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Temporal leadership is a new construct that predicts team outcomes. This study examines the mediating role of shared temporal cognitions and the moderating role of time pressure in the relationship between temporal leadership and project success within sustainable construction projects.

The multi-source and multi-wave data were collected via self-administered questionnaires from teams working on sustainable construction projects. The direct and mediating hypotheses were tested using multi-level structural equation modelling, while moderated mediation hypotheses were examined by applying the bootstrap method using SPSS Process Macro.

The results showed that temporal leadership enables project success via shared temporal cognitions. Temporal leadership is most beneficial for facilitating project success via shared temporal cognitions when teams experience high time pressure.

This is the first study examining shared temporal cognitions as a mediator of the relationship between temporal leadership and project success. Also, this is the first study that considered time pressure as a boundary condition that influences the relationships between temporal leadership, shared temporal cognitions and project success within sustainable construction projects. The study provides valuable advice to project managers and project-based construction organizations about using and managing time within projects.

Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep learning model for capturing dynamic spatial effects.

A novel deep learning model founded on the transformer architecture, called the spatiotemporal transformer network, is presented. This model has three components: the temporal transformer, spatial transformer and spatiotemporal fusion modules. The dynamic temporal dependencies of each attraction are extracted efficiently by the temporal transformer module. The dynamic spatial correlations between attractions are extracted efficiently by the spatial transformer module. The extracted dynamic temporal and spatial features are fused in a learnable manner in the spatiotemporal fusion module. Convolutional operations are implemented to generate the final forecasts.

The results indicate that the proposed model performs better in forecasting accuracy than some popular benchmark models, demonstrating its significant forecasting performance. Incorporating dynamic spatiotemporal features is an effective strategy for improving forecasting. It can provide an important reference to related studies.

The proposed model leverages high-frequency data to achieve accurate predictions at the micro level by incorporating dynamic spatial effects. Destination managers should fully consider the dynamic spatial effects of attractions when planning and marketing to promote tourism resources.

This study incorporates dynamic spatial effects into tourism demand forecasting models by using a transformer neural network. It advances the development of methodologies in related fields.

纳入动态空间效应在提高旅游需求预测的准确性方面具有相当大的潜力。本研究提出了一种捕捉动态空间效应的创新型深度学习模型。

本研究提出了一种基于变压器架构的新型深度学习模型, 称为时空变压器网络。该模型由三个部分组成：时空转换器、空间转换器和时空融合模块。时空转换器模块可有效提取每个景点的动态时间依赖关系。空间转换器模块可有效提取景点之间的动态空间相关性。提取的动态时间和空间特征在时空融合模块中以可学习的方式进行融合。通过卷积运算生成最终预测结果。

结果表明, 与一些流行的基准模型相比, 所提出的模型在预测准确性方面表现更好, 证明了其显著的预测性能。纳入动态时空特征是改进预测的有效策略。它可为相关研究提供重要参考。

所提出的模型利用高频数据, 通过纳入动态空间效应, 在微观层面上实现了准确预测。旅游目的地管理者在规划和营销推广旅游资源时, 应充分考虑景点的动态空间效应。

本研究通过使用变压器神经网络, 将动态空间效应纳入旅游需求预测模型。它推动了相关领域方法论的发展。

La incorporación de efectos espaciales dinámicos ofrece un considerable potencial para mejorar la precisión de la previsión de la demanda turística. Este estudio propone un modelo innovador de aprendizaje profundo para capturar los efectos espaciales dinámicos.

Se presenta un novedoso modelo de aprendizaje profundo basado en la arquitectura transformadora, denominado red de transformador espaciotemporal. Este modelo tiene tres componentes: el transformador temporal, el transformador espacial y los módulos de fusión espaciotemporal. El módulo transformador temporal extrae de manera eficiente las dependencias temporales dinámicas de cada atracción. El módulo transformador espacial extrae eficientemente las correlaciones espaciales dinámicas entre las atracciones. Las características dinámicas temporales y espaciales extraídas se fusionan de manera que se puede aprender en el módulo de fusión espaciotemporal. Se aplican operaciones convolucionales para generar las previsiones finales.

Los resultados indican que el modelo propuesto obtiene mejores resultados en la precisión de las previsiones que algunos modelos de referencia conocidos, lo que demuestra su importante capacidad de previsión. La incorporación de características espaciotemporales dinámicas supone una estrategia eficaz para mejorar las previsiones. Esto puede proporcionar una referencia importante para estudios afines.

El modelo propuesto aprovecha los datos de alta frecuencia para lograr predicciones precisas a nivel micro incorporando efectos espaciales dinámicos. Los gestores de destinos deberían tener plenamente en cuenta los efectos espaciales dinámicos de las atracciones en la planificación y marketing para la promoción de los recursos turísticos.

