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Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

This study aims to investigate the association of FinTech innovation (FinTechINN) and firm performance (FP) by considering the role of knowledge assets (KA) as a causal mechanism underlying the FinTechINN – FP association.

In this study, the authors consider panel data of 1,049 Chinese A-listed firm and construct a structural model for corporate FinTech innovation, knowledge assets and firm performance while considering endogeneity issues in analyses over the period of 2014–2022. The modified value added intellectual capital (VAIC) and research and development (R&D) expenses are used as a proxy measure for knowledge assets, considering governance and corporate performance measures.

According to the findings of this study FinTech innovation (FinTechINN) has a positive significant effect on firm performance. Particularly; the findings disclose that FinTech innovations has a link with knowledge assets, FinTech innovations indirectly affects firm performance, and the association between FinTech innovation and firm performance is partially mediated by knowledge assets (MVAIC and R&D expenses).

Rooted in the dynamic capability and resource-based view, this study pioneers an empirical exploration of the association of FinTech innovation with firm performance. Moreover, it introduces the novel dimension of knowledge assets (on firm-level), acting as a mediating factor with in this relationship.

The objective of this study is to investigate how the coronavirus disease 2019 (COVID-19) pandemic affects firms' financial management in China's manufacturing sector. In addition, the authors analyze the changes in various financial indicators before and during the COVID-19 pandemic. Further, the authors make a cross-country comparison of the COVID-19's impact on financial management between China and Romania.

The study uses the balanced panel data of 2,272 manufacturing listed companies from 2019 to 2020, and applies the t-test method and multiple regression method.

The results show that firms' financial performance in most manufacturing sub-sectors decreased during the observed period. In addition, the authors find that equity financing, proper liquidity management and an expanded firm scale can improve firms' financial performance. The authors further compare the results with the Romanian results, and find that the negative impact of debt-to-equity ratio on firms' financial performance in Romania is greater than that in China and the positive impact of financial autonomy ratio and working capital ratios is greater in China than that in Romania.

The findings can help corporate managers make the best financial management decision in response to crisis.

This study is one of the pioneers that analyze how manufacturing companies carried out their financial management during the COVID-19 crisis in the Chinese context, and provides a cross-country analysis of corporate financial management practices in China and Romania.

This study aims to unveil the pivotal components and implementation pathways in the digital innovation of smart tourism destinations, while constructing a theoretical framework from a holistic perspective.

The research focuses on 31 significant urban smart tourism destinations in China. Secondary data was collected through manual search supplemented by big data scraping, whereas primary data was obtained from interviews with municipal tourism authorities. Grounded theory was used to theoretically construct the phenomenon of digital innovation in smart tourism destinations.

This research has formulated a data-driven knowledge framework for digital innovation in smart tourism destinations. Core components include digital organizational innovation, smart data platforms, multi-stakeholder digital collaborative ecosystem and smart tourism scenario systems. Destinations can achieve smart tourism scene innovation through closed innovation driven by smart data platforms or open innovation propelled by a multi-stakeholder digital collaborative ecosystem.

Based on insights from digital innovation practices, this study proposes a series of concrete recommendations aimed at assisting Destination Management Organizations in formulating and implementing more effective digital innovation strategies to enhance the sustainable digital competitiveness of destinations.

This study advances smart tourism destination innovation research from localized thinking to systemic thinking; extends digital innovation theory into the realm of smart tourism destination innovation; repositions the significance of knowledge in smart tourism destination innovation; and constructs a comprehensive framework for digital innovation in smart tourism destinations.

本研究致力于揭示智能旅游目的地数字创新中的核心组件及实施路径, 并创建一个整体视角下的理论框架。

研究选定中国31座重要城市型智能旅游目的地为研究对象。通过人工检索结合大数据抓取的方式收集二手资料, 以各市旅游主管部门为访谈对象收集一手资料。运用扎根理论对智能旅游目的地的数字创新现象进行理论构建。

本研究构建了一个数据型知识驱动的智能旅游目的地数字创新框架。其中, 核心组件包括数字组织创新、智慧数据平台、多主体数字协同生态和智慧旅游场景体系。目的地可通过智慧数据平台驱动的内生型创新或多主体数字协同生态推动的开放式创新, 实现智能旅游场景创新。

