Spatial visualisation of stakeholders based on cartographic methodology in management systems

Author(s): Ján Závadský,Zuzana Závadská,Cezary Stępniak,Aida Stępniak / Language(s): English Issue: 9-10/2019

This study presents a model of a tool for spatial visualization of processes occurring in the stakeholder environment concerning relationship management according to the ISO standards for management systems. Spatial visualization is based on cartographic methodology extended with technological capabilities used in GIS (Geographic Information Systems) systems.Thanks to the method, different types of issues using environment maps can be presented. This paper proposes a model of a tool enabling multi-criteria spatial visualization of states, phenomena, processes and plans taking place in the discussed environment. The proposed model of visualization is to be used in the future to present the results of research in the discussed field. They concern stakeholder relationship management according to the ISO management systems. Appropriate technology is required for the application of the model. The study is part of a stream of works aimed at using the concept of space to describe various sections of reality. It may have both theoretical implications (visualizations based on spatial models), as well as practical ones related to popularizing the use of various types of space to describe phenomena and planning. The originality of this study is that the present model-based visualization features selected stakeholders within the ISO standards. As part of the visualization example, heuristic spaces were defined, on which objects representing different types of stakeholders were placed, their significance as part of the ISO standard being determined according to each of the features: power, interest and predictability. The data was obtained in a branch of an international corporation operating in the packaging industry.

Unconventional means of preventing chaos in the economy

Author(s): Gheorghe Doncean,Marilena Doncean / Language(s): English Issue: 2/2021

This research explores five barriers, acting as obstacles to chaos in terms of policy (A), economic (B), social (C), demographic effects (D) and natural effects (E) factors for six countries: Russia, Japan, USA, Romania, Brazil and Australia and proposes a mathematical modelling using an original program with Matlab mathematical functions for such systems. The initial state of the systems is then presented, the element that generates the mathematical equation specific to chaos, the block connection diagram and the simulation elements. The research methodology focused on the use of research methods such as mathematical modelling, estimation, scientific abstraction. Starting from the qualitative assessment of the state of a system through its components and for different economic partners, the state of chaos is explained by means of a structure with variable components whose values are equivalent to the economic indices researched.

Porozumienie towarzystw regionalnych z Gliwic i Zduńskiej Woli. Przykład dobrej praktyki (z teorią w tle)

Author(s): Damian Kasprzyk / Language(s): Polish Issue: 26/2020

Retail Data Measurement Tools, Cognitive Artificial Intelligence Algorithms, and Metaverse Live Shopping Analytics in Immersive Hyper-Connected Virtual Spaces

Author(s): Katarina Zvarikova,Katarina Frajtova Michalikova,Mark Rowlands / Language(s): English Issue: 21/2022

Based on an in-depth survey of the literature, the purpose of the paper is to explore retail data measurement tools, cognitive artificial intelligence algorithms, and metaverse live shopping analytics in immersive hyper-connected virtual spaces. In this research, previous findings were cumulated showing that artificial intelligence chatbot customer service can boost customer engagement and hyper-realistic personalized interactive experiences by use of visual analytics, shopper behavioral data, and location data, and we contribute to the literature by indicating that digital inter- active performance in relation to virtual products and possessions shapes customer habits by harnessing location data. Throughout February 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse” + “live shopping analytics,” “retail data measurement tools,” “cognitive artificial intelligence algorithms,” and “immersive hyper-connected virtual spaces.” As research published in 2022 was inspected, only 87 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 18 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

Predictive Algorithms, Data Visualization Tools, and Artificial Neural Networks in the Retail Metaverse

Author(s): Laura Rydell / Language(s): English Issue: 21/2022

In this article, I cumulate previous research findings indicating that, by leveraging natural language processing, sentiment analytics, business intelligence tools, data-driven decision making, and real-time Internet of Things data, online and virtual marketplaces configure customer loyalty and demand, shopping habits, and changing customer order patterns, while customizing user experiences. I contribute to the literature on predictive algorithms, data visualization tools, and artificial neural networks in the retail metaverse by showing that natural language processing and data sharing technologies, together with data visualization capabilities and sentiment analysis, can enhance business performance in livestreaming e-commerce, configuring consumer purchasing habits and improving customer expectations, confidence, loyalty, and engagement. Throughout March 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “retail metaverse” + “predictive algorithms,” “data visualization tools,” and “artificial neural networks.” As I inspected research published in 2022, only 84 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 17, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, ROBIS, and SRDR.

