Research Paper
Data, information and knowledge management in the field of smart business
Mohsen Aazami; Mohaddes Nadershahi; Ali Asghar mobasheri; Sayedeh Nahid Hosseini
Abstract
The current research was conducted with the aim of designing a model for using cloud computing in Small and medium-sized enterprise. This study is a developmental in terms of its purpose and it is a qualitative research in terms of the nature of data collection and analysis, and was conducted using the ...
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The current research was conducted with the aim of designing a model for using cloud computing in Small and medium-sized enterprise. This study is a developmental in terms of its purpose and it is a qualitative research in terms of the nature of data collection and analysis, and was conducted using the grounded theory method. The statistical population consists of experts and entrepreneurs in the field of handicrafts and university professors of Kermanshah city, among which 14 people were selected as sample members by snowball sampling. semi-structured interviews was used for data collection. The results show that improving competitive advantages and improving operational processes explain why cloud computing should be used in these Enterprise. The findings also indicate that cultural-management facilitators, infrastructural facilitators and facilitators related to cloud computing are among the factors that can act as contextual factors. In addition, two categories of intervening factors (promoting and inhibiting factors) can affect the use of these technologies in these enterprises. The strategies of using cloud computing are also identified at two enterprises and environmental levels, and the consequences of using these technologies are also identified in four categories of operational, managerial-executive, entrepreneurial and competitive consequences.
Introduction
Throughout history, small and medium-sized enterprises (SMEs) have always been considered as a place for job creation, transformation and innovation, and they have drawn the attention of many economic development policy makers around the world. On the other hand, the increasing global changes in recent years have strongly affected the environment of SMEs and made their stability and resilience dependent on the use of new technologies. In this new situation, SMEs should be able to build their business processes based on new technologies such as cloud computing. The right use of cloud computing not only increases the accuracy and reliability of the operations of SMEs such as handicrafts, but can also lead to improved services, reduced costs, and improved competitive advantage. Nevertheless, the use of cloud computing technology in handicraft businesses requires detailed and scientific studies in order to explain the mechanisms affecting this process. However, the review of literature related to the subject shows that the use of cloud computing in handicraft businesses has not received the attention of researchers so far and And the questions related to this topic are unanswered questions. Therefore, the current research has been carried out in order to design a model for using cloud computing in handicraft businesses and to answer these questions.
Research Questions
Why should cloud computing be used in craft businesses?
What factors affect the use of these technologies in handicraft businesses?
What strategies are needed to use cloud computing in SMEs such as handicrafts?
What are the consequences of using cloud computing in crafts businesses?
Literature Review
2.1. SMEs
Small and medium businesses refer to businesses that employ less than 250 people. These businesses are one of the most important elements of the global economic system, which play a very important role in improving the economic situation of different countries. Handicraft businesses are also included in the category of SMEs that play an important role in improving the living standards of local communities by creating employment and increasing the income of local residents.
2.1. cloud computing
Cloud computing has its roots in communication technologies such as the Internet, networking, virtualization, and the like, and in fact, it is an evolutionary process of communication and information technologies for which no standard and universal definition has been provided so far. Cloud computing is a new method of processing in which scalable and often virtualized resources are provided as processing services through communication networks such as local area networks and the Internet. The characteristics of cloud computing, such as universality and freedom from time and place limitations, scalability, flexibility, ability to share resources and pay per use, distinguish it from common communication technologies, facilitate its use for businesses, especially sm SMEs.
Methodology
This study is an exploratory qualitative research that was conducted using grounded theory, which is a systematic method for conducting qualitative research. The statistical population of the research consists of experts and entrepreneurs in the field of handicrafts and university professors of Kermanshah city. Among them, 14 people were selected as sample members by non-probability (targeted) snowball sampling method. Individually semi-structured interviews were used in order to collect data and theoretical saturation rule was in order to select the number of interviewees (sample size).
Results
In the process of data collection, after conducting each interview, the collected data were carefully checked and the appropriate phrases for the purpose of the research were extracted from the topics. After that, the extracted phrases were examined and coding of these phrases and identification of primary themes was done. In the following, all the created codes (initial themes) were reviewed and while removing duplicate codes and merging similar codes, 66 final codes (themes) were identified. Then, by categorizing the final codes (themes) with semantic and conceptual commonality, the basic themes were identified. Then, in the axial coding stage, the basic themes were categorized in the form of grounded theory dimensions. After the end of the axial coding, in the process of selective coding (the third stage of the grounded theory), while creating a connection between the main themes (the six dimensions of the grounded theory), the paradigm model of the research was developed in the format of Figure 1.
Figure 1. the paradigm model of the research
Causal factors
* Competitive factors
* Improving operational processes
Strategies
* Business level strategies
* Environmental strategies
contextual factors
* Cultural-managerial factors
*Infrastructure factors
*Characteristics of cloud computing technology
consequences
* operational
* Managerial-executive
* Entrepreneurial
Intervening factors
* Promoting factors
* inhibiting factors
central phenomenon
using cloud computing in SMEs
Conclusion
The results can provide practical guidelines for managers and planners at the micro (business) and macro (economic policy) levels. The identified causal factors can increase the awareness of managers and planners regarding the necessity of using cloud computing in SMEs and thereby increase their mental readiness to accept these technologies. Contextual factors can also improve the awareness of business managers regarding the prerequisites of using cloud computing in businesses and introduce them to the areas that need to be strengthened in this regard. Identifying the intervening factors also increases the awareness of the policy makers of the economic system regarding the factors affecting the use of cloud computing in SMEs. The strategies also describe how to create better conditions for the use of cloud computing at the micro (business) and macro (environmental) levels for managers and planners and introduce the necessary measures to them.
Keywords: Cloud Computing, Small and Medium-Sized Enterprises, Handicraft Enterprises, Grounded Theory.
