فهرست مطالب ایوب محمدیان

Considering the high speed of growth and development of the Persian Gulf countries and their need for civil development, and since Iran has abundant resources and potential to produce high-quality construction products, and because of its neighborhood and cost-effectiveness in terms of transportation, these countries are very profitable destination for export. Therefore, the current research was conducted with the aim of providing a digital marketing model for the development of export markets for construction industry products in the Persian Gulf countries.This research has been analyzed and coded by using the Strauss and Corbin approach of grounded theory. Data obtained from semi-structured interviews conducted with 24 experts active in construction companies of Kish Island continued until the theoretical saturation of this process was reached. Based on this model, among the extracted concepts, supply and demand pressure from neighboring countries, logistical issues due to geographical location, technological platform in terms of using block chain technology, budget allocation, Arabic language website design, content marketing according to the need and culture of the neighboring Arab-speaking countries and specialized consultations were among the components that were particularly important in the discussion of export in the construction industry. The findings of this research can help the activists in the construction industry and the export of construction products to implement efficient digital marketing in order to achieve its major benefits, including profitability and foreign exchange.

Government data collected from public funds and contains valuable data, if opened, can be usable in various areas, can stimulate innovation. It is necessary to investigate contexts and factors affecting the Open Government Data driven Innovation (OGDI). The main question of research is: How does open government data lead to the creation of innovation? So that, trying to answer six sub-questions consisting: causal conditions, background conditions, intervening conditions, main phenomenon, strategies, and consequences about OGDI. This research, according to mixed method (qualitative-quantitative), first used the grounded theory based on Strauss-Corbin method; then due to qualitative analysis of data obtained from interviews, three-stage coding was used; next a quantitatively evaluated done by using Shannon's entropy method. Based on data sufficiency principle, up to theoretical saturation stage, 11 semi-structured interactive interviews with experts were done. Due to results obtained from interviews, 6 main categories according to the sub-questions of the research, and 20 sub-categories containing 95 concepts were extracted. Attention requirements per each main categories, subcategories and concepts were suggested for future research. Proposed theoretical model shows that, at first step, if "setting of supporting laws for OGDI", and "the demands of external stakeholders" (causal conditions) are done correctly; and at second step if simultaneously "market development and investment in OGDI" (context conditions), "drafting the data governance document" (main phenomenon), and "utilizing the capacity of the private sector in form of PPP"(intervention condition), executed correctly; also in third step, by using all types of innovation (strategy), it will achieve consequences such as transparency in the organization, solving "stagnation of private businesses" and "unemployment in society" problems.

Digital transformation as a new environmental paradigm is rapidly changing the internal and external dimensions of the business environment. Traditional businesses face more challenges in this new technology-motivated situation. The complexity and high uncertainty of the business environment, the need for more knowledge and experience in transformation management, the high cost of technology adoption, and internal resistance to change are obstacles to decision-making for digital transformation in traditional industries like the fashion retail industry. Lack of information and knowledge of management for reinventing their business model and forming their digital transformation strategies require solutions. To manage the situation strategically, organization leaders need a conceptual model to design their thinking about the path of digital transformation, reduce the ambiguity in their strategic decision-making process, and reduce the waste of resources in their organizational digital transformation. The model would help the organization understand the strategy formation process in digital transformation.

This is an applied developmental study with a descriptive approach. This study developed a new conceptual model using the five-step method of the grounded theory literature review. In this research method, the findings of the existing studies are investigated using content analysis and open and axial coding in the fundamental theory method. The distinction of this method is the possibility of introducing a model and framework derived from the findings of previous studies, which ultimately led to the design of a conceptual model of strategy formation for the digital transformation of fashion retail.

By mining the existing body of literature, 36 studies were systematically screened, and based on content analysis and open and axial coding in a grounded theory approach to the articles' findings, 75 codes and 27 main categories were extracted. In the next stage, the categories were prioritized using the Shannon entropy technique based on the frequency of article codes. The final presented model has three main parts: drivers, dimensions, and consequences of strategy formation in the digital transformation of fashion retail.

