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This research navigates the confluence of data analytics, machine learning, and artificial intelligence to revolutionize the management of urban services in smart cities. The study thoroughly investigated with advanced tools to scrutinize key performance indicators integral to the functioning of smart cities, thereby enhancing leadership and decision-making strategies. Our work involves the implementation of various machine learning models such as Logistic Regression, Support Vector Machine, Decision Tree, Naive Bayes, and Artificial Neural Networks (ANN), to the data. Notably, the Support Vector Machine and Bernoulli Naive Bayes models exhibit robust performance with an accuracy rate of 70% precision score. In particular, the study underscores the employment of an ANN model on our existing dataset, optimized using the Adam optimizer. Although the model yields an overall accuracy of 61% and a precision score of 58%, implying correct predictions for the positive class 58% of the time, a comprehensive performance assessment using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) metrics was necessary. This evaluation results in a score of 0.475 at a threshold of 0.5, indicating that there's room for model enhancement. These models and their performance metrics serve as a key cog in our data analytics pipeline, providing decision-makers and city leaders with actionable insights that can steer urban service management decisions. Through real-time data availability and intