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This study aims to analyze the paths and mechanisms of firms’ sustainable high growth. Firms’ high growth is susceptible to interruption, stagnation or reversal. Thus, how firms can achieve sustainable high growth is an important topic that requires urgent discussion and has significant implications for sustainable economic development and employment.

This study applies a longitudinal case study approach to portray the process by which Jiashu orchestrated digital elements with traditional resources to continuously fulfill their user demands and ultimately achieve sustainable high growth.

This study reveals three resource orchestration strategies: trust-oriented, demand-oriented and efficiency-oriented. These strategies are adopted in an organization’s startup, expansion and maturity periods, respectively. By dynamically integrating and orchestrating digital elements with traditional resources, firms implement a growth strategy with expanding and stacking dimensions, leading to sustainable high growth. The replicability and connectivity resulting from orchestrating digital elements and traditional resources encourage firms to expand their dimensions of growth and achieve sustainable high growth in multiple dimensions.

This study conducts a preliminary exploration of the relationship between the integration of digital and traditional elements and the sustainable high growth of enterprises. A more stable theoretical relationship between the two requires further multi-case studies and empirical analysis for substantiation.

This study first clarifies the concept of sustainable high growth and reveals a unique nonlinear path characterized by growth with expanding and stacking dimensions. The findings contribute to deepening the theories of sustainable high growth and resource orchestration in the digital economy era and offer practical implications for the sustainable high-growth practices of firms.

Enhancing total factor productivity through digital transformation is a crucial pathway for the high-quality development of manufacturing enterprises. This research aims to investigate the impact mechanisms of manufacturing enterprises’ total factor productivity in the context of digital transformation.

Using the data from 536 Chinese listed manufacturing enterprises from 2018 to 2021, this research divides digital transformation into two dimensions (i.e. digital transformation breadth and digital transformation depth) and examines their impacts on total factor productivity as well as the mediation effects of innovation capability and reconfiguration capacity.

It is found that digital transformation breadth, digital transformation depth and their interaction can positively affect manufacturing enterprises’ total factor productivity. The innovation capability and reconfiguration capacity of manufacturing enterprises act as mediators between digital transformation breadth and total factor productivity, as well as between digital transformation depth and total factor productivity.

This study is one of the first attempts to investigate the impact mechanisms of manufacturing enterprises’ total factor productivity from the perspective of digital transformation breadth and depth.

Innovation resilience, which refers to firms’ ability to consistently innovate and recover from disruptions, has recently gained increasing attention. Digital transformation plays a crucial role in the innovation of manufacturing firms. This paper aims to investigate the impact mechanisms of manufacturing firms’ innovation resilience in the context of digital transformation.

Using panel data from Chinese A-share listed manufacturing firms spanning from 2017 to 2022 as an example, this research examines the impact of digital transformation on innovation resilience. It also tests the moderating effect of innovation network embeddedness and the mediation effect of absorptive capacity.

It is found that digital transformation can enhance the innovation resilience of manufacturing firms. Furthermore, the structural embeddedness and relational embeddedness of manufacturing firms within innovation networks moderate the relationship between digital transformation and innovation resilience. The absorptive capacity of manufacturing firms acts as a mediator in the relationship between digital transformation and innovation resilience.

This paper is one of the first studies that investigates the impact mechanisms of digital transformation on the innovation resilience of manufacturing firms based on network embeddedness theory and dynamic capability theory.

While the economic benefits of the exhibition industry for the hotel sector have been addressed, the impact of exhibitions on individual hotels is unknown, especially when individual hotels’ star classification and locations are considered. This study aims to provide a better understanding of how room rates of different hotels change during different stages of the Canton Fair in China from a spatial-temporal perspective.

Room rates of 681 star-hotels within the city of Guangzhou before, during and after the Fair were extracted from websites. Through spatial interpolation and autocorrelation analysis and geographical detector (GeoDetector) technique, spatial and temporal patterns of hotel room rates and the interdependence between the convention center and the hotels with different star classification and locations were examined.

An inverse-U shape of room rate change was identified before, during and after the Fair, and the five-star hotels had the sharpest increase. Moreover, the distribution of hotel room rates followed the law of distance decay. The variation of hotel rates became larger when the distance to the convention center was larger. Spatial high-high clusters varied among hotels with different star classification.

