Multidimensional Nature Research Articles

Digital Transformation: The Strategic Integration of Technology in Modern Business

Digital transformation transcends mere technological implementation to fundamentally reshape how organizations operate, compete, and deliver value in today's market landscape. This article explores the multidimensional nature of transformation across business processes, business models, and organizational culture, highlighting how these dimensions must evolve simultaneously to achieve meaningful results. The strategic benefits of transformation span from enhanced decision-making capabilities and operational excellence to improved customer experiences and business model innovation. Organizations successfully navigating this journey recognize that technology and culture are deeply interdependent, requiring integrated approaches that address both human and technical elements. The evidence demonstrates that organizations effectively integrating digital capabilities with cultural adaptation achieve superior performance across profit margins, operational efficiency, talent attraction, and market responsiveness, positioning themselves advantageously in increasingly complex digital ecosystems

Systemic Risk Management and Stakeholder Engagement: Insights From Business CSR Disclosure

ABSTRACTThis study investigates corporate strategies for integrating non‐financial risks and stakeholder engagement into business management frameworks. Our inquiry analyzes the extent to which companies explicitly or implicitly incorporate stakeholder perspectives into their risk management practices. Based on the four fundamental pillars of risk management outlined by the Institute of Risk Management (IRM 2002), this study seeks to elucidate the multidimensional and comprehensive nature of stakeholder engagement in risk management processes. This study is based on a content analysis of 253 sustainability reports and Non‐Financial Statements drawn from different categories of companies representing the Italian market: large companies, small and medium‐sized enterprises (SMEs), cooperatives, and public utilities. The results reveal that companies primarily address risk management and control in their reports, aligning with the literature. Although risk components are equally important in managing adverse events, the results show a high percentage of risk analysis unlike what emerged from the literature, and a smaller percentage of companies focused on risk monitoring and risk communication. Stakeholder engagement levels vary based on company type and the activities performed in the risk governance process. From a theoretical perspective, this study contributes to systemic risk management research by integrating stakeholders into risk governance models. From a managerial perspective, this study offers implications for both risk management and sustainability disclosure practices. Limitations include the sample of Italian companies only and the different publication years of the collected reports.

"Healthy Relationships": A Scoping Review of Definitions, Components, and Measures of Healthy Dating Relationships Among Teens and Young Adults.

Healthy relationships (HR) education has been widely adopted as an alternative or complement to dating abuse prevention education among youth and young adults. This scoping review evaluated the literature on HR among young people to identify definitions, components, and measures of HR. Both academic, peer-reviewed articles and gray literature were included and documents meeting a priori inclusion criteria were screened for: focus on healthy romantic or intimate relationships; published in English; scholarly publication; published between 2005 and 2021; focus on teens or young adults; and including a definition, components, or measures of HR. A total of 964 non-duplicated documents were identified. After full-text screening and data extraction, 69 articles were included in the review. Definitions, components, and measures of HR varied greatly between documents. While most included documents provided components of HR, only 17 articles included definitions of HR. These definitions largely focused on the components of HR, though some also discussed the nature of HR. In total, 223 components of HR were identified from the included documents, which this analysis distills into 12 categories. In addition, 47 measures were used to measure HR, and measures are rarely repeated across documents, indicating a need to increase consistency in conceptualization and measurement. HR has been implicitly defined by a set of components rather than through the use of theory. To develop standards for HR education, a consistent framework should be identified that includes the multidimensional nature of HR and can be consistently measured.

Development and Validation of the Comprehensive Acute Pancreatitis Pain Core Outcome Set (CAPPOS): Study Protocol.

