, in the decline stage, no significant relationship was found in any of the three models.

Financing patterns should minimize the weighted average of capital and maximize shareholder value. This study aimed to evaluate the factors affecting the financing model through a capital increase and its effect on abnormal stock returns. This mixed study was conducted based on interviews with 16 experts. Factors such as investment purposes of the capital increase, sources of the capital increase, and differences in the rules of the Tehran Stock Exchange, such as the scope of oscillation and characteristics of the company, are the essential components affecting the pattern of capital increase. In addition, the results of the qualitative analysis were measured by using the questionnaire tool and asking the opinions of 400 financial managers and university professors using the structural equation analysis method. The results showed that the investment objectives of the capital increase, the methods of increasing cash from shareholders and stock premium, and stock dilution significantly affected capital increase and, consequently, abnormal and negative stock returns.

Invertible members of some of the most famous multiplicative quasilinear spaces are exactly equal to invertible elements of the linear subspace of such spaces. But with the old definition of invertible elements, we do not get anything extra. So, in the present paper, we develop the introductory algebra and introduce an extended model of invertible elements. This new concept plays a fundamental role in the definition of the generalized spectrum model. These new objects are constructed in such a way that can provide acceptable results. For example, we will be able to generalize the well-known theorem ``Spectral mapping property for polynomials'' with these new notions.

Integrating art, industry, and architecture and creating outstanding urban cultural spaces make attractive viewpoints for citizens and travellers, and raise the position of urban elements as the elements of the city’s identity. Therefore, this study aimed to evaluate the urban cultural space based on structural, perceptual, and functional-social identity. This analytical survey study was conducted on eight cultural spaces in Tabriz, Iran, using a questionnaire and descriptive and inferential statistics. Based on the descriptive findings, the elements of the traditional Bazaar and Ali Monsieur’s house scored the highest and lowest points regarding structural and functional-social identity. Among other elements, the El Goli Building of Tabriz was more successful regarding perceptual identity. In addition, architectural style and behavioral diversity had the most and least roles in selecting urban elements, respectively. A group t-test was used to check the position of each component of the studied styles. The results indicated the favorable condition of the Municipal Palace, Traditional Bazaar, and Eel Goli in all three styles. The urban cultural space was compared based on the identity components between the pairs of existing groups using the parametric t-test. The results showed a significant difference between the average evaluation of the examined couples based on gender, education, and frequency of visits. However, no significant difference was observed between the purpose of the couple’s reference in evaluating the urban cultural environment. The Pearson correlation results confirmed a relationship between structural and perceptual identity components at less than 0.01. In contrast, no significant relationship was observed between functional-social identity components.

The main purpose of this study is to shape, design and present a model that can be used to develop the level of customer service through social networks in the banking system. For this purpose, a large part of the mentioned structures was extracted using the ultracomposite method. Therefore, in the first step, an extensive search was conducted among various sources (including books, book summaries, periodicals, case studies, doctoral dissertations, etc. based on keywords) and more than four hundred sources were collected. Then, by separating the categories, themes and coding, using qualitative data analysis software, the results will be extracted and finally, multiple structures will be extracted to compile the model. In the following, by using "content validity indices and content validity ratio", the validity of the desired measures was measured by the opinions of the experts and then with the limited use of questionnaire items, the reliability of the items that make up the functional structures, as well as the reliability of the questionnaire tool (alpha Cronbach's) calculation and the result was 0.89.

The idea of receiving tax from cash or bank transactions (BTT) (not new) has been used many times in different economic and political fields during the decades since the introduction of financial transaction tax (FTT). This study examines the provision of the optimal model of financial transaction tax (FTT) with an interpretive structural model (ISM). The method of the current research is practical in terms of its purpose and it is mixed (qualitative-quantitative) in terms of data collection. The qualitative research method was qualitative content analysis with an inductive approach. The participants in the qualitative part of the research were experts in the tax field, and 12 people were interviewed using the theoretical snowball sampling method. The estimation of the desired sample size was done based on the theoretical saturation of the data. The data collection tool in the qualitative part was a semi-structured interview. The triangulation method and Christiansen angle technique were used to check the validity of the qualitative part. At first, research components were identified through literature and semi-structured interviews with experts. The interviews were coded with three coding methods, open, central and selective, and finally, fifteen components were identified and in the quantitative part, an interpretive structural model was created using MATLAB software to provide an optimal model for financial transaction tax. After that, the position of the identified components was determined using Mikmak software based on influence and dependence. The results show that the structural interpretation model of the study can be presented in five levels. Micmac analysis also showed that the components of the optimal tax pattern are divided into the group of dual, regulatory, independent, leveraged and influential variables. The findings show that the optimal tax model is an unstable system.

