Organizational Information Research Articles

Perceptions of Organizational Change Readiness for Sustainable Digital Transformation: Insights from Learning Management System Projects in Higher Education Institutions

The adoption of Learning Management Systems (LMS) in Higher Education Institutions (HEI) offers a transformative potential to enhance educational quality, operational efficiency, and cost-effectiveness while promoting sustainable digital transformation. However, resistance to LMS implementation often undermines these benefits. Initial perceptions of an Organizational Change Readiness (OCR) play a crucial, as they shape attitudes and behaviors, often resulting in rumors, disengagement, and resistance. The objective of the study is to explore how attributes of change, leadership support, internal organizational context, and attributes of change targets impact OCR in the context of LMS implementation. Drawing from organizational change management and information systems literature, this study examines key factors influencing these early perceptions within LMS initiatives. A cross-sectional survey was conducted with 316 university personnel across seven public universities and three private colleges. Data were analyzed using partial least squares, revealing that vision clarity, change appropriateness, top-management support, project champion effectiveness, and organizational flexibility explaining 75% of the variance in perceived OCR. Conversely, factors such as change efficacy, organizational history of change, organizational conflicts, and group self-efficacy demonstrated limited influence. These findings underscore the importance of aligning LMS initiatives with institutional goals, fostering sustainable digital practices, and enhancing policy frameworks to facilitate smooth adoption. This study provides actionable insights for promoting sustainable educational transformation in HEIs, particularly in contexts where traditional teaching methods prevail and resistance to technological change is common.

KEBERKESANAN LAMAN WEB ULPL@POLINILAI: PENGURUSAN MAKLUMAT LATIHAN DAN PEMBANGUNAN PENGURUSAN KAKITANGAN

Ongoing training and management of staff development is essential to maintaining a competitive edge in the work environment. It can also increase the efficiency and job satisfaction of staff. The Training & Continuous Education Unit is under the academic support division responsible for organizing In-Service Courses, planning and managing Lifelong Learning programs, and managing management facilities at ULPL. The development of this training and staff development information website was developed to help provide comprehensive and organized information covering training management, facilities, and services provided. The objective of this research is to identify the level of effectiveness of the ULPL@POLINILAI website through the perception of usefulness and the perception of ease of use of the website. This study is based on primary sources and uses a purposive sampling technique that focuses on ULPL service users from November 2023 to March 2024. The results of the study are analyzed using Statistical Packages for The Social Sciences 25.0 software to meet the objectives of the study. Findings show the effectiveness of the website through the perception of usefulness and the perception of convenience at a high level. It found the ULPL@POLINILAI website effective for internal and external course management, PSH management, and facility management. It is also in line with current technological advances with the website being easier in the accessibility of information to staff.

HISTORICAL ANALYSIS OF THE ORGANISATIONAL LEARNING OF EXERCISES WITHIN THE ARMED FORCES OF UKRAINE (DECEMBER 1991–FEBRUARY 2022)

The article examines the historical aspects of organisational learning of military exercises within the Ukrainian Armed Forces (from their creation in December 1991 until the largescale Russian invasion of Ukraine on 24 February 2022). It compares this activity with the relevant practice of the North Atlantic Alliance. The research paper highlights two key stages in the operational and combat training of the Armed Forces of Ukraine: “Decline” (December 1991–April 2014), when the military learning was ineffective, which impacted the ability of Ukrainian troops to adapt and functionally counter Russian armed aggression, and ‘Modernization’ (April 2014–February 2022), during which the approaches to analyse and implement lessons were improved by the NATO standards. A comparative analysis of the organisational learning of military exercises within the Armed Forces of Ukraine and NATO during the above period (1991–2022) was carried out on the basis of studying five key elements of the lessons learned capability: organisational structure, process, tools, training, and information sharing.