Acute pancreatitis (AP) is a leading cause of gastrointestinal hospitalizations worldwide, with rising incidence, significant morbidity, and high healthcare costs. Pain, a hallmark symptom of AP, remains inadequately assessed, often relying on unidimensional scales such as visual analogue score, which fail to capture its multidimensional nature. Poorly managed acute pain negatively impacts clinical outcomes, prolongs recovery, and increases the risk of chronic pain syndromes. Comprehensive pain assessment tools specific to AP are lacking, highlighting the need for improved evaluation methods. The proposed study aims to develop and validate the Comprehensive Acute Pancreatitis Pain Outcome Set (CAPPOS) to address this evidence gap. The CAPPOS initiative follows COMET and COSMIN guidelines. Three systematic reviews will identify pain domains and assessment methods in AP, acute abdominal pain, and post-pancrectomy pain. A consensus process, using a modified Delphi approach, will involve multidisciplinary experts and patients to confirm and define key domains. Measurement tools will be selected for each domain and refined through iterative feedback. Pilot testing with 50 patients will evaluate the feasibility, clarity, and responsiveness to change of the preliminary tool. Validation studies with 200 AP patients will assess structural, content, and criterion validity, reliability, and sensitivity to change, ensuring content validity and clinical utility. CAPPOS will provide a validated, multidimensional core outcome set to optimize pain assessment in AP. It will also facilitate standardized reporting in clinical trials, advancing research and care for AP-related pain.

A multi-dimensional data integration approach for machining system multi-level energy consumption modeling and prediction

ABSTRACT Multi-level energy consumption modeling and prediction (MECMP) of machining systems is crucial for refined energy management (REM). Due to the complexity of the coupling relationship between system levels (equipment, part and process) and corresponding energy influencing factors, it is difficult to select appropriate data for MECMP. Moreover, the multi-dimensional nature of the influencing factors also poses a challenge to integrate them for energy consumption modeling. To fill these gaps, this paper proposes a multi-dimensional data integration (MDDI) approach for MECMP. First, the associated influencing factors are identified by analyzing the energy consumption nature of machining systems, and a data cube model is established to facilitate efficient MDDI. Second, energy consumption models at three levels are developed to establish the correlation between energy consumption and multi-dimensional data. Then, a convolutional neural network with long short-term memory (CNN-LSTM) model is designed for energy consumption prediction. Finally, a milling case is exploited to verify the effectiveness of the proposed method. The results show that the proposed model achieves 99% accuracy in multi-level energy consumption prediction, and MDDI improves the accuracy by 7–8% compared to single dimension data. Furthermore, CNN-LSTM model outperforms the benchmark model in prediction accuracy and response time, thereby supporting REM implementation and promoting sustainable manufacturing.

Enhancing Person-Centred Care in Suicide Prevention: A Nursing Perspective.

Suicide prevention within nursing has historically been dominated by biomedical models that emphasize risk assessment and symptom management. While these frameworks offer structure and liability reduction, they often fail to capture the deeply personal and existential dimensions of suicidality. The reliance on predictive tools with modest accuracy, such as the Columbia-Suicide Severity Rating Scale (C-SSRS), has led to a gap between assessment and meaningful intervention. Critics argue that this model fosters a procedural approach that discourages patient disclosure and limits therapeutic engagement. In contrast, person-centered care (PCC) emphasizes relational trust, individualized understanding, and the integration of patient narratives into clinical decision-making. This paper examines the need to shift from standardized, symptom-focused approaches toward a dynamic, patient-centered framework. This paper critically evaluates the limitations of biomedical suicide prevention strategies by synthesizing theoretical contributions from key suicidologists, including Edwin Shneidman, Antoon Leenaars, Konrad Michel, Igor Galynker, and David Jobes. Evidence-based, person-centered models such as the Collaborative Assessment and Management of Suicide (CAMS) and the Narrative Crisis Model (NCM) are explored in contrast to traditional suicide risk assessments. Additionally, barriers to implementing PCC in nursing-such as time constraints, administrative demands, and gaps in professional training-are examined. While biomedical models provide standardized risk management strategies, their over-reliance on quantifiable indicators fails to address suicidality's multidimensional nature. The predictive limitations of suicide screening tools often lead to overestimation or underestimation of risk, increasing the likelihood of missed intervention opportunities. Furthermore, systemic factors such as high-acuity environments and compassion fatigue contribute to nurses' challenges in engaging with person-centered interventions. Models like CAMS and NCM have demonstrated greater efficacy in fostering trust, enhancing clinical engagement, and addressing the subjective experiences of suicidal individuals, ultimately improving outcomes. The limitations of traditional biomedical approaches underscore the necessity of integrating person-centered care into nursing practice. Suicide prevention should not be dictated solely by standardized risk assessments but should instead prioritize therapeutic alliance, empathy, and the co-construction of meaning. Nurses, given their frontline role in patient care, are uniquely positioned to transform suicide prevention through narrative-based interventions and compassionate engagement. However, achieving this paradigm shift requires institutional support, expanded nursing education, and systemic recognition of the importance of relational care. This paper advocates for a holistic approach that moves beyond risk prediction toward meaningful, person-centered interventions that address the lived experiences and psychological distress of individuals at risk for suicide.

