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Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

This study aims to examine the impact of peer-to-peer (P2P) accommodation platforms’ green marketing on consumers’ pro-environmental behavioural intention through the mediation of consumer trust and engagement, following the social influence theory and the stimulus–organism–response model.

A questionnaire survey was designed to collect data from American P2P accommodation consumers. Data collection was conducted through an outsourced survey company. Partial least squares structural equation modelling was used to analyse the data.

The study reveals that P2P accommodation platforms’ green marketing orientation was positively associated with consumer trust in the platform and consumer engagement with the platform. Both consumer trust and consumer engagement positively enhanced consumers’ pro-environmental behavioural intention in the P2P accommodation consumption, serving as effective mediators between consumers’ perceptions of green marketing orientation and pro-environmental behavioural intention.

The study offers practical insights for P2P accommodation platforms and operators in engaging in green marketing and fostering consumers’ pro-environmental consumption behaviours in P2P accommodations.

The study addresses the grand question of whether business operators’ responsible production behaviour can possibly lead to consumers’ responsible consumption behaviour in the P2P accommodation sector. It contributes to the literature on P2P accommodation by providing evidence to show green marketing practices of P2P accommodation platforms can lead to consumers’ pro-environmental behavioural intention. It provides both theoretical value for knowledge advancement and practical value to guide more sustainable industry practices.

This study aims to provide a timely review of hospitality and tourism live streaming (HTLS) research, aiming to understand the intellectual foundation in the past and identify opportunities for future research.

This study collected 56 papers from journals in the Social Science Citation Index database or the Australian Business Deans Council journal quality list and adopted a hybrid systematic literature review combining bibliometric analysis and the theory-context-characteristics-method framework-based approach. Additionally, a cross-tabulation analysis was conducted to compare the research on two specific forms of HTLS – tourism e-commerce live streaming (TEcLS) and travel live streaming.

The study found that the current research lacks in-depth theoretical insights, focuses on China as the national context and viewers as the research subject, mainly uses online surveys and lacks first-order knowledge. Moreover, it identified five research themes, including the impact of HTLS on viewer behavior, purchase behavior in HTLS and introduction of HTLS, within which eight categories of research constructs, such as viewer-related, streamer-related and relationship-related, are applied.

In terms of research, the study reveals various gaps in the existing literature and provides potential research directions to advance the field. As for practice, it offers valuable strategies for practitioners to optimize their marketing efforts using HTLS.

This study provides an up-to-date review of the HTLS field through a systematic and reproducible method. It offers critical discussions and suggestions for academic research and industry practices.

Lack of access to finance is a major constraint to the growth of small and medium-sized enterprises (SMEs) and entrepreneurship in developing countries. The recent proliferation of mobile phone services, access to the internet and emerging technologies has led to a surge in the use of FinTech in Africa and is transforming the financial sector. This paper aims to examine whether FinTech developments heterogeneously contribute to the growth of digital finance for SMEs and entrepreneurship in 47 African countries from 2013 to 2020.

The paper uses a novel method of moments quantile regression, which deals with heterogeneity and endogeneity in diverse conditions for asymmetric and nonlinear models.

The empirical results reveal that the rise of FinTech companies offering services in Africa heterogeneously increases digital finance for SMEs and entrepreneurship in their different stages of growth. FinTech developments have a strong and positive impact in countries with higher levels of digital finance than those with lower levels. FinTech developments and digital finance positively and significantly influence entrepreneurship in Africa, particularly in the nascent and transitional development stages of entrepreneurship. Institutional quality has a considerable positive moderating effect when used as a control rather than an interaction variable.

The results suggest the need to promote FinTech developments in Africa: to provide a wide range of alternative digital finance schemes to SMEs and to promote entrepreneurship, especially in countries where entrepreneurship is in the nascent and transitional development stages. The results also underscore the need to promote FinTech development through supportive regulations and institutional quality to reduce risks related to FinTech and digital financing schemes.

To the best of the authors’ knowledge, this paper is one of the first attempts to account for the often overlooked heterogeneity effects and show that the influence of FinTech developments is not homogenous across the varying development stages of digital finance and entrepreneurship.