本研究将智能旅游目的地创新相关研究由局部思考推向系统思考; 将数字创新理论扩展到智能旅游目的地创新的研究中; 重新定位知识在智能旅游目的地创新中的重要地位; 以及构建了一个智能旅游目的地数字创新整体框架。

本研究基于数字创新实践洞察, 提出了一系列具体建议。旨在帮助目的地管理组织更有效地制定和实施数字创新策略, 以增强旅游目的地可持竞争力。

La investigación se centra en 31 destacados destinos turísticos urbanos inteligentes de China. Los datos secundarios se recopilaron mediante una búsqueda manual complementada con técnicas de big data, mientras que los datos primarios se obtuvieron a partir de entrevistas con las autoridades turísticas municipales. Se empleó la teoría fundamentada para construir teóricamente el fenómeno de la innovación digital en los destinos turísticos inteligentes.

Esta investigación tiene como objetivo identificar los componentes esenciales y las rutas de implementación de la innovación digital en destinos turísticos inteligentes, y construir un marco teórico desde una perspectiva holística.

Este estudio ha desarrollado un marco de conocimiento basado en datos para la innovación digital en destinos turísticos inteligentes. Los componentes centrales incluyen la innovación organizativa digital, la plataforma de datos inteligentes, el ecosistema digital colaborativo de múltiples actores y el sistema de escenarios turísticos inteligentes. Además, tanto la innovación endógena impulsada por la plataforma de datos inteligentes como la innovación abierta impulsada por el ecosistema digital colaborativo de múltiples actores contribuyen a la innovación por escenarios en destinos turísticos inteligentes.

A partir de las prácticas de innovación digital, este estudio ofrece una serie de recomendaciones dirigidas a las Organizaciones de Gestión de Destinos (DMOs) para la formulación e implementación de estrategias de innovación digital de manera más efectiva, y mejorar la competitividad digital sostenible de los destinos turísticos.

Este estudio avanza la investigación sobre innovación en destinos turísticos inteligentes desde el pensamiento localizado hasta el pensamiento sistémico; extiende la teoría de la innovación digital al ámbito de la innovación en destinos turísticos inteligentes; reposiciona la importancia del conocimiento en la innovación de destinos turísticos inteligentes; y construye un marco integral para la innovación digital en destinos turísticos inteligentes.

We empirically investigate the impact of fintech innovation on dividend payout (DP) decisions. In addition, we also examine the mediated and moderated role of intellectual capital (IC) and board characteristics (BC) respectively in the fintech innovation-DP relationship.

Using a sample of 9,441 firm-year observations over the period 2014–2022, we develop a structural model that encompasses fintech innovation, IC, BC and DP decisions. We utilize fixed effects regression to empirically test the model. A battery of tests such as the two-step Generalized Method of Moment, Heckman’s two-stage selection correction and Difference-in-Difference regression are used to check the robustness and sensitivity of the estimates.

Our results suggest that fintech innovation significantly and positively impacts DP decisions and IC partially mediates the fintech innovation–DP relationship. In addition, BC such as independence, age and gender diversity are found to moderate this relationship.

This study’s originality lies in its micro-level analysis of the impact of fintech innovation on DP decisions, considering a novel firm-level innovation metric derived from patent applications. To our knowledge, no previous work has empirically examined the mediating role of IC and the moderating influence of BC in the fintech innovation–DP relationship, offering a unique perspective on the complex interactions shaping dividend policies in the digital era.

Using the sample between 2005 and 2011, the purpose of this paper is to investigate the effect of a new fund entry on incumbents using the overlap measure in portfolio holdings.

Empirical methodology is used in this study.

The authors find that incumbents that have a higher overlap with the entrants underperform subsequently. Based on the characteristic-based approach of Daniel et al. (1997), the authors find that the characteristic selectivity component is negatively correlated with the overlap measure, and thereby the decline in performance is driven by the stock-picking ability. The authors also discuss the unobserved actions of incumbents using the approach proposed by Kacperczyk et al. (2008) and find that incumbent unobserved actions do not benefit mutual fund investors in China. Finally the authors find that investors respond to the supply-side competition between entrants and incumbents quickly. These findings help us understand the mutual fund completion in China.