Stages prediction of Alzheimer’s disease with shallow 2D and 3D CNNs from intelligently selected neuroimaging data

Detection of Alzheimer’s Disease (AD) is critical for successful diagnosis and treatment, involving the common practice of screening for Mild Cognitive Impairment (MCI). However, the progressive nature of AD makes it challenging to identify its causal factors. Modern diagnostic workflows for AD use cognitive tests, neurological examinations, and biomarker-based methods, e.g., cerebrospinal fluid (CSF) analysis and positron emission tomography (PET) imaging. While these methods are effective, non-invasive imaging techniques like Magnetic Resonance Imaging (MRI) are gaining importance. Deep Learning (DL) approaches for evaluating alterations in brain structure have focused on combining MRI and Convolutional Neural Networks (CNNs) within the spatial architecture of DL. This combination has garnered significant research interest due to its remarkable effectiveness in automating feature extraction across various multilayer perceptron models. Despite this, MRI’s noisy and multidimensional nature requires an intelligent preprocessing pipeline for effective disease prediction. Our study aims to detect different stages of AD from the multidimensional neuroimaging data obtained through MRI scans using 2D and 3D CNN architectures. The proposed preprocessing pipeline comprises skull stripping, spatial normalization, and smoothing. It is followed by a novel and efficient pixel count-based frame selection and cropping approach, which renders a notable dimension reduction. Furthermore, the learnable resizer method is applied to enhance the image quality while resizing the data. Finally, the proposed shallow 2D and 3D CNN architectures extract spatio-temporal attributes from the segmented MRI data. Furthermore, we merged both the CNNs for further comparative analysis. Notably, 2D CNN achieved a maximum accuracy of 93%, while 3D CNN reported the highest accuracy of 96.5%.

An experiential perspective on uncertainty in peer-to-peer platform services

PurposeThe rapid growth of digital peer-to-peer (P2P) platforms has contributed to increased circular consumption characterized by high consumer uncertainty, which in turn affects consumer attitudes and behaviors. However, research has addressed uncertainty in platform services through a narrow conceptualization that neglects its experiential nature. Thus, this study develops an experiential perspective on uncertainty in platform services.Design/methodology/approachThe authors collected data on consumers’ experiences with P2P platform services through focus groups and in-depth interviews. The data were interpreted by applying customer experience as a conceptual lens, following the principles of enabled theorizing and systematic combining.FindingsThe study conceptualizes “uncertainty” in P2P platforms through an experiential perspective, shedding light on its multidimensional and experiential nature, the diverse stimuli that trigger the uncertainty experience, and consumer’s strategies to manage it.Originality/valueThis research contributes to the literature on platform services and customer experience by offering an alternative experiential perspective to conceptualize uncertainty in P2P platforms, thus shedding light on several unaddressed aspects of this phenomenon.

Measurement Scale of Climate Finance: Development and Validation.

Climate finance is pivotal in addressing climate change, enabling countries and organizations to transition to low-carbon and climate-resilient development pathways. Despite its importance, measuring climate finance remains a challenge due to the multidimensional nature of the concept. This study aims to develop and validate a measurement scale for climate finance by identifying key dimensions, generating item statements, and conducting factor analysis to assess the scale’s reliability and validity. Key Words: Climate finance, measurement scale, sustainability, environmental finance, factor analysis.