USING SUPPORT VECTORS TO BUILD A RULE-BASED SYSTEM FOR DETECTING MALICIOUS PROCESSES IN AN ORGANISATION'S NETWORK TRAFFIC

The growing complexity and sophistication of cyberattacks on organisational information resources and the variety of malware processes in unprotected networks necessitate the development of advanced methods for detecting malicious processes in network traffic. Systems for detecting malicious processes based on machine learning and rule-based methods have their advantages and disadvantages. We have investigated the possibility of using support vectors to create a rule-based system for detecting malicious processes in an organisation's network traffic. We propose a method for building a rule-based system for detecting malicious processes in an organisation's network traffic using the distribution data of the relevant features of support vectors. The application of this method on real CSE-CIC-IDS2018 network traffic data containing characteristics of malicious processes has shown acceptable accuracy, high clarity and computational efficiency in detecting malicious processes in network traffic. In our opinion, the results of this study will be useful in creating automatic systems for detecting malicious processes in the network traffic of organisations and in creating and using synthetic data in such systems.

Health Care Financing Practices Among U.S. Amish.

The Amish are a rapidly growing Christian ethnoreligious group located in the U.S. and Canada. Characterized by self-reliance and a caution regarding the acceptance of modern technologies, the Amish have traditionally relied on community-based mutual aid to finance health care expenditures instead of commercial insurance or public assistance options. However, the cost, structure, and efficacy of Amish mutual aid programs are not well-described. We surveyed 1006 Amish households in 12 states using a 31-question instrument that asked respondents about demographic information, their health, and participation in mutual aid organizations. Statistical analysis was performed with returned surveys. One hundred fifty-five surveys were returned for a response rate of 15.4%. 81% of respondents reported mutual aid membership. The reported annual health care spending ranged from $500 to $18,000 among nine mutual aid organizations. More than 90% of respondents indicated that they "agree" that their community will help them pay for health care, though 39% reported "sometimes" avoiding recommended medical care due to cost. There were statistically significant differences in treatment avoidance due to cost and perceptions of affordability between Indiana Amish and those in Michigan and Wisconsin. The financing mechanisms employed in our cohort included negotiating organizations, subscription models, and voluntary donation. Though mutual aid mechanisms were ubiquitous, the success of individual organizations may depend on Amish population distribution and relationship with health systems. Providers treating this population should understand Amish practices regarding medical billing. Further studies are necessary to develop institutional best practices for Amish and other self-pay populations.

The Role of Knowledge-Sharing Mediation and its Impact Between Organizational Justice and Innovative Work Behavior

This study explores the impact of organizational justice on teachers' innovative work behavior in Yogyakarta's religious education sector. The research methodology employed in this study is quantitative, which is utilized to ascertain the correlation between independent and dependent variables. We used a survey instrument comprising 372 participants. Researchers utilize Structural Equation Modeling (SEM), or Analysis of Covariance Structures, and causal modeling to test the hypothesis using the AMOS tool to analyze the Moment of Structures. The findings indicate that distributive and informational justice positively influence innovative behavior, although procedural and interpersonal justice do not. Distributive and interpersonal justice are important factors that influence knowledge-sharing among teachers. Knowledge sharing has been demonstrated to facilitate innovative work behavior, mediating between distributive justice and innovative work behavior. The results highlight the significance of organizational justice and information sharing in promoting innovation in the religious education setting in Yogyakarta. Distributional and informational justice significantly impact innovative work behavior, although procedural and interpersonal justice does not play a significant role.

