Core Dimensions Research Articles

Leveraging Six Values for Company Performance: Adaptation of Sustainable Business Model Innovation Strategies in Chinese Electric Vehicle Brand Enterprises

Business model innovation is crucial for enhancing company performance. This study aims to investigate the relationship between the six dimensions of sustainable business model innovation and company performance among Chinese electric vehicle brands. A structural equation model is constructed based on a comprehensive literature review and hypothesis development. Using PLS-SEM, this study empirically analyzes questionnaire data collected from the top 12 electric vehicle brands in China to explore the relationship between these six core dimensions and company performance. The results indicate that innovation in “value proposition to customers”, value creation, value delivery, and “value of residual” have a significantly positive impact on the performance of Chinese electric vehicle brands. However, value capture innovation and “value of after-sales service” innovation were not found to be statistically significant. This paper provides an in-depth analysis of the mechanism through which sustainable business model innovation impacts company performance, enriching the theoretical foundation of academic research in this field and broadening its practical applications in management.

Procedural fairness in algorithmic decision-making: the role of public engagement

AbstractDespite the widespread use of automated decision-making (ADM) systems, they are often developed without involving the public or those directly affected, leading to concerns about systematic biases that may perpetuate structural injustices. Existing formal fairness approaches primarily focus on statistical outcomes across demographic groups or individual fairness, yet these methods reveal ambiguities and limitations in addressing fairness comprehensively. This paper argues for a holistic approach to algorithmic fairness that integrates procedural fairness, considering both decision-making processes and their outcomes. Procedural fairness emphasizes the importance of fair decision-making procedures, which aligns with theories of relational justice that stress the quality of social relations and power dynamics. We highlight the need for substantive procedural fairness to ensure better outcomes and address forward-looking responsibilities. Additionally, we propose leveraging Public Engagement, a core dimension within the well-established Responsible Research and Innovation framework, to enhance procedural fairness in ADM systems. Our contribution underscores the value of Public Engagement in fostering fairer ADM processes, thereby expanding the current focus beyond technical outcome-based approaches to encompass broader procedural considerations.

The change process questionnaire (CPQ): A psychometric validation.

Tracking therapeutic processes and outcomes session to session, known as feedback-informed treatment (FIT), has shown many significant benefits for systemic family therapists. However, more clinically useful FIT measures are needed in our field. In response, we conceptualize core dimensions of the therapeutic change process and propose a measure-the Change Process Questionnaire (CPQ)-based on some of those dimensions to provide a clinically useful FIT measure. Developed as a 25-item measure, this study evaluated the measure's psychometric properties, resulting in a refined version with 18 items organized into four subscales (client relationships, client well-being, therapist regard, and therapeutic effect) that demonstrate some alignment with core dimensions of the change process. In this article, we provide a preliminary overview of the CPQ's psychometric validity and potential to contribute to the therapeutic change process and its accompanying scholarly literature.

Genuine small talk, rapport, and negotiation outcomes in B2B relationship

Purpose Small talk is often regarded as important in business interactions, yet the effect of genuine engagement on B2B communication remains underexplored. Hence, the purpose of this study is to explore the concept of genuine small talk, contextualize its key dimensions and examine how it contributes to building rapport and mediates negotiation outcomes in B2B relationships. Design/methodology/approach This study uses a qualitative abductive research approach for this exploratory investigation as it allows for an in-depth examination of the complex relational dynamics inherent in B2B communication. Data were collected through semistructured interviews with 35 industry professionals from diverse sectors, ensuring a diverse understanding of the phenomenon across different B2B contexts. Findings The study identifies eight core dimensions of genuine small talk in B2B interactions: empathy, curiosity, adaptability, active listening, a nonjudgmental disposition, respect for boundaries, positivity and humility. These dimensions collectively contribute to the development of rapport. The findings also highlight that rapport, fostered through genuine small talk, plays a mediating role in achieving favorable negotiation outcomes. Originality/value This study adds to the B2B marketing literature by advancing the understanding of genuine small talk and its strategic importance in building rapport and improving negotiation outcomes.