Industrial digital transformation drivers include customer push for digitalization, pressure of competitors' progress, and supply chain push. Internal drivers are digital transformation leadership competency, employee readiness, digital technology capacity, financial expectancy, and strategic capacity for digital transformation. Digital technology penetration, sustainability, social and economic trends, and legal requirements are megatrends driving digital transformation. The customer push and the widespread influence of information technology in all aspects of human life are the most crucial drivers of the external environment. The organization's strategic capacity and technological infrastructure are essential internal drivers in forming a digital transformation strategy, which implies the necessity of digital acceptance in context and digital competency in the organization to start the transformation process. These drivers stimulate and direct the digital transformation process in the fashion retail organization. Organizations have no control over these drivers but need to know drivers and their dynamics for the strategy designing stage. The dimensions of digital transformation strategy in fashion retail organizations include customer experience, data and technology management, executive processes and operations redesigning, digital organization, employee experience, and digital supply chain management. Due to retail industry specifications, among the seven dimensions of the digital transformation strategy, customer digital experience, digital technology management, and data management need more investment and attention, and redesigning digital business models according to new opportunities and challenges should be considered. Organizations need strategy, plan, and budget to transform these dimensions.The consequences of digital transformation strategy formation in fashion retail organizations were also classified as value co-creation, financial performance improvement, competitive position and customer satisfaction, organization sustainability, smartness, and increasing efficiency and effectiveness. Although there are multiple consequences of digital transformation in retail organizations, The value co-creation between customers and the retail industry is an essential consequence resulting in emerging innovative products and services. Also, it will direct the fashion retail industry to join the sharing economy and circular economy in the future.

Digital transformation is rapidly changing apparel retail organizations. The high speed of new knowledge and the uncertainty of the fashion world do not allow organizations to make strategic plans, and force them to make strategic decisions in this field. Identifying and conceptualizing the drivers of strategic decisions for the digital transformation of apparel retail organizations is the primary goal of this research by using the multi-grounded theory research strategy. In the theoretical grounding stage, twenty-three international articles were selected and codes and concepts were extracted using the metanalysis method. In the experimental grounding stage, interviews were conducted with seventeen experts, and the codes and concepts extracted from the metanalysis stage were re-examined, redefined, and completed. Finally, by going back and forth and enriching the theory, the conceptual framework model of strategic decision-making drivers of digital transformation in Iran's apparel retail was designed. The results indicate that the drivers of strategic decisions for the digital transformation of apparel retail organizations are in seventeen concepts and four categories under the headings of "organizational drivers," industry and market pressure," "government infrastructure requirements," and "environmental macro trends." The economic pressure and the spread of information technology and bio-social changes from the environmental macro trends and the expectation of financial performance and digital infrastructure of the organization and the employees' pressure from the category of organizational drivers and customer pressure and the pressure of the competitive environment from the category of Industry and market pressure seem to have the most importancecompared to other concepts.

the aim of the current research was to identify the barriers to the implementation of this system as well as the relationships between these barriers. Prior to any enforcement action, it is necessary to identify barriers to the implementation of such a system. This study is of a mixed type (qualitative and quantitative), with a practical purpose. the interview method and tools were used in the qualitative part of the research, and the questionnaire method (based on the ISM method and the DEMATEL model) employed in the quantitative part. After identifying the barriers, the relationship between these categories was investigated in two stages: intra-group (6 different matrices) and inter-group (extraction of the most causal and effected categories). Finally, the most important barriers with the most causal (as well as effected) role were identified. This study showed that there are many barriers for the implementation of a total health information system in Iran, among which the most important one with the greatest causality is related to the economic rent, lobbying, and huge incomes resulting from the lack of transparency and the lack of access to information in this area. As a result, the interest groups in this area are always trying to prevent development of a total information system in the health sector. In the meantime, the role of the security perspective on the category of information sharing,

Today, responding to social and environmental challenges as well as the economic aspects is a major strategic concern for businesses. In the digital age, the lifestyle of customers has changed; therefore, businesses are struggling to present their products and services in novel digital ways to the new generation of consumers. To meet such challenges, every business needs to rely on its internal capabilities, update its internal capabilities based on external changes, and get out of the static state. The purpose of this study is to provide a model for business innovation in line with the sustainability and developments of the digital age based on the dynamic capabilities of businesses. Previous research did not investigate the required dynamic capabilities for creating sustainable digital business models. In addition, earlier models were presented statically. None of them considered the sequence and relationship of related capabilities. The present study tries to resolve this scientific gap.

This is a mixed methods study (both qualitative and quantitative). In the qualitative phase, meta-synthesis and content analysis were used and in the quantitative stage, the quantitative method of Interpretive Structural Modeling (ISM) was adopted.

The proposed model by this study consists of three approaches, four aspects, 16 dimensions, and 37 components, which are based on quantitative modeling of 16 dimensions in four main levels of "Sustainable Computing", "Sustainable Execution", "Sustainable Engagement" and "Sustainable Results", respectively. Because earlier models were presented in a standing and non-process manner, the sequence and relationship of the components related to all were not determined. This study eliminates this scientific gap.

