Search

Modern life and society are heavily reliant on technology. Technology has the potential to revolutionize educational access by transcending geographical barriers and catering to diverse learning needs, paving the way for equitable and inclusive education for all. Various studies have confirmed that use of technology tools in education would democratize access, personalize learning experiences, enhance engagement and promote learning opportunities. Background digital infrastructure is a critical enabler of educational technology tools. This study is such an attempt. It tries to systematically evaluate the digital infrastructure ecosystem, needed to advance technology in education. Specifically, the study tries to assess the status of digital infrastructure for online learning in higher education. We focused this study on India, which has the third largest higher education system in the world. A composite index was developed with the use of Principal Component Analysis (PCA) to evaluate the IT infrastructure by relying on relevant secondary data. Based on this index score, digital infrastructure status of various States of the country was determined. Results suggested regional disparities in digital infrastructure and areas to focus to strengthen digitally enabled higher education. The study's findings have implications for reducing the digital divide by improving digital infrastructure and designing policy interventions, particularly in developing countries. [ABSTRACT FROM AUTHOR]

Purpose: Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation. Design/methodology/approach: This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique. Findings: Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources. Originality/value: This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance. [ABSTRACT FROM AUTHOR]

This article explores the application of blockchain technologies (BT) in managing IT infrastructure projects with the aim of enhancing security levels. It examines the potential of blockchain to ensure data protection, access control, and process automation through decentralized structures and immutable records. It is noted that the use of smart contracts and cryptographic methods can minimize the risks of cyberattacks and data leaks, while ensuring transparency and network resilience. The successful integration of blockchain solutions to optimize processes and improve IT system security is demonstrated through examples from companies like IBM, Walmart, and JP Morgan. The article discusses the advantages and challenges of implementing blockchain in existing systems, highlighting the necessity of a comprehensive approach and strategic planning for successful integration. [ABSTRACT FROM AUTHOR]

Purpose – This paper evaluated the effectiveness of blended learning of business courses in higher learning institutions (HEIs) in developing economies. Design/methodology/approach – A survey, involving 215 learners, was used to collect data. A stratified sampling technique was used in this study. The data were analyzed using the PROCESS macro in SPSS. Findings – In the blended learning approach, student attitudes, social presence, IT infrastructure and flexible learning are all favorable predictors of learner satisfaction. The impact of blended learning on learner satisfaction is further mediated by IT infrastructure, social presence and learner attitude. Practical implications – HEIs need to invest in planning and resource mobilization in order to realize several benefits derived from the use of blended learning. For optimal learning outcomes, this should be combined with training on IT infrastructure usage for both facilitators and learners. In order to assist learners in developing competencies through consistent use, institutions should also invest in tailored blended learning technologies. In addition, emphasis should be placed on training all actors in order to better manage change. Originality/value – This paper presents and ranks several dimensions for blended learning success in low-budget universities. In addition, the study contributes to the understanding of intervening variables necessary for enhancing the potential of pedagogy in maximizing learner satisfaction.

Subject indexing is one of the core activities of libraries. Due to the proliferation of digital documents it is no longer possible to annotate every single document intellectually, which is why we need to explore the potentials of automation. At ZBW the efforts to automate the subject indexing process started as early as 2000 with experiments involving external partners and commercial software. The conclusion from that first period was that supposedly shelf-ready solutions would not cover the requirements of the library. In 2014 the decision was made to start doing the necessary applied research in-house by establishing a corresponding PhD position. However, the prototypical machine learning solutions they developed were yet to be integrated into productive operations at the library. Therefore in 2020 an additional position for a software engineer was established and a 4-year pilot phase was initiated with the goal to build a software architecture that allows for real-time subject indexing with our trained models and the integration thereof into the other metadata workflows at ZBW. This paper gives an account of how we tackled the task of transferring results from applied research into a productive subject indexing service (the "AutoSE service"), including the milestones we have reached, the challenges we were facing on a strategic level, and the measures and resources (computing power, software, personnel) that were needed in order to be able to effect the transfer and get a first version going, which went live in 2021. The models used by AutoSE until now were models from classical machine learning. We therefore also touch on the question if and how the recent advent of large language models (LLMs) has changed our outlook on the task of automating subject indexing and on the role of metadata in information management and retrieval in general, and the ways in which it impacts our research and development roadmap going forward. [ABSTRACT FROM AUTHOR]