Phenomenology of Mystical Psychedelic Experiences: The Case of Existential Anxiety

AbstractThe essay offers an interpretation of psychedelic peak experiences. It criticizes the quasi-scientific naturalistic attempts to explain such experiences and offers an alternative ontology underlying a more complex sense of naturalism, thus defending an entheogenic view irreducible to mere psychological effects. First, the mainstream ontology in the paradigm of natural sciences is exposed as being a version of the ontology of presence. This fact is shown as the reason for the phenomenological gap and the impotence of the natural sciences to address human experience. Next, existential anxiety is interpreted in terms of Heidegger’s ontology and is suggested as the core dimension of possible spiritual transformation. Finally, the phenomenology of mystical psychedelic experiences (MPE) is interpreted in terms of overcoming existential anxiety– a well-documented effect of MPE – and explicated in ontological terms. The psychedelic experience is shown to be mystical in a sense of transcending the everyday mode of existential denial of the enigmatic nature of the universe by facing the nothingness in a way that transforms one’s stand within it into a stand of original belongingness to the field of emptiness (Nishitani). Different aspects of psychedelic experience are explained and co-related in terms of such a transformation.

Pioneering the Game: Visionary Leadership in Higher Education Athletics and Athletes’ Sport Engagement

This study investigates the correlation between visionary leadership practices and athletes' engagement in higher education sports, focusing on five core dimensions: Inspiring Vision, Strategic Thinking, Innovation and Creativity, Team Empowerment, and Adaptability and Resilience. Data were collected from athletes participating in various sports at five universities in China. Results indicate that athletes positively evaluated visionary leadership across all dimensions, with "Inspiring Vision" receiving the highest ratings. Engagement in sports was found to be highly correlated with strong leadership practices, particularly in areas like Clear Vision, Individualized Development, and Coach-Athlete Relationships. No significant differences in leadership evaluations were found when considering demographic variables like sex and academic program. This research underscores the importance of visionary leadership in enhancing student-athletes' involvement and success in higher education athletics.

Harm avoidance and incompleteness core motivations in obsessive-compulsive disorder: validation of the Farsi version of the Obsessive-Compulsive Trait Core Dimensions Questionnaire (F-OC-TCDQ) in Iran

BackgroundAttention to the heterogeneous manifestations of obsessive-compulsive symptoms observed in clinical and nonclinical populations has motivated researchers to use tools to identify homogeneous subgroups of obsessive-compulsive disorder (OCD) patients. The Obsessive-Compulsive Trait Core Dimensions Questionnaire (OC-TCDQ) is used to evaluate two motivational dimensions of OCD (harm avoidance (HA) and incompleteness (INC)), which has been developed in recent years based on the core dimensions model, and to classify homogeneous subgroups. This study aimed to validate the Farsi version of the OC-TCDQ in Iran.MethodsThe psychometric properties of the OC-TCDQ were tested in two clinical samples (209 patients with OCD) and nonclinical samples (209 participants without OCD). Confirmatory factor analysis (CFA) was conducted to test the two-factor structure. The measurement invariance between the clinical and nonclinical groups was evaluated. Reliability was tested using Cronbach’s alpha, split-half, and retesting (two-week intervals). Convergent and divergent validity were analysed with Pearson’s correlation and the incremental validity of this scale in predicting Yale-Brown Obsession Scale (Y-BOCS) and Beck Anxiety Inventory (BAI) scores using hierarchical regression analysis. The discriminant validity of the two clinical and nonclinical groups was investigated with a t-test.ResultsSimilar to the original version, the CFA showed a good fit for the two-factor structure. The invariance of measurement between samples, good internal consistency and retest reliability, and convergent and divergent validity of this scale were confirmed. The results of hierarchical regression analysis indicated the increasing validity of this scale in predicting the Y-BOCS and BAI compared to the OBQ-44 (p < 0.05), and comparing the scores of two groups with and without OCD indicated its discriminant validity (p < 0.01).ConclusionThese findings show that the Farsi-OC-TCDQ is a valid tool for evaluating the motivational dimensions of harm avoidance and incompleteness in Iranian individuals with and without OCD, and it allows us to compare the scores across groups.