Research Paper
Management approaches in the field of smart
Shiva sadat Ghasemi; Abbas khamseh; Seyed Javad Iranban
Abstract
In the contemporary landscape of technology-driven industries, the integration of artificial intelligence into technology scouting is imperative for enhancing innovation and sustaining competitiveness. This research aims to forge a framework for technology scouting based on artificial intelligence, with ...
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In the contemporary landscape of technology-driven industries, the integration of artificial intelligence into technology scouting is imperative for enhancing innovation and sustaining competitiveness. This research aims to forge a framework for technology scouting based on artificial intelligence, with a specific focus on technology-based companies. Employing a qualitative approach, data collection utilized the meta-synthesis method devised by Sandelowski and Barroso. This involved a systematic review of 28 articles relevant to the research goal out of a pool of 253 primary articles. The final selection of articles was based on predefined inclusion criteria. The research's validity was confirmed through adherence to criteria, team meetings, expert consultations, and an exhaustive audit for theoretical consensus, while reliability was ascertained through the Critical Evaluation Skills Programme. The framework spans five dimensions: technology scouting tools, technology life cycle, firm environment, firm's approach to the environment, and firm's absorptive capacity. The findings underscore the pivotal role of AI-based technology scouting tools, elucidate the nuanced dynamics of the technology life cycle, and reveal the multifaceted aspects of the enterprise environment. The research outlines strategic approaches for navigating the evolving technology landscape, underscoring the imperative of absorptive capacity for the effective utilization of artificial intelligence technologies. By delivering actionable insights and strategic counsel, this research serves to furnish technology-based companies with a robust underpinning for negotiating the intricate intersection of AI and technology surveillance. In doing so, it propels sustainable growth, fortifies competitive advantage, and fosters enduring innovation.
Introduction
In the dynamic world of technology-driven industry, the role of strategic technology management, particularly in the technology selection and acquisition phases, cannot be overemphasized if success is sought in innovation-driven companies. Focusing on technology-oriented companies that currently face a rapid industrial evolution, the present study highlights the indispensable role of technology scouting, equipped specifically with artificial intelligence (AI), in grappling with the imminent competitive environment. The study proposes a framework that anticipates a future where AI plays a central role in technology acquisition and that strives to enhance absorptive capacities by bridging the adaptation gap. Drawing upon AI, the propsoed framework not only ensures proper technology selection by firms but also drives them toward cutting-edge technological innovations. Serving as a guide for decision-makers, technology strategists, and specialists, the study is expected to contribute, both theoretically and practically, to the understanding and advancement of technology scouting in tech-driven companies. Moreover, it explores and identifies the needs of organizations navigating the intricate technology landscape to derive actionable insights that ensure sustainable innovation leadership.
What is the framework for technology scouting based on artificial intelligence in technology-oriented companies?
Literature Review
In today's rapidly evolving tech landscape, it is essential to cope with the changing business environment (Kujawa and Paetzold, 2019). Ahammad et al. (2021) linked strategic agility to search strategies. Wang and Quan (2021) studied the impact of technology selection uncertainty on firms’ absorptive capacity. Vuorio et al. (2018) explored the significance of competitive edge in tech-driven enterprises. Kerr and Phall (2018) developed a scouting process model. Nasullaev et al. (2020) reiterated the alignment of strategy and tech scouting. Xu et al. (2021) advocated patent analysis in scouting. Sikandar et al. (2021) reiterated patents' innovation measure. Tabrizi et al. (2019) observed a shift to tech-centric business models. Stute et al. (2021) noted the importance of AI in supply chain enhancement. Mariani et al. (2023) classified the motivations underlying AI adoption. Stahl et al. (2023) addressed AI ethics while D'Almeida et al. (2022) categorized AI applications. Wang et al. (2020) identified AI algorithms. Despite these efforts, scant research has been reported on tech transformation, especially AI. This study adopts the meta-synthesis method to explore the digital transformation complexities, focusing on AI's transformative potential and bridging the gaps to derive a roadmap for navigating tech-driven industries.
Methodology
Employing a qualitative approach and the meta-synthesis method, a seven-step process (including goal setting, review, selection, extraction, analysis, quality control, and model development) was meticulously followed to develop an AI-based technological scouting model for advanced tech firms. A systematic search yielded 253 articles, 28 of which met the inclusion criteria and were validated through team meetings, software analysis, and expert consultation. Reliability was ensured since 89% of the articles received excellent scores via the Critical Evaluation Skills Program, indicating high quality.
Results
The research adopted a classified analysis perspective, utilizing inductive analysis based on Sandelowski and Barroso (2007). This involves extracting primary codes related to AI-based technology observation in high-tech companies, identifying patterns through open coding, and classifying concepts into sub-categories and main categories via axial coding.
Table 1. Factors Affecting AI-Based Technology Scouting
Category
Subcategory
Concepts
Technology Scouting Tool
Open Source Intelligence (OSINT) Tools
Web scraping tools, social media monitoring, online forums, patent databases, news aggregators, competitive intelligence tools, and data analytics platforms.
Machine Learning and AI Tools
Natural Language Processing (NLP), predictive analytics, pattern recognition, chatbots, sentiment analysis, machine learning, and cognitive computing tools.
Collaboration and Communication Platforms
Online collaboration tools, project management platforms, virtual team collaboration, idea management, crowdsourcing, communication apps, and workflow automation.
Technology Life Cycle
Innovation and Invention
Idea generation, R&D, concept testing, prototyping, patenting, technology transfer, proof of concept, funding, collaborative research, and feasibility studies.
Technology Adoption and Diffusion
Technology readiness, market analysis, adoption theories, market penetration, standardization, compliance, user testing, and overcoming adoption barriers.
Technology Evolution and Obsolescence
Continuous improvement, iterative development, versioning, obsolescence management, legacy systems, discontinuation planning, sustainability, disruptive tech, and sunset planning.