Harmonizing Diversity: Insights from Zhuangzi’s Concept of Zhi 知

Zhuangzi articulates a framework for harmonizing diversity in both thought and practice. An in-depth analysis of the concept of zhi 知 is essential for understanding Zhuangzi’s perspective on achieving harmony concerning the diverse and ever-changing nature of existence. Previous studies on Zhuangzi either label his philosophy as anti-intellectual or fail to sufficiently examine the multi-dimensional nature of zhi as presented in his writings. This article identifies a hierarchical framework of knowledge in the Zhuangzi, including xinzhi 心知 (conscious knowing), xiaozhi 小知 (lesser knowledge), dazhi 大知 (greater knowledge), and zhenzhi 真知 (true knowledge), and discusses its implications for both inner and external harmony. It illustrates Zhuangzi’s critique of conventional forms of knowledge, which often create rigid divisions. The study reveals how practices such as xinzhai 心齋 (fasting of the heart-mind) lead from limited understanding toward zhenzhi, culminating in the realization of zhenren, who lives in accordance with dao. The analysis of various levels of knowing illuminates Zhuangzi’s approach to transcending conventional epistemology while proposing methods to embrace diverse perspectives and achieve better harmony in existence.

How Does Digital Capability Shape Resilient Supply Chains?—Evidence from China’s Electric Vehicle Manufacturing Industry

In recent years, the rapid advancement of digital technologies and the growing demand for sustainability have driven unprecedented transformations in the automotive industry, particularly toward electric vehicles (EVs) and renewable energy. The EV supply chain, a complex global network, has become increasingly vulnerable to globalization and frequent “black swan” events. The purpose of this study, grounded in organizational information processing theory, aims to systematically examine the role of digital capability in strengthening supply chain resilience (SCR) through improved risk management effectiveness. Specifically, it explores the multidimensional nature of digital capability, clarifies its distinct impact on SCR, and addresses existing research gaps in this domain. To achieve this, this study develops a theoretical framework and validates it using survey data collected from 249 EV supply chain enterprises in China. Partial Least Squares Structural Equation Modeling (PLS-SEM) is employed to empirically test the proposed relationships. The findings provide valuable theoretical insights and actionable guidance for EV manufacturers seeking to leverage digital transformation to mitigate risks effectively and enhance supply chain resilience. However, as the study focuses on Chinese EV supply chain enterprises, caution is needed when generalizing the findings to other regions. Future research could extend this investigation to different markets, such as to Europe and the United States, to explore potential variations.

Understanding AI-enabled conversational agent customer experiences in religious tourism

Purpose The purpose of this paper is to investigate the impact of artificial intelligence (AI)-enabled Conversational Agents (AICAs) on religious tourists’ experiences. It explores how AICA attributes influence religious tourists’ cognitive and affective states and how these evaluations, in turn, affect their memorable religious tourism experiences (MRTEs) and continuous use intentions of AICAs. Design/methodology/approach Drawing on the stimulus-organism-response model and the Technology Readiness Index, the authors propose a new theoretical framework to examine the relationships among AICA attributes (stimuli), religious tourists’ cognitive and affective evaluations (organism), and their behavioral responses (MRTEs and continuous use intentions). The model is conceptual, with relationships supported through a comprehensive literature review. Findings The model posits that AICA attributes, such as informativeness, accessibility, empathy and personalization, shape religious tourists’ cognitive and affective evaluations of AICAs. These evaluations impact tourists’ MRTEs, influencing their willingness to continue using AICAs in future religious tourism experiences. Additionally, religious tourists’ technology readiness is posited to moderate the relationship between AICA attributes and their cognitive and affective evaluations. Recommendations are made on how future research can be conducted to investigate and test the proposed conceptual model. Originality/value This paper enhances the literature on AI in tourism by examining AICAs’ influence on religious tourism experiences and exploring the multidimensional nature of AICA adoption. The proposed conceptual model provides a foundation for future empirical research. It offers insights for tourism operators and service providers, guiding the strategic use of AICAs to enhance MRTEs while respecting the sacred nature of spiritual journeys. These insights can inform the development of more effective and culturally sensitive AI-driven solutions in religious tourism contexts.

Multidimensional Perspective of Sustainable Agroecosystems and the Impact on Crop Production: A Review