This study contributed to the hotel literature by providing empirical evidence regarding how hotels with different star classification and locations were affected by events. This study also advanced the event literature by introducing GeoDetector. The findings of this study offered insights into the hotel location selection, pricing strategies and hotel collaboration with events.

虽然展览业对酒店业的经济效益已经得到解决, 但展览对单个酒店的影响尚不清楚, 尤其是在考虑单个酒店的星级和位置时。本研究旨在从时空角度更好地了解中国广交会不同阶段不同酒店的房价变化情况。

网站提取了广交会前、中、后广州市内681家星级酒店的房价。通过空间插值和自相关分析以及地理探测器（GeoDetector）技术, 研究了酒店房价的时空格局以及会议中心与不同星级和位置的酒店之间的相互依赖关系。

会前、会中、会后房价变化呈倒U型, 其中五星级酒店涨幅最大。此外, 酒店房价的分布遵循距离衰减规律。到会展中心的距离越远, 酒店价格的变化就越大。不同星级酒店的空间高-高集群存在差异。

该研究通过提供关于不同星级和位置的酒店如何受到事件影响的经验证据, 为酒店文献做出了贡献。这项研究还通过引入 GeoDetector 推进了事件文献。研究结果为酒店选址、定价策略和酒店与活动的合作提供了见解。

Infrastructure projects play a significant role in community development. Infrastructure consists of many subcategories such as roads, bridges, railways, airports, communication infrastructure and harbors. The expressway is an essential part of modern transportation infrastructure. Due to its span and complexity, expressway construction results in several environmental impacts comparatively higher than typical road construction. In that event, environmental sustainability assessment in expressway construction and determining environmental measures to address those impacts is essential. Therefore, this research intends to investigate the environmental measures applicable to expressway projects in Sri Lanka.

This study involves a comparative analysis of different environmental impacts validated through expert interviews. The data required to perform the analysis were extracted through expert interviews and the Battelle method.

The findings revealed the importance of environmental indicators for expressway projects in Sri Lanka by assigning weightages. The Construction Phase received the highest weightage among three themes indicating that the construction phase causes greater environmental impact in expressway construction. Furthermore, the Site Maintenance Plan and Tree Compensating received the highest weightages under indicators.

The study makes an original contribution through the identification of indicators that lead to the improvement of environmental sustainability in expressway projects in Sri Lanka. Furthermore, the use of the Battelle method within the context of measuring environmental sustainability of expressways projects in general — and within the context of Sri Lanka — is a novel research approach.

The purpose of this paper are to examine: first, whether the consumer style inventory (CSI) consumer decision-making styles were related to opinion seeking using electronic word of mouth (eWOM) in social networking sites (SNSs) and attitudes toward online social shopping using SNSs; and second, whether opinion seeking in SNSs and attitudes mediated the links between decision-making styles and intent to social shop online for apparel using SNSs.

The conceptual foundation was based on Engel, Kollat, and Blackwell's model. In total, 304 college students who are SNS users provided usable responses. Structural equation modeling was employed to test the proposed model and research hypotheses.

Among the CSI consumer decision-making styles, novelty/fashion consciousness decision-making style was the most important antecedent of opinion seeking using eWOM. The brand consciousness decision-making style was the most important antecedent of favorable attitudes. Novelty/fashion consciousness, brand consciousness, and price consciousness decision-making styles had indirect effects on intent to social shop online for apparel using SNS, mediated by both opinion seeking and favorable attitudes.

This study contributes to further theoretical understanding of the types of consumers that are drawn to eWOM and their online social shopping behaviors for apparel using SNSs. By identifying individual consumer characteristics, this study can provide retailers with an initial profile of consumers who shop apparel using SNSs. Retailers can use this information to further develop the design of their social shopping sites using SNSs to meet the needs of their customers.

The purpose of this study is to address the low localization accuracy and frequent tracking failures of traditional visual SLAM methods in low-light and weak-texture situations, and we propose a mobile robot visual-inertial localization method based on the improved point-line features VINS-mono algorithm.