The Virtual Economy of the Metaverse: Computer Vision and Deep Learning Algorithms, Customer Engagement Tools, and Behavioral Predictive Analytics

Author(s): Robert Watson / Language(s): English Issue: 21/2022

The purpose of this study is to examine the virtual economy of the metaverse in terms of computer vision and deep learning algorithms, customer engagement tools, and behavioral predictive analytics. In this article, I cumulate previous research findings indicating that tailored services in the virtual economy focus on customer retention, increased brand recognition, and optimized digital shopping experiences, by tracking consumer sentiment, behavior, and engagement, thus improving business competitiveness. I contribute to the literature on optimized purchase behavior as regards items traded in the metaverse by showing that customer engagement and product data management can optimize brand visibility and performance, increasing average order and customer lifetime value. Throughout February 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “virtual economy,” “computer vision algorithms,” “deep learning algorithms,” “customer engagement tools,” and “behavioral predictive analytics.” As I inspected research published between 2021 and 2022, only 82 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 16, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, MMAT, and SRDR.

Behavioral Analytics, Immersive Technologies, and Machine Vision Algorithms in the Web3-powered Metaverse World

Author(s): Mária Kováčová,Jakub Horák,Michael Higgins / Language(s): English Issue: 21/2022

We draw on a substantial body of theoretical and empirical research on behavioral analytics, immersive technologies, and machine vision algorithms in the Web3-powered metaverse world. With increasing evidence of data tracking, management, measurement, optimization, and analysis across metaverse worlds, there is an essential demand for comprehending whether technology-enabled live shopping can improve customer engagement and satisfaction in virtual and augmented reality-based immersive environments. In this research, prior findings were cumulated indicating that ambient scene detection and visual analytics can drive customer retention and acquisition in the virtual retail market, building brand awareness and hyper-personalization across e-commerce operations. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2022, with search terms including “metaverse” + “behavioral analytics,” “immersive technologies,” and “machine vision algorithms.” As we analyzed research published in 2022, only 80 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 15, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR.

Virtual Retail in the Metaverse: Customer Behavior Analytics, Extended Reality Technologies, and Immersive Visualization Systems

Author(s): Donald Adams / Language(s): English Issue: 21/2022

The aim of this systematic review is to synthesize and analyze virtual retail in the metaverse in terms of customer behavior analytics, extended reality technologies, and immersive visualization systems. With increasing evidence of consumer values on blockchain-based metaverse platforms, there is an essential demand for comprehending whether digitized retail products and augmented reality shopping tools in virtual malls can integrate consumer intelligence, contextual awareness, and brand perception metrics to result in computational efficiency improvement. In this research, prior findings were cumulated indicating that consumer journey analytics can assist in virtual asset purchasing by articulating personalized shopping experiences. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout February 2022, with search terms including “metaverse” + “virtual retail,” “customer behavior analytics,” “extended reality technologies,” and “immersive visualization systems.” As I analyzed research published in 2022, only 79 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, I decided on 15, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.

Immersive and Engaging Digital Content, Data Visualization Tools, and Location Analytics in a Decentralized Metaverse

Author(s): Nela Mircică / Language(s): English Issue: 21/2022

In this article, I cumulate previous research findings indicating that immersive technologies, automated machine learning, data visualization tools, and location analytics can assist in retaining repeat shoppers, influencing consumer patterns and driving user engagement in virtual retail stores. I contribute to the literature on the decentralized metaverse by showing that data sharing technologies and visual analytics can optimize operations and livestream video shopping experiences in retail and business locations as regards digital ownership in the blockchain-based virtual economy. Throughout March 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “immersive digital content,” “engaging digital content,” “data visualization tools,” and “location analytics.” As I inspected research published between 2021 and 2022, only 76 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 14, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Virtual Marketplace Dynamics Data, Spatial Analytics, and Customer Engagement Tools in a Real-Time Interoperable Decentralized Metaverse

Author(s): Katarína Valášková,Veronika Machová,Elizabeth Lewis / Language(s): English Issue: 21/2022

Despite the relevance of virtual marketplace dynamics data, spatial analytics, and customer engagement tools in a real-time interoperable decentralized metaverse, only limited research has been conducted on this topic. In this article, we cumulate previous research findings indicating that tailored product data enhancement and targeting can lead to customer engagement through integrated machine learning predictions by leveraging personalized content. We contribute to the literature on scalable and sustainable businesses in the metaverse by showing that tailored product data enhancement and targeting can lead to customer engagement through integrated machine learning predictions by leveraging personalized content. Throughout February 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “virtual marketplace dynamics data,” “spatial analytics,” and “customer engagement tools.” As we inspected research published in 2022, only 83 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 17, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT.