Watt’s fair in Mumbai: intermediaries’ impact on energy justice in informal settlements

Abstract India’s ongoing energy transitions are a systemic response to addressing critical challenges associated with climate change. Importantly, it leverages decarbonization as a strategic pivot to simultaneously mitigate and adapt to climate risks. The decarbonization agenda is largely skewed towards mitigation, struggling with adaptation alignments. Energy justice is a core dimension of adaptation intervention and it is important to explore how energy justice is or can be conceptualized and delivered as the decarbonization agenda is underway. Existing research suggests that, in the cities of the Global South, active involvement of intermediaries becomes a pivotal anchor and pathway to access infrastructure services, especially in low-income and informal settlements. Importantly, advocacy efforts by intermediaries also tackle existing injustices that restrict these settlements from accessing essential infrastructure services. Intermediaries become especially important in cities like Mumbai, where 41% of the people live in informal settlements (slums). Using Mumbai as a case study, this paper explores two questions in the context of intermediaries, energy access, and energy justice. First, how do intermediaries engage with infrastructure and governance structures to enable access to electricity in informal settlements? Second, does this ‘intermediation’ deliver just outcomes? Empirical fieldwork reveals that intermediaries serve as a quasi-political counterbalance by engaging in ‘politics from the bottom’ to articulate justice concerns, mobilize stakeholders, and produce knowledge that feeds back into the intermediation process. We argue that this is important if we need to ensure that energy transitions do not create systemic inequities and that the benefits of the ongoing transition are widespread and just.

Deriving the PedsUtil health state classification system to measure health utilities for pediatric populations based on the PedsQL: a confirmatory factor analysis.

An important methodological challenge in conducting pediatric economic evaluations is estimating the preference-based health-related quality of life (HRQoL) of children. Current methods are highly variable and there is no single instrument available to value HRQoL consistently across multiple pediatric age groups. The Pediatric Quality of Life Inventory (PedsQL) is a non-preference-based generic HRQoL instrument validated for children 2-18 years, but it cannot be directly used in economic evaluations. The aim of this study was to establish the core dimension structure of the PedsUtil health state classification system using confirmatory factor analysis, which is the first step of deriving a preference-based measure of HRQoL based on the PedsQL. Four competing dimension structures of the PedsUtil health state classification system were developed based on published literature and expert opinion. Using data from the Longitudinal Study of Australian Children (LSAC) (n = 45,207), the 4 dimension structures were evaluated using the robust weighted least squares estimation method. The analyses were stratified by 2-year age intervals (from 2 to 17 years) to reflect the study design of the LSAC, as well as special healthcare needs status of the child. Model fit was evaluated by examining standardized factor loadings and various fit indices including the comparative fit index (CFI), Tucker-Lewis Index (TLI), and the root mean square error of approximation (RMSEA). Modification indices and residual correlations were examined to re-specify the models to improve model fit when necessary. The findings supported a 7-dimension structure (i.e., Physical Functioning, Pain, Fatigue, Emotional Functioning, Social Functioning, School Functioning, and School Absence) of the PedsUtil health state classification system. The 7-dimension model exhibited adequate fit across subgroups with CFI values that ranged from 0.929 to 0.954, TLI values from 0.916 to 0.946, and RMSEA values from 0.058 to 0.102. This study established the core dimension structure of the PedsUtil health state classification system using confirmatory factor analysis. The 7-dimension structure was found to be applicable across diverse pediatric populations. Research is currently ongoing to select the most representative item within each dimension of the PedsUtil health state classification system and valuation surveys will be fielded to estimate the PedsUtil scoring system.