Company Environment
Competitive Landscape Analysis
Competitor mapping, SWOT analysis, industry benchmarking, market share analysis, competitive intelligence, PESTLE analysis, collaboration strategies, positioning, and sustainable advantage.
Regulatory and Legal Environment
Intellectual property management, standards compliance, regulatory impact, patent landscape analysis, legal risk, data protection, ethics, antitrust, government policies, and international regulations.
Internal Organizational Environment
Culture, cross-functional collaboration, governance, change management, talent, agile structures, infrastructure, decision-making, metrics, and employee engagement.
The Company's Approach in Facing the Environment
Innovation Strategy Formulation
Roadmapping, open innovation, blue ocean strategy, core competency analysis, innovation ecosystems, portfolio management, ambidextrous approach, horizon scanning, lean methodologies, and design thinking.
Adaptive and Resilient Practices
Crisis management, scenario planning, risk management, agile project management, supply chain resilience, continuous learning, adaptive capabilities, technology portfolio flexibility, and fostering innovation culture.
Strategic Alliances and Partnerships
Collaborative innovation, joint ventures, technology ecosystems, university-industry collaborations, innovation networks, open source, licensing, technology transfer, competition, and strategic partnerships.
Absorption Capacity of the Company
Learning and Knowledge Management
Organizational learning, knowledge creation, sharing platforms, communities of practice, intellectual capital, training programs, technology scouting, learning culture, and tacit knowledge transfer.
Resource Allocation and Utilization
Technology budgeting, allocation models, ROI analysis, portfolio management, cross-functional sharing, resource efficiency, project prioritization, dynamic reallocation, innovation finance, and risk management.
Adoption of Emerging Technologies
Scanning trends, piloting new tech, foresight methodologies, early adoption, readiness assessments, and collaborative ecosystems for adoption, mitigating risks, cross-functional teams, integration, and continuous monitoring.
Discussion
To address the crucial gap in technology scouting in technology-oriented companies involved in the joint AI and technology scouting, the study develops a framework of five dimensions. Open-source smart tools and machine learning are explored as essential components of the "Technology Scouting Tool"dimension to contribute to the development of a cohesive strategy. The "Technology Life Cycle" dimension guides the firm through the innovation, adoption, and evolution stages. The "Company Environment" dimension adopts a multifaceted approach, considering competitive analysis, regulatory factors, and internal dynamics. The strategic components of the "Firm's Approach to the Environment" underline the contributions of innovation strategy, adaptability, and alliances while "Firm's Absorptive Capacity" offers practical insights by underscoring learning, resource allocation, and technology adoption.
Conclusion
The proposed framework provides a strategy tailored for tech-oriented firms incorporating AI into scouting and offers strategic insights across the five dimensions to tackle nuanced challenges in the technology landscape. Advocating advanced open-source tools and strategic approaches, it explores the technology life cycle, considers diverse aspects of firm environment, and launches an AI-driven future. Acknowledging limitations and emphasizing proper deployment of AI, the study lays the foundations for future studies to validate and expand the framework while ensuring responsive and sustainable application of AI-based surveillance technologies in corporate contexts.
Keywords: Artificial Intelligence, Technology Scouting, Technology-Oriented Companies, Digital Transformation.
Research Paper
Management approaches in the field of smart
Peyman Ghafari Ashtiani; Maryam Ghiasaadi Farahani
Abstract
The current research has identified the factors affecting the management and organization of businesses based on e-commerce through a meta-combination approach. The research is applied in terms of purpose and qualitative in nature with an exploratory approach. The community of this research is the articles ...
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The current research has identified the factors affecting the management and organization of businesses based on e-commerce through a meta-combination approach. The research is applied in terms of purpose and qualitative in nature with an exploratory approach. The community of this research is the articles in the field of managing and organizing e-commerce jointly or separately. The method of collecting information is the document-library method with the efficiency of the meta-combination method for extracting factors. The sampling method is also selected based on the entry and exit criteria of the prism method. In order to answer the research questions, 96 articles were examined and analyzed, which led to the extraction of 15 categories and 95 meaningful codes. The results showed that business management based on e-commerce includes the components of online sales, digital marketing, suppliers, leadership, product or service, human resources, organizational culture, customer, market, organizational structure, and organizing business based on E-commerce includes the components of technical dimension, organizational dimension, environmental dimension, economic dimension and financial dimension.
Introduction
Almost a quarter-century has passed since the commercial use of the Internet and the World Wide Web. During this period, the business landscape has changed rapidly. Large multinational companies such as Google, Facebook, Amazon, Alibaba, eBay, and Uber, which were unknown until twenty years ago, have emerged as key players in the modern economy. In 2015, online sales accounted for 7.4% of total retail spending in the United States, the highest percentage since inception in 1999 (Pascoe et al., 2022).
The literature review indicates that the majority of previous research has taken a quantitative approach, and there is a gap in conducting qualitative research. Additionally, there has been little investigation into management concepts in the field of e-business. Examination of e-commerce concepts with their unique characteristics has expanded the boundaries of knowledge in the field of technological business. The expansion of e-businesses, thanks to the digital economy, has made managing and organizing these businesses a strategic necessity. Therefore, it is of great importance for managers and researchers to know about the factors that affect the proper managing and organizing of e-businesses. Therefore, this research tries to answer the question: What are the effective factors in the correct managing and organizing of e-businesses using the meta-synthesis approach?
Literature Review
Paying attention to the growth of technology and the increasing use of virtual world, the need of different strata of society for this space is increasing day by day. On the other hand, meeting these needs and exchanging information in this field has paved the way for high-yield investments (Mahdi and Hassan, 2021). In recent years, the start-ups that have formed by taking advantage of this opportunity and using virtual space technology, have been able to achieve considerable growth and dynamics (Wei et al., 2021).
E-business as one of the subcategories of information and communication technology has experienced high growth in the past, So in terms of organizational policy, most commercial institutions have been successful in accepting and using e-business to enter global markets and attract new customers (Chen et al., 2022).