Based on the results of this study, to innovate a business model, in addition to designing the business based on social and environmental sustainability components as well as digital technologies, it is necessary to pay attention to a new component called sustainable engagement. The concept indicates the need to pay attention to the empathy of businesses with society and the environment in addition to customers. Therefore, it is necessary for different businesses to pay attention to the mechanisms of creating sustainable engagement from the beginning of business design as a first step in their business design. For this purpose, it is necessary for business managers to acquire the skills and knowledge of design thinking in business. In addition, due to the increasing speed of environmental changes, it is necessary for businesses to consider agility and learning by doing in their business design. In addition, the digital technology factor is the most independent and influential. The economic, social, and environmental sustainability factors come with the least influence but the most dependence on other factors. The proposed model by this study can be used as a business model canvas to redesign and innovate the business model of large companies and start-ups that seek sustainability in the digital age based on dynamic capabilities.

Despite the enormous volume of data and the benefits it can bring to marketing activities, it is unclear how to use it in the literature, and very few studies have been conducted in this field. In this regard, this study uses dynamic capabilities view to identify the dynamic capabilities of data-driven marketing to focus on data in the development of marketing strategies, make effective decisions, and improve efficiency in marketing processes and operations. This research has been carried out in a qualitative method utilizing the content analysis strategy and interviews with specialists. The subjects were 18 professionals in the field of data analytics and marketing. They were selected by the purposeful sampling method. This study provides data-driven marketing dynamic capabilities, including; Ability to absorb marketing data, aggregate and analyze marketing data, the ability to data-driven decision-making, the ability to improve the data-driven experience with the customer, data-driven innovation, networking, agility, and data-driven transformation. The results of this study can be a step towards developing the theory of dynamic capabilities in the field of marketing with a data-driven approach. Therefore, it can be used in training and creating new organizational capabilities to use big data in the marketing activities of organizations, to develop and improve data-driven products and services, and improve the customer experience

The purpose of this paper is to determine the effective factors influencing the value of FinTech start-ups from the perspective of venture capitalists in the field of financial technology in the early stage of their life cycle.

This research is qualitative that uses the Grounded theory method. In this study, by interviewing 19 venture capitalists active in the field of financial technology, 46 final codes were extracted via open coding. In the next step, through axial coding, a paradigm model was presented for the main value of the start-up FinTech company.

This study showed that the value of FinTech start-ups is majorly influenced by the intervening factors related to their main buyers, i.e. banks and financial institutions because the benefits of buying fintech companies are strategic for banks and financial institutions and can create a competitive advantage for them compared to other banks and financial institutions. In addition, it was found that underlying conditions such as investor exit routes, the need for reinvestment, and the consequences of their merger and acquisition also affect the value of FinTech start-ups.

The value of FinTech start-ups is more affected by the intervention of their buyers than other technology start-ups, because the benefits of buying FinTech companies are strategic for banks and financial institutions, and it can give them a competitive advantage over other banks.

Government data contains a large amount of valuable data that can be exploited in various fields if opened. Utilizing open government data, in addition to providing the opportunity to monitor government performance and to create transparency and justice, has another very important function. It helps with developing innovation and the issue has recently been considered by many researchers. However, past research has inconsistently examined the intra-organizational factors influencing open government data to achieve innovation. The present study seeks to identify the intra-organizational factors affecting open government data to achieve innovation in government services through applying the systematic meta-combination method.

In this research, to identify the intra-organizational factors affecting open government data, the systematic meta-synthesis method was used. For this purpose, 888 related articles based on title, abstract and content were filtered and 51 final articles were obtained.

 Based on the results obtained from the theme analysis method, four main categories including technological, managerial, human, and governance dimensions were distinguished. Also, 13 sub-categories including infrastructure, application systems, data, structural, process, strategic, economic, individual, organizational communication, organizational culture, policy, legal, and governance data were extracted which includes 101 concepts and 479 final codes.

The results of this study, contrary to the initial expectations, proved hard technological factors as the least important and other factors, including data, structural and legal factors, respectively as the most important. Thus, in data policies, first, it’s necessary to access data and consider the data quality. In structural policies, it is necessary to pay attention to how to mobilize resources and facilities. In strategic policies, how to interact with stakeholders is vital to be explained. Based on the findings of this research, the internal organizational factors affecting the formation of innovation based on open government data were classified into four main categories for better policy-making. In the category of technology, it is necessary to consider the technical and technological principles of open data from the aspect of required infrastructure, application systems, and data sources. In the management category, it is necessary to pay attention to structural and process requirements along with strategic and economic aspects. In the human category that examines the soft aspects, it is necessary to pay attention to the issue of open data from individual perspectives, communication, and organizational culture. In the category of governance, policy aspects, organizational rules, and factors related to data governance need to be considered with the aim of achieving innovation from open government data. Therefore, the present study initially tried to provide a comprehensive framework for policy-making in government institutions by interpreting and presenting a new category of internal factors. Secondly, it sought to smooth the path of future research to expand and spread innovation based on open data.