A model for determining the oil market transferability turmoil on the financial markets of the Iranian economy using the dynamic systems approach. At first, data related to oil, gold, stock exchange and foreign exchange were extracted from statistics related to the World Bank, Central Bank and Statistics Center of Iran and were analyzed with statistical analysis and simulation software. Then the research model was constructed using simulation methods and system analysis and the results were analyzed. The oil market in supply and demand for price determination is based on global systemic behavior. this simulation has used the factors affecting oil supply, oil demand, the expectations that shape this supply and demand, as well as macro factors such as macroeconomic indicators of the US economy, sanctions on the oil sector in Iran, the rate of world industry development and the available knowledge on oil substitution. Hidden mechanisms are the main reason for some oil price behaviors. The results of the research have led to the forecast of oil prices in the baseline scenario until 2025. The presence of political problems due to the interconnectedness of parallel markets in Iran causes widespread fluctuations in the currency and gold sectors in the Iranian economy

Internal marketing has been developed in various forms in all types of organizations. Mainly, internal marketing has been studied as a motivational strategy in service companies. Goods manufacturing industries have not benefited much from the use of internal marketing in strengthening employees' extra-role behaviors. Customer orientation is one of the extra-role behaviors of employees, which in turn is the source of value for internal and external customers. When we follow the internal process segmentation approach, the organization is divided into a set of internal suppliers and internal customers. In this case, it becomes important to study the customer-oriented behavior of employees in the exchanges within the organization. To ensure the implementation of internal marketing in manufacturing organizations, in a way that best meets the needs of these organizations, it was necessary to conduct a study specific to manufacturing industries; a study that included the identification of internal marketing components with a customer-oriented approach. The purpose of the current research was to identify and introduce the dimensions of internal marketing with a customer-oriented approach of employees in manufacturing industries.

This is a sequential mixed research in the inductive paradigm that was conducted in qualitative-quantitative phases. Its purpose is practical and its nature is exploratory. The data collection of the qualitative phase was carried out during semi-structured interviews that continued until theoretical saturation, and finally 15 experts and managers of manufacturing industries and university professors in the field of management participated in it. Qualitative phase analysis was done with them analysis approach using MAXQDA software. In the quantitative part, the fuzzy Delphi questionnaire was used to reach the consensus of the expert group on the dimensions identified in the qualitative phase.

The results indicate the extraction of internal marketing dimensions with a customer-oriented approach in comprehensive themes (individual factors of employees and managers, organizational factors, motivational factors) and in 9 organizational themes, 1- Demographic characteristics 2- Organizational citizenship behavior of employees and managers 3 - Managers' support 4- Internal communication 5- participatory management 6- Promotion of customer-oriented culture 7- Employee job security 8- Job satisfaction 9- Appreciation and 44 basic themes.

A construction project is a combination of various planned or unplanned events that happen during the life cycle of the project and continue to exist under changes in the environment. In the meantime, some factors have double importance in the success of a project or its failure; these factors are known as project success factors. The purpose of this research is to provide a framework for the success of construction projects in Iran, focusing on large national projects. In terms of the nature of the research, the present research is an exploratory study. In terms of research strategy, it is a single case study about large national projects. The data collection tool in the research is the interviewing method. In the present investigation, the snowball sampling method, which requires consultation with knowledgeable people, has been used to introduce suitable cases for the research by them. To analyze the data, the thematic analysis and thematic network analysis methods have been used. The findings showed that the competence of the project manager was repeated more than other items in all the interviews. Therefore, the most important factor in project management is the competence of the project manager and the competence of the team. Nowadays, the employment of skilled and qualified personnel is an essential requirement for construction projects. It has been considered an important factor in other industries of the country, and the results of gathering the opinions of experts in the construction industry in this research also confirm this is the issue. Among the critical factors affecting the success of construction projects in Iran, the lack of use of advanced and up-to-date technologies was the most important factor. In other words, technology is changing and improving every day so it has entered into new fields.