DETERMINANTS AND BENEFITS OF KNOWLEDGE MANAGEMENT: CASE OF THE DRGB SONATRACH TRC

Knowledge management has become essential for organizations seeking a sustainable competitive advantage. However, its success depends on several prerequisites. This article aims to provide an overview of knowledge management applied within an Algerian company, the Regional Directorate of Bejaia, for transporting hydrocarbons by pipelines, "DRGB SONATRACH TRC." To this end, we employed two research instruments: an interview guide for a hierarchical manager and a questionnaire addressed to employees. Our final sample consists of 51 employees from various professional categories. SPSS version 23 was used for the analysis of the collected data, and the non-parametric Spearman's rho correlation test was utilized to verify the research hypotheses. Our findings indicate that knowledge management in the studied enterprise manifests through the combination of five subprocesses: creation, acquisition, application, sharing, and storage of knowledge. These processes are influenced, to varying degrees, by the following determinants: organizational culture, leadership, information technologies, and strategy. Our study also highlighted the benefits of knowledge management, such as increased market share, improved quality of products and services offered, and enhanced company image and productivity. In light of these results, we recommend the formalization of knowledge management practices and their integration into the company’s strategy, the promotion of a flexible compensation system that includes rewards for innovative ideas and solutions, as well as the relaxation of bureaucratic procedures to encourage individual initiatives and creativity. This study enriches the existing literature, which tends to analyze the knowledge management process in a fragmented manner, by proposing a focus on concrete mechanisms applicable in practice. Its practical contribution is reflected in the identification of strengths to leverage and obstacles to overcome.

Peran Media Sosial X Dalam Pemanfaatan Upaya Mitigasi Bencana

Social media has become a strategic tool in supporting disaster mitigation efforts, including in the rapid and widespread dissemination of information. This study analyzes the role of social media X (formerly Twitter) in supporting disaster mitigation efforts for the eruption of Mount Lewotobi Laki-laki on November 8, 2024. This mountain erupted twice with the eruption column reaching 10 km above the peak, producing thick volcanic ash that affected the surrounding area. The National Disaster Management Agency (BNPB) utilized social media X to provide the latest information, early warnings, and safety guidance to the public. The research method used a descriptive-qualitative approach with content analysis of BNPB's official posts on the X platform. The results showed that social media X was effective in disseminating real-time information, raising public awareness, and coordinating emergency response efforts. In less than an hour after the first eruption, BNPB managed to reach thousands of users with information related to the affected areas, evacuation steps, and health recommendations related to volcanic ash. However, there are challenges such as the potential for the spread of false information that can cause panic in the community. This study confirms that social media X has an important role in disaster risk management. Optimal use of social media, supported by organized information management, can help save lives and minimize the impact of disasters. This study recommends intensive training for BNPB officers in utilizing social media effectively for disaster mitigation.

Advanced depth-layering using a synthetic-depth map and deep neural network for real-world object-based holographic displays

We propose an advanced layering method for real-world object-based holographic displays, leveraging what we believe to be a novel synthetic-depth map and deep neural network. The proposed system aims to implement a holographic display that displays natural-like three-dimensional visualizations of real objects by enhancing data quantity and ensuring accurate depth layers. A simplified light-field image acquisition system combined with a deep neural network is employed to efficiently gather organized omnidirectional three-dimensional information from the object, achieving high quality while minimizing processing time. Subsequently, a novel high-accuracy synthetic-depth map containing data from both initial depth and position maps is estimated. Finally, the sub-holograms for each depth layer are generated and integrated as a single main hologram by encompassing comprehensive object information, which is displayed on the spatial light modulator of a holographic display system and illuminated by a coherent light source. Experimental results confirm the superiority of the proposed system, particularly demonstrating its effectiveness for objects with a wide depth range or multiple objects separated by considerable distances.

Digital transformation of primary health care in Moscow

The modern appearance of the Moscow digital clinic was mainly set in 2011 in the context of complex changes in the city management system, which subsequently took the form of the Moscow city development concept “Smart City – 2030”. The initial goals for changing primary health care included providing Muscovites with access to information and communication technologies in medical organizations, eliminating fragmentation and duplication of functions, and ensuring compatibility of data used in various information systems. Aim. To identify and describe step-by-step changes in the organization of primary health care in Moscow, related to the introduction of digital technologies and aimed at improving the organizational forms and methods of operation of public medical institutions in the capital, improving the access of the urban population to timely and high-quality medical care. Materials and methods. An analysis of regulatory legal acts and scientific literature was carried out in the “manual search” mode for the period 2011–2024. Results. Informatization of key processes in primary healthcare in the capital has reduced the waiting time for patients to receive an appointment. The number of people waiting 4 days or more to see a therapist has dropped to 2 %. An AIDS based on artificial intelligence was introduced into the practice of primary care doctors, available in all adult clinics in Moscow. Telemedicine services were provided for patients with COVID-19, which were subsequently expanded to other categories of patients. Conclusion. A review of data related to the digitalization of healthcare shows that changes in the work of clinics of the Moscow public health system are best practices that correspond to the practices of leading foreign countries, partly surpassing them in the systematicity of urban management issues.