In the digital age, data can be considered as the most important organizational resource. Given the increasing volume, velocity and variety of data in Iranian businesses, it has become a concern for their executives how to gain innovation as well as business value from data. In this regard, the purpose of this study is to investigate the role of big data and related analytics on innovation and then on business value using survey method. The study population was 158 Iranian businesses in Information Technology and E-business sector. In this case, businesses were questioned through judgmental sampling and questionnaires were analyzed via structural equation modeling (SEM). The results showed that the characteristics of big data have a positive and significant effect on big data analytics in those organizations. It was also found that data analytics in the businesses have a positive impact on the innovation and business value of the firms. Moreover, the impact of big data-driven innovation on business value creation in Iranian digital businesses has been confirmed. Also, the research results confirm the significant relationship between big data characteristics and innovation. Finally, the mediating role of innovation on the relationship between big data analytics and business value was approved. The results showed that innovations resulting from the analysis of large volumes of diverse data can lead to business value in Iranian businesses.

Today, excessive waste generation, severe resource scarcity and environmental damages are serious problems of current business models. Designing circular business models is not only a good solution to these problems, but also a good opportunity to gain a competitive advantage and achieve economic benefits. The purpose of this study was to comprehensively identify the building blocks of circular business models and provide a framework for the circular business models. We used the Sandelowski  and Barros  7-step meta-synthesis method to identify the building blocks of circular business models and the thematic analysis to analyze  and combine the findings. Based on the findings of the study, the building blocks of the circular business model are classified into 3 main categories, 9 sub-categories and 40 final codes. In addition, our design options has introduced the practical instances to be used  for implementing the circular business models. Also, the proposed canvas of the research can be applied as a facilitator tool to lead the way that the professionals and managers design circular business models in   organizations.

Today, large volumes of data that are generated from various sources with high velocity and variety, has led to innovation and transformation in many industries. Many industries, such as the retail industry, have sought to use big data technology due to the growing importance of creating value from data in this industry. But many industry leaders face a number of decision-making dilemmas for applying this technology, as well as the challenges of implementing it. Therefore, the main purpose of this study is to determine the big data applications in the retail industry that has fewer implementation challenges. In this research, using the meta-synthesis method with systematic search in reputable scientific databases, first, related articles on how to use big data technology in the retail industry have been examined. Then, using the content analysis method, bigdata applications in the retail industry have been analyzed and categorized, by identifying the criteria related to the challenges of big data applications and using quantitative multi-criteria decision-making methods -a combination of BWM, DEMATEL and TOPSIS methods, the priority of big data applications in the Iranian retail industry has been determined. The findings of this study show that the three applications of big data including determining market trends, determining the optimal product portfolio and micro-segmentation of retail customers have the least challenge and therefore the highest priority and three applications of data-driven cooperation, elimination of counterfeit products and the layout of the store space had the most challenge and the least priority in the Iranian retail industry.

Circular business models are a good solution to the problems of current linear business models that cause excessive waste generation and resource scarcity. They also provide a good opportunity for businesses to gain a competitive advantage, obtain economic benefits and reduce environmental damage. To implement circular economy strategies at the business level and create a framework for better design of circular business models, the purpose of this paper is to propose a framework for identifying and classifying circular business model patterns that align with circular economy strategies.

In this research, a qualitative method was applied. Sandelowski and Barros 7-step meta-synthesis method was used to identify circular business models and Nickerson taxonomy development method was used to classify circular business model patterns.

This study drew up a comprehensive list of 29 circular business model patterns including their name, definition, and example(s). It also proposed a comprehensive taxonomy framework for circular business model patterns based on the circular economy strategies. Under this framework, 11 dimensions for classifying 29 business model patterns were identified, including patterns for 1) dematerialization, 2) consumption efficiency, 3) circular supplies, 4) optimal production, 5) reverse and optimal logistics, 6) long-life products, 7) extending the products and parts life cycle, 8) extending materials life cycle, 9) extending resource life cycle, 10) actors of main activities in the circular value network, and 11) facilitators of activities in the circular value network.

