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Quantile-adaptive probabilistic forecast combining
Get PDFCombining forecasts of cumulative probability distributions (CDFs) allows aggregation of the available information to improve accuracy. The linear opinion pool is commonly used, but it can yield overdispersed distributional forecasts. An alternative, leading to lower dispersion, is to average the quantiles of the CDF, which can be viewed as horizontal CDF averaging, with the averaging of probabilities in the linear opinion pool viewed as vertical averaging. Empirical results show that horizontal and vertical averaging can each be preferable for different parts of the CDF. For example, one method might be better for tail quantiles, while the other is better for central quantiles. To address this, we develop a method that transitions between vertical and horizontal averaging across the CDF. It relates to angular averaging, which is a recent proposal that performs aggregation along lines at an angle. Our new method averages along lines with slopes that smoothly transition across the CDF. The method is quantile-adaptive in the sense that the slopes of the lines vary across the quantiles, or equivalently, across the probabilities. We set the lines to emanate from a small number of fixed points, which are the parameters of the method. Viewing the lines as rays, we term the method radial averaging. Our theoretical results show that the method has the versatility to generate CDF forecasts that are sharper than horizontal averaging, and less sharp than vertical averaging. Our empirical results provide support for the new approach
Anchor entrepreneurs as microfoundational agents of regional industry emergence:the genesis of Scotland’s space industry
Get PDFSocial sustainability in architectural practice:Examining experiences of architectural offices in B-Corp certification in the United Kingdom
Get PDFPurpose: Social sustainability (SS) is one of the key pillars of sustainability along with environmental and economic sustainability. Several impact assessment frameworks (IAF) exist to evaluate sustainability in the built environment, yet SS is often neglected. This paper is the first to investigate the effectiveness of the B-Corp certification scheme as an IAF to promote SS in architectural practice. With almost 3.5 folds increase in the number of B-Corp-certified UK-based architectural offices, in the last two years, and the neglect of the social dimension of sustainability in IAF application; the key question of this research is “What roles does B-Corp play in architectural practice to promote SS in the UK?” Design/methodology/approach: This research is based on qualitative data collection and thematic analysis. Eight semi-structured online interviews were conducted with B-Corp-certified architectural offices in the UK. The interview questions focused on understanding the offices' B-Corp experiences around three categories: motivations, challenges and changes. Through a coding process, the interviews were analysed to find the similarities and differences between the offices' approaches to SS and their experiences as B-Corps. Keywords were identified and themes with an inductive approach, applying the research question as a lens. Findings: Data was analysed to understand how B-Corp and its IAF relate to the architectural offices. The study concluded that B-Corp can make it easier to establish inter-actor relationships and B-Corp’s IAF can provide a holistic approach in which architectural offices can better measure their sustainable values by switching the evaluation scale from “building” to “business” unlike common IFAs in the built environment; with these two roles, it can effectively contribute to social sustainability. Originality/value: It is the first research to introduce the B-Corp certification to the architectural literature. Even though over 90 publications are covering B-Corp in other domains, there has yet to be any research looking at B-Corp-certified architectural offices, its merits as an IAF and limitations. This paper presents novel contributions to the knowledge concerning the assessment of social sustainability in architecture.</p
Will hope light the way? The interplay of hope, loneliness and extraversion in shaping entrepreneurs’ business exit intentions
Get PDFPurposeThe neglect of hope, a powerful yet under-researched psychological capital in entrepreneurship research, has left an obtrusive gap in understanding entrepreneurial behaviour. This study develops and tests a model showing that trait hope reduces entrepreneurs’ business exit intentions by alleviating their loneliness. It also shows how extraversion influences this relationship, highlighting when trait hope affects business exit.Design/methodology/approachWe conducted two three-wave, time-lagged surveys with entrepreneurs in Indonesia (n = 227) and the United States (US) (n = 215).FindingsOur findings reveal that entrepreneurs’ loneliness mediates the relationship between trait hope and business exit intentions in both countries. Extraversion further shapes this relationship, with stronger effects of trait hope on entrepreneurs’ loneliness and exit intentions generally observed among more extraverted entrepreneurs.Originality/valueThis research highlights trait hope as a psychologically potent yet dependent on entrepreneurs’ extraversion as an individual difference. We thereby contribute to hope research in the entrepreneurship context and the business exit literature. In addition, our study extends current research on entrepreneurs’ loneliness by identifying hope as a factor that can act as the source of “light” to combat loneliness in entrepreneurs
ITSEF:Inception-based two-stage ensemble framework for P300 detection