A cryo-electron tomography study of ciliary rootlet organization

Ciliary rootlets are striated bundles of filaments that connect the base of cilia to internal cellular structures. Rootlets are critical for the sensory and motile functions of cilia. However, the mechanisms underlying these functions remain unknown, in part due to a lack of structural information of rootlet organization. In this study, we obtain 3D reconstructions of membrane-associated and purified rootlets from mouse retina using cryo-electron tomography. We show that flexible protrusions on the rootlet surface, which emanate from the cross-striations, connect to intracellular membranes. In purified rootlets, the striations were classified into amorphous (A)-bands, associated with accumulations on the rootlet surface, and discrete (D)-bands corresponding to punctate lines of density that run through the rootlet. These striations connect a flexible network of longitudinal filaments. Subtomogram averaging suggests the filaments consist of two intertwined coiled coils. The rootlet’s filamentous architecture, with frequent membrane-connecting cross-striations, lends itself well for anchoring large membranes in the cell.

A cryo-electron tomography study of ciliary rootlet organization.

Ciliary rootlets are striated bundles of filaments that connect the base of cilia to internal cellular structures. Rootlets are critical for the sensory and motile functions of cilia. However, the mechanisms underlying these functions remain unknown, in part due to a lack of structural information of rootlet organization. In this study, we obtain 3D reconstructions of membrane-associated and purified rootlets from mouse retina using cryo-electron tomography. We show that flexible protrusions on the rootlet surface, which emanate from the cross-striations, connect to intracellular membranes. In purified rootlets, the striations were classified into amorphous (A)-bands, associated with accumulations on the rootlet surface, and discrete (D)-bands corresponding to punctate lines of density that run through the rootlet. These striations connect a flexible network of longitudinal filaments. Subtomogram averaging suggests the filaments consist of two intertwined coiled coils. The rootlet's filamentous architecture, with frequent membrane-connecting cross-striations, lends itself well for anchoring large membranes in the cell.

Structured clinical reasoning prompt enhances LLM's diagnostic capabilities in diagnosis please quiz cases.

Large Language Models (LLMs) show promise in medical diagnosis, but their performance varies with prompting. Recent studies suggest that modifying prompts may enhance diagnostic capabilities. This study aimed to test whether a prompting approach that aligns with general clinical reasoning methodology-specifically, using a standardized template to first organize clinical information into predefined categories (patient information, history, symptoms, examinations, etc.) before making diagnoses, instead of one-step processing-can enhance the LLM's medical diagnostic capabilities. Three hundred twenty two quiz questions from Radiology's Diagnosis Please cases (1998-2023) were used.We employed Claude 3.5 Sonnet, a state-of-the-art LLM, to compare three approaches: (1) Baseline: conventional zero-shot chain-of-thought prompt, (2) two-step approach: structured two-step approach: first, the LLM systematically organizes clinical information into two distinct categories (patient history and imaging findings), then separately analyzes this organized information to provide diagnoses, and (3) Summary-only approach: using only the LLM-generated summary for diagnoses. The two-step approach significantly outperformed the both baseline and summary-only approaches in diagnostic accuracy, as determined by McNemar's test. Primary diagnostic accuracy was 60.6% for the two-step approach, compared to 56.5% for baseline (p = 0.042) and 56.3% for summary-only (p = 0.035). For the top three diagnoses, accuracy was 70.5, 66.5, and 65.5% respectively (p = 0.005 for baseline, p = 0.008 for summary-only). No significant differences were observed between the baseline and summary-only approaches. Our results indicate that a structured clinical reasoning approach enhances LLM's diagnostic accuracy. This method shows potential as a valuable tool for deriving diagnoses from free-text clinical information. The approach aligns well with established clinical reasoning processes, suggesting its potential applicability in real-world clinical settings.