Copyright of Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article aims to analyse the contribution of Information Technology (IT) infrastructure responsiveness in the initiative of using knowledge sharing to enhance the technological innovation capability of industrial companies. The research uses a sample of 90 multinational companies, and structural equation modelling to assess the hypotheses. The results show that initiatives to encourage knowledge sharing positively impact the technological innovation capability. Additionally, the research presents empirical evidence that the responsiveness of the IT infrastructure can induce knowledge sharing as a factor in expanding the technological innovation capability. Understanding how knowledge sharing can enhance technological innovation capability can help organisational theorists predict behaviours based on this innovative capability. Additionally, this understanding may expose mechanisms that enhance the effects of this sharing. This research contributes to the insertion of new views on studies involving the effects that IT responsiveness can exert on the technological innovation capability of companies. [ABSTRACT FROM AUTHOR]

Information technology infrastructure (ITI) has gone through an exponential change due to the rapid evolution of digital technologies during the past few years. It is therefore relevant to identify the factors that push organizations towards the adoption of new technologies. This paper considers a specific case study of the higher education institutions (HEI) to present (i) the motivational factors that push HEIs toward the adoption of new technologies, and (ii) the key challenges HEIs face in the adoption of these technologies. The data was gathered after conducting 17 open-ended interviews with practitioners working at HEIs in Finland and Pakistan. Data analysis identified 10 motivational factors and 41 challenges faced by HEI in the adoption of the latest technologies. Furthermore, the data was further classified to identify broad themes and categories representing the challenges and motivation factors. [ABSTRACT FROM AUTHOR]

The integration of Digital Twins (DTs) is becoming increasingly important in various industries. This entails the need for a comprehensive and practical IT infrastructure framework. This paper presents a modifiable medium-level architecture that serves as a link between established reference architectures such as RAMI 4.0 and the pragmatic implementation of Digital Twins. The functionalities of an IT infrastructure are considered, and functional hardware and software components for fulfilling these are described. The proposed architecture is suitable for various deployment scenarios, including local, cloud and hybrid cloud–edge configurations. In order to improve the applicability of the medium-level architecture, a step-by-step procedure is also proposed, which helps to transfer the overarching requirements for a Digital Twin into a suitable IT infrastructure. Finally, the results are demonstrated by an exemplary application to a two-stage industrial gearbox. [ABSTRACT FROM AUTHOR]

In the context of the rapid growth of the fintech industry in Indonesia, the study explores the choice of IT infrastructure in particular between on premise and cloud in digital wallet fintech start-ups to improve cost efficiency. With a lack of detailed information in the literature about the critical role of infrastructure in the development of fintech, the study uses Mixed Methods The Convergent Parallel Design to provide in-depth insights into the impact of infrastructural decisions on operational and financial efficiency. The findings show that the adoption of cloud infrastructure, chosen for its scalability, flexibility, and cost efficiency, is significant in reducing operating and maintenance costs, while strengthening market positions. However, the decision also calls for serious consideration of security aspects, data privacy, and regulatory compliance. The findings provide important contributions for policymakers, regulators, and industry stakeholders in understanding the importance of data security strategies and company-specific needs in selecting IT infrastructures. In conclusion, choosing the right IT infrastructure is key to reducing costs and supporting sustainable growth in the fintech sector, especially for digital wallet start-ups. [ABSTRACT FROM AUTHOR]

In recent decades the agricultural intensification led to a landscape simplification, where once heterogeneous landscapes turned into more monocultured cropping regions. The main driver behind it was to be able to use larger and more powerful agricultural machinery in order to increase productivity and specially to decrease labor costs. With the advent of robots in combination with new methods of AI it is obvious that this is not only a new step of automated mechanization. New robotic systems open up new opportunities of how to cultivate crop plants. Different robotic concepts with different properties are discussed and how these might contribute to achieve the indisputably needed improvements in sustainable and environmental-friendly crop production systems. In a performed case study, it is demonstrated that even if larger robotic solutions when operated in isolation still can achieve higher area outputs, smaller and often specialized robotic systems can achieve a substantially improved work quality in the use case of seeding.

