Pub Date : 2022-07-29DOI: 10.7250/csimq.2022-31.00
Bartosz Marcinkowski
This thematic issue introduces two structured literature review articles as well as a couple of empirical ones. The authors of the literature reviews move into the broad field of assuring the quality of IT artifacts, focusing on different dimensions of the software engineering process. With the ever-increasing scale of computerization in more and more areas of life, insufficient emphasis on quality is not only associated with significant costs of bug-fixing. After all, considerable risks arise from the possibility of exploiting the vulnerabilities of the target product. In extreme cases, poor quality can lead to loss of health and life. Not surprisingly, academics and practitioners alike have been looking at this challenge for many years, and from numerous perspectives. The quality of IT artefacts also depends on the education of professionals and good understanding of application domains. The empirical papers concern educational issues regarding Enterprise Architecture and deepen our understanding of decentralized autonomous systems.
{"title":"Selected Topics on Business Informatics: Editorial Introduction to Issue 31 of CSIMQ","authors":"Bartosz Marcinkowski","doi":"10.7250/csimq.2022-31.00","DOIUrl":"https://doi.org/10.7250/csimq.2022-31.00","url":null,"abstract":"This thematic issue introduces two structured literature review articles as well as a couple of empirical ones. The authors of the literature reviews move into the broad field of assuring the quality of IT artifacts, focusing on different dimensions of the software engineering process. With the ever-increasing scale of computerization in more and more areas of life, insufficient emphasis on quality is not only associated with significant costs of bug-fixing. After all, considerable risks arise from the possibility of exploiting the vulnerabilities of the target product. In extreme cases, poor quality can lead to loss of health and life. Not surprisingly, academics and practitioners alike have been looking at this challenge for many years, and from numerous perspectives. The quality of IT artefacts also depends on the education of professionals and good understanding of application domains. The empirical papers concern educational issues regarding Enterprise Architecture and deepen our understanding of decentralized autonomous systems.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125348441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-29DOI: 10.7250/csimq.2022-31.01
Jordan Hermann, B. Tenbergen, Marian Daun
Conceptual models are an effective and unparalleled means to communicate complicated information with a broad variety of stakeholders in a short period of time. However, in practice, conceptual models often vary in clarity, employed features, communicated content, and overall quality. This potentially impacts model comprehension to a point where models are factually useless. To counter this, guidelines to create “good” conceptual models have been suggested. However, these guidelines are often abstract, hard to operationalize in different modeling languages, partly overlap, or even contradict one another. In addition, no comparative study of proposed guidelines exists so far. This issue is exacerbated as no established metrics to measure or estimate model comprehension for a given conceptual model exist. In this article, we present the results of a literature survey investigating 109 publications in the field and discuss metrics to measure model comprehension, their quantification, and their empirical substantiation. Results show that albeit several concrete quantifiable metrics and guidelines have been proposed, concrete evaluative recommendations are largely missing. Moreover, some suggested guidelines are contradictory, and few metrics exist that allow instantiating common frameworks for model quality in a specific way.