The findings in this study can help scholars, industry experts and regulatory authorities to understand the effect of competition in Chinese mutual fund industry.

Existing hospital building operations involve numerous information technology applications and complex building systems; therefore, an intelligent facility management (FM) platform is required to ensure their continuous operation. To address the persistent issues of data silos, inefficient data interoperability, and workflow incoordination that have been identified in the current body of FM practice and literature, the present study develops a data-asset (DA) centric FM platform specifically designed for hospital buildings.

This study proposes a semi-customized approach to develop the DA-centric FM platform for hospital buildings. To elucidate the precise function requirements of the hospital FM platform, focus group interviews are employed. By seamlessly integrating the as-built BIM model, IoT sensor data and FM workflow data, the BIM-based DA model with a data transfer mechanism is developed. The development of the FM platform with function modules in a case study is guided by a five-tier architecture and the coordination theory (CT). The case study provides an in-depth introduction to the applications of DA management, space management and maintenance management modules.

The capabilities of the developed DA-centric hospital FM platform are validated through the case application and user satisfaction survey, which assess data quality, automation level, operation efficiency, flexibility and functionality. For hospital FM activities, this DA-centric FM platform realizes data integration and seamless transformation, optimizes workflow coordination and enhances operation performance.

The initial scholarly contribution is the establishment of the BIM-based DA model, which serves as the data middle platform for continuous data integration, transmission and sharing within the FM platform. Subsequently, under the guidance of the CT, the business process of function modules is designed, improving the intra-module and inter-module workflow coordination. The developed DA-centric FM system along with its performance benchmarking application, assists facility managers and decision-makers in implementing smart operations for hospital buildings and achieving the management goals of safety, efficiency, energy savings and convenience.

The purpose of this study is to examine knowledge management (KM) infrastructure and processes on automobile manufacturing firm innovative performance through the mediating role of agile project management (APM) practice.

The data collection involved purposive and convenience sampling techniques to gather information from 692 employees employed in various public and private automobile manufacturing firms operating in Pakistan. To test the hypothesis, data analysis was conducted using Smart PLS software version 4, using the partial least squares and structural equation modeling technique.

The result revealed that knowledge management infrastructure and processes has a positive and significant effect on firm innovative performance. Moreover, agile project management practices positively and significantly mediate the relationship between knowledge management infrastructure and processes and firm innovative performance.

The performance of high-tech automobile manufacturing firms can be enhanced by implementing agile project management practices, especially when stimulated by external factors such as innovation. In an increasingly dynamic environment, innovation acts as a favorable factor that amplifies the positive impact of agile methodologies on firm performance.

Researchers can use these findings to identify knowledge gaps that need to be addressed in future studies and understand how strategies relate to processes within the KM-APM framework. This study provides practitioners with insights on applying KM practices in an APM context to enhance knowledge performance. Practitioners can use the framework to plan KM activities that support corporate strategy across all organizational layers, ensuring the appropriate knowledge is conveyed at each level.

The Biophilic Interior Design Matrix (BID-M) was created to assist designers with identifying biophilic interior design features for optimizing nature integration for evidence-based design. The BID-M was developed and tested with interior design practitioners in the United States. There was a need to further develop the BID-M for other cultures along with understanding the designers' perceptions of biophilia.

A mixed methods approach was used with 101 interior designers/architects practicing in China using a pre- and post-questionnaire surrounding a room assessment using the BID-M.

The Chinese translation of the BID-M was perceived as beneficial to design practice, evaluated as reliable and valid. The Chinese designers perceived a significant increase in knowledge and importance of biophilia after using the BID-M and it was useful in assisting all parts of the design process. The designers had some prior experience with biophilic design and clients have been requesting suitable natural and artificial light features.

The BID-M was seen as a human centered design tool that is useful to evaluate biophilic design features in the built environment.

Overall, the BID-M appears to be useful throughout the design process to ultimately support well-being. The participants' cultural background expands use of the BID-M and provides opportunities for additional cultural applications of biophilic design and future research. The BID-M offers additional language for incorporating biophilic design as well as serving to educate and guide feature selection.