The impact of trauma core dimensions on anxiety and depression: a latent regression model through the Post-Traumatic Symptom Questionnaire (PTSQ)

Adverse life events (e.g., severe accidents, violence/abuse, organic disorders) can elicit traumatic responses characterized by intrusive thoughts, hyperarousal, and avoidance—highlighting the need for sound assessment tools. Also, these traumatic components could heighten anxiety and depression symptoms. This study aims included to: (1) assessing the psychometric properties of the Post-Traumatic Symptom Questionnaire (PTSQ) and delineating clinical cut-offs; (2) investigating how distinct trauma components contribute to anxiety and depression symptoms. Involving 761 participants who experienced a traumatic event, Part I tested the PTSQ psychometric properties, defining clinical cut-offs. Part II tested the impact of traumatic components on anxiety and depression symptoms, using a multiple multivariate latent regression model. PTSQ exhibited exemplary fit indices and robust psychometric properties. Clinically relevant cut-offs were identified. The differential contributions of intrusion, avoidance, and hyperarousal to anxiety and depression symptoms were evaluated, elucidating the strength and nature of these relationships. This study reaffirms the PTSQ as a psychometrically sound and reliable instrument. It underscores the effects of intrusion, avoidance, and hyperarousal on anxiety and depression symptoms in individuals with traumatic experiences. These insights advocate for evidence-based interventions aimed at alleviating the psychological suffering associated with trauma components, fostering adaptation and supporting psychological health.

PopBERT. Detecting Populism and Its Host Ideologies in the German Bundestag

Abstract The rise of populism concerns many political scientists and practitioners, yet the detection of its underlying language remains fragmentary. This paper aims to provide a reliable, valid, and scalable approach to measure populist rhetoric. For that purpose, we created an annotated dataset based on parliamentary speeches of the German Bundestag (2013–2021). Following the ideational definition of populism, we label moralizing references to “the virtuous people” or “the corrupt elite” as core dimensions of populist language. To identify, in addition, how the thin ideology of populism is “thickened,” we annotate how populist statements are attached to left-wing or right-wing host ideologies. We then train a transformer-based model (PopBERT) as a multilabel classifier to detect and quantify each dimension. A battery of validation checks reveals that the model has a strong predictive accuracy, provides high qualitative face validity, matches party rankings of expert surveys, and detects out-of-sample text snippets correctly. PopBERT enables dynamic analyses of how German-speaking politicians and parties use populist language as a strategic device. Furthermore, the annotator-level data may also be applied in cross-domain applications or to develop related classifiers.

Achieving smooth motion in displacement amplification piezoelectric stick-slip actuator.

Traditional piezoelectric stick-slip actuators often suffer from significant backward motion phenomena, which greatly impact their output performance. To overcome this issue, a novel displacement amplification piezoelectric stick-slip actuator was meticulously designed. It integrates an L-shaped displacement amplification mechanism with a parallelogram-compliant mechanism. By dynamically adjusting the compressive force between the stator and the mover, this actuator effectively increases the single-step displacement, resulting in smooth and stable motion output. The design process involved thorough structural feasibility validation and core dimension optimization, utilizing Castigliano's second theorem and finite element simulation analysis. These efforts successfully yielded a substantial increase in the single-step output displacement. Experimental results demonstrate the actuator's capability to achieve smooth and stable motion output, even under challenging conditions, such as symmetric excitation signals and horizontal loading. Under specific operating parameters-preloading force of 3 N, input voltage of 100VP-P, and driving frequency of 625Hz sinusoidal excitation signal, the actuator achieves an impressive maximum driving speed of 25.22 mm/s, with a substantial maximum load capacity of 2.1 N. Compared to previous studies, the designed actuator exhibits superior adaptability to various excitation signals, offering significant potential for enhancing the performance and expanding the applications of piezoelectric stick-slip actuators.

Neural Representations of Concreteness and Concrete Concepts Are Specific to the Individual.

Different people listening to the same story may converge upon a largely shared interpretation while still developing idiosyncratic experiences atop that shared foundation. What linguistic properties support this individualized experience of natural language? Here, we investigate how the "concrete-abstract" axis-the extent to which a word is grounded in sensory experience-relates to within- and across-subject variability in the neural representations of language. Leveraging a dataset of human participants of both sexes who each listened to four auditory stories while undergoing functional magnetic resonance imaging, we demonstrate that neural representations of "concreteness" are both reliable across stories and relatively unique to individuals, while neural representations of "abstractness" are variable both within individuals and across the population. Using natural language processing tools, we show that concrete words exhibit similar neural representations despite spanning larger distances within a high-dimensional semantic space, which potentially reflects an underlying representational signature of sensory experience-namely, imageability-shared by concrete words but absent from abstract words. Our findings situate the concrete-abstract axis as a core dimension that supports both shared and individualized representations of natural language.