Effective management of information technology infrastructure (ITI) is key to success for any enterprise offering IT services in this contemporary digital era. Considering the importance of the topic both for research and practice, a Systematic Mapping Study (SMS) was conducted (with the following research questions) to present state-of-the-art concerning the management of ITI, (i) what focus areas related to the management of IT Infrastructure have been considered in the extant literature?, (ii) what are the publication trends and characteristics of existing research on IT Infrastructure Management?, (iii) what are the main challenges in the context of managing IT Infrastructure reported in the existing literature?, and (iv) what recommendations and guidelines have been proposed to overcome the reported challenges? Following the systematic approach, n=57 articles from extant literature satisfying this study’s inclusion and exclusion criteria were considered for analysis to find answers to these research questions. The findings reveal (i) research focus areas categorized into 6 categories (i.e., resource, service, learning style, self-care, data sharing & access, and human ITI capability), (ii) a set of variables to map publication trends and characteristics of existing research with “evaluation research”, “constructive research” and “models” recognized as the most common paper type, research methods, and contribution type respectively, (iii) 28 challenges related to ITI management in enterprises were identified, and (iv) 68 guidelines and recommendations for organizations and personnel were identified to manage the ITI more efficiently. The findings such as research focus areas and publication trends are important from a research perspective offering guidance to researchers to drive further research on the topic. Meanwhile, the challenges, recommendations, and guidelines have practical implications, providing practitioners with insights into better understanding and management of their respective ITI.

The article is devoted to the disclosure of the process of carrying out comprehensive IT monitoring of the company. IT infrastructure monitoring, an important process, helps a company track changes in the infrastructure. Monitoring purpose is the collection and analysis of IT services data, components of the information infrastructure and use received data to control all elements, prevent failures, errors, and finally, for the company's security. For monitoring, specialized IT infrastructure monitoring systems are used, they collect all the necessary data, combine them into a single database, where structuring and analysis takes place. By constantly monitoring various parameters and metrics, such as system load, availability of processor resources, network speed, usage of processor resources, memory, and disk space, certain problems can be identified in advance and take the necessary measures to eliminate them. IT monitoring includes the use of various tools and technologies, in particular: resource monitors, notification systems, event logs, analytical reports, control panels that help to obtain, analyze, visualize data on the state of IT infrastructure and services. The compliance of the monitoring system with established metrics and indicators allows to ensure IT system efficiency, quickly respond to emerging problems (identify operational problems, equipment malfunction), identify possible security breaches (malicious attacks) and plan future resources. Monitoring is a necessary element of IT environment management, as it allows to identify, control, and solve problems that arise in the infrastructure and affect the IT services quality and performance. Effective monitoring helps to improve the availability, productivity, and quality of IT services, which, in turn, helps to achieve business goals and meet user needs. Particular attention in the article was paid to the elements of the IT infrastructure that are subject to monitoring (servers, network devices, databases, software), since the monitoring of these elements allows quickly identify problems, control resources, and take timely measures to solve them [ABSTRACT FROM AUTHOR]

Technical support of IT infrastructure is a crucial aspect of organizational operations, with the most challenging task being ensuring service continuity. Quality support guarantees high IT efficiency, but complex incidents reduce support quality and require effective management. Incident management includes configuration processes and control of technical solutions. To improve technical support, adhering to both quantitative and qualitative standards and considering system specifics is necessary. According to service level agreements (SLA), the resolution time of incidents is important. „Service Desk“ tools, applying machine learning methods, can help optimize these processes. Incorrectly classified user requests lead to additional work for the IT team and delay incident resolution. Machine learning methods, such as K-means clustering, Random Forest regression, and classification, can optimize incident management and speed up resolution time. The research analyzes „Service Desk“ incident data to model resolution times and improve incident management. Article in Lithuanian. Incidentų valdymo modelio tobulinimas, taikant mašininio mokymosi metodus Santrauka IT infrastruktūros techninis palaikymas yra esminis organizacijos veiklos aspektas, kurio sudėtingiausia užduotis yra užtikrinti veikimo tęstinumą. Kokybiškas palaikymas garantuoja aukštą IT efektyvumą, tačiau sudėtingi incidentai sumažina palaikymo kokybę ir reikalauja veiksmingo valdymo. Incidentų valdymas apima konfigūracijų procesus ir techninių sprendimų kontrolę. Siekiant pagerinti techninį palaikymą, būtina laikytis tiek kiekybinių, tiek kokybinių standartų ir atsižvelgti į sistemų specifiką. Pagal paslaugų lygio sutartis (SLA) svarbus incidentų sprendimo laikas. „Service Desk“ įrankiai, taikant mašininio mokymosi metodus, gali padėti optimizuoti šiuos procesus. Naudotojų neteisingai klasifikuotos užklausos lemia papildomą IT komandos darbą ir vilkina incidentų sprendimą. „K-means“ klasterizacijos, „Random Forest“ regresijos ir klasifikacijos mašininio mokymosi metodai gali optimizuoti incidentų valdymą ir pagreitinti sprendimo laiką. Tyrimo tikslas yra analizuoti „Service Desk“ incidentų duomenis, siekiant modeliuoti sprendimų laiką ir pagerinti incidentų valdymą. Reikšminiai žodžiai: IT infrastruktūra, techninis palaikymas, incidentų valdymas, incidentų sprendimo laikas, Service Desk, mašininio mokymosi metodai, užklausos klasifikavimas.

In today's rapidly evolving educational landscape, European universities are increasingly relying on digital technologies for collaboration and learning. European Universities, as transnational alliances, aim to reshape higher education by fostering academic exchange and innovation across borders. With over 40 alliances in existence, enhancing virtual mobility and exchange through interconnected learning infrastructures has become imperative. This paper provides insights into Learning Management System (LMS) adoption within European alliances, focusing on the Unite! alliance as a case study. While Unite! demonstrates successful implementation of Moodle as its central LMS, challenges persist in achieving uniformity across all partners. A desktop analysis of European alliances reveals that Moodle might be the most often used LMS in February 2023. A description of the LMS implementation within the Unite! analysis shows as well that a majority uses Moodle – at least as a second LMS. So, although the decision for a federated LMS based on Moodle might be the right one, these results as well indicate the need for tailored technical solutions for future developments for some partners and disparities in lecturers‘ and students‘ concerning a Moodle so that pre-emptive measures to ensure equitable participation are important. Despite these challenges, Unite!'s experience underscores the potential of Moodle as a widely adopted platform, prompting further exploration into solutions like LTI integration.

This study aimed to examine the mediating role of technological vigilance within commercial banks in Jordan in supporting the relationship between information technology (IT) infrastructure (hardware, software, network, security, maintenance, information quality, and interoperability) and Accounting Information Systems (AIS) efficiency. AMOS and Statistical Package of Social Science (SPSS) were used in order to screen and analyze the data collected from 161 financial and accounting managers within commercial banks in Jordan. The results indicated that technological vigilance mediates the relationship between IT infrastructure and AIS efficiency; it is based on the idea that the use of IT infrastructure, such as networks, hardware, and software to support business processes has a direct impact on the efficiency of AIS. Accordingly, this study recommends focusing on the role of IT infrastructure and the mediating role of technological vigilance in achieving AIS efficiency in Jordanian commercial banks. The originality of the study lies in its ability to address the role of IT infrastructure in increasing AIS efficiency, as well as its focus on the mediating role that technological vigilance. The study also has a novel contribution to the field by exploring the interconnectedness between technology, operational efficiency, and watchfulness. Through an in-depth analysis of empirical case studies, a deeper understanding of the interplay between these three variables was presented.