Methodology
The present research seeks to identify the factors affecting the management and organization of e-commerce based businesses by relying on the study of published resources and documentation in this field؛ Therefore, in terms of purpose, research is practical and descriptive in terms of information collection. In this regard, due to the lack of clear and accurate explanation of the factors affecting the management and organization of e-commerce based businesses in all previous works، the method of meta-synthesis has been used. What are the factors affecting the management and organization of e-commerce businesses to answer the question؟ It was done and in order to explain its steps in e-commerce-based businesses (what?) has been written. The stages of the Meta-Synthesis approach are based on the model of Sandlowsky and Barroso (2006).
Conclusion
The results of qualitative studies using meta-synthesis approach extracted from previous research showed that the effective factors on the managing and organizing of e-businesses have 2 dimensions, 15 categories and 95 classified indicators. Managing e-business includes the components of online sales, digital marketing, suppliers, leadership, product or service, human resources, organizational culture, customer, market, organizational structure, and organizing e-business includes the components of technical dimension, organizational dimension, environmental dimension, economic dimension and financial dimension. Below is the conclusion of each question:
Question 1: What are the effective components for managing e- businesses?
Leadership: competence, powerful leadership, monitoring and evaluation, awareness and attitude of managers to e-business, knowledge management, integration management, senior management commitment, procurement management.
Product or service: response cycle speed in product supply, product data management, and product list updates regularly, product management in the sales channel, product catalog expansion, product transportation, product deliverable value, standard product quality control, nature Product, variety of products and services, product production level.
Human resources: human resources training, human resources management, staff expertise and skills, staff characteristics, human resources development.
Organizational culture: favorable organizational culture, organizational learning, customers' religion, intra-organizational communication, external communication, facilitating the payment process, sending goods on time, language of market customers.
Customer: successful customer relations, target and potential customer identification, customer retention, customer order processing, distribution channel, customer bargaining power, customer orientation, customer awareness and understanding of e-business, privacy protection, business acceptance Electronics by the customer, gaining customer trust, consumer protection.
Market: understanding customer needs, product distribution, timely delivery of goods and services, market size, business partners, competitive situation.
Organizational structure: organizational rules, technology, human resources, storage, customer information system, work process.
Suppliers: acceptance of electronic business by suppliers, bargaining power of suppliers, favorable relations with suppliers, external support.
Digital marketing: digital advertising, updating products, coordination in digital marketing, using new technologies in marketing
E-commerce sales: online market, e-retailer, direct sales - affiliates.
Second question: What are the effective components for organizing e-businesses?
Infrastructure or technical dimension: production schedule, transportation, website design, system integration and update, proper bandwidth and speed, low access cost, site availability.
Infrastructure or organizational dimension: operational flexibility, structural flexibility, strategic flexibility, high level of communication systems in the organization, management of external relations, visibility of information, creation of security and trust, innovation in technology, technological readiness.
Infrastructure or environmental dimension: digital architecture, information management, business dynamics, digital business speed.
Infrastructure or economic dimension: GDP, inflation rate, unemployment rate, economic stability.
Infrastructure or financial dimension: asset management, revenue model cost structure, investment.
Keywords: E-Commerce, Management, Organizing, Meta-Synthesis.
Research Paper
Management approaches in the field of smart
Fahime Mahavarpour; feiz davood; Morteza Maleki MinBashRazgah
Abstract
Augmented Reality (AR) is an emerging topic for managers across different disciplines While augmented reality technology literature is growing, there is no comprehensive analysis of augmented reality technology in marketing transformation The research aims to bridge the knowledge gap by providing a multifaceted ...
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Augmented Reality (AR) is an emerging topic for managers across different disciplines While augmented reality technology literature is growing, there is no comprehensive analysis of augmented reality technology in marketing transformation The research aims to bridge the knowledge gap by providing a multifaceted bibliographic overview of augmented reality technology literature in marketing and reveal its trends, areas of focus and intellectual foundations. The study is based on 496 articles published on Web of Science between 1996 and 2023. According to the findings, the concept mainly revolves around seven main areas: human-machine interaction in future of digital marketing and Metaverse, advertising and customer response in online purchases, marketing challenges in industry 4 and new technologies, the effect of virtual technology on customer loyalty in retail, adoption of behavioral technology of Tourism customers, augmented reality technology marketing in the decision-making process of buyers and brands, and finally the richness of social media in e-commerce in Covid 19. While priorities and research topics have evolved over time, key concepts such as buying experience, shopper behavior, buying decision making, technology adoption have been repeated. The three influential schools of augmented reality technology in marketing are associated with integrated theory, planned behavior theory (TPB) and cognitive evaluation theory that have shaped the intellectual foundations of the discipline but we believe that a greater diversity of fields is needed to examine and describe augmented reality technology in marketing transformation.
Introduction
Global data paint a promising future for Augmented Reality (AR) technology in the retail industry. The concept of Augmented Reality (AR) is multifaceted, encompassing a diverse spectrum of disciplines that offer a comprehensive assessment of practical knowledge in AR marketing. Consequently, the knowledge base of (AR) in marketing is discrete, and crafting a comprehensive map of all knowledge forms, spanning various dimensions and relevant aspects, poses a challenge. Current efforts in this regard, focusing on evolving developments, include a systematic study analyzing the directions and marketing aspects of AR technology (Jayaswal, P., & Parida, B. 2023). The objective of systematic reviews is to dissect and evaluate the various approaches and orientations adopted by studies, through extensive analysis, to unearth the evolutionary aspects of the subject (Romaní, F., Huamaní, C., & González-Alcaide, g. 2011). Bibliometrics, a methodological concept used in the field of Artificial Intelligence and Machine Learning, enables the study of scholarly activity (Vosgerau, D. S. A. R., & Romanowski, J. p. 2014). Firstly, this systematic review provides insights into a diverse range of interpretations of scientists, references, journals, organizations, and countries that establish the groundwork for defining the scope, conceptualization, and performance of a specific field. Secondly, bibliometric analysis reveals the structure of knowledge, focal areas, and subtopics, aiding in the scientific mapping of a field. However, recent systematic research in (AR) technology in marketing has overlooked the evolution of (AR) technology. The recent study conducted by researchers Jayaswal, P., and Parida, titled "Past, Present, and Future of Augmented Reality Marketing Research: A bibliometric and thematic analysis approach," sufficiently maps the current marketing process and the evolution of (AR) marketing. Therefore, in this study, the researcher initially delved into systematic marketing analysis of (AR) technology, clustering (AR) technology evolution in marketing through bibliometric analysis. As a result, the research objectives were defined in two sections based on systematic methodology:
Performance Objectives:
Identification of growth or decline trends in AR technology marketing studies.
