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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.

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.

This study aims to investigate the mediating effect of innovation on the relationship between KM (KM) capabilities and organisational performance in the context of construction firms operating in Pakistan. Worldwide innovation predicts the performance of any firm. Today, the construction industry in Pakistan is booming, which reinforces the need for a study on innovation and KM in this sector.

This empirical study uses a correlational research design. An online survey questionnaire was used as a data collection method. Through convenient sampling, the sample comprised 277 employees from different construction firms working under the Defence Housing Authority (a construction company operating in major cities) in Pakistan. Data were analysed through partial least squares-structural equation modelling (Smart PLS-SEM version 3) to assess the hypothesis.

Data analysis reveals that KM dimensions, knowledge acquisition, application and protection positively and significantly influence organisational performance; however, knowledge conversion is insignificant. Furthermore, innovation positively and substantially mediates the relationship between knowledge acquisition, application, protection, organisational performance and the insignificant terms of knowledge conversion.

This study is limited to the construction industry, and future research should be conducted on larger scales for better generalisation. Other mediators between KM and organisational performance (i.e. organisational complexity, workplace environment, employee knowledge-sharing attitude) should be investigated.

These results are crucial and encourage managers in the construction industry, especially from a developing country like Pakistan, to understand the importance of innovation, the application of KM and the essential role it has in boosting business performance.

This research contributes to the scholarly debate on the mediating role of innovation in the relationship between KM and organisational performance. It also expands the literature on KM through an empirical investigation on the innovation of the construction industry in Pakistan from a management perspective.

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.

This study aims to explore the relationship between speed behavior of participants and driving styles on interchange ramps. A spiral interchange in Chongqing was selected as an experimental road to carry out field driving experiment.

The continuous operating speed during experiment was selected by Mobile Eye, and the driving style was selected via two inventories.

Different driving behaviors showed great differences in age, driving mileage and driving experience. During driving process, male pursued driving stimulation more, whereas female pursued driving steadiness more. Therefore, driving characteristics of male were more disadvantageous to driving safety than that of female. Except for the large speed difference at the entrance and exit of the ramps, the differences at other positions were small. And the operating speed of male was slightly higher than that of female. The difference between different genders at the ascending end position achieved 4–5 kph, and the difference at other feature points were mostly 1–2 kph. During driving process, risky participants were more likely to pursue driving stimulation, and the poor speed control behavior was reflected in wide range of desired operating speed. Based on the results of analyzing at feature points, melancholy and sanguine participants more tended to take a high operating speed, and the poor speed control behavior was reflected in the most widely desired speed range. The speed control behavior of mixed participants was more cautious.

Advanced driving assistance system combined with two inventories was used to explore difference of speed behavior.

This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.

In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.

This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.

According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.

This study examines whether real earnings management (REM) choices are connected with the ownership structure of politically connected businesses (PCBs). The authors also discuss the moderating role of audit quality (AQ) and family control (FC) on the relationship between PCBs and REM.

The authors' study sample comprises firms registered on the Pakistan Stock Exchange (PSE). The sample examines the financial data of the firms that remained listed for the last eight years, i.e. from 2011 to 2018, excluding nonfinance companies and firms with incomplete data. The authors test the hypothesis using feasible generalized least squares (FGLS) regression methods.

The authors find that PCBs show a high level of involvement in income-decreasing REM compared to nonPCBs due to lower litigation risk in REM. However, the authors' results also show that two monitoring mechanisms, AQ and FC, curb the opportunistic behavior of PCBs and reduce the intensity of REM in PCBs.

The findings of the study are beneficial in decision-making for both internal and external stakeholders, such as creditors, shareholders and competitors. In countries like Pakistan, which fall in the category of emerging economies, PCBs show involvement in income-decreasing REM to change the accurate picture of financial information to attain personal goals, and investors in such countries have a low level of knowledge about earnings management strategies; thus, this study offers detailed knowledge and information to investors and shareholders about political connections and REM. This plays a crucial role for regulators in stiffening the rules and regulations to further assist in more secure financial reporting.

This study contributes to the literature by providing a nuanced understanding of the interplay between political connections, REM, FC and AQ in the business context. Second, family-controlled businesses often exhibit distinct characteristics and governance structures compared to nonfamily-controlled firms. Exploring the moderating role of FC in the following relationship could provide valuable insights into how family dynamics influence the financial reporting practices of PCBs. Third, AQ is a critical factor in ensuring financial reporting transparency. However, the interaction between AQ, political connections, and REM remains relatively unexplored. This study explains how audit oversight affects the earnings management behavior of PCBs.

The current study aims to ascertain how green entrepreneurial orientation (GEO) affects green innovation performance (GIP) through the mediating mechanism of the knowledge creation process (KCP) and whether or not these associations can be strengthened or hampered by the moderating impacts of resources orchestration capabilities (ROC).

The research used data from managers at various levels in 154 manufacturing enterprises in Pakistan to evaluate the relationships among the constructs using hierarchical regression analysis and moderated mediation approach.

The study indicates that GEO substantially impacts firms' GIP. GEO and GIP's relationship is partially mediated by two KCP dimensions: knowledge integration (KI) and knowledge exchange (KE). Furthermore, ROC amplifies not only the effects of GEO on KE but also the effects of KE on GIP. The moderated mediation results demonstrate that KE has a greater mediating influence on GEO and GIP when ROC is higher.

To better understand GEO's advantages and significance, future studies should look into the possible moderating mechanisms of environmental, organizational culture/green capability in the association between GEO, KCP and GIP.

The research helps expand the field of green entrepreneurship and GIP literature by providing a deeper knowledge of GEO and offering insight into how to boost GI in manufacturing firms.

This research helps fill in knowledge gaps in the field by delving further into the mechanisms by which GEO promotes GIP, both directly and indirectly, via the mediating role of KCP and the moderating impacts of ROC.