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This paper aims to identify potential avenues for innovation in urban hotel management by analyzing self-reported data from visitors regarding their experience with interior design.

A qualitative exploratory computer-assisted content analysis was conducted to identify the impact of interior design on the guest experience. Leximancer 4.0 software analyzed 2,562 reviews from urban hotels collected through a reservation website.

The findings reveal that data reported by guests on interior design play a crucial role in shaping guest experiences, both positively and negatively. The esthetic appeal of interior design is shown to impact resting and comfort, affecting overall performance significantly. The study also highlights how different star categories of hotels and variations in visitors' purposes for their stay lead to distinct guest experiences and different opportunities to innovate.

The study’s results provide evidence for researchers and practitioners of the potential of the guest-reported interior design experience as a valuable source for fostering innovation. In addition, in the hotel industry, innovation may eventually be attained through interior design renovation.

Self-reported data from guests on interior design is an effective tool for innovation. Making interior design a priority throughout the establishment and ongoing management of a hotel is crucial. By integrating interior design, not only can potential negative experiences be avoided, but greater guest satisfaction can also be achieved during their stay, promoting memorable experiences that align with the hotel category and customer expectations.

This research emphasizes the importance of interior design as a catalyst for innovation and improved social experiences in the hospitality industry. Innovation in interior design can improve hotel performance in several dimensions, including attracting more visitors to the hotel and the area, increasing tourism revenue for local businesses and contributing to the broader societal goal of reducing environmental impact and promoting sustainability.

This article adopts a guest-centered methodology to provide valuable insights for hotel managers to leverage interior design as a tool for innovation in the hospitality industry after showing that interior design enhances guests' experiences, comfort and hotel differentiation.

Existing studies have been conducted to explain the process of digital transformation. This work aims to identify the paradoxes encountered by companies in undertaking digital transformation and the role of digital affordances in overcoming these paradoxes.

This study uses rich empirical data from four traditional Chinese manufacturers that have successfully achieved digital transformation to explain how companies can overcome the digital transformation paradox with the help of digital affordances.

The authors identify the paradoxes that traditional companies encounter when carrying out data transformation based on the experience of four Chinese traditional manufacturing enterprises that have successfully achieved digital transformation – the paradox of flexibility and stability of organization structure, the paradox of cost and profit and the paradox of perception between executives and employees. Based on this, we propose three digital affordances that play an important role in overcoming the digital transformation paradoxes – digital decentralization, digital agility and digital citizenship.

This study identifies three forms of critical digital affordances and introduces citizenship into digital transformation contexts.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

The purpose is to investigate how to create a new premium new energy vehicle brand.

This study employed a two-stage design. Firstly, a single-case study of NIO was undertaken to execute a thematic analysis, from which propositions were proposed and a theoretical model was constructed. Subsequently, quantitative data were collected through the questionnaire method to empirically test the model developed in the first stage.

NIO creates great user experience through four aspects: product, service, digital touchpoints and lifestyle. Functional experience is shaped by product and digital touchpoints, while emotional experience is affected by service and lifestyle. NIO wins extremely high user satisfaction through great user experience. User satisfaction is affected by both functional and emotional experience. Taking extremely satisfied users as the core, NIO leverages word-of-mouth recommendations to increase brand awareness and build premium brand image, so as to achieve high performance in the long term.

This study contributes to the literature by proposing and testing a theoretical model of creating a new premium new energy vehicle brand. It highlights the significance of emotional factors in the process of creating a new premium brand. It proposes employing the “ripple model” to translate user satisfaction into financial performance. It provides a three-step guide to creating a new premium brand for managers.

This study investigates the causal relationship and mechanisms between the development of digital finance and household carbon emissions. Its objective is to explore how digital finance can influence the carbon footprint at the household level, aiming to contribute to the broader understanding of financial innovations' environmental impacts.

The research combines macro and micro data, employing input-output analysis to utilize data from the China Household Finance Survey (CHFS) for the years 2013, 2015, 2017, and 2019, national input-output tables, and Energy Statistical Yearbooks. This approach calculated CO2 emissions at the household level, including the growth rate of household carbon emissions and per capita emissions. It further integrates the Peking University Digital Financial Inclusion Index of China (PKU-DFIIC) for 2012–2018 and corresponding urban economic data, resulting in panel data for 7,191 households across 151 cities over four years. A fixed effects model was employed to examine the impact of digital finance development on household carbon emissions.

The findings reveal that digital finance significantly lowers household carbon emissions. Further investigation shows that digital transformation, consumption structure upgrades, and improved household financial literacy enhance the restraining effect of digital finance on carbon emissions. Heterogeneity analysis indicates that this mitigating effect is more pronounced in households during the nurturing phase, those using convenient payment methods, small-scale, and urban households. Sub-index tests suggest that the broadening coverage and deepening usage of digital finance primarily drive its impact on reducing household carbon emissions.

The paper recommends that China should continue to strengthen the layout of digital infrastructure, leverage the advantages of digital finance, promote digital financial education, and facilitate household-level carbon emission management to support the achievement of China's dual carbon goals.

The originality of this paper lies in its detailed examination of the carbon reduction effects of digital finance at the micro (household) level. Unlike previous studies on carbon emissions that focused on absolute emissions, this research investigates the marginal impact of digital finance on relative increases in emissions. This method provides a robust assessment of the net effects of digital finance and offers a novel perspective for examining household carbon reduction measures. The study underscores the importance of considering heterogeneity when formulating targeted policies for households with different characteristics.

This study investigates augmented reality (AR) retailing and attempts to develop a profound understanding of consumer decision-making processes in AR-enabled e-retailing.