Identification of the most influential authors in AR technology marketing.
Identification of the most influential countries in AR technology marketing.
Network Objectives:
Identification of the most effective co-citation patterns.
Identification of the most effective co-authorship patterns.
Identification of the most effective co-citation patterns (Moradi & Miralmasi, 2020).
This research is organized as follows to address these questions: Section 2 demonstrates the methods used and outlines exclusion criteria for analysis. Section 3 presents findings and discussions related to the questions. In the final section, the evaluation concludes with some suggestions for further work.
Literature Review
Augmented reality technology enhances consumers' online shopping experience and influences consumers' purchasing decisions. Augmented reality (AR) technology is different from other virtual reality (VR) technologies. Augmented reality (AR) technology describes the visual alignment of virtual content with real-world contexts (Wang., Cao., & Ameen. 2023). Loyalty represents customers' commitment to the mall and their intention to revisit it and give positive recommendations. According to (Ambik., Shin., & Jain,. 2023.), the concept of loyalty is based on behavioral loyalty (which focuses on repurchase and patronage behavior) and attitudinal loyalty (which focuses on the customer's evaluation of how close the shopping center is to their expectations) (Ameen,Hosany & Paul, 2022).Advances in technology and the use of interactive technologies, in particular, have completely transformed the consumer shopping experience and consumer interaction landscape. Augmented reality technology is an immersive technology that creates a highly exciting and enjoyable experience. The value of pleasure produced by augmented reality technology significantly affects behavioral intentions (Kumar,.2022).
Methodology
Augmented Reality (AR) technology in marketing is developing and advancing. A large number of articles are published annually in the field of marketing. The growing volume of literature on this subject necessitates an examination of the evolution of this field and the identification of the current state of knowledge in this area. A systematic approach is required for this study to ensure the quality of the systematic review report. Therefore, to ensure the quality of the systematic review, we applied the "PRISM" checklist. This checklist is available at http://prisma-statement.org/PRISMAstatement/checklist.aspx (accessed on September 7, 2021) and consists of four consecutive stages: identification, screening, eligibility, and inclusion, designed to assist authors in conducting better systematic reviews. The researcher preprocessed the researcher and citation data in the form of a PRISM protocol and imported them into the VOSviewer software based on the positivist paradigm, and subjected them to analytical decomposition. VOSviewer software is a widely used tool with a graphical interface designed for creating bibliometric networks of journals, authors, publications, organizations (universities), and countries active in a particular field (Sharifi, 2020). This platform has been significantly utilized in studies and contains over one billion cited reference links and rich bibliometric data collected over the past decades, enabling researchers to perform various analyses in bibliometric software tools like VOSviewer. The researchers of the current study designed an extensive search query to analyze studies related to Augmented Reality (AR) technology in marketing. The keywords in the search command in the Web of Science database include title, abstract, and keywords. The search phrase in the Web of Science database includes marketing and Augmented Reality technology terms, as stated in the search command (Table 1).
Key words in search command
((“augmented reality” AND (marketing* OR purchase decision* OR Advertising* OR Consumer behavior* OR marketplace OR sale* OR Consumer* OR trading* OR promotion OR sell* OR buying* OR retail*OR business OR distribution OR purchasing OR product* OR Price OR packing OR Innovation*)).
The search link from the webofscience database contains
https://www.webofscience.com/wos/woscc/summary/b3f9ea0b-63d7-4bae-ba10-286acc21de22-9b5ee768/relevance/1
Results
Since the publication of the first article in 1996, approximately 496 augmented reality (AR) technology articles in marketing have been published in the Web of Science database until 2023. This figure indicates an irregular publication trend, with an exponential increase in the number of publications since 2015, where about 50% of the journals have been published in the past three years. The study years (2023-1996) are classified into two categories based on the publication rate. The initial period includes the years 1996 to 2020, a time when publication rates were slow and fluctuating. Overall, only 128 articles (25% of the sample) were published during this period. The second period includes the years 2020 to 2023, during which publication rates have increased, with a total of only 496 articles (75% of the sample) published during this period. We will address several factors contributing to the accelerated growth rate of research publications over these periods, especially during the second period from 2020 to 2023
Keywords: Marketing, Augmented Reality Technology, Bibliometrics.
Research Paper
Management approaches in the field of smart
Maryam Nooraei abadeh; Soheila Zarin jouy alvar; Soraya Bakhtiari bastaki
Abstract
In the digital age where changes are happening at an increasing speed, businesses are steadily moving to cloud models. New business models have many advantages, but at the same time, they are accompanied by new risks and challenges. Waterfall failures are one of the most important challenges that can ...