Agroecosystems form a natural ecosystem component, allowing the proper classification of a regional biome at a global scale. It is important to view agroecosystems from a micro-environmental perspective given that they are characterised by a combination of factors, including the interaction of soil–plant–atmosphere conditions, which are largely responsive to human management practices. The published literature generally provides a limited explanation of the multidimensional nature of agroecosystems. In combination, agroecosystem practices promote efficient water use and nutrient cycling in defence of regenerative agriculture ethos. Sustainable agroecosystem practices can be combined to explain how to mitigate the risks to biodiversity. This study aims to present a review of predominant advances in sustainable crop production from the perspective of the agroecosystem. A hybrid methodology of data mining and interpretation was used to establish the meaning and relationships of the major research areas that have emerged over time and dominate the narrative of sustainable agroecosystem definition and practices. Crop diversification, sustainable soil management, integrated pest management, sustainable water resource management, and precision agriculture were selected using document summarisation and entity relation modelling to generate and explain relationships between various components of sustainable agroecosystems based on the existing literature. A major finding is the confirmation of comparable applications in different regions, whose explanation is enhanced by recent advances in data summation. This review concludes that sustainable agroecosystems are separable in meaning and impact. However, it is reasonable to recommend the need for future research into their integration for implementation and interpretation.

Improving the methods for managing the operational dependability of distributed energy facilities

Improving the management of the technical state of equipment, devices, and installations, whose service life exceeds the respective standard value, is a most important problem of national security, as their proportion already exceeds 60%. The paper presents the findings of an analysis of literature data in the respective subject area that confirms its relevance and significance. Importantly, the findings apply not only to electrical power systems, but to many other industrial systems as well. The primary difficulties associated with solving the problem at hand are, first and foremost, the small quantity of statistical data that characterise operational dependability, their multidimensional and random nature. The authors suggest solving the problem by abandoning average annual dependability indicators in favour of average monthly operational dependability indicators. The authors provide a brief description of the individual solutions as part of the overall problem as regards overhead power lines that together represent a new methodology for managing the technical state of distributed facilities. The research-intensive, cumbersome, and time-consuming calculation algorithms suggest employing intelligent systems. The management of the electrical power system and its individual business units is to receive monthly specialised forms with recommendations as to the ways of improving the dependability of overhead power lines by restoring wear and tear.

Correlations of pilot trainees' brainwave dynamics with subjective performance evaluations: insights from EEG microstate analysis.

This study aims to investigate the relationship between the subjective performance evaluations on pilot trainees' aircraft control abilities and their brainwave dynamics reflected in the results from EEG microstate analysis. Specifically, we seek to identify correlations between distinct microstate patterns and each dimension included in the subjective flight control evaluations, shedding light on the neurophysiological mechanisms underlying aviation expertise and possible directions for future improvements in pilot training. Proficiency in aircraft control is crucial for aviation safety and modern aviation where pilots need to maneuver aircraft through an array of situations, ranging from routine takeoffs and landings to complex weather conditions and emergencies. However, the neurophysiological aspects of aviation expertise remain largely unexplored. This research bridges the gap by examining the relationship between pilot trainees' specific brainwave patterns and their subjective evaluations of flight control levels, offering insights into the cognitive underpinnings of pilot skill efficiency and development. EEG microstate analysis was employed to examine the brainwave dynamics of pilot trainees while they performed aircraft control tasks under a flight simulator-based pilot training process. Trainees' control performance was evaluated by experienced instructors across five dimensions and their EEG data were analyzed to investigate the associations between the parameters of specific microstates with successful aircraft control. The experimental results revealed significant associations between aircraft control levels and the parameters of distinct EEG microstates. Notably, these associations varied across control dimensions, highlighting the multifaceted nature of control proficiency. Noteworthy correlations included positive correlations between microstate class E and class G with aircraft control, emphasizing the role of attentional processes, perceptual integration, working memory, cognitive flexibility, decision-making, and executive control in aviation expertise. Conversely, negative correlations between microstate class C and class F with aircraft control indicated links between pilot trainees' cognitive control and their control performance on flight tasks. The findings underscore the multidimensional nature of aircraft control proficiency and emphasize the significance of attentional and cognitive processes in achieving aviation expertise. These neurophysiological markers offer a basis for designing targeted pilot training programs and interventions to enhance trainees' aircraft control skills.

Who attends a free sexual health center in Paris for HIV/STI screening? an observational study.