Valuation of medical services information in the efficient organization of public self-financing healthcare institutions

The efficient organization of public healthcare institutions is essential for ensuring a functional healthcare system that meets the needs of the population while also becoming financially sustainable. In the context of self-financing these institutions, the proper utilization of information related to medical services plays a crucial role in optimizing resources and enhancing performance. To achieve adequate self-financing, healthcare institutions must adopt effective strategies for managing the services they provide, based on precise and up-to-date information. This information may include data on the types of medical services provided, the number of patients, the costs associated with each type of service, as well as the assessment of the quality of care delivered. The article aims to explore the fundamental concepts, offering a correlation of relevant terms for a complete understanding of the healthcare system.

How Digital Twins Impact Responsiveness: A Dynamic Fit Approach to Information Processing for High-Involvement Product Demand Management

In an era of rapidly evolving customer demands and technological advancements, organisations face mounting pressure to enhance their responsiveness. Digital Twins offer novel capabilities by providing comprehensive transparency on customer demands through dynamic and interactive links between real-world entities and their digital counterparts. As a result, Digital Twins have the potential to enable organisations to respond more swiftly and effectively to fluctuating customer demands across volume, process, and product dimensions. However, Digital Twins still lack empirical explorations and theoretical embedment, leading to conceptual ambiguity. Through a case study approach, the study integrates Digital Twins into the framework of Organisational Information Processing Theory (OIPT). Empirical evidence proposes that Digital Twins offer a spectrum of capabilities rather than a one-size-fits-all solution. The findings further emphasise the need for aligning Digital Twin sophistication levels with Information Processing Needs and Constraints, highlighting that the dynamic interplay between Digital Twin advancements, Information Processing Constraints, and Information Processing Capabilities creates a dynamic cycle of adaptation and optimisation. On the whole, the study presents four key implications: (1) Awareness about the versatile application areas of Digital Twins is created. (2) The positive impact of Digital Twins on volume, process, and product responsiveness is outlined. (3) The concept of Information Processing Constraints is introduced to OIPT. And (4) a dynamic cycle of aligning Digital Twin sophistication with Information Processing Capabilities and Constraints is suggested. Therefore, the study contributes not only to a deeper understanding of Digital Twins in demand management but also proposes a new dynamic fit perspective on OIPT.

United We Stand, Divided We Fall: An Autogenic Perspective on Empowering Cybersecurity in Organizations

Cybersecurity groups navigate complex, challenging environments in their mission to protect their organizations. They experience uncertainty from adaptive threats from external attackers and unpredictable stakeholders. Under such volatility, business groups operate best when they are psychologically empowered. Recognizing the potential for empowerment to reduce organizational risk, we sought to learn how cybersecurity groups come to be (dis)empowered and how this (dis)empowerment is sustained. Instead of the conventional view of the empowerment process as designed, we advance an emergent view of the empowerment process. We abductively surface this process from our case analyses of 15 U.S. organizations. We offer three insights: First, organizations with empowered cybersecurity groups enjoy an enhanced level of protection from breaches. Second, we highlight generative rules through which groups become empowered—via their bridging initiatives that co-opt stakeholders into security behaviors and stakeholder responsiveness to bridging, rather than unilaterally applied buffering initiatives. Third, we highlight reinforcing rules through which empowered states persist—via the group’s ability to safeguard organizational information assets, thereby ensuring cybersecurity group viability, continued bridging, and motivated stakeholder responsiveness. For practitioners, our study underscores the interdependence between cybersecurity groups and their stakeholders in securing an organization and posits processes for empowering cybersecurity groups.