{"title":"Metrics to Estimate Model Comprehension Quality: Insights from a Systematic Literature Review","authors":"Jordan Hermann, B. Tenbergen, Marian Daun","doi":"10.7250/csimq.2022-31.01","DOIUrl":"https://doi.org/10.7250/csimq.2022-31.01","url":null,"abstract":"Conceptual models are an effective and unparalleled means to communicate complicated information with a broad variety of stakeholders in a short period of time. However, in practice, conceptual models often vary in clarity, employed features, communicated content, and overall quality. This potentially impacts model comprehension to a point where models are factually useless. To counter this, guidelines to create “good” conceptual models have been suggested. However, these guidelines are often abstract, hard to operationalize in different modeling languages, partly overlap, or even contradict one another. In addition, no comparative study of proposed guidelines exists so far. This issue is exacerbated as no established metrics to measure or estimate model comprehension for a given conceptual model exist. In this article, we present the results of a literature survey investigating 109 publications in the field and discuss metrics to measure model comprehension, their quantification, and their empirical substantiation. Results show that albeit several concrete quantifiable metrics and guidelines have been proposed, concrete evaluative recommendations are largely missing. Moreover, some suggested guidelines are contradictory, and few metrics exist that allow instantiating common frameworks for model quality in a specific way.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125588301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-30DOI: 10.7250/csimq.2022-30.04
V. Žentiņš, D. Rusovs, Aleksandrs Soročins, V. Kulakova
Accurate production planning in both the short and long term is very important in cogeneration plants. Especially if the cogeneration unit operates under free electricity market conditions, which complicates the decision-making process as an additional planning condition with variable heat, fuel, and CO2 costs. On the other hand, when a cogeneration plant uses a heat accumulation system, it is impossible to make a production decision without using a computer system; the human factor in decision-making can lead to erroneous decisions without traceability. The role of modern computer systems is growing and greatly influences the optimal production planning process in cogeneration plants, regardless of the installed capacity and in the operation with heat accumulation. One of the problems solved by the research is the integration of real operating modes and conditions (applied thermal insulation solution) into the production decision algorithms. The developed methodology allows not only to plan the operating modes of the cogeneration plant, but also to evaluate the efficiency of the battery solution. This study shows the developed methodology for calculating heat loss for a heat accumulator depending on the operating mode and the need to introduce a correction coefficient. When determining the total influencing expenses of the cost model of the heat accumulator operation mode, their mutual influence is shown and integrated into the decision-making algorithm for the next day's free-market conditions. The aim of the algorithm is maximally increasing the total gross revenue threshold for the planning of cogeneration operations and to exclude operating modes that may cause losses.
{"title":"Decision Making Control Algorithm for Cogeneration Plants in Operating with the Heat Accumulator Deep Analysis Model","authors":"V. Žentiņš, D. Rusovs, Aleksandrs Soročins, V. Kulakova","doi":"10.7250/csimq.2022-30.04","DOIUrl":"https://doi.org/10.7250/csimq.2022-30.04","url":null,"abstract":"Accurate production planning in both the short and long term is very important in cogeneration plants. Especially if the cogeneration unit operates under free electricity market conditions, which complicates the decision-making process as an additional planning condition with variable heat, fuel, and CO2 costs. On the other hand, when a cogeneration plant uses a heat accumulation system, it is impossible to make a production decision without using a computer system; the human factor in decision-making can lead to erroneous decisions without traceability. The role of modern computer systems is growing and greatly influences the optimal production planning process in cogeneration plants, regardless of the installed capacity and in the operation with heat accumulation. One of the problems solved by the research is the integration of real operating modes and conditions (applied thermal insulation solution) into the production decision algorithms. The developed methodology allows not only to plan the operating modes of the cogeneration plant, but also to evaluate the efficiency of the battery solution. This study shows the developed methodology for calculating heat loss for a heat accumulator depending on the operating mode and the need to introduce a correction coefficient. When determining the total influencing expenses of the cost model of the heat accumulator operation mode, their mutual influence is shown and integrated into the decision-making algorithm for the next day's free-market conditions. The aim of the algorithm is maximally increasing the total gross revenue threshold for the planning of cogeneration operations and to exclude operating modes that may cause losses.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125624978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-30DOI: 10.7250/csimq.2022-30.01
C. Tsai, J. Zdravkovic, Janis Stirna
The changing business landscapes urge organizations to collaborate and combine their expertise to stay competitive. Organizations establish partnerships and collaborate via the Internet, which often happens dynamically and at fast pace resulting in formation of Digital Business Ecosystems (DBEs). DBEs are complex and their management requires having explicit and up-to-date information about them. Modeling enables thorough visual analysis and facilitates the understanding and formation of DBEs. It also allows viewing DBEs through multiple perspectives, as well as exploring alternatives in the course of DBE formation or management. This systematic review aims to synthesize existing studies pertaining to Conceptual Modeling for analysis, design, and management of DBEs. A total of 94 studies were included in the review. The findings suggest that there is a scarcity of existing Conceptual Modeling methods and tools supporting DBEs. Additionally, the extensive emphasis on DBEs’ actors in modeling leads to an urgent need for the methods to be extended to support the establishment of holistic views for integrating multiple perspectives of DBEs. Future research should focus on these areas to facilitate the transformation of how organization’s collaborations are viewed – from a single-organization to a multitude of viewpoints on organizational networks of collaboration, coexistence, and competition. Such models also need to support the key features of DBEs, such as resilience and automation.