Blockchain-based Metaverse Platforms: Augmented Analytics Tools, Interconnected Decision-Making Processes, and Computer Vision Algorithms

Author(s): Barbara Crowell / Language(s): English Issue: 21/2022

Based on an in-depth survey of the literature, the purpose of the paper is to explore augmented analytics tools, interconnected decision-making processes, and computer vision algorithms in relation to blockchain-based metaverse platforms. In this research, previous findings were cumulated showing that changing consumer demands during purchase journeys can be optimized through visual analytics, messaging tools, natural language processing technologies, and real-time inter- operable networks, and I contribute to the literature by indicating that purchase intentions, customer behavior, immersive virtual experiences, and online retail spending on livestreaming shopping platforms can be assessed by data visualizations, voice biometrics, augmented analytics, and search engine algorithms. Throughout March 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse” + “augmented analytics tools,” “interconnected decision-making processes,” and “computer vision algorithms.” As research published in 2022 was inspected, only 86 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, I selected 18 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

Decision Intelligence and Modeling, Multisensory Customer Experiences, and Socially Interconnected Virtual Services across the Metaverse Ecosystem

Author(s): Elvira Nica,Miloš Poliak,Gheorghe H. Popescu,Ioana-Alexandra Pârvu / Language(s): English Issue: 21/2022

This article reviews and advances existing literature concerning decision intelligence and modeling, multisensory customer experiences, and socially interconnected virtual services across the metaverse ecosystem. In this research, previous findings were cumulated showing that customer experience analytics can articulate digital shopping journeys in immersive virtual environments, and we contribute to the literature by indicating that live shopping events are decisive in virtual item purchasing, increasing engagement rates through location data. Throughout February 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse” + “decision intelligence and modeling,” “multisensory customer experiences,” and “socially interconnected virtual services.” As research published in 2022 was inspected, only 89 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 19 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR.

Immersive Virtual Shopping Experiences in the Retail Metaverse: Consumer-driven E-Commerce, Blockchain-based Digital Assets, and Data Visualization Tools

Author(s): Thomas Jenkins / Language(s): English Issue: 21/2022

Based on an in-depth survey of the literature, the purpose of the paper is to explore immersive virtual shopping experiences in the retail metaverse as regards consumer-driven e-commerce, blockchain-based digital assets, and data visualization tools. In this research, previous findings were cumulated showing that livestreaming e-commerce can integrate consumer retail data to enhance real-time customization services and optimize immersive virtual shopping experiences, thus increase user engagement, and I contribute to the literature by indicating that deep learning algorithms, digital neural networks, image recognition, and data-driven decision making can drive operational efficiencies as regards customization and responsiveness, enriching customer intelligence. Throughout March 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse” + “immersive virtual shopping experiences,” “retail brands,” “consumer-driven e-commerce,” “blockchain-based digital assets,” and “data visualization tools.” As research published in 2022 was inspected, only 89 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, I selected 19 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

Digital Commerce in the Immersive Metaverse Environment: Cognitive Analytics Management, Real-Time Purchasing Data, and Seamless Connected Shopping Experiences

Author(s): Sofia Bratu,Ramona Ioana Sabău / Language(s): English Issue: 21/2022

In this article, we cumulate previous research findings indicating that data visualization tools and retail analytics can build consumer relationships in online marketplaces and immersive digital environments as regards virtual stores. We contribute to the literature on digital commerce in the immersive metaverse environment by showing that computer vision algorithms and sentiment analytics can be decisive in changing customer habits and purchasing decisions by improving immersive virtual experiences. Throughout February 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “digital commerce,” “cognitive analytics management,” “real-time purchasing data,” and “seamless connected shopping experiences.” As we inspected research published between 2021 and 2022, only 89 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 20, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, ROBIS, and SRDR.

Live Shopping in the Metaverse: Visual and Spatial Analytics, Cognitive Artificial Intelligence Techniques and Algorithms, and Immersive Digital Simulations

Author(s): Andrej Novák,George Lăzăroiu,Tomáš Klieštik / Language(s): English Issue: 21/2022

The purpose of this study is to examine live shopping in the metaverse in terms of visual and spatial analytics, cognitive artificial intelligence techniques and algorithms, and immersive digital simulations. In this article, we cumulate previous research findings indicating that retail analytics can build brand awareness and improve operational performance across shared virtual environments by customizing user experiences. We contribute to the literature on retail business models in the metaverse environment by showing that cognitive artificial intelligence techniques and algorithms can be pivotal in virtual commerce by enhancing digital shopping experience through location data. Throughout March 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “live shopping,” “visual analytics,” “spatial analytics,” “cognitive artificial intelligence techniques and algorithms,” and “immersive digital simulations.” As we inspected research published between 2021 and 2022, only 89 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 20, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, MMAT, and SRDR.