INTRODUCTION: IT infrastructure resources in large-sized companies have evolved into large-scale intelligent enterprise systems due to the emergence of Big Data, Internet of Things, and artificial intelligence technologies. OBJECTIVES: The purpose of this study was to analyze the effect of eHRM implementation and the availability of IT infrastructure on top management/CEO support and the performance of logistics companies in Semarang city. METHODS: This study uses a quantitative method with an analytical tool using SEM-PLS. The sampling method for this study used a purposive sampling technique with a total sample of 120 samples. RESULTS: IT infrastructure has a significant effect on top management support in logistics companies, the role of eHRM has a significant effect on top management support, the role of eHRM has a significant effect on CEO support, eHRM has a significant effect on company performance, IT infrastructure has a significant effect on company performance, support CEO has a significant effect on company performance, IT infrastructure has a significant effect on company performance, and the role of eHRM has no significant effect on company performance. CONCLUSION: IT Infrastructure and CEO Support influence Supply Chain Performance in Small-Scale Logistics Companies. [ABSTRACT FROM AUTHOR]

The management of telework is in essence to correctly perform the technologies continuously at work and thus adapt to the abrupt changes produced by digital disruption; in that sense the present study has as main objective to determine the relationship between the management of telework and digital disruption in the administrative staff of a public university. In the same way it is intended to determine the relationship between the dimensions: IT infrastructure, organization, control and general awareness; and the variable digital disruption. The method used was quantitative, basic type, correlational level, according to the method, general and scientific, non-experimental research design of cross-sectional type; the sample consisted of 201 administrative workers. For data collection, the survey was used as a technique and the questionnaire as an instrument. According to the results, a Rho de Spearman coefficient of = 0.548 was obtained, with a p-value = 0.000 < 0.05. Therefore, it is concluded that there is a considerable positive relationship between telework management and disruption in the administrative staff of a public university. [ABSTRACT FROM AUTHOR]

Subject indexing, i.e., the enrichment of metadata records for textual resources with descriptors from a controlled vocabulary, is one of the core activities of libraries. Due to the proliferation of digital documents, it is no longer possible to annotate every single document intellectually, which is why we need to explore the potentials of automation on every level. At ZBW the efforts to partially or completely automate the subject indexing process started as early as 2000 with experiments involving external partners and commercial software. The conclusion of that first exploratory period was that commercial, supposedly shelf-ready solutions would not suffice to cover the requirements of the library. In 2014 the decision was made to start doing the necessary applied research in-house which was successfully implemented by establishing a PhD position. However, the prototypical machine learning solutions that they developed over the following years were yet to be integrated into productive operations at the library. Therefore in 2020 an additional position for a software engineer was established and a pilot phase was initiated (planned to last until 2024) with the goal to complete the transfer of our solutions into practice by building a suitable software architecture that allows for real-time subject indexing with our trained models and the integration thereof into the other metadata workflows at ZBW. In this paper we address the question of how to transfer results from applied research into a productive service, and we report on the milestones we have reached so far and on those that are yet to be reached on an operational level. We also discuss the challenges we were facing on a strategic level, the measures and resources (computing power, software, personnel) that were needed in order to be able to affect the transfer, and those that will be necessary in order to subsequently ensure the continued availability of the architecture and to enable a continuous development during running operations. We conclude that there are still no shelf-ready open source systems for the automation of subject indexing – existing software has to be adapted and maintained continuously which requires various forms of expertise. However, the task of automation is here to stay, and librarians are witnessing the dawn of a new era where subject indexing is done at least in part by machines, and the respective roles of machines and human experts may shift even further and more rapidly in a not-so-distant future. We argue that in general, the format of “project” and the mindset that goes with it may not suffice to secure the commitment that an institution and its decision-makers and the library community as a whole will have to bring to the table in order to face the monumental task of the digital transformation and automation in the long run. We also highlight the importance of all parties – applied researchers, software engineers, stakeholders – staying involved and continuously communicating requirements and issues back and forth in order to successfully create and establish a productive service that is suitable and equipped for operation.

AbstractThis study explores the link between inventory optimization and operational efficiency in public sector organizations in Ethiopia. The study specifically examines the role of Capacity utilization, Inventory precision, IT infrastructure, administrative purchasing procedures, Workforce competence and proficiency, Record-keeping towards achieving optimal inventory management and operational efficiency in these organizations. The research is based on a quantitative approach, with primary data collected through a survey of 186 public sector organizations in Ethiopia. Utilizing a descriptive and explanatory research design, primary and secondary data were collected and analyzed through the application of SPSS version 24 and presented with descriptive and inferential statistics. The results indicate a significant and positive correlation between Inventory Optimization and operational efficiency. Additionally, multiple regression analysis revealed that inventory utilization, administrative purchasing procedures, record-keeping and documentation, staff skills and knowledge, inventory accuracy, and IT infrastructure have a significant impact on operational efficiency. Consequently, the study provides data-driven insights into the importance of inventory optimization in enhancing operational efficiency in public sector organizations in Ethiopia. This study recommends that the management of Ethiopian public sector organizations should focus on developing short administrative purchasing procedures, ensuring good record-keeping and documentation, utilizing adequate information and communication technology, and investing in staff skills training to enhance Inventory Optimization and overall organizational operational efficiency.