The study is grounded in rich informational cues and information processing mechanisms by incorporating the elaboration likelihood model (ELM) and trust transfer theory. This study employs a mixed analytic method that incorporates structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to provide a complete picture of individual information process mechanisms in AR retailing under the tenet of ELM.

The SEM analysis results confirm the relationships between the central and peripheral route factors, information processing outcomes and eventual behavioral intentions. Moreover, all configurations revealed by the fsQCA include both central and peripheral factors. Hence, the dual routes proposed in the ELM are verified by using two distinct analytical approaches.

This study is pioneering in validating and contextualizing ELM theory in AR retailing. In addition, this study offers a methodological paradigm by demonstrating the application of multi-analysis in exploring consumers’ information process mechanisms in AR retailing, which offers a holistic and comprehensive view to understand consumers’ decision-making mechanisms.

This study delves into the less-explored domain of teachers’ readiness for leadership roles by investigating the direct and indirect relationships between positive school culture and teachers' readiness for leadership roles through affective-identity motivation to lead, and teacher optimism.

This study employed partial least squares structural equation modelling (WPLS-SEM) for data analysis. The data were gathered from 424 elementary school teachers who do not hold any leadership positions in Xi’an, China. A total of 391 samples were used after sampling weight adjustments.

There is a significant and positive direct relationship between positive school culture and teachers’ readiness for leadership roles. Affective-identity motivation to lead and teacher optimism emerged as significant mediators in this dynamic.

This study complements and expands on the study of the relationship between positive school culture, affective-identity motivation to lead, teacher optimism and teachers' readiness for leadership role. This research has established a theoretical framework for school stakeholders to cultivate future teacher leaders.

These findings provide valuable theoretical insights into educational leadership literature and contribute to a more comprehensive understanding of the factors influencing teachers in assuming leadership roles, particularly in the context of Asian societies.

This paper aims to explore the effect of teacher–student collaboration on academic innovation in universities in different stages of collaboration.

Based on collaboration life cycle, this paper divided teacher–student collaboration into initial, growth and mature stages to explore how teacher–student collaboration affects academic innovation.

Collecting data from National Science Foundation of China, the empirical analysis found that collaboration increases the publication of local (Chinese) papers at all stages. However, teacher–student collaboration did not significantly improve the publication of international (English) papers in the initial stage. In the growth stage, teacher–student collaboration has a U-shaped effect on publishing English papers, while its relationship is positive in the mature stage.

The results offer suggestions for teachers and students to choose suitable partners and also provide some implications for improving academic innovation.

This paper constructed a model in which the effect of teacher–student collaboration on academic innovation in universities was established.

Cross-cultural cognitive paradoxes have frequently broken the existing boundaries of knowledge and stimulated demands for knowledge creation (KC), and such paradoxes have triggered and will continue to trigger novel risks in the context of international business (IB). Given the nascency of relevant issues, this study aims to develop a more comprehensive understanding of KC across cultures by proposing a Yin-Yang dialectical systems theory of KC as micro-foundation to more systematically frame the risk/paradox-resolving mechanism elicited by cultural collisions.

This paper is conceptual in nature. The authors first critically review the literature to lay a broad theoretical foundation. Integrating the philosophy- and praxis-based views, the authors reposition knowledge as a Yin-Yang dialectical system of knowing, with yin representing the tacit while yang represents the explicit. Next, the authors justify the underling logic of realising KC through a contradiction-resolving process. On this basis, the authors draw upon the Yijing’s Later Heaven Sequence (LHS) as the source domain of a heuristic metaphor to reconceptualise KC as a dynamic capability in the IB context.

Using the LHS paradigm to metaphorically map the intricate patterns of interaction and interconnectivity among the involved individuals, organisations and all related stakeholders, this research identifies and theorises the overall dynamic capability of KC in the IB context, which comprises five sets of processes: contradiction, conflict, communication, compromise and conversion.

This research highlights that KC is simultaneously activated and constrained by human actions as well as by the socially constructed context in which it emerges, which helps individuals, organisations and policy makers more clearly frame the novel risks induced by cross-cultural cognitive conflicts in the IB context.

The authors synthesise Yin-Yang dialectics with the approach of collective phronesis, proposing a novel, praxis-oriented Yin-Yang dialectical systems theory of KC. It provides a deeper understanding of the epistemological paradox inherent in all knowledge, thus enabling KC to be rationalised by a sounder logical reasoning. By fusing the macro and micro perspectives on KC, the authors also enrich existing theory and future theory building in the domain of knowledge management.

Traditional visual simultaneous localization and mapping (SLAM) systems are primarily based on the assumption that the environment is static, which makes them struggle with the interference caused by dynamic objects in complex industrial production environments. This paper aims to improve the stability of visual SLAM in complex dynamic environments through semantic segmentation and its optimization.

This paper proposes a real-time visual SLAM system for complex dynamic environments based on YOLOv5s semantic segmentation, named YLS-SLAM. The system combines semantic segmentation results and the boundary semantic enhancement algorithm. By recognizing and completing the semantic masks of dynamic objects from coarse to fine, it effectively eliminates the interference of dynamic feature points on the pose estimation and enhances the retention and extraction of prominent features in the background, thereby achieving stable operation of the system in complex dynamic environments.

Experiments on the Technische Universität München and Bonn data sets show that, under monocular and Red, Green, Blue - Depth modes, the localization accuracy of YLS-SLAM is significantly better than existing advanced dynamic SLAM methods, effectively improving the robustness of visual SLAM. Additionally, the authors also conducted tests using a monocular camera in a real industrial production environment, successfully validating its effectiveness and application potential in complex dynamic environment.

This paper combines semantic segmentation algorithms with boundary semantic enhancement algorithms to effectively achieve precise removal of dynamic objects and their edges, while ensuring the system's real-time performance, offering significant application value.