Virtual Commerce in a Decentralized Blockchain-based Metaverse: Immersive Technologies, Computer Vision Algorithms, and Retail Business Analytics

Author(s): Emily Hopkins / Language(s): English Issue: 21/2022

I draw on a substantial body of theoretical and empirical research on virtual commerce in a decentralized blockchain-based metaverse. With increasing evidence of immersive technologies, computer vision algorithms, and retail business analytics, there is an essential demand for comprehending whether voice biometrics technology, search engine algorithms, sensor data, and decision support tools can shape customer behavior and deliver business value across immersive 3D worlds. In this research, prior findings were cumulated indicating that immersive technologies can enhance operational performance across virtual stores by assessing purchasing decisions, customer confidence, engagement, and habits through data visualization in retail business and operations. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout February 2022, with search terms including “metaverse” + “virtual commerce,” “immersive technologies,” “computer vision algorithms,” and “retail business analytics.” As I analyzed research published in 2022, only 81 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, I decided on 16, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR.

Metaverse Applications, Technologies, and Infrastructure: Predictive Algorithms, Real-Time Customer Data Analytics, and Virtual Navigation Tools

Author(s): Raluca-Stefania Balica,Jana Majerova,Adela-Claudia Cuțitoi / Language(s): English Issue: 21/2022

The aim of this systematic review is to synthesize and analyze metaverse applications, technologies, and infrastructure in relation to predictive algorithms, real-time customer data analytics, and virtual navigation tools. With increasing evidence of metaverse live-video shopping events, there is an essential demand for comprehending whether consumer digital engagement as regards virtual assets improves immersive shopping journeys and experiences. In this research, prior findings were cumulated indicating that consumer journey analytics and data-driven decision making can determine purchase intentions across immersive 3D worlds and in virtual stores. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2022, with search terms including “metaverse” + “predictive algorithms,” “real-time customer data analytics,” and “virtual navigation tools.” As we analyzed research published between 2021 and 2022, only 86 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 20, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.

Virtual Immersive Shopping Experiences in Metaverse Environments: Predictive Customer Analytics, Data Visualization Algorithms, and Smart Retailing Technologies

Author(s): John Hudson / Language(s): English Issue: 21/2022

In this article, I cumulate previous research findings indicating that smart connected devices can assist data-driven decisions in retail livestreaming by articulating personalized shopping experiences as regards digital ownership across extended reality environments. I contribute to the literature on virtual immersive shopping experiences in metaverse environments by showing that contextual awareness and real-time performance data can typify immersive retail experiences, improving brand recognition. Throughout February 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “virtual immersive shopping experiences,” “predictive customer analytics,” “data visualization algorithms,” and “smart retailing technologies.” As I inspected research published between 2021 and 2022, only 83 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 16, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Digital Consumer Engagement on Blockchain-based Metaverse Platforms: Extended Reality Technologies, Spatial Analytics, and Immersive Multisensory Virtual Spaces

Author(s): Pavol Kral,Katarina Janoskova,Ana-Mădălina Potcovaru (Bîgu) / Language(s): English Issue: 21/2022

Despite the relevance of digital consumer engagement on blockchain-based metaverse platforms, only limited research has been conducted on this topic. In this article, we cumulate previous research findings indicating that retail business analytics can assess interconnected virtual experiences by harnessing user data across 3D immersive environments. We contribute to the literature on shared virtual environments and immersive digital worlds by showing that customer behavior analytics can optimize purchase journeys and personalized shopping experiences by use of synthetic data, scale visualization, and physiological and behavioral biometrics. Throughout March 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “meta- verse” + “digital consumer engagement,” “extended reality technologies,” “spatial analytics,” and “immersive multisensory virtual spaces.” As we inspected research published between 2021 and 2022, only 89 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 20, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT.

TÜRKİYE’DE ÖRGÜTSEL DEĞİŞİM VE ÖRGÜT GELİŞTİRME ALANINDAKİ BİLİMSEL ÇALIŞMALARIN BİBLİYOMETRİK ANALİZİ

Author(s): Nihat Erdoğmuş,Züleyha SAYIN / Language(s): Turkish Issue: Sp. Issue/2022

Scientific studies in the field of organizational change and organization development in Turkey began to increase in the 1990s. With the reflection of the changes in the world on working life and organizations, certain changes have also been experienced in organizational change and organization development studies. For this reason, the aim of the study is to reveal the changes and developments in the field of organizational change and organizational development in Turkey. In this context, articles, theses and books in the field of organizational change and organizational development since the 1990s were analyzed bibliometrically. Along with the study, changes and developments in organizational change and organizational development studies in Turkey are discussed periodically. As a result of the bibliometric analysis, it was seen that there were more conceptual studies in the first years, empirical studies increased over time, public institutions were frequently preferred as application areas, and the studies focused on business, public administration and education. Based on these findings, the developments and changes in the field are discussed.