First, the current research identified various types of circular business model patterns for the development of businesses based on a circular economy. Second, by creating a framework for classifying strategies and circular business models, it showed how to make strategies and circular business models attuned. The results of this study can help companies that intend to implement circular economy strategies in their business to identify and apply appropriate circular business models. It should be noted that the strategy of the circular value network and the patterns of the circular business model based on it, which indicate various methods of cooperation between the actors of the circular value network, were introduced for the first time in the research.

Deploying IoT-based education can allow students to explore the environment using embedded sensors. They can access educational materials and other information at any time. Teachers can also use wearable devices and smartphones in the classroom to improve teaching and learning. Although new technologies such as smart schools, e-learning, e-learning content and smart classroom equipment have had a positive impact on the process of teaching and conveying concepts to learners, they have not been able to meet the challenges in this area well enough. Since the Internet of Things, in addition to using the mentioned technologies through technology convergence such as cloud computing, massive data, blockchain, smart phones, objects and classroom environment, etc. has a tremendous effect  on the education industry by creating  new teaching and learning methods, developing the systems of monitoring and control and improving the decisions through data analysis, it is argued that the IoT can empower the education sector to solve the problems and challenges it faces by providing practical solutions.

This research is an applied research in terms of purpose and it is based on mixed methods research (qualitative- quantitative) considering how the data are collected.  At the beginning of the research, the Meta-synthesis method was used to identify the applications of the IoT in education. In this method, 4638 articles were found, and after being reviewed,  490 articles were extracted  among these  128 articles were used for the final analysis. Also, using the questionnaire as a tool to prioritize the Internet of things applications in education, the best-worst multi-criteria decision-making method  was  used.

The findings showed that applications such as "Smart Campus" and "Student Health" have the highest priorities, respectively. Applications such as "Education (Teaching) and Learning", "Smart Class" and "Smart Tracking or Intelligent Transportation stsyem" were the next priorities.

According to the findings, suggestions can be made to solve the problems of the education industry. In the field of application, with the help of IoT technology, there are problems such as the limitation of education to one place and time, wasting class time due to high density of people, lack of  intelligence and high maintenance costs of educational centers, lack of accurate monitoring of students' health and hygiene, and the inadequacy of educational facilities for the physically disabled reducing the lack of smartness of the transportation system. Education industry policymakers can also be advised to pay special attention to these areas, given that the areas of "smart health monitoring", "smart energy" and "security" are more important than other sub-applications and they should also pay attention to these special sections. Also, action should be taken for public education and extensive publicity in familiariing the society with smart products and IoT technology in order to increase user acceptance and create demand. Among the limitations of the research, the limited number of experts familiar with IoT technology in the country's education sector vcan be mentioned. It is suggested to examine the relationships between applications and sub-applications and their priority based on the feasibility and attractiveness of the indicators in the future research.

By using big data, companies can be accurately informed about future market trends and customer preferences. Accordingly, innovate in marketing activities. However, to take advantage of this new technology in marketing, elements and factors are needed. In this regard, the current study has identified the necessary Prerequisites for using big data to innovate in marketing activities. the methodology of current research is a qualitative method by getting interviews and using content analysis. The subjects were 18 experts in the fields of data science that were selected by purposeful sampling method. By analyzing the interviews, 6 main concepts and 17 sub-concepts were identified. The results showed that antecedents for using big data in marketing activities are data-driven culture, data-driven skills, data-driven systems creation, dynamic resources provision, data-driven marketing capabilities, and support and perception CEOs. The results of this study can be used to assess the readiness to use big data in the marketing activities of organizations to develop and improve products and services and better experience for their customers.

The purpose of this study is to identify platform-based services and their priorities in order to apply them in Iran’s public libraries.

This research is an applied study in terms of purpose, including a mixed approach in terms of the research framework. First, the platform-based services were identified through using the meta-synthesis method. Then, after searching through the literature and selecting the appropriate sources by meta-synthesis, 9 articles were eventually investigated as the final selected resources. Then, after the key codes were extracted from the sources and the concepts were categorized, platform-based services were identified. In the second stage of the research, a researcher-made questionnaire was used in order to determine the importance of the services extracted by 38 experts and professionals of public libraries. In order to identify the most important services based on the professionals’ views, data was analyzed by SPSS using the Binomial test.

Through the meta-synthesis applied, 28 services were extracted under 3 categories: education-oriented services (11 services), accessibility and information services (9 services), cultural and leisure services (8 services). According to the experts, the most important services to be applied in the Iranian public libraries include: three education-oriented services (teaching children how to interact, lifelong learning education, and health literacy education), five services related to accessibility and information (establishing a digital library, information consultation for entrepreneurs, access to local information, access to health information, and interlibrary loan) and seven cultural and leisure services (allocating space to groups and associations, creating space for public gatherings, providing equipment and facilities for studying or doing homework, setting up an attendance program for entrepreneurs and producers, creating space for public participation, creating space for scientific conferences, and interaction between suppliers and demanders).