{"title":"Modeling Digital Business Ecosystems: A Systematic Literature Review","authors":"C. Tsai, J. Zdravkovic, Janis Stirna","doi":"10.7250/csimq.2022-30.01","DOIUrl":"https://doi.org/10.7250/csimq.2022-30.01","url":null,"abstract":"The changing business landscapes urge organizations to collaborate and combine their expertise to stay competitive. Organizations establish partnerships and collaborate via the Internet, which often happens dynamically and at fast pace resulting in formation of Digital Business Ecosystems (DBEs). DBEs are complex and their management requires having explicit and up-to-date information about them. Modeling enables thorough visual analysis and facilitates the understanding and formation of DBEs. It also allows viewing DBEs through multiple perspectives, as well as exploring alternatives in the course of DBE formation or management. This systematic review aims to synthesize existing studies pertaining to Conceptual Modeling for analysis, design, and management of DBEs. A total of 94 studies were included in the review. The findings suggest that there is a scarcity of existing Conceptual Modeling methods and tools supporting DBEs. Additionally, the extensive emphasis on DBEs’ actors in modeling leads to an urgent need for the methods to be extended to support the establishment of holistic views for integrating multiple perspectives of DBEs. Future research should focus on these areas to facilitate the transformation of how organization’s collaborations are viewed – from a single-organization to a multitude of viewpoints on organizational networks of collaboration, coexistence, and competition. Such models also need to support the key features of DBEs, such as resilience and automation.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122964938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-30DOI: 10.7250/csimq.2022-30.02
C. Stary, Matthes Elstermann, A. Fleischmann, W. Schmidt
Digital Twins are digital models of Cyber-Physical Systems to enable not only continuous monitoring but also active functional improvement of networked services, physical products, machines and devices. This capacity is of utmost importance when recognizing and exploring business opportunities in terms of organizational and technology innovations, as well as enriching the scope of system-relevant applications. Before being operated in their target ecosystems, such as smart cities, Cyber-Physical Systems can be validated and be run as Digital Twin through executable behavior models. The development of these models captures both, the horizontal, and the vertical integration of CPS components, thus allowing to consider specific system qualities, such as pollution effects of traffic. This article investigates methodological and technological aspects of developing and operating Digital Twins along system transformation processes. We consider integration depth and breadth, connectivity, organizational intelligence, validation, and implementation variability in the context of human-centered modeling and development. The approach enriches the understanding of digital twins towards digital representation of Cyber-Physical Systems allowing for dynamic allocation of physical and digital parts according to operational conditions. An exemplary case study in traffic management demonstrates the feasibility and practicability of the communication-centered approach.
{"title":"Behavior-Centered Digital-Twin Design for Dynamic Cyber-Physical System Development","authors":"C. Stary, Matthes Elstermann, A. Fleischmann, W. Schmidt","doi":"10.7250/csimq.2022-30.02","DOIUrl":"https://doi.org/10.7250/csimq.2022-30.02","url":null,"abstract":"Digital Twins are digital models of Cyber-Physical Systems to enable not only continuous monitoring but also active functional improvement of networked services, physical products, machines and devices. This capacity is of utmost importance when recognizing and exploring business opportunities in terms of organizational and technology innovations, as well as enriching the scope of system-relevant applications. Before being operated in their target ecosystems, such as smart cities, Cyber-Physical Systems can be validated and be run as Digital Twin through executable behavior models. The development of these models captures both, the horizontal, and the vertical integration of CPS components, thus allowing to consider specific system qualities, such as pollution effects of traffic. This article investigates methodological and technological aspects of developing and operating Digital Twins along system transformation processes. We consider integration depth and breadth, connectivity, organizational intelligence, validation, and implementation variability in the context of human-centered modeling and development. The approach enriches the understanding of digital twins towards digital representation of Cyber-Physical Systems allowing for dynamic allocation of physical and digital parts according to operational conditions. An exemplary case study in traffic management demonstrates the feasibility and practicability of the communication-centered approach.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127108763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-30DOI: 10.7250/csimq.2022-30.03
L. Eglite, I. Birzniece
This systematic literature review examines the deep learning (DL) models for retail sales forecast. The accuracy of a retail sales forecast is a prevalent force for uninterrupted business operations. Accuracy for retailers means limiting supply chain and storage costs, ensuring no product is out of stock, and facilitating smooth promotional operations. The study analyses the DL frameworks used in reviewed literature. Tested DL models are listed, as well as other machine learning and linear models used for the evaluation comparison. Additionally, the review presents the metrics used by the authors for the model evaluation. This article concludes by describing the benefits and limitations of DL models for sales forecasting.