Get PDFTo address the problems of low signal-to-noise ratio, significant individual differences between subjects, and class imbalance in P300-based brain-computer interface (BCI), this paper proposes a novel Inception-based two-stage ensemble framework (ITSEF) to improve detection accuracy. Firstly, an Inception-based convolutional neural network (ICNN) is designed to extract multi-scale features and conduct cross-channel learning. In addition, a two-stage ensemble framework (TSEF) combined with a pre-training and fine-tuning strategy is developed, aiming to enhance the classification performance of the minority class and improve the generalization ability of the model. The framework comprises a conventional learning branch and a re-balancing branch, each based on an ICNN pre-trained with a different loss function. The prediction results of both branches are dynamically weighted by a cumulative learning strategy, so that the model gradually shifts its learning focus from the majority class to the minority class, comprehensively improving the identification ability for both classes. Experimental results on two datasets, Dataset II of BCI Competition III and BCIAUT-P300, demonstrate that the proposed ITSEF achieves state-of-the-art performance in the P300 classification task, with average classification accuracies of 86.16 % and 92.13 %, respectively. Compared with the existing state-of-the-art methods, the ITSEF achieves improvements of 4.61 % and 1.01 % on the two datasets, respectively. Furthermore, it exhibits significant improvements compared to baseline models and widely used class re-balancing strategies. The proposed ITSEF method provides an innovative deep learning framework for P300 signal analysis and has application potential in the field of P300-BCI.</p
Photo- and electro-luminescence studies of a new nine-coordinate ternary Eu(III) complex
Get PDFA new 4′-(3,4-dimethoxyphenyl)-2,2′:6′,2″-terpyridine (DmP-TerPy) ligand has been synthesized and utilized as the ancillary ligand in conjunction with the primary antenna ligand 4,4,4-trifluoro-1-phenyl-1,3-butanedione (btfa) to develop a new nine coordinate red emitting ternary Eu(III) complex, [Eu(btfa) 3(DmP-TerPy] (Eu1). Eu1 was characterised by analytical and spectroscopic techniques and its photophysical properties were analysed. The experimental results were complemented by computational methods, namely, density functional theory (DFT), time-dependent density functional theory (TD-DFT), and the Lanthanide Luminescence Software Package (LUMPAC), to establish the photoluminescence (PL) properties of the sensitised Eu(III) complex and the energy transfer (EnT) processes involved. Finally, to test the application of Eu1 as a narrow band red emitter, the material was used as the emitting layer (EML) in a multi-layered host-guest device to fabricate highly monochromatic red organic light-emitting diodes (R-OLED).</p
“I want to be honest...but how much can I share?”:Sustainable Influencing and Experiences of Moral Residue
Get PDFTransparency is the cornerstone of social media influencing. Research has explored how influencers disclose commercial interests, yet little is known about influencers’ self-disclosure of private consumption. Building on the transparency management and moral hypocrisy literatures, this paper explores how sustainable influencers navigate moral dilemmas as they communicate about sustainability. Through interviews and analysis of media articles, we find that sustainable fashion influencers experience persistent emotional baggage, which we frame as moral residue as well as moral hypocrisy, in navigating three moral dilemmas: (anti)consumption; (non)promotion; and (non)commercialization. To reconcile this, sustainable fashion influencers engage in transparency management, choosing between strategies of confessing, concealing, and/or conning. These strategies may inadvertently lock sustainable influencers in perpetual cycles of moral residue and moral hypocrisy. In explicating the process and potential outcomes of managing transparency around moral dilemmas, we provide an intrapersonal view of moral hypocrisy and offer implications for theory and practice
Electoral politics over automation in a dual economy
Get PDFWhen automation in a developing economy displaces low-skilled workers in the advanced sector, backward sector wages may fall due to in-migration of the ‘newly’ unemployed. Fear of job and income loss may then induce office-seeking political parties to announce regulatory policies on automation for electoral success. We show that absent sectoral spillover, democratic adoption of automation is relatively higher and protects only high-skilled jobs in the advanced sector. However, the possibility of spillover limits this adoption. More specifically, if the backward sector is large, automation faces full resistance. In contrast, if the advanced sector is large, automation is moderate, making only the low-skilled jobs vulnerable. But these vulnerable workers, unlike their counterparts in the backward sector, may prefer automation because their advanced-sector wages fall below the severance pay plus backward-sector opportunities. When neither sector is large, the size of automation becomes uncertain, pushing similar economies into different growth paths
From Intention to Action:Understanding Youth Electoral Participation Across Countries through Civic Education
Get PDFDeclining youth electoral participation threatens the long-term legitimacy of representative democracy. However, timely cross-national indicators of early disengagement remain scarce. This study draws on data from the IEA International Civic and Citizenship Education Study (ICCS) to examine (a) whether eighth-grade students’ stated voting intentions [are associated with] their cohort’s eventual electoral participation, and (b) which individual-level factors best explain those intentions after controlling for country-level characteristics. First, we align students’ voting intentions from IEA ICCS 2009 and 2016 with [corresponding] official age-specific turnout rates in each cohort’s first national election. The analysis reveals a moderate, statistically significant association, indicating that higher proportions of “likely future voters” in grade eight are associated with higher turnout once these cohorts reach voting age. Second, to identify the drivers of voting intentions, we pool microdata from all three IEA ICCS cycles (2009, 2016, 2022; N ≈ 316 000 students) and estimate fixed-effects models to account for time-invariant national confounders. Results show that students’ political interest emerges as the strongest predictor, followed by civic knowledge, self-efficacy, trust in the political system and its institutions, and parental political interest. Student background characteristics (e.g., gender or language at home) lose statistical significance once these factors are accounted for. The findings validate adolescent voting intentions as an early-warning indicator and highlight malleable psychological levers (i.e., interest, knowledge, efficacy) that civic-education policy can target
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