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In the digital age where changes are happening at an increasing speed, businesses are steadily moving to cloud models. New business models have many advantages, but at the same time, they are accompanied by new risks and challenges. Waterfall failures are one of the most important challenges that can have many negative consequences for businesses. Cascading failures refer to the occurrence of an unfortunate event in one part of the cloud business model, which can cause chain damage to other parts of the system and lead to the collapse of the entire system. By using appropriate approaches, the probability of these types of failures can be reduced, and if they do occur, they can be quickly identified and eliminated. The purpose of this article is to examine various factors related to waterfall failures in cloud business models and introduction of suitable approaches for forecasting is the prevention and management of these types of failures. In this article, the literature review method using natural language processing is used to collect information and analyze the topic. The sources used included scientific articles in the field of information technology and business from 2015 to 2024 from the IEEE Xplore, Google Scholar, and arXiv datasets, and 23 articles were analyzed with natural language processing methods. The use of advanced NLP techniques also adds a valuable addition to this process and allows for a more accurate assessment and deeper analysis of the factors associated with cascading failures. Also, rooting out errors and formulating a practical roadmap for their better management allows businesses to facilitate improvement and productivity in their cloud environment and take a more sustainable path. These steps not only help to increase the quality and efficiency of cloud services, but also greatly reduce the costs and time required to fix problems. Various factors related to waterfall failures in cloud business models have been examined in detail. These factors include technical problems, management problems and marketing problems. Also, different approaches for predicting, preventing and managing these types of failures have been introduced.
Introduction
Waterfall failures are one of the most important challenges that can have many negative consequences for businesses. Cascading failures refer to the occurrence of an unfortunate event in one part of the cloud business model, which can cause chain damage to other parts of the system and lead to the collapse of the entire system. By using appropriate approaches, the probability of these types of failures can be reduced, and if they do occur, they can be quickly identified and eliminated. The purpose of this article is to examine various factors related to waterfall failures in cloud business models and introduction of suitable approaches for forecasting is the prevention and management of these types of failures. In this article, the literature review method using natural language processing is used to collect information and analyze the topic. The sources used include scientific articles, research studies and reports of reputable organizations in the field of information technology and business, which have been analyzed with natural language processing methods. The use of advanced NLP techniques also adds a valuable addition to this process and allows for a more accurate assessment and deeper analysis of the factors associated with cascading failures. Also, rooting out errors and formulating a practical roadmap for their better management allows businesses to facilitate improvement and productivity in their cloud environment and take a more sustainable path. These steps not only help to increase the quality and efficiency of cloud services, but also greatly reduce the costs and time required to fix problems. Various factors related to waterfall failures in cloud business models have been examined in detail. These factors include technical problems, management problems and marketing problems. Also, different approaches for predicting, preventing and managing these types of failures have been introduced. The stages of this research to investigate the factors of cascading failures in cloud business models are as follows:
Examining the factors of cascading failures: In this step, various factors that lead to the occurrence of cascading failures in cloud business models are identified and investigated. It includes the examination of technical, operational, managerial and organizational factors, which are more important in cloud environments.
Error rooting: In this step, the rooting of errors in cloud business models is discussed. It is possible to accurately analyze errors and determine their sources and causes, including problems related to infrastructure, software, resource management, security, and other factors.
Presentation of error management methodology: In this phase, a suitable methodology is presented to manage errors in the cloud business. This methodology includes processes, methods and tools used to identify, track, evaluate and fix errors in cloud business models.
Providing a qualitative model for the analysis of cascading failures: In this step, we present a qualitative model for analyzing cascading failures in cloud business models. This model includes various factors that can lead to cascading failures in cloud business models, and provides methods and solutions to prevent and manage these failures.
Compilation of a practical road map for managing cascading failures in cloud business: In this section, the formulation of strategies, goals and expectations from the road map, as well as the selection of suitable solutions to reduce the probability and negative effects of cascading failures, are discussed.
By using a qualitative model, it is possible to provide a more accurate methodology for managing errors and solving problems in the cloud business model, and make a significant improvement in the performance and stability of the cloud business model. Also, by considering the priority features according to the qualitative model, there were significant improvements in the performance and sustainable use of the cloud business model. These improvements can include improving efficiency, increasing reliability, increasing security, and maintaining compliance with changes and customer needs.
Literature Review
The emergence of Industry 4.0 and related technologies (cyber-physical systems, Internet of Things, cloud computing and big data) creates the potential for SMEs stakeholders to compete in a highly competitive global market (Argyroudis et al., 2022). However, as machines, devices, services, and software become heterogeneous and hyperconnected along the cyber supply chain, SMB stakeholders must better understand the potential threats associated with this new business landscape (Rogers, 2023). Bull's (2021) research provides a glimpse of small and medium businesses from the perspective of cyber threats related to key technologies that have become prerequisites for entering this new industrial revolution and cyber supply chain.
Research objective
The aim of this research is to investigate various factors related to waterfall failures in cloud business models and to introduce appropriate approaches for predicting, preventing and managing these types of failures.
Methodology
The stages of this research to investigate the factors of cascading failures in cloud business models, are:
Examining the factors of cascading failures.
Rooting errors.
Presentation of error management methodology.
Presenting a qualitative model of cascade failure analysis.
Developing a practical roadmap for managing cascade failures in cloud business.
Conclusion
Today, the use of online cloud data storage as a solution to preserve data and ensure continuous access to it by individuals and organizations is increasing day by day; But to provide this service, cloud providers need to provide equipment, infrastructure, strong human resources and high potential to prevent and manage cascading failures to ensure security and continuous availability. In fact, every second of data center downtime can damage reputation and revenue. Also, cloud storage as a backup solution, recovery and data rescue service is essential in the industry for a long time. Cascading business failures refer to a series of interconnected failures in a company that can lead to a chain reaction of negative consequences. These failures can start with a single issue, but quickly spread throughout the organization, affecting different aspects of its operations, potentially leading to business failure.
Keywords: Cascading Failures, Business Models, Cloud Models, Prediction.
Research Paper
Data science, intelligence and future analysis
Mohammad Amin Yalpanian; Iman Raeesi Vanani; Mohammad Taghi Taghavifard
Abstract
The ever-increasing development of digital technologies has brought about significant changes in business performance. The increase in the number of published articles on this topic also shows the special attention of researchers in information systems, business management, and innovation. While digital ...