Developing a Holistic Framework for Assessing the Development of the Digital Economy

Rapid advancements in information and communication technologies (ICT) have accelerated the expansion of the digital economy (DE). However, the lack of a universally accepted definition has hindered a systematic assessment of the progress of the DE. A robust framework to evaluate various aspects of DE activities is crucial to fully capture the potential of the DE. This study conducts a systematic review of academic literature to identify and analyse various dimensions of the DE, aiming to propose a framework to assess the development of the DE. A comprehensive analysis of 161 articles from the Scopus database (2010–2024) identifies four core dimensions, namely digital infrastructure, digital industrialisation, industrial digitisation and digital innovation as the primary focus of existing DE research. These findings lay the groundwork for developing the framework to assess the development of the DE.

Low-carbon information quality dimensions and random forest algorithm evaluation model in digital marketing

The growing urgency for low-carbon lifestyles necessitates developing effective strategies to promote sustainable consumer choices. This study investigates key dimensions of information quality that shape consumer behavior within digital marketing to achieve this goal. Employing a mixed-methods approach that integrates grounded theory and machine learning, this study identifies three core dimensions of low-carbon information quality: matching quality, presentation quality, and interpretability quality. These dimensions underscore the importance of aligning information with consumer needs, ensuring clear and accurate presentation, and fostering transparency for trustworthiness. A Random Forest algorithm-based evaluation model is constructed to assess low-carbon information quality, demonstrating its effectiveness in identifying high-quality, sustainable content. This research provides a practical tool for digital marketers to enhance their strategies, raise consumer awareness of sustainable options, and ultimately contribute to the growth of the low-carbon consumption market.

Overview and confirmatory and exploratory factor analysis of AI literacy scale

Comprehensive concepts of AI literacy (AIL) and valid measures are essential for research (e.g., intervention studies) and practice (e.g., personnel selection/development) alike. To date, several scales have been published, sharing standard features but differing in some aspects. We first aim to briefly overview instruments identified from unsystematic literature research in February 2023. We identified four scales and one collection of items. We describe the instruments and compare them. We identified common themes and overlaps in the instruments and developmental procedure. We also found differences regarding scale development procedures and latent dimensions. Following this literature research, we came to the conclusion that the literature on AI literacy measurement was fragmented, and little effort was undertaken to integrate different AI literacy conceptualizations. The second focus of this study is to test the factorial structures of existing AIL measurement instruments and identify latent dimensions of AIL across all instruments. We used robust maximum-likelihood confirmatory factor analysis to test factorial structures in a joint survey of all AIL items in an English-speaking online sample (N=219). We found general support for all instruments' factorial structures with minor deviations from the original factorial structures for some of the instruments. In a second analysis step, to address the issue of fragmented research on AI literacy conceptualization and measurement, we used principal axis exploratory factor analysis with oblique rotation to identify latent dimensions across all items. We found four correlated latent dimensions of AIL, which were mostly interpretable as the abilities to use and interact with AI, to design/program AI (incl. in-depth technical knowledge), to perform complex cognitive operations regarding AI (e.g., ethical considerations), and a common factor for the abilities to detect AI/differentiate between AI and humans and manage persuasive influences of AI (i.e., persuasion literacy). Our findings sort the multitude of AIL instruments and reveal four latent core dimensions of AIL. Thus, they contribute importantly to the conceptual understanding of AIL that has been fragmented so far.

Journeys to functionality: A dimensional analysis of personal narratives of recovery from depression.