Originality/value: 

From a platform perspective, Iran’s public libraries, should be not only a conduit for access to information and information resources, but also an interface between users and local organizations. In the area of education, public libraries should be a platform for providing education by various organizations to people; In the area of ​​accessibility, they should provide access to government, local and commercial information; In the field of cultural services and leisure, which was more important for the experts under study, in addition to being a place of communication for people, they should also use the physical space of the library as a venue for providing services. Iran’s public libraries should provide a platform for local users, organizations, companies or any other type of body to use the physical space of public libraries for official ceremonies, festivals, traditional markets and exhibitions.

As more and more data are generated day by day, the applicability of internet of things (IoT) devices becomes inevitable. The analysis of such data can have many benefits for the organizations and societies. Since previous research has not addressed the identification and prioritization of these applications, the purpose of this study is to identify and rank big IoT data analyses.

This article was divided into two sections. In part 1, the researchers used the meta-synthesis method to identify the applications; and in part 2, the multivariable method was used to prioritize the applications. Moreover, TELOS feasibility (Technical, Economic, Legal, Operational, & Scheduling) and AHP were used to weight and rank the criteria. Then, the applications were ranked based on the experts’ opinions through Vikor’s method.

In this research, the meta-synthesis method has been used to identify the applications of big IoT data analyses. In this meta-synthesis method, 490 articles were initially identified and after eliminating conference papers, 257 articles were selected to initiate the meta-synthesis process. Finally, 51 articles were selected and as a result, 256 sub-applications were identified which were categorized into 114 main categories, 16 industries, and 7 analytic applications. It is also noteworthy that the diagnostic application within the health and transportation industries (with 102 & 100 applications, respectively), as well as the monitoring application within the health, transportation, and agriculture industries were reported to have the highest functioning. The most identified applications in industry-analysis belong to transport-diagnostic (32 applications), health-diagnostic (29 applications), health-monitoring (26 applications), agriculture-monitoring (25 applications), and transport-monitoring (20 applications). In the prioritization step, after calculating the weights based on the experts’ opinions and hierarchical analysis, the applications of transportation and health industries were ranked using TELOS feasibility as well as the experts’ ratings and the Vikor’s method. According to the experts’ opinions and TELOS feasibility criteria, the predictive applications in the transportation industry and the automation applications in the health industry have received the highest priorities.

According to the research findings, big IoT data analysis is mostly used in the transportation and health industrieswhere the predictive applications in the transportation industry and the automation applications in the health industry have been regarded as a priority. Based on these results, the two health and transportation industries and their priority applications are proposed for the companies that want to work in this area. Due to differences in prioritization of the applications in the two transportation and health industries, the justifications for the two industries are different as well.

The agricultural sector is going to face enormous challenges in order to feed the 9.6 billion people that the FAO predicts are going to inhabit the planet by 2050: food production must increase by 70% by 2050, and this has to be achieved. The advent of Internet of Things (IoT) that is the hot points in the Internet field has shown a new direction of innovative research in agricultural domain. Hence, in this research we seek to identify the applications of IoT in smart agriculture. This research is an applied research in nature and it would be classified as qualitative regarding data collection. In order to identify the usages of IoT in smart agriculture with the help of meta-synthesis approach, at first we have examined 480 researches among which only 168 have been selected for the final analysis, then we categorized them in 8 area of agriculture that consist of “farming”, “greenhouse”, “urban agriculture”, “Smart Gardening”, “smart fishery”, “smart forestry”, “smart livestock” and “smart supply and distribution network”. based on data analysis applications in 6 categories of “monitoring”, “control”, “tracing”, “diagnosis” and “descriptive planning” are categorized. Finally, agricultural area based on sustainable development indicators are respectively: smart greenhouse, smart supply and distributions network of agriculture, smart livestock, smart Gardening, smart fishery, smart farming, smart forestry and smart urban agriculture.

In the last decade, we have encountered a new type of start-up companies which have used high digital technologies to provide innovative services in the financial industry. The purpose of this reseach was to answer this question what are the point of views of venture capitalists when making decisions in the first stage of investing in startups in Iran? This research is applied in terms of purpose, qualitative in terms of data collection. In-depth interview and observation data were analyzed and interpreted through the grounded theory methodology. For collecting data, 17 venture capital managers in the field of financial technology services who had at least once a history of investing in start-ups, targeted as a statistical population.The results showed that there were two main types, including investors with a strategic perspective and with a financial perspective, and each group can be divided into three subtype with different viewpoints and criteria in the field of investment in financial technology, which need to be considered by start-ups.