{"title":"Retail Sales Forecasting Using Deep Learning: Systematic Literature Review","authors":"L. Eglite, I. Birzniece","doi":"10.7250/csimq.2022-30.03","DOIUrl":"https://doi.org/10.7250/csimq.2022-30.03","url":null,"abstract":"This systematic literature review examines the deep learning (DL) models for retail sales forecast. The accuracy of a retail sales forecast is a prevalent force for uninterrupted business operations. Accuracy for retailers means limiting supply chain and storage costs, ensuring no product is out of stock, and facilitating smooth promotional operations. The study analyses the DL frameworks used in reviewed literature. Tested DL models are listed, as well as other machine learning and linear models used for the evaluation comparison. Additionally, the review presents the metrics used by the authors for the model evaluation. This article concludes by describing the benefits and limitations of DL models for sales forecasting.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121756771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.7250/csimq.2021-29.00
Birger Lantow, Erika Nazaruka, K. Sandkuhl
Business Informatics is the scientific discipline combining computer science, business administration and information technology and investigating related phenomena in their socioeconomical context, including companies, organizations, administrations, and society in general. As a field of study, it is closely related to the fields of management science, organizational science, computer science, systems engineering, information systems, information management, social science, and economics information science. The objective of this thematic issue was to show the diversity of research in the field of business informatics, both from the perspective of application areas and from the research methodologies applied. Application areas visible in this issue are product development in manufacturing industries, online learning in universities, innovation activities in networks of museums, and curriculum engineering in educational organizations. Research methods include various quantitative and qualitative approaches combined with prototyping and the design science paradigm. The thematic issue collection opens with the article entitled “Virtual Prototyping: Evaluating the Digital Twin Based Virtual Factory for New Product Introduction”. In this article, the authors address the need of several industries to replace physical prototyping with virtual prototyping for reducing product and production lifecycle costs and time. The focus of the paper is on new product introduction and the use of virtual prototyping in virtual factories and their “digital twins”. The study has the ambition to provide knowledge closing the gap between theories supporting the design and management of complex manufacturing systems, and integration and implementation of technologies in the application domain. The contribution to systems engineering is based on two industrial case studies and expert evaluations of a comprehensive concept, which integrates state-of-the-art technologies with systems development processes. The results indicate the usefulness of digital twin based virtual factories in new product introduction particularly for progressing the development of production processes and systems. The second article, “An Empirical Research on Study Success in Times of COVID-19
{"title":"Selected Topics on Business Informatics: Editorial Introduction to Issue 29 of CSIMQ","authors":"Birger Lantow, Erika Nazaruka, K. Sandkuhl","doi":"10.7250/csimq.2021-29.00","DOIUrl":"https://doi.org/10.7250/csimq.2021-29.00","url":null,"abstract":"Business Informatics is the scientific discipline combining computer science, business administration and information technology and investigating related phenomena in their socioeconomical context, including companies, organizations, administrations, and society in general. As a field of study, it is closely related to the fields of management science, organizational science, computer science, systems engineering, information systems, information management, social science, and economics information science. The objective of this thematic issue was to show the diversity of research in the field of business informatics, both from the perspective of application areas and from the research methodologies applied. Application areas visible in this issue are product development in manufacturing industries, online learning in universities, innovation activities in networks of museums, and curriculum engineering in educational organizations. Research methods include various quantitative and qualitative approaches combined with prototyping and the design science paradigm. The thematic issue collection opens with the article entitled “Virtual Prototyping: Evaluating the Digital Twin Based Virtual Factory for New Product Introduction”. In this article, the authors address the need of several industries to replace physical prototyping with virtual prototyping for reducing product and production lifecycle costs and time. The focus of the paper is on new product introduction and the use of virtual prototyping in virtual factories and their “digital twins”. The study has the ambition to provide knowledge closing the gap between theories supporting the design and management of complex manufacturing systems, and integration and implementation of technologies in the application domain. The contribution to systems engineering is based on two industrial case studies and expert evaluations of a comprehensive concept, which integrates state-of-the-art technologies with systems development processes. The results indicate the usefulness of digital twin based virtual factories in new product introduction particularly for progressing the development of production processes and systems. The second article, “An Empirical Research on Study Success in Times of COVID-19","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114903783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.7250/csimq.2021-29.01