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The ever-increasing development of digital technologies has brought about significant changes in business performance. The increase in the number of published articles on this topic also shows the special attention of researchers in information systems, business management, and innovation. While digital changes are inevitable in the digital age, previous research has been limited to a specific domain. This research aims to identify key themes and macro topics through a systematic review of 201 articles from 2018 to 2023 through two high-quality databases (Scopus and Web of Science). First, using thematic analysis, the main themes are identified, and their relationships are investigated from the perspective of digital technology development. In the next step, by using topic modeling (Latent Dirichlet Allocation), the major domains of the impact of these technologies will be investigated, and future research trends will be identified using the scientometric approach. The realization of digital transformation leads to value creation for business by enhancing the accuracy of management decision-making, making profit through increasing sales and reducing operational and fixed costs, reducing the time of performing processes and responding to changes, and increasing efficiency, and productivity. On the other hand, it affects customer experience improvement of received services, which leads to long-term relationships between the parties, which is very important in today's competitive market in the digital age. The innovation of this research is to design the thematic network through an in-depth review of texts and text mining analysis, which leads to a better understanding of the relationships between main components. Thematic network analysis and the making of relationship with topic modeling concepts is as an artifact that recommendations are given to researchers and managers to conduct future research.
Introduction
In recent years, the industrial world has been transforming into a digital world at a remarkable speed, and extensive advances in digital technologies have accelerated the realization of this transformation in businesses (Schmitt, 2023). Moreover, the threefold increase in published research in this field also shows the interest of academics and industries (Müller et al., 2024).
The adoption of digital technologies, including AI, IoT, machine learning, digital twins, virtual reality, robotic process automation, digital platforms, social media, etc., creates digital capabilities and new opportunities for businesses to improve operations, structures, and procedures (Khalil et al., 2022). According to scientific research, 84% of digital transformation projects have failed or reached goals less than expected (Facchini et al., 2022). As a result, analyzing the impact of digital transformation technologies on business performance has become one of the main priorities in management and information systems research (Oduro et al., 2023). However, despite the importance of the topic and the attention of researchers in the last decade, no comprehensive research has been conducted in the mentioned field, and the research conducted has been limited to a specific field, which shows the need for a holistic framework (Kraus et al., 2022).
Research Question
RQ1: What are crucial themes related to the impact of the development of digital technologies that can be used in providing solutions for the realization of digital transformation on business performance improvement?
RQ2: What are the major topics related to the impact of digital technologies that indicate opportunities and valuable changes to realize digital transformation on business performance improvement?
Literature Review
Digital transformation as a radical change represents an emerging digital paradigm for businesses worldwide. It usually begins with developing a digital technology infrastructure and is considered one of the fundamental requirements for the modernization of businesses (AlNuaimi et al., 2022). Digital transformation technologies create an integrated approach to the entire value chain by simplifying, optimizing, automating, and accelerating existing processes. These technologies create, store, process, manage, and transmit data (Papagnanou et al., 2022). They allow businesses to monitor production operations, identify bottlenecks, analyze market trends, consider customer behavior, manage inventory, and predict future demand by analyzing data. Automating activities and providing real-time information leads to task acceleration in existing processes. Also, due to the development of knowledge management systems, information transfer between stakeholders to share knowledge provides the basis for collaborative learning. On the other hand, digital technologies affect how businesses interact with customers and move businesses towards cross-border (Sandberg et al., 2022).
Research Methodology
This research approach is design science, which has been the focus of researchers in information systems and management, especially information technology management. This research is considered qualitative due to its review of the current situation and the use of articles. Advanced keywords such as digital transformation approach, business performance, digital technologies, and business processes were searched to select the articles. 201 targeted articles were chosen after applying the criteria. After studying the different parts of the articles, a thematic network is drawn. Then, the abstract texts are prepared using text preprocessing techniques; this work aims to use text mining algorithms for future analysis. Topic modeling analyzes and determines existing relationships and extracts hidden patterns. The coherence score is used to ensure that the selected model is optimal. After analyzing the findings, the results are interpreted, and solutions are presented to increase the impact of digital transformation technologies on business performance.
Results
Through thematic analysis of the articles, 7 main themes (digital technology development, digitalization, collaborative learning, digital interaction, data-driven decision-making, digital transformation, and business performance improvement) are interpreted. This research uses MAXQDA software to identify significant themes and draw the theme network.
The development of digital transformation technology affects different business sectors, and digitalization leads to intelligent automation, process improvement, and human error reduction. It is also imperative to increase the knowledge level of employees through collaborative learning. In addition, developing digital communication technologies enhances digital interaction and increases online communication between businesses and their customers, suppliers, employees, and other stakeholders. Also, digitization, analytical tools, and monitoring systems lead to real-time data analysis, which realizes data-driven decision-making and effectively causes digital transformation. Digital transformation leads to business models, flexible hierarchical structures, strategy planning, digital ecosystem, promoting employees' digital skills, production and quality control, supply chain management, marketing, digital servitization, financial management, and research and development. As a result, the creation of digital capabilities leads to business performance. It effectively reduces the product life cycle, creates value for customers, earns profits, and reduces risk in changing market conditions.
Figure 1. Thematic Network
Topic modeling findings show the effects of digital transformation technology as an inevitable opportunity to develop intelligent systems and create value to improve decision-making and increase agility based on the analysis of online interactions between businesses, customers, and partners in digital platforms.
Conclusion and Future Research Directions
Considering this research approach, which is a review of retrospective articles, it is suggested that researchers move toward prospective research. This will help them identify potential challenges and opportunities that may arise and require further attention and research. In today's industries, where digital technologies are rapidly advancing and becoming more complex, prospective research can aid in finding the best solutions and strategies to tackle challenges. Focusing on emerging issues or those that may arise in the future can help develop knowledge and progress in this field.