The agricultural sector needs to produce more food, both in terms of quantity and quality, on a planet that face enormous challenges like scarce resources and changing climate. The advancement of digital technologies, Internet of Things and analytics offers new solutions to these complex challenges. Hence, the purpose of this research is to identify the applications of IoT in smart agriculture. With the help of meta-synthesis approach, we have examined 480 academic documents written in English and published over a period of 8 years (2010-2017), among which only 168 have been selected for the final analysis. Selected documents were categorized into eight areas of agriculture (including “farming,” “greenhouse,” “urban agriculture,” “horticulture,” “livestock” and “supply and distribution network of agriculture”) and then clustered into six analytics domains corresponding to: “monitoring,” “control,” “tracing,” “diagnosis” and “descriptive planning”. Finally, by using the Shannon entropy method, the effect coefficient of the elements was determined in selected documents and technical uses of internet of things in each agriculture sector have been addressed.

In the present era, networking between government agencies has become an important factor in delivering integrated services that actually create public value and service design from the citizens' point of view. To this end, government agencies need a new capability called network capability. The purpose of this study is to model the process of forming network capabilities in government agencies active in the Iranian single window.

In this qualitative study, grounded theory was used based on Strauss and Corbin method and in order to analyze the data obtained from interviews, documentation, and minutes of the single window project, a three-stage open, axial and selective coding method was used.

In this study, 35 concepts, 13 subcategories and 6 main categories were identified to form the network capability, which were classified into five levels of analysis including network, environment, inter-organizational, technological and organizational levels. In addition, five steps were proposed to form the network capability as well as six main hypotheses and twelve sub-hypotheses for future research.

The proposed theoretical model shows that internal and external motivations are the causal conditions for building network capability and the dimensions of network capability in government organizations include both internal capabilities and interorganizational capabilities. Macro and micro environmental conditions have been one of the influential underlying conditions for network capability development. Also, the characteristics of network governance and network information technology architecture are among the intervening conditions affecting the development of network capability. According to the proposed theoretical model, at the maturity level of Iranian organizational mechanisms are: integration and dynamic interoperability and strategies are communication and cooperation. Finally, the implications of developing network capability for network governers, organizations, and policymakers have been proposed.

The increasing impact of innovative marketing strategies on the competitive advantage and business performance has led organizations to constantly apply new digital technologies for innovation in marketing mix. The advent of Internet of Things technology has made many innovations in businesses and marketing. Experts believe that IOT will revolutionize marketing by 2020. On the other hand, the development and diffusion of IOT is heavily influenced by market forces, legal conditions, technological infrastructures and interactions among them. Therefore, the purpose of this research is to prioritize the implications of IOT for innovation in marketing mix using these conditions. In this research, prioritization has been done using the opinions of experts familiar with the IOT technology and marketing. Analytic Hierarchy Process (AHP) method is used for weighting the critera and Fuzzy Topsis method is used for prioritizing. The research results indicate that market factors are more important than other factors and secondly, IoT implications in different marketing mix domains based on the mentioned criteria respectively include product, promotion, physical equipment, processes, locations, Price and people that have a higher priority for Iranian businesses. finally, it is suggested for developing IoT applications in the country, business executives should focus on business model design, ecosystem development, and the development of user-friendly services and policymakers should pay particular attention to implementing demand-side policies.

Nowadays organizations are compelled to use and implement digital transformation in their organization in order not to retreat from competitors in a competitive environment and to be able to respond to customers' needs. But one of the most important ambiguities in this area is the understanding of the concept of digital transformation in the organization. Digital transformation maturity model is one of the important frameworks to understand digital transformation in an organization the digital transformation model. A maturity model consists the dimensions and the phases of the digital transformation. Understanding the important dimensions and phases of maturity is important for decision makers because they can make good decisions based on understanding their organization's place in the digital transformation mature. Given that the first step in implementing the digital transformation is to evaluate digital transformation maturity, the objectives of this study are this study is to develop a maturity model for digital transformation and to determine its phases. This paper presents a comprehensive overview of different maturity models and their phases. For this purpose, the Meta-synthesis method is used to conduct this study. This method has been used to search and select appropriate articles related to the subject of research in various scientific databases on the Internet and extract the necessary information from them. A total of 228 original articles are obtained after the evaluations and finally 28 papers are selected. By analysing and interpreting the dimensions and phases of maturity models presented in previous articles, the maturity model presented in this study consists of five phases and 10 dimensions. These dimensions are as follows: Leadership, Information Technology, Employees, Operations and Processes, Culture, Organizational Structure, Innovation and Change, Strategy, Intelligent Products and Services, and Customer. Finally, the maturity level of 20 pharmaceutical companies is measured by using the maturity model presented in the current study and the results showed that most of the pharmaceutical companies include level 2 to level 3 of the maturity model.