Aurel_AI: Automating an Institutional Help Desk Using an LLM Chatbot

The Aurel_AI research project was born from the need to implement a virtual help desk for a university, providing accurate organizational information to both internal and external clients. The information includes details about academic programs, regulations, processes, and personnel. Aurel_AI is part of a broader research program on the use of AI in academia. Traditional solutions for a help desk, such as telephone call centers, present quality and efficiency issues that are difficult to solve. Call center staff generally lack comprehensive knowledge about the institution, rely on specific information that is sometimes outdated, require additional systems for information retrieval, and experience high turnover rates. This leads to associated costs and issues related with outdated information, resulting in inaccurate responses and long waiting times. Generative artificial intelligence models, known as Large Language Models (LLMs), offer an interesting alternative for an automated virtual help desk. These models can understand even vague and poorly structured questions and generate reasonably appropriate answers. However, they are not without flaws, as they tend to present issues like "hallucinations" when the required information is not present in their training data. To minimize this problem, it is crucial to ensure that the model has precise and comprehensive information, which needs a specific methodology for information collection, validation, and updating. Base models require an adaptation process to be used for specific cases, for which techniques like Fine-Tuning and Retrieval Augmented Generation (RAG) exist. Fine-tuning retrains a model's weights with new specific information, while RAG uses both proprietary information—in this case, from the university—and publicly available internet data. Both techniques have pros and cons that need to be evaluated to select the most suitable option. They also demand appropriate and specialized infrastructure, which is often expensive. Thus, another challenge is to find a balance between suitable equipment and reasonable costs. The final system, from the user's perspective, must be accurate, flexible, and adaptable to deliver a satisfactory experience. As the results show, Aurel_AI represents an advance in the digitalization of educational services, standing out for its ability to generate accurate and personalized responses. However, its current limitations, such as handling concurrent queries and hallucinations, underscore the need for adjustments to both infrastructure and data processing methodology. With strategic improvements, the system has the potential to consolidate itself as a replicable model for multiple university digital services.

How Romantics and Victorians Organized Information: Commonplace Books, Scrapbooks, and Albums by Jillian M. Hess (review)

How Romantics and Victorians Organized Information: Commonplace Books, Scrapbooks, and Albums by Jillian M. Hess (review)

A Systematic Literature Review of Enterprise Architecture Evaluation Methods

Enterprise Architecture (EA) is a systematic and holistic approach to designing and managing an organization's information systems components, aiding in optimizing resources, managing risk, and facilitating change. It weighs different architectural quality attributes against each other to achieve the most advantageous architecture. However, the evaluation of EA lacks a systematic approach. This study employs a Systematic Literature Review, analyzing, in detail, 109 articles carefully selected from 3644 papers published since 2005. The key outcome of the research reveals that a crucial factor for the extensive worldwide adoption of EA evaluation methods lies in the automation of the assessment and architecture modeling processes, particularly emphasizing the facet of data collection. The automation of EA evaluation will empower organizations to streamline their processes, make data-driven decisions, and respond more effectively to change, ultimately contributing to their competitiveness and long-term success in the global market. The study identifies diverse evaluation methods, determines evaluation criteria, examines the extent to which these methods have been verified in practice, and provides directions for further research and advancement.

Examining the Effects of Industry 4.0 Adoption, Information Acquisition Capability, and Organizational Ambidexterity on Innovation and Circular Economy Performance

ABSTRACTRegulatory authorities are putting a lot of pressure on manufacturers to devise strategies to boost their contribution to the circular economy. The limited comprehension surrounding the complex interplay that exists between the deployment of Industry 4.0 (I4.0) strategies, the capability to acquire information, and the ability to balance exploration and exploitation activities within an organization acts as a barrier for manufacturers to attain the optimal levels of organizational performance. As a result, the purpose of the current investigation is to investigate the strategic execution of I4.0 on manufacturers' information acquisition capability in order to foster the ambidexterity required to flourish in the innovation‐driven high‐performance ecosystem for attaining circular economy performance. In this study, data from a cross‐sectional survey that included responses from a sample of 238 Indian manufacturers were assessed using structural equation modeling. According to the results, I4.0 technologies assist organizations in strengthening their exploitative and explorative capabilities, allowing them to achieve success in innovation, which is directly related to their performance in circular economy activities. Unexpectedly, the association between an organization's information acquisition capability and its innovation performance is not substantial, but it is completely mediated by both exploitative and explorative capabilities, which are characterized as organizational ambidexterity.