Recovery from depression constitutes a long journey that is understood as a unique and multifaceted process encompassing various dimensions. To understand what constitutes recovery from depression and to develop greater insights into the unique dimensions of the recovery journey, the study of recovery memoirs is essential. This article performs a dimensional analysis on six Indian first-hand accounts of recovery from depression collected in Amrita Tripathi and Arpita Anand's Real Stories of Dealing with Depression to examine the journeys toward healing and the uniqueness of the recovery processes. Through the dimensional analysis, four core dimensions of recovery from depression-Problems, Social Supports, Position of Recovery and Functionality-are identified. The process of recovery, consisting of understanding the problems (causes) through sensed adversities (sensed effects), making use of received social supports to transform oneself, finding out the position of recovery, and lastly, functioning peacefully for living, corresponds to the four dimensions of recovery. Drawing on Herbert Blumer's theory of social interactionism, the article examines how different individuals interpret their experiences of depression in unique ways and develop distinctive recovery strategies. The identified dimensions of recovery correspond to the need for unique approaches to recovery articulated by each of the narrators. The selected narratives reveal that the problems are unique, and for each of the unique problems, there has to be a distinctive support mechanism. The recovery narratives are centred around the unique problems wherein the individuals attempt to understand what happened to them and why it happened. The article concludes by suggesting that healthcare practitioners can utilise the dimensions and the subdimensions as a lead to understand fully how their clients conceptualise their problems and try to understand how each client defines the recovery itself.

Healing Love: Toward a Theory of Communion for Black Men

ABSTRACT Guided by the three core tenets of a Black feminist love-politic, this article offers a framework of communion for Black men within higher education. Emanating from the embodied experiences of Black men in academe participating in the “site” of communion (i.e. The Gathering) through an Association for the Study of Higher Education (ASHE) virtual symposium session, four core dimensions of theory emerged: spiritual, relational, material, and political. Life-notes from each session participant are used to capture each dimension of communion. Implications for praxis related to the spiritual and material well-being of Black men within higher education are offered.

Integrated approach for the development of railway as a core dimension of spatial planning

ABSTRACT The sustainable development of railway represents an essential dimension of spatial planning and a priority of the European Union as it constitutes a safe and environmentally friendly transportation mode. This paper focuses on the application of an integrated approach supporting the development of railway in Greece. A Decision Support System (LIPSOR) was used in order key components, key actors and possible future states to be explored; alternative scenarios were designed and assessed in combination with policy goals and measures. The main outcomes indicated the need to upgrade rail infrastructure and services, increase railway extroversion and reinforce investments.

A Stochastic FRET Study on the Core Dimension of Polystyrene-block-Poly(Polyethylene Glycol Monomethyl Ether Acrylate) Micelles.

Polystyrene-b-poly(polyethylene glycol monomethyl ether acrylate) (PSt-b-PPEGA) copolymers featuring pyrene and perylene as the Förster resonance energy transfer (FRET) donor (denoted as D-BCP) and acceptor (denoted as A-BCP), respectively, were synthesized via the reversible addition and fragmentation chain transfer (RAFT) polymerization. These copolymers were then used to form DA-mixed micelles via a dialysis method. The micelles consisted of D-BCP (mole fraction fD = 0.04), A-BCP (fA = 0.04), and label-free PSt-b-PPEGA (fN = 0.92). The decrease in fluorescence intensity of pyrene in the micelles confirmed the occurrence of FRET, with an observed efficiency of 0.32. A Monte Carlo approach was employed to estimate the expected FRET efficiency, assuming the random fractional distribution of D-BCP and A-BCP, along with the random spatial distribution of pyrene and perylene within the micellar core. The observed FRET efficiency suggested a core radius (Rc) of 0.95R0, where R0 was the Förster critical distance. With R0 calculated to be 3.2 nm based on Förster theory, Rc was determined to be approximately 3.0 nm, aligning closely with the dried-out core radius estimated from aggregation number and polystyrene density. This stochastic FRET methodology was further applied to investigate the swelling behavior of the polymer micelles in a mixture of N,N-dimethylformamide (DMF) and water. Dynamic light scattering analysis revealed minimal change in core dimension below 60 vol % DMF content. However, FRET analysis provided a deeper insight, showing an increase in core radius with DMF content up to 20 vol %, followed by saturation up to 50 vol %, offering a more comprehensive understanding of the micelle swelling behavior.