There is almost no comprehensive and integrated view of the diverse applications of Internet of Things (IoT) in digital marketing by far. Given the increasing trend of research in this field, the present study aims to systematically and scientifically integrate previous studies to identify innovative uses of IoT in digital marketing and also to provide a comprehensive classification in this field. In addition, it is expected to determine which countries are leading in the use of IoT in marketing, how the IoT technology is used in each of the marketing areas, which marketing areas are affected the most by the use of Internet of things technology, and what mechanism are applied more by the researchers in the field of marketing.

This fundamental study uses both qualitative and quantitative methods. In this way, firstly, the meta-integrated approach was used to identify the applications of IoT in marketing, and thencontent analysis was used to understand the trends and hot topics in this field. In the present research, Sandlowski and Barrowso's seven-step method was used to perform the meta-integration. The study population consisted of exclusively English-language articles in the databases of Google Scholar, Science Direct, IEEE Explorer Scopus, and Emerald Insight between 2005 and November 2018. And the content analysis method was used to analyze the data.

Having examined and integrated the uses of IoT in all the different articles, initially the concepts encompassing the sub-applications and then the main categories that encompass the main applications are extracted into seven marketing integrated categories. Most applications have been reported in the field of promotion, as the majority of the articles have highlighted the ability of data obtained from the Internet of Things to understand customers’ behavior and personalized suggestions and advertising based on this information. The second highest contribution of IoT is reported on the applications of smart products in marketing and the changes that these products have made accordingly. The applications of Internet of Things in marketing have been investigated since 2012 onwards. In addition, product and process domains have been the first areas to propose the application of IoT technology, which makes sense given the development of intelligent products and the increasing role of IoT in process automation. On the other hand, the use of IoT in the field of human resources has recently been included in studies and has received the least number of researches which confirms the diminishing role of the human resources in the IoT era. Throughout time, Internet of Things has been used the most within the domains of products and promotions.

According to the results of this study and based on qualitative and interpretive content analysis, Internet of Things have effects on seven integrated marketing areas including product, location, price, promotion, processes, physical evidence and human resources. In terms of the impact of the Internet of Things on the product domain, the advancement of product features, product support, product quality, blending and branding of products and services can be taken into account. In terms of promotion, one can consider the use of new advertising methods and the creation of personal promotions as well as sales promotions, improvement of public relationships in marketing and direct marketing. In terms of of marketing processes, innovation in both sales processes and support and marketing research processes have attracted the attention of many companies and researchers. In terms of pricing, online data gathering and analysis have provided the opportunity to apply changing pricing methods and create diverse and effective discounts, as well as new revenue models. In terms of distribution, the Internet of Things has also been used as a new distribution channel and also for locating, especially in retails. In terms of physical evidence, the use of smart devices has also provided a more interesting customer experience. Applying IoT to human resources training and evaluating their performance have also been influenced by Internet of Things. Given the wide range of opportunities provided by IoT in marketing, it should also be noted that data protection and customer privacy are among the major threats of implementing IoT in marketing. It was even considered as a new and very important element of the marketing integration in the era of information.

Today, search engine services are one of the most widely used and basic ICT services in all countries. In recent years, many leading countries such as China and South Korea have managed to achieve macroeconomic and micro level economic impacts, with the establishment of Local search engine, given their specific cultural and linguistic characteristics. Therefore, the policy makers of Iran having understood such a necessity went on to implement a national plan to support development of Local search engines in the country. Since one of the main goals of this project was to improve economic aspects, the purpose of this research is to examine and explain how the economic impacts of the local search engines have been gained. for this purpose, Initially, through interviews with the main actors of this plan, the factors influencing the economics of the search engine were identified that includes: 1) business startups , 2) search engine program, 3) ministry (ICT) and 4) governance . Then the evaluation indicators of each factors were extracted through the study of  formal documents of the search engine project. Furthermore collecting field data was done by selecting a sample of active startups in the search engine program. The findings and results of this research based on data analysis using the PLS3 software showed that the significant economic effects of this national plan were merely due to the support of this national program from the start-ups. Therefore, it has been suggested to support  startups for successful implementation of national projects . It should be considered that the intervening of governance institutions in the economic success of the search engine program had a negative impact.