E. Yıldız, Charles Møller, A. Bilberg, Jonas Kjær Rask
Shortening lifecycles and increasing complexity make product and production lifecycle processes more challenging than ever for manufacturing enterprises. Virtual Prototyping (VP) technologies promise a viable solution to handle such challenges in reducing time and physical builds as well as increasing quality. In previous studies, the Digital Twin (DT) based Virtual Factory (VF) concept showed significant potential to handle co-evolution by integrating 3D factory and product models with immersive and interactive 3D Virtual Reality (VR) simulation technology as well as real-time bidirectional data synchronisation between virtual and physical production systems. In this article, we present an extension to the paper “Demonstrating and Evaluating the Digital Twin Based Virtual Factory for Virtual Prototyping” presented at CARV2021. The study presents an evaluation by industry experts of the DT based VF concept for VP in the context of New Product Introduction (NPI) processes. The concept is demonstrated in two cases: wind turbine blade manufacturing and nacelle assembly operations at Vestas Wind Systems A/S. The study shows that the VF provides an immersive virtual environment, which allows the users to reduce the time needed for prototyping. The industry experts propose several business cases for the introduced solution and find that the phases that would have the most gain are the later ones (production) where the product design is more mature.
{"title":"Virtual Prototyping: Evaluating the Digital Twin Based Virtual Factory for New Product Introduction","authors":"E. Yıldız, Charles Møller, A. Bilberg, Jonas Kjær Rask","doi":"10.7250/csimq.2021-29.01","DOIUrl":"https://doi.org/10.7250/csimq.2021-29.01","url":null,"abstract":"Shortening lifecycles and increasing complexity make product and production lifecycle processes more challenging than ever for manufacturing enterprises. Virtual Prototyping (VP) technologies promise a viable solution to handle such challenges in reducing time and physical builds as well as increasing quality. In previous studies, the Digital Twin (DT) based Virtual Factory (VF) concept showed significant potential to handle co-evolution by integrating 3D factory and product models with immersive and interactive 3D Virtual Reality (VR) simulation technology as well as real-time bidirectional data synchronisation between virtual and physical production systems. In this article, we present an extension to the paper “Demonstrating and Evaluating the Digital Twin Based Virtual Factory for Virtual Prototyping” presented at CARV2021. The study presents an evaluation by industry experts of the DT based VF concept for VP in the context of New Product Introduction (NPI) processes. The concept is demonstrated in two cases: wind turbine blade manufacturing and nacelle assembly operations at Vestas Wind Systems A/S. The study shows that the VF provides an immersive virtual environment, which allows the users to reduce the time needed for prototyping. The industry experts propose several business cases for the introduced solution and find that the phases that would have the most gain are the later ones (production) where the product design is more mature.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123089430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.7250/csimq.2021-29.03
Susanne Marx
Open Innovation (OI) research has covered various organizational forms in dimensions of durability (permanent versus temporary organizing) and organizational scope (intra- or inter-organizational). Inter-organizational forms - both temporary and permanent – are regarded mainly as modes of OI. However, these organizational forms also act as initiators of OI activities to extend knowledge transfer across the inter-organizational consortium borders, which is hardly researched. To address this gap, the research presented in this article develops an OI process for inter-organizational projects (IOP) as initiators of OI. The initial model is developed by action research with an IOP of museums and educational institutions implementing a series of hackathons. The model’s applicability is then evaluated for other IOPs by a survey, indicating the model’s suitability for practitioners. Findings point to the importance of collaborative activities for aligning the OI initiative with both individual partners’ and common project goals, while outbound activities are regarded least important despite the time-limitation of the project. The research is limited by its focus on the specific IOP environment of EU-funded projects and the small scope of the survey.