Key stakeholders across different industries with competing visions, motivations and technology bets are investing significant financial resources in developing the building blocks of the metaverse. The purpose of this opinion piece aimed primarily at practitioners is to explore the key question: What is needed to make the metaverse real? What are the key uncertainties that must be resolved? We are motivated by shedding light on whether the metaverse is just a new marketing buzzword or a new transformative trend. We have identified six areas with key uncertainties, which require agreement and solutions from industry players – the space, the interface, the IT infrastructure, the monetary infrastructure, the digital ID and the energy. These uncertainties will be resolved in a series of cooperative and competitive games among the key stakeholders who will need to work on being aligned on a set of standards. The practical implication is that the metaverse cannot be ignored, but there are non-trivial challenges that need to be resolved first. Our paper provides a framework for practitioners to think through these issues in a more systematic fashion.

Information technology (IT) is a critical resource and asset for a firm's internal operations and external interactions with outside stakeholders. This paper explores IT capabilities that enable a retailer's value chain activities and interfaces with suppliers and customers. IT capabilities that enable the value chain activities of logistics and operations as well as those of marketing and sales are identified to examine how they influence a retailer's implementation of value chain interfaces. Through the lens of organizational information processing theory (OIPT), we find that both IT capabilities and IT infrastructure play a pivotal role in implementing value chain interfaces but in distinctive ways. On the supplier-facing side, a retailer's IT infrastructure and IT capabilities enabling logistics and operations are essential to its vendor-managed inventory (VMI) system. On the customer-facing side, a retailer's e-commerce website requires IT infrastructure and IT capabilities that enable marketing and sales. Moreover, synergies are found downstream for e-commerce website that benefits from the integration of IT infrastructure and IT capabilities enabling logistics and operations while such synergies are not found upstream for VMI. This partial complementary effect is explicated by the sequential asymmetric information dependency of value chain activities. Finally, we discuss the implications of our findings for the research and practice of IT enablement and integration. [ABSTRACT FROM AUTHOR]

Presently, many enterprises are automating all processes in their production, and the metallurgical industry is no exception. There are many software products for industrial automation on the market today. Such products allow bringing certain processes to a single management process, displaying all processes and automatically monitoring performance indicators, thereby assessing the effectiveness of the models implemented in the enterprise and the operation of the entire enterprise in general. The purpose of this study is to consider which production planning models are currently used for manufacturing execution system (MES) and highlight their features, specifically when implemented at metallurgical enterprises. The study employed the following methods: analysis, synthesis, comparison, graphical presentation of data. The information basis of this paper included the studies of Russian, European, American, Asian specialists investigating the implementation of an integrated management system (MES) in the metallurgical industry. The results of this study allowed highlighting the features of existing production planning models for manufacturing execution systems (MES) in the metallurgical industry. This study is of practical importance because it allows highlighting the major features of various production planning models for manufacturing execution systems (MES) in the metallurgical industry and based on a comparative analysis, choosing the best one to implement at the enterprise. The results of a comparative analysis of production planning models for manufacturing execution systems (MES) in the metallurgical industry can also lead to the fact that an enterprise may abandon one model that is already operating in the enterprise and switch to a new, more progressive model that meets all the requirements and development trends market in the steel industry

The improvement in the reliability, availability, and maintenance of the IT infrastructure components is paramount to ensure uninterrupted services in large-scale IT Infrastructures. The massive system logs generated by infrastructures have proved to be advantageous to pursue the runtime circumstances and behavior of the system. Existing literature has log-based failure detection techniques carrying semantic analysis but on limited log features, reflecting ineffectiveness in anomaly detection for unstable and unseen log records. We have proposed in this paper a semantic log analysis model with three log features to apprehend the gist of the log message. BERT pre-trained model is employed to adapt the feature embedding. The generated numerical vectors are further furnished to train an attention-based OLSTM (Optimized Long Short-Term Memory Networks) classifier to detect failures in diverse infrastructures. The proposed model is evaluated on five different infrastructures: Apache from a server application, OpenStack from the Distributed Systems, Windows from the Operating System, BGL from a Supercomputer, and Android from the Mobile System. The findings illustrate that the proposed system delivers improved and stable results, considering the varied IT infrastructures.