Cargo fleet routing problem is part of the problems that arise and are used in the transportation industry. In this research, one of the specific types of this issue as the time fleet tracking with a limited time period which is the most common problem in operations research at the present time will be discussed. The aim of solving this problem is to provide service to many customers at different locations and different demands by a sufficient fleet. Considering these limitations each customer should set a period of time in service and delays in service are to a certain extent. In this study, reach sooner at the fleet to each of the destinations has given the delay in the service to a certain amount of the fines in accordance with the early and late is acceptable. In terms, they call it (period of application). According to surveys, in order to achieve the above objectives, the use of Bees Algorithm is used in this thesis. Using the Bee algorithm in this research is due to the evolutionary nature of this algorithm.

This paper aims to investigate the asymmetric effect of discretionary and nondiscretionary components of accruals on the relation between earnings dispersion and excess returns. With the increase of discretionary and nondiscretionary components of accruals, what behavior does the earnings distribution show and what effect does this issue have on the excess returns? This research presents an asymmetric correlation in terms of method and nature. Using a systematic sampling method from the companies listed in the Tehran Stock Exchange (TSE), 137 companies were selected as a sample from 2014 to 2020. After examining the classical assumptions of regressions, the panel data model with fixed effects was determined. The results show that (1) there is a positive and significant relation between earnings dispersion and excess stock returns, (2) the accrual's discretionary components have an insignificant effect on the relation between earnings dispersion and excess stock returns, (3) with the increase of discretionary components of accruals, the relation between earnings dispersion and excess stock returns increases, (4) the accrual's nondiscretionary components have a negative and significant effect on the relation between earnings dispersion and excess stock returns, (5) with the increase of accrual's nondiscretionary components, the relation between earnings dispersion and excess stock returns goes up.

Tax collection has always been one of the main problems of governments for a long ago because companies evade paying taxes and deceive governments for several factors. Therefore, this paper identifies and prioritizes the effective factors in reducing tax evasion in the tax affairs organization. This is qualitative and quantitative research. This article identifies and prioritizes effective factors in preventing tax evasion through the content analysis method, Delphi survey method, and Analytical Hierarchy Process (AHP) by drawing a decision tree. Moreover, data was collected using a researcher-made questionnaire, as well as examining the conceptual relationship between the indicators and the questionnaire pairwise comparisons. The sample includes 25 experts working for the Tax Affairs Organization in 2022. The hierarchical analysis results have identified five main factors affecting tax evasion, including managerial, economic, political, social, and rules and regulations factors. Also, 19 effective factors in reducing tax evasion were identified and agreed upon by experts. The findings showed that the factor of rules and regulations with a relative weight of 0.381 and political and managerial factors with weights of 0.228 and 0.204, respectively have the highest degree of importance in reducing tax evasion from the Tax Affairs Organization experts’ opinions. Governments strive to maximize tax revenue to meet rapid growth and economic development; therefore, governments always seek a solution to prevent tax evasion to achieve a stable level of tax revenue. Therefore, accurate identification of the effective factors in this field helps governments to take steps towards the realization of their goals. The research findings show that this article can be a good start to address the effective factors and priorities in reducing tax evasion for the government.

In this present investigation, for functions of the form $f(z) = 1/z^p + \sum^∞_{k=1−p} a_kz^k$, which are analytic in the punctured unit disk $U^∗ =\{z ∈ C : 0 < |z| < 1\}$, we introduce a new subclass of meromorphically p-valent functions and investigate convolution properties, Coefficient estimates and containment for this subclass.

Data platforms with large dimensions, despite the opportunities they create, create many computational challenges. One of the problems of data with large dimensions is that most of the time, all the characteristics of the data are not important and vital to finding the knowledge that is hidden in them. These features can have a negative effect on the performance of the classification system. An important technique to overcome this problem is feature selection. During the feature selection process, a subset of primary features is selected by removing irrelevant and redundant features. In this article, a hierarchical algorithm based on the coverage solution will be presented, which selects effective features by using relationships between features and clustering techniques. This new method is named GCPSO, which is based on the optimization algorithm and selects the appropriate features by using the feature clustering technique. The feature clustering method presented in this article is different from previous algorithms. In this method, instead of using traditional clustering models, final clusters are formed by using the graphic structure of features and relationships between features. The UCI database has been used to evaluate the proposed method due to its extensive characteristics. The efficiency of the proposed model has also been compared with the feature selection methods based on the coverage solution that uses evolutionary algorithms in the feature selection process. The obtained results indicate that the proposed method has performed well in terms of choosing the optimal subset and classification accuracy on all data sets and in comparison with other methods.