First, the line feature information is introduced into VINS-mono. Subsequently, the EDlines line feature extraction algorithm is optimized with a short line merging strategy and a dynamic length suppression strategy to reduce redundant short lines and fragmented segments. In the back-end sliding window optimization, line feature reprojection errors are incorporated, and Huber kernel functions are added to the inertial measurement unit residuals, point-line feature residuals and loop closure constraints to reduce the impact of outliers on the optimization results.

Comparison and verification experiments are carried out on the EuRoC MAV Data set and real weakly textured environment. In the real low-light and weak-texture scenarios, the improved mobile robot localization system achieves over 40% higher accuracy compared to VINS-mono.

The main contribution of this study is to propose a new visual-inertial SLAM method combining point-line features, which can achieve good localization effect in low-light and weak-texture scenes, with higher accuracy and robustness.

The purpose of this paper is to test an online apparel co-design experience model and to investigate six determinants (perceived ease of use, perceived usefulness, enjoyment, level of personalization, social presence, and attitude towards the co-designed product) of online apparel co-design experience and effects on behavioural intention.

Female college students (n=265) were surveyed after an actual online apparel co-design experience in a computer lab and interactions with other users wherever such arenas were provided. structural equation modelling was used for data analysis.

The findings revealed that subjects’ apparel co-design experience was positively affected by enjoyment, attitude towards the co-designed product, perceived ease of use, and social presence. And behavioural intention towards the mass customization sites was positively affected by subjects’ attitude towards the co-design experience, subjective norm, and enjoyment.

The research makes a unique theoretical contribution by conceptualizing MC 2.0 (MC sites that provide arenas for user interaction) and by incorporating and confirming the significance of both “enjoyment” and “social presence” variables as predictors of online apparel co-design experience.

The purpose of this paper is to conduct performance evaluation of eight main scientific data sharing platforms in China and find existing problems, thus providing reference for maximizing the value of scientific data and enhancing scientific research efficiency.

First, the authors built an evaluation indicator system for the performance of scientific data sharing platforms. Next, the analytic hierarchy process was employed to set indicator weights. Then, the authors use experts grading method to give scored for each indicator and calculated the scoring results of the scientific data sharing platform performance evaluation. Finally, an analysis of the results was conducted.

The performance evaluation of eight platforms is arranged by descending order by the value of F: the Data Sharing Infrastructure of Earth System Science (76.962), the Basic Science Data Sharing Center (76.595), the National Scientific Data Sharing Platform for Population and Health (71.577), the China Earthquake Data Center (66.296), the China Meteorological Data Sharing Service System (65.159), the National Agricultural Scientific Data Sharing Center (55.068), the Chinese Forestry Science Data Center (56.894) and the National Scientific Data Sharing & Service Network on Material Environmental Corrosion (Aging) (52.528). And some existing shortcomings such as the relevant policies and regulation, standards of data description and organization, data availability and the services should be improved.

This paper is mainly discussing about the performance evaluation system covering operation management, data resource, platform function, service efficiency and influence of eight scientific data sharing centers and made comparative analysis. It reflected the reality development of scientific data sharing in China.

As artificial intelligence technology empowers service robots, they increasingly communicate with consumers in a human-like manner. This study aims to investigate the effect of service robots’ different conversational styles (competent conversational style vs. cute conversational style) on consumer service acceptance and demonstrate the moderating role of consumers’ technology anxiety.

Based on anthropomorphism theory and social presence theory, the authors conducted two scenario-based experiments (restaurant scenario and hotel scenario) to investigate this issue.

The results indicate that service robots’ conversational styles impact consumers’ willingness to accept the use of service robots through perceived social presence and positive emotion. Moreover, consumers perceived social presence and positive emotion play a serial mechanism. In addition, the effect of competent conversational style on consumers perceived social presence is less effective than that of cute conversational style. Finally, the authors demonstrate the moderating role of consumer technology anxiety in the relationship between conversational styles and perceived social presence.

To provide consumers with a positive human–robot interaction experience at the service front line, managers need to make better use of the conversational styles of service robots by comprehensively considering the characteristics of consumer technology anxiety.

This research extends the literature on service robots by integrating consumer characteristics and robots’ conversational styles. These findings highlight the effectiveness of cute conversational style in alleviating consumer technology anxiety.