{"title":"Open Innovation Process for Inter-Organizational Projects","authors":"Susanne Marx","doi":"10.7250/csimq.2021-29.03","DOIUrl":"https://doi.org/10.7250/csimq.2021-29.03","url":null,"abstract":"Open Innovation (OI) research has covered various organizational forms in dimensions of durability (permanent versus temporary organizing) and organizational scope (intra- or inter-organizational). Inter-organizational forms - both temporary and permanent – are regarded mainly as modes of OI. However, these organizational forms also act as initiators of OI activities to extend knowledge transfer across the inter-organizational consortium borders, which is hardly researched. To address this gap, the research presented in this article develops an OI process for inter-organizational projects (IOP) as initiators of OI. The initial model is developed by action research with an IOP of museums and educational institutions implementing a series of hackathons. The model’s applicability is then evaluated for other IOPs by a survey, indicating the model’s suitability for practitioners. Findings point to the importance of collaborative activities for aligning the OI initiative with both individual partners’ and common project goals, while outbound activities are regarded least important despite the time-limitation of the project. The research is limited by its focus on the specific IOP environment of EU-funded projects and the small scope of the survey.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115244180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.7250/csimq.2021-29.04
Peteris Rudzajs, M. Kirikova
Continuous and rapid developments in science and technology have raised a challenge for compliance between the learning content provided by study programs and (1) the actual state of art in the domains the programs are addressing and (2) the actual needs of companies that will employ the graduates of these programs. To achieve such compliance continuously, the digitalization of learning content (curriculum) engineering could provide supporting tools that facilitate awareness of incompliance, which is the first step in introducing changes in the learning content. In this article we discuss how such awareness, regarding the needs of companies, can be supported by a service system that monitors the gap between educational demand and offer. The proposed service system provides possibilities for automatic, semi-automatic and manual analysis of texts representing the educational demand, versus the texts representing the educational offer. The implementation of the service system has been demonstrated, having been applied at university. The experiments showed that the system can provide valuable information for educational content development, but its maintenance and incorporation in study process management and curriculum engineering still require additional research.
{"title":"Monitoring Services to Support Continuous Curriculum Engineering","authors":"Peteris Rudzajs, M. Kirikova","doi":"10.7250/csimq.2021-29.04","DOIUrl":"https://doi.org/10.7250/csimq.2021-29.04","url":null,"abstract":"Continuous and rapid developments in science and technology have raised a challenge for compliance between the learning content provided by study programs and (1) the actual state of art in the domains the programs are addressing and (2) the actual needs of companies that will employ the graduates of these programs. To achieve such compliance continuously, the digitalization of learning content (curriculum) engineering could provide supporting tools that facilitate awareness of incompliance, which is the first step in introducing changes in the learning content. In this article we discuss how such awareness, regarding the needs of companies, can be supported by a service system that monitors the gap between educational demand and offer. The proposed service system provides possibilities for automatic, semi-automatic and manual analysis of texts representing the educational demand, versus the texts representing the educational offer. The implementation of the service system has been demonstrated, having been applied at university. The experiments showed that the system can provide valuable information for educational content development, but its maintenance and incorporation in study process management and curriculum engineering still require additional research.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132710382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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