In this research, the system dynamics method has been used to simulate the causal loop model of the goals of the West from the nuclear dispute with Iran. First, we deal with the crises in which the Western world, the US at its head (especially the US), is involved. In the following, the status of sanctions policy and economic sanctions are discussed as the pressure lever in contrast to political issues and international conflicts. Given the existence of the Iran-West nuclear dispute, and the US at its head (mainly the US), the effects of the sanctions are expressed below and the relationship between the goals of the West and the nuclear dispute with Iran is shown by developing a comprehensive model. In the model, the goals of the West from the nuclear dispute with Iran, including the transition of the West from fossil fuels to new energy, the US trade deficit by raising the price of oil, the systemic leap of the West, the survival of the military industry of the West, and the project of the passageway of Western civilization using causal loops are modeled. The developed models provide a comprehensive and systematic perspective for policymakers.

Healthcare services supply chain performance evaluation in hospitals that deal with society's well-being has significant importance on their performance improvement. The purpose of this research was to evaluate healthcare services supply chain performance using a neutrosophic multiple attribute decision-making technique in Tehran’s hospitals. Comprehensive performance evaluation was conducted by applying both objective attributes that focused on the outcome along subjective attributes that were based on the judgment of evaluators. In this regard, neutrosophic logic has been deployed to face uncertainties in the expert’s judgment for determining the priority of attributes over each other explained via linguistic variables in the form of trapezoidal neutrosophic numbers. Eigenvector-power as one of the multiple attribute decision-making techniques concerned with evaluating and choosing the best option among the available ones based on diverse and conflicting attributes was used to ascertain attributes’ importance in addition to guaranteeing obtainment of the largest eigenvalue of the characteristic polynomial, has led to reduction of calculations. Neutrosophic algebraic operations embedded in the eigenvector-power technique after efficiency confirmation of the technique was acquired. In order to gap analysis, a paired t-test was exploited to discover the existence of differences between the current and desired performance of attributes. Then, attributes’ weighted performance gaps were calculated by multiplying the weight of each attribute by its performance gap which smoothed attributes’ performance gap criticality definition by applying quartiles. ``Staff job satisfaction" and ``response to demands" attributes were categorized as very highly critical, ``treatment branding" and ``proportion of service with cost" attributes were classified as highly critical, ``technological comfort" and ``stakeholder’s interests" attributes were grouped as moderately critical and ``access" and ``treatment plan fulfilment" attributes were relegated as low critical, respectively according to the weighted performance gap.

Banks are the engine of providing financial resources in the economy and have special importance for governments. Accordingly, presenting the factors and components affecting financing restrictions and changes in the corporate debt bonds yield, risk management, as well as changes in their stock prices, in terms of bank management and from a macroeconomic perspective, can be considered as the leader of the economy and government. On the other hand, the proper management of banking challenges and the improvement of factors affecting the efficiency and effectiveness of banking resources can move the economic cycle in the right direction, considering that the banks' primary activity is to grant loans and provide them to applicants. Accordingly, the researcher addressed the effect of the ability to manage political relations and financial crises on performance improvement. Therefore, a combination of Data Envelopment Analysis (DEA) and Two-Stage least squares (2SLS) regression analysis was used. This study is descriptive research with the correlational and post-event approach. In this way, the information about 11 banks in a period of 9 years (2014-2023) was analyzed. The results showed that the improvement of ability level and proficiency in bank management will lead to the improvement of financing constraints, changes in corporate bond yield, and the growth rate of stock and non-shared incomes. The management authority not only affects credit risks, credit risk management and liquidity risk but also does not affect the stock price drop.

The purpose of this research was to present a communication model of customer participation and competitive business with social media based on brand (case study: manufacturing and trading companies of Ahvaz). The statistical population of the research was formed by the experts of manufacturing and trading companies in Ahvaz city. In this research, the considered variables were identified by using interviews and examining the opinions of experts of the investigated companies. 10 experts have been selected using the saturation sampling method. This research, using the foundation's data analysis method, is a type of cross-sectional research in which the data was collected for several weeks. In the quantitative part, the research community is the customers of food manufacturing and trading companies in the industrial towns of Ahvaz city which have been selected to fit the model. Due to the unlimitedness of the statistical population, 384 samples have been considered, and finally, 312 questionnaires have been analyzed. Using Maxqda software, interviews and Coding is done. Smart PLS 2.0 and SPSS 22 software were used in the validation section. In this research, to check the validity, the findings of the research were presented to the participants and the text of the theory was studied by them and their points of view were applied. The reliability of the model was evaluated using the Kappa index. Kappa index value equal to 0.788. Calculated and placed at the valid agreement level. 58 open codes have been identified among 256 concepts. 58 primary codes in the form of 18 categories, including company performance, electronic services, customer value, customer attitude, social responsibility, competitive advantage, customer loyalty, customer desire, advertising and marketing, brand awareness, customer trust, social media, validation, sharing Content, customer participation, service innovation, organizational factors, branding. Validation of the model showed that the overall index of fit (GOF) is equal to 0.661, which is a strong index and shows the overall high quality of the model. The identified factors have had a significant impact.