Este estudio incorpora efectos espaciales dinámicos a los modelos de previsión de la demanda turística mediante el empleo de una red neuronal transformadora. Supone un avance en el desarrollo de metodologías en campos afines.

The authors proposed a conceptual model by examining the influence of threats to their freedom on tourists’ psychological distance including social distance, spatial distance, and temporal distance, which effect psychological reactance and the consequent online Airbnb booking intentions. Furthermore, media intrusiveness as a moderator determines the boundary conditions between perceived threats to their freedom and social distance, spatial distance, and temporal distance.

Data was gathered from 491 Chinese travelers to provide empirical evidence. The authors performed data analysis in Amos 26.0 using structural equation modeling (SEM) and Hayes (2013) PROCESS macro.

The findings positively reinforced all the structural relationships of the study. Notably, media intrusiveness significantly moderates the association between perceived threats to their freedom and psychological distance (i.e. social distance, spatial distance, and temporal distance).

The findings contribute significantly to the field of social psychology, advertising, and consumer behavior derive prolific implications for policymakers and sharing economy platforms. Lastly, by identifying limitations, this research opens doors for future scholars.

Governments' acute precautionary measures in response to the COVID-19 outbreak have confined individual freedom across the globe. This study illuminates how tourists conceive these preventative measures as perceived threats to their freedom, and subsequently engage psychological reactance.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

Drawing on conservation of resources theory, this study aims to examine the relationship between temporal leadership (TL) and employees’ thriving at work (TW) by focusing on the positive mediating role of perception of work-goal progress (PWP), the negative mediating roles of job-based psychological ownership (JPO) and the moderating role of synchrony preference (SP).

We employed a dedicated data collection platform called Credamo for two waves of online questionnaires in China between March 2022 and April 2022. A total of 326 questionnaires were collected and analyzed to test the hypotheses.

(1) TL directly and positively affects TW. (2) TL indirectly and positively affects TW via PWP. (3) TL indirectly and negatively affects TW via JPO. (4) SP positively moderates the positive mediating effect of PWP on the relationship between TL and TW. (5) SP negatively moderates the negative mediating effect of JPO on the relationship between TL and TW.

Supervisors in organizations ought to discreetly practice TL and try to maximize the positive role of PWP and minimize the negative role of JPO.

The findings simultaneously discuss the effects of TL on TW from dark and bright perspectives. The influence of interaction between contextual and individual features on TW is also specified.

With the goal of helping consumers bounce back from the financial challenges they faced as a result of the COVID-19 pandemic, many firms developed and announced consumer-targeted resiliency programs (e.g. Walgreens waived delivery fees, Associated Bank allowed deferred mortgage payments). However, there is a paucity of research examining the unique features of these programs, and whether firms' investors (the first external stakeholder group to provide them with feedback regarding their strategies) were receptive to these programs during a period of time in which firms themselves were suffering financially. Drawing on resilience theory and stakeholder theory, the present research incorporates an event study of consumer-targeted resiliency program announcements to understand their financial implications for firms, and to learn whether firms witnessed different financial effects as a result of firm- and program-specific factors.

This study referred to business news publications and newswire services to collect a comprehensive list of consumer-targeted resiliency programs announced by publicly traded U.S. firms during the pandemic. The resulting dataset consisted of 145 announcements made during the period of February–June 2020. An event study was conducted in order to precisely measure the main effect of consumer-targeted resiliency programs on firm value, as manifested through abnormal stock returns. Finally, a moderation analysis (regression) was conducted to uncover whether firm characteristics or specific features of firms' consumer-targeted resiliency programs lead certain firms to witness stronger financial effects than others.

The main effect of consumer-targeted resiliency programs on firm value was found to be positive – a 1.9% increase on average. The moderation analysis finds that non-financial firms were rewarded more positively than financial firms (e.g. banks and credit card companies). In addition, financial aid (i.e. allowing customers to defer their payments to a firm for its products/services, versus a reduction in the price of a product/service or offering it for free or giving cash back to customers) and temporal characteristics (i.e. an offer being framed as limited-time, vs being indefinite or for the foreseeable future) are not found to have a moderating effect.

This theory-driven empirical study uncovers practical implications for managers of firms interested in whether investing in corporate social responsibility during times of crisis is a wise allocation of resources. Any form of financial aid for consumers, regardless of temporal limitations, is received positively by investors.

The study investigates the antecedents and consequences of digital ad avoidance in the e-commerce industry. This study aims to investigate how digital ad avoidance relates to internet usage over time, using a two-wave longitudinal research design. This study also explores how real-world advertising clutter (clutter and non-clutter) affects these relationships.