Keywords: Digital Technology, Business Performance Improvement, Digital Transformation, Thematic Analysis, Advanced Text Analytics
Research Paper
Data science, intelligence and future analysis
roya abadeh; Alireza Hassanzadeh; ُShaban Elahi
Abstract
The most important objectives of this research are to evaluate and illustrate the knowledge map of data mining in covid-19 research, to identify the various components and relationships between data mining concepts in different fields of covid-19 studies. The research method is applied and descriptive. ...
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The most important objectives of this research are to evaluate and illustrate the knowledge map of data mining in covid-19 research, to identify the various components and relationships between data mining concepts in different fields of covid-19 studies. The research method is applied and descriptive. In this research, we utilize the content analysis and text mining techniques. One of the findings of the current research is that a group of researches was related to the "structure and human nature of the disease". Another group of research looked at the set of factors related to adulthood that could be the basis for the absorption of the Covid-19 virus. In the co-authoring section, the highest amount of cooperation was between America and India. The data mining map of Covid-19 is based on thematic modeling including the structure and human nature of the disease, the background and structure of the virus, pandemic prevention, and computer science and artificial intelligence. In this research, according to the use of information technology tools and text mining techniques, a large amount of research has been studied. The presented knowledge map deals with the thematic separation of the researches and information discovery in each collection, so it enables the possibility of comparison between specific thematic groups. In this research, the components of data mining concepts in different fields of Covid-19 studies were examined in six dimensions. In the sixth dimension, the data mining map of Covid-19 was presented based on thematic modeling.
Introduction
What the experience of health officials during the Corona crisis has proven is that it is not possible to manage the disease by relying on traditional methods. Modern information technologies should be used for the optimal management of this disease. Data mining and data analysis can greatly help in preventing, identifying and solving crises. One of the ways that helps researchers to achieve their research goals in their specialized field is to have an overview of the scientific framework of the field in question and previous studies. In this regard, this research has drawn a map of knowledge in the field of Corona data mining by monitoring authors and important and influential works, text mining of studies and specifying thematic clusters formed over time and visualizing information in the field of data mining of Corona. Conducting research in different subject groups provides the possibility of comparing and discovering connections between different fields of knowledge. The provided knowledge map can be used in evidence-based studies in covid-19 researches.
Literature Review
Considering the large amount of data related to Covid-19 that are produced from various sources such as scientific articles, reports of health organizations, clinical and laboratory data, social networks and media, the need for data mining is felt to extract useful and reliable knowledge (Chen et al., 2020). Data mining can help identify risk factors, diagnose and predict disease, evaluate the effects of treatments and vaccines, analyze social and economic behaviors, and provide solutions (Lee et al., 2020). One of the ways that helps researchers to achieve their research goals in their specialized field is to have a general understanding of the scientific framework of the field in question. In this regard, visualizing information or drawing a map and drawing the scientific structure of that field seems necessary. In a knowledge map that is drawn based on the scientific-research outputs of scientists of a scientific field, influential authors, thematic clusters formed over time and important and influential works are determined and introduced. In knowledge maps, the appearance of new areas and the cessation of some saturated scientific areas can be clearly observed and studied. Anderson (2021) used the text mining clustering approach to evaluate the different foci of a large number of abstracts related to Covid-19. Thakur and Kumar (2021) highlight the applied text mining techniques on published scientific articles by carefully reviewing the studies conducted in the last ten years.
Methodology
This research uses applied methodology in terms of purpose. The statistical population of this research is all the researches published in reliable publications that are in the Scopus database. The statistical sample of this research is all scientific documents registered on the topic of data mining of Covid-19 in the years 2020, 2021 and 2022 in the Scopus database. The number of examined documents is 1749, which includes conference and research articles. In this research, all scientific documents where data mining and covid-19 were simultaneously one of its keywords were extracted. Then, by using appropriate algorithms and, text mining software, knowledge map drawing was done.
Results
As a result of topic analysis or Topic Modeling with the help of LDA or Latent Dirichlet Allocation algorithm, four topic keyword sets are displayed as described as follows:
Group 1: includes words that focus on data analysis related to the covid-19 crisis.
Group 2: includes words that seem to focus on machine learning models used to study covid-19.
Group 3: includes words about public information and social aspects of the covid-19 crisis.
Group 4: includes the words also includes data mining and modeling but seems to focus more on the results obtained from these methods in studying different aspects of the crisis.
In the second part of this study, the co-occurrence map analysis of key words in data mining research on Covid-19 shows the conceptual structure of the relationship between concepts or words in a set of publications.
Discussion
In order to identify the components and relationships between data mining concepts in different areas of Covid-19 studies, they were identified using text mining and bibliometric methods. As a result of the process of text mining and the application of different algorithms, it can be said that data mining is one of the most widely used techniques in the following 4 areas in the research of Covid-19: 1. Understanding public reactions or crisis impact, 2. Predicting outcomes or analyzing patient data, 3. How to disseminate information through the media and public reactions, and 4. Studying different aspects of the crisis.
As a result of checking the co-occurrence map of keywords, thematic modeling was divided into the following 4 sub-categories: The first category is in the field of social media, machine learning, and in other words around concepts related to artificial intelligence. Another category is related to topics and concepts such as public health, vaccination, psychology, people's thoughts, communication, fear and emotions. The collection of this cluster can be known as a pandemic. The third category of studies can be considered as "structure and human nature of the disease". The fourth category of studies can be considered related to adulthood. The most widely used data mining method in covid-19 research with the highest reproducibility rate is Classification algorithm with 221 repetitions.
Conclusion
The components of data mining concepts in different fields of Covid-19 studies were examined in six dimensions. In the sixth dimension, the data mining map of Covid-19 was presented based on thematic modeling.
Keywords: Knowledge Map, Data Mining, Covid-19, Text Mining, Visualization.