Food security has been an ongoing concern of governments and international organizations. This study aims at ensuring food security using geospatial technology to find suitable sites for building food industry plants. In this respect, geospatial technology including remote sensing, geospatial information system, and global positioning system was implemented to identify suitable sites for the construction of food industry plants in Qaemshahr County, Iran and an up-to-date and efficient geodatabase for this purpose was prepared. Since rice and citrus are the main products of the study area, to ensure food security and income for the people of the region, suitable site selection to build food industry plants to sort, package, store, convert, and process rice and citrus is very important. On the other hand, because Ghaemshahr is the main hub of rice and citrus production in the country as well as export, food security at the national level can also be ensured. To support the achieved result of selected sites for food industry plants, several analyses were carried out. The resulting suitability map was reclassified based on proximity to raw food materials as well as main roads and cities. Consequently, among the obtained suitable sites, the most suitable places based on these factors were identified. In addition, a comparative analysis was performed between the selected sites and the existing industrial zones in the study area. The findings of this study are useful to ensure food security in the region and country. The study also demonstrated the effectiveness of geospatial technology for this purpose.

The aim of this research was to estimate the influencing factors on the size of the underground economy using fuzzy logic. The illegal nature of the underground economy also limits private investment and economic growth. For example, companies that operate in the underground economy are not able to use the institutions that support the market economy (judiciary and courts), which makes them less inclined to invest. Therefore, it can be said that one of the most important issues that should be considered in economic policies is the underground sector of the economy. The research method in this research is of a descriptive-survey type, and the type of research in the current research is causal and practical in terms of the purpose, because the expected results of the research can be used in examining the dimensions of the underground economy. It is used in university and economic resources. To estimate the index of the underground economy and examine its trend using fuzzy logic, it is necessary to perform these steps; Accurate determination of indicators, fuzzification, definition of basic rules, inference engine, determinism and sensitivity analysis. To estimate the index of the underground economy with fuzzy logic, they are divided into three sub-criteria including the financial sector, the monetary sector and the real sector. The results showed that the informal sector constitutes an important part of the economy and the labor market in developing countries. This sector plays a major role in production, creating employment and income by producing goods and services, transferring skills by newcomers to the sector, reducing unemployment and using individual capital.

Investment in and allocating investment resources to business activities is done through financial market and banking credit market is part of this market. The most role of banks in financial market is giving credit to customers. In this matter the capital adequacy assessment and credit risk are important and their control is considered as one of the key effective factors in bank operation and plays a major role in banks and financial institutes’ stability. So, the aim is determining the effect of macroeconomic variables (GDP, liquidity, inflation rate and exchange rate) on Capital adequacy, liquidity risk and credit risk. The results showed that macroeconomic variables have a significant effect on banking risks.

Due to the emergence of social networking platforms, a large number of users around the world are being part and partial of this platform. At a fraction of the time users on social media are communicating digital files in the form of text, video, images, voice and music which ultimately generates big data. The matter of interest is to estimate precisely the average file size at time duration (occasion). The time may hours or days or months. This paper presents a sample-based methodology to deal with mean size estimation of digital communication content spreading on a social media platform. An estimator is suggested using a random sample from big data and its properties are derived. A simulation method is suggested that computes the confidence interval (CI) for the prediction of précised range of digital file size. The proposed method produces an optimal confidence interval at the suitable choice of constant. These estimated confidence intervals can be used for developing $\alpha$-control charts for constant monitoring of the growth in file size in social media storage at the data centre. If the growth of mean digital file size crosses the upper limit then additional storage infrastructure is needed at the administration level of the social media site. One can generate machine learning algorithms proposed method for monitoring the growth of average digital file size over time duration.

In this study, the concept of C-class functions in the setup of Sb-metric spaces is introduced and common coupled fixed point theorems for these mappings in complete Sb-metric spaces which involve altering distance function and ultra altering distance functions are established. A few instances are given to support our major findings. We also provided an application for integral equations.