A key-population approach to sexually transmitted disease prevention does not fully take into account the multidimensional nature of sexual risk behavior. Visits to sexual health centers for HIV/STI screening provide an opportunity to spread prevention messages and tools, but few data are available on patients' sexual and prevention behaviors. This study aimed to identify the profile of patients consulting for HIV/STI testing in a Parisian sexual health center. This observational study included 5,130 patients who attended the center for HIV/STI testing from August 2017 through January 2020 and completed a self-administered electronic questionnaire. Data were obtained from the consultation database and the questionnaire. The data included STI results, sociodemographic characteristics, sexual and prevention behaviors, as well as HIV knowledge. To identify homogeneous groups of patients regarding sexual risky behavior, we conducted a mixed approach including both a priori classification and agglomerative hierarchical clustering (AHC) based on multiple correspondence analysis (MCA). Sexual behaviors and substance use were included in the MCA. Median age of patients was 26 years [Q1-Q3:23-32]. Seven clusters of patients were identified. Two clusters had a high HIV/STI positivity rate (15-19%) with very different profiles: cluster 1 included socially disadvantaged patients who had no health insurance and cluster 5 included 89% of men who have sex with men. Two clusters had an HIV/STI positivity rate corresponding to that observed in the overall study population (10-11%) but exhibited risky behaviors (cluster 7 with a high frequency of unprotected sexual intercourse, substance use, cannabis use and weekly binge drinking) or lack of knowledge on HIV (cluster 6 including 100% of patients having transactional sex). The multidimensional approach demonstrated that both key populations and lower-risk populations visit a sexual health center. While several groups could benefit from tailored interventions, knowledge of HIV and its treatment should be enhanced for every patient visiting a sexual health center. To provide a complete offer in sexual health, patients' profiles and expectations need to be taken into account.

Impulsivity: A Transdiagnostic Approach to Understanding Adolescent Substance Use

Background: Impulsivity, characterized by the tendency to act on impulse without consideration for consequences, has been implicated in health disorders such as problematic substance use among adolescents. Understanding impulsivity's nature, clinical manifestations, quantification, and management in a clinical context could help address underlying disorders. Methods: We reviewed previous studies where different impulsivity dimensions were identified and explored the manifestations of impulsivity across conditions characterized by high impulsivity. Similarly, we pursued a literature search on various factors influencing impulsivity, methods employed to quantify them, and commonly used treatments for impulsivity control. Results: The multidimensional and transdiagnostic nature of impulsivity was acknowledged across several studies. Various health disorders such as substance use disorders, borderline personality disorder, and attention-deficit/hyperactivity disorder implicated impulsivity, even among the adolescent groups. We identified biological, psychological, and environmental factors influencing impulsivity. We also present the commonly employed approaches to quantifying impulsivity and new measurement approaches under active investigation that are relevant in characterizing impulsivity in adolescents. Treatment options to manage impulsivity were also reviewed and are presented in this work. Conclusion: This work offers a comprehensive understanding of impulsivity as one of the underlying factors in adolescent substance use and related health disorders, emphasizing factors affecting impulsivity, approaches for measurement, and implications of high impulsivity on mental health and behaviors.

Oscillating Mindfully: Using Machine Learning to Characterize Systems-Level Electrophysiological Activity During Focused Attention Meditation

Oscillating Mindfully: Using Machine Learning to Characterize Systems-Level Electrophysiological Activity During Focused Attention Meditation

Care, Control and Calories: A Genealogy of Measuring International Undernutrition

This article documents the historical development of the calory and its application in international measurement of undernutrition. It provides an empirical account of the origins of caloric measurement as a scientific instrument, its uptake into international statistics on undernutrition produced by the League of Nations and the United Nations, and eventual use in monitoring global development goals. The historical analysis explores and discusses how a dialectic of care and control is embedded in macrosocial measurement of hunger: Caloric statistics have served as a condition of possibility for states and international agencies to render food systems governable through constituting a novel form of legibility that pushed the frontiers for modern schemes of top-down intervention and control. Such measurements have furthermore served as a vital resource to legitimize and justify the ambitions of the UN and modern development agenda, serving to establish and shape grand narratives of humanity’s progress under different food regimes. Based on this historical analysis, the article provides a normative and epistemic argument for centring the perspectives and knowledges of those affected by hunger in the enumeration of nutrition and food security. Such democratic agency should however not just be an object of measurement but be leveraged through participatory methodologies that draw upon the voices of the food insecure to better capture the multidimensional nature of food security through numbers.

Burden in caregivers of adults with epilepsy: A critical review.

Burden in caregivers of adults with epilepsy: A critical review.