To answer the questions: what roles windows of opportunity act in the catchup process of latecomers, what strategies latecomer enterprises should adopt to size windows of opportunity to catch-up with incumbents even going beyond?

This paper studies the catch-up history of the Chinese mobile phone industry and proposes a sectoral innovation system under scenario of technology paradigm shifts. Then a history-friendly simulation model and counterfactual analysis are conducted to learn how different windows of opportunity and catch-up strategies influence the catch-up performance of latecomers.

Results show latecomers can catch up with technology ability by utilizing technology window and path-creating strategy. However, catching up with the market is not guaranteed. Demand window can help latecomers to catch up with market as it increases their survival rates, different sized windows benefit different strategies. However, it also enlarges incumbents' scale effect. Without technology window technology catch up is not guaranteed. Two windows have combination effects. Demand window affects the “degree” of change in survival rates, while the technology window affects the “speed” of change. Demand window provides security; technology window provides the possibility of a breakthrough for technology ability.

The findings of this paper provide theoretical guidance for latecomer enterprises to choose appropriate catch-up strategies to seize different opportunity windows.

This paper emphasizes the abrupt change of industrial innovation system caused by technology paradigm shifts, which makes up for the shortcomings of previous researches on industrial innovation system which either studied the influence of static factors or based on the influence of continuous changes.

In the practice of live streaming e-commerce, the consumer demand is usually uncertain, and the inventory and prices can be decided by brand owners or streamers. To this end, this study examines the inventory and pricing decisions of the brand owner and streamer in a live streaming e-commerce supply chain under demand uncertainty.

In this study, four scenarios are considered, i.e. the brand owner determines the inventory and price (Scenario BB), the brand owner determines the inventory and the streamer determines the price (Scenario BS), the streamer determines the inventory and the brand owner determines the price (Scenario SB), and the streamer determines the inventory and price (Scenario SS).

The results show that the inventory and prices, as well as the profits of the brand owner and streamer increase with the consumer sensitivity to streamer’s sales effort level under the four scenarios. The inventory (price) is the highest under Scenario SS (SB), while that is the lowest under Scenario BB (BS). In addition, when the sensitivity is low, the brand owner’s profit is the highest under Scenario BB, otherwise, the profit is the highest under Scenario SS. Regardless of the sensitivity, the streamer’s profit is always the highest under Scenario SS.

Few studies focused on the inventory and pricing decisions of brand owners and streamers in live streaming e-commerce supply chains under demand uncertainty, while this work bridges the research gap. This study can provide theoretical basis and decision support for brand owners and streamers.

This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.

Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.

The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.

The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.

With an emphasis on the moderating impact of trust, this study examines determinants influencing the purchase intentions of young consumers in augmented reality (AR) shopping platforms. This research study aims to pinpoint essential elements, including the enjoyment dimensions (i.e. entertainment, visual appeal and hedonic component) and practicality dimensions [i.e. informativeness, navigation and perceived usefulness (PU)], that are imperative in influencing young consumers’ purchase intentions in AR-based shopping platforms.

The present study used a quantitative approach grounded in the stimulus-organism-response model and the extended technology acceptance model, which analysed purchase intention among the youth using AR shopping platforms. One hundred seventy-two samples were gathered through self-administered questionnaires and underwent partial least squares structural equation modelling analysis to predict the relationships between the proposed variables.

The results of the current study suggested the independent variables (e.g. entertainment, visual appeal, informativeness and navigation) had a significant impact on hedonic components and PU. Furthermore, both hedonic components and PU had a significant and positive influence on purchase intention. Nevertheless, it is noteworthy that hedonic components and PU in relation to purchase intention were not moderated by trust.

The developed research framework is significant for understanding the perceptions of shopping behaviour among young consumers in the Borneo region of Malaysia. This is one of the few studies that explored the interplay between enjoyment and practicality’s dimensions on purchase intention via AR shopping platforms in the less explored region of Malaysia. Hence, this study plays a pivotal role in contributing to the existing marketing and technology management literature. Moreover, it holds practical importance for business operators and marketers as it aids in decision-making and strategic planning for the future direction of businesses in the young consumer market.

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.