This study aims to examine the relationship between Organisation culture, IT infrastructure and Knowledge Management Process, towards Knowledge Management implementation effectiveness in a Malaysian manufacturing company. This study was conducted among the permanent employees across all departments in the GLC Manufacturing Plant in Malaysia. Quantitative data were collected using self-administered questionnaires to a sample of 108 permanent employees. Based on the findings from multiple regression analysis, Organisation Culture had the most significant impact towards KM implementation effectiveness; whilst IT Infrastructure had a significant relationship but KM Process had no significant relationship with KM implementation effectiveness. The study had made significant contribution where it extended the literature on KM enablers influencing KM implementation effectiveness and contribute towards strategizing better policies on organizational culture and IT Infrastructure to improve overall KM effectiveness in manufacturing organization.

The paper proposes a process model approach to enhance the economic efficiency of production systems driven by the transformation of their IT infrastructure under the dynamics of the external environments. To achieve the goal, a new notation is suggested that allows to formalize processes in organizational systems, allocate the management subject in an explicit form, simulate the work of the process model for the decision support system in order to study its performance and efficiency. As a result of the study, an algorithm has been developed to estimate how the changes of the IT infrastructure parameters affect the efficiency of the production system performance; in addition, this algorithm can be used to determine the key performance indicators of the organizational system through scheduling development plans. [ABSTRACT FROM AUTHOR]

Background: New emerging technologies enable healthcare centers to enhance their information technology (IT) infrastructure, which offers an opportunity to provide adequate services to patients. In Saudi Arabia, the government has initiated artificial intelligence-based technologies to increase productivity in organizations. However, recent studies demand innovative approaches for quality management in healthcare centers. In addition, there is a scarcity of techniques for evaluating the performance of healthcare professionals. Methods: The study intended to investigate the role of IT in quality management in Saudi Arabian healthcare centers. A set of hypotheses were proposed to identify the relationship between IT and quality management. A web-based questionnaire was used and interviews were conducted in the healthcare centers of Riyadh and Eastern provinces. A total of 233 healthcare professionals and management employees participated in the survey. A mixed-method approach was applied to evaluate the responses. Furthermore, exploratory and confirmatory factor analyses were used to draw insights from the data. Results: The outcome reveals a positive relationship between IT and quality management. Moreover, the thematic findings outline the importance of IT competence in healthcare centers. Conclusions: The study's findings can support healthcare centers to deploy valuable tools and techniques to improve the quality of service.

The new generation of industry, i.e. Industry 4.0, pertains to the processing of immense amounts of data, resulting, among other things, from the large-scale use of microcontrollers to control machines, an increase in the scale of automation, the use of the Internet of Things technology — e.g. in sensors installed at different stages of the production process, the implementation of the digital twin concept, and many other technologies designed to collect data (e.g. GPS or RFID). These data are collected in the enterprise’s variety of resources and databases. These data can be a valuable source of information and knowledge if the right approach to advanced data analysis is adopted, which depends, among other things, on the enterprise’s existing IT infrastructure. This paper sets out to present conclusions formulated on the basis of research consisting in the analysis of multinational manufacturing companies’ existing IT infrastructures. Three basic model solutions of IT architecture occurring in multi-site enterprises were identified, which made it possible to identify the main problems stemming from the IT architecture in place and concerning the analysis of data for the needs of company management. Additionally, this paper discusses the challenges faced by multi-site manufacturing companies. One such activity is the modification and expansion of the company’s IT infrastructure, including the implementation of Big Data and Master Data Management (MDM) solutions. The contribution provided by this paper consists in the analysis of the IT infrastructure in large, multi-site enterprises, which enabled the identification of problems and challenges related to advanced data analysis in this type of companies.