The data were collected from 192 online consumers in Türkiye, and a two-wave longitudinal research design and structural equation modeling were conducted to test the hypotheses of the conceptual model.

The results indicated that perceived goal impediment and prior negative experience had positive effects on affective avoidance in both ad-clutter and non-clutter periods. Further, affective avoidance had a significant positive effect on both cognitive and behavioral avoidance in either period. In addition, ad clutter moderated the effects of cognitive and behavioral avoidance on online purchase intention.

This research provides new evidence of the crucial role perceived goal impediment, prior negative experience and perceived control each play in driving digital ad avoidance. This paper contributes to the body of knowledge in the field by exploring how advertising clutter (both cluttered and non-cluttered settings) moderates these relationships through a two-wave longitudinal study.

Owing to highly volatile and chaotic external events, predicting future movements of cryptocurrencies is a challenging task. This paper advances a granular hybrid predictive modeling framework for predicting the future figures of Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Stellar (XLM) and Tether (USDT) during normal and pandemic regimes.

Initially, the major temporal characteristics of the price series are examined. In the second stage, ensemble empirical mode decomposition (EEMD) and maximal overlap discrete wavelet transformation (MODWT) are used to decompose the original time series into two distinct sets of granular subseries. In the third stage, long- and short-term memory network (LSTM) and extreme gradient boosting (XGB) are applied to the decomposed subseries to estimate the initial forecasts. Lastly, sequential quadratic programming (SQP) is used to fetch the forecast by combining the initial forecasts.

Rigorous performance assessment and the outcome of the Diebold-Mariano’s pairwise statistical test demonstrate the efficacy of the suggested predictive framework. The framework yields commendable predictive performance during the COVID-19 pandemic timeline explicitly as well. Future trends of BTC and ETH are found to be relatively easier to predict, while USDT is relatively difficult to predict.

The robustness of the proposed framework can be leveraged for practical trading and managing investment in crypto market. Empirical properties of the temporal dynamics of chosen cryptocurrencies provide deeper insights.

The concept of lean and ISO 14001 as a combined approach is an evolving strategy for streamlining operational processes and attaining environmental sustainability in the manufacturing context. This paper explores the critical success factors (CSFs) for a combined lean and ISO 14001 implementation in the manufacturing industry for achieving the operational and environmental benefits.

A systematic literature review (SLR) based on Scopus and Web of Science databases is conducted to present peer-reviewed articles on the CSFs for lean and ISO 14001 implementation in manufacturing operations. This article applies the CSF theory to classify the CSFs for a joint lean and ISO 14001 adoption.

Numerous CSFs are synthesised from the SLR across seven theoretical contexts of industry, competitive strategy, managerial position, environmental, temporal, internal/external, monitoring and building/adapting factors for a combined lean and ISO14001 implementation.

Numerous CSFs are synthesised from the SLR across seven theoretical contexts of strategic direction, competitive strategy, leadership and management, environmental, temporal, internal/external, monitoring and continuous process improvement factors for a combined lean and ISO 14001 implementation.

This paper contributes to academic scholarship by providing a theoretical perspective through classification of CSFs for a combined lean and ISO 14001 implementation to achieve operational and environmental performance. This paper also contributes to practitioners and policymakers who can use the emergent theoretical framework for application in practice for a more efficient and effective deployment of both strategies in the manufacturing industry.

To the best of author's knowledge, this study is the first to propose a theoretical framework of CSFs for a combined lean and ISO 14001 implementation based on the CSF theory and SLR findings in the manufacturing industry.

There is a wealth of value hidden in regional cultural heritage, but its preservation status is not optimistic. This study introduces a method that focuses on the inherent cultural value of regional cultural heritage to preserve it by value construction and release.

Based on the great value of regional cultural heritage due to spatial adjacency and temporal continuity, this paper focuses on its inherent cultural value to explore the preservation path and chooses Shichahai cultural heritage digital resources for a case study. This paper draws lessons from the narrative method of ancient Chinese historiography, constructs a cultural space and tells cultural stories. A linked data organization model for digital resources is created to construct a conceptual cultural space. Then, the space is materialized by linked dataset creation. The authors tell cultural stories discovered from the space, which are presented by various user interfaces using visualization technologies.

A cultural space promotes the development of a fine-grained description of regional cultural heritage and aids in relationship discovery to enhance the value construction ability. Additionally, storytelling via interactive user interfaces is helpful in the utilization and dissemination of knowledge extracted from a cultural space and enhances the value release of regional cultural heritage. In this way, a path with the inherent cultural value of regional cultural heritage as the core is established, and preservation is achieved.

This study focuses on the inherent cultural value of regional cultural heritage and proposes a new path to preserve these resources. This approach will enrich research on the preservation of regional cultural heritage and contribute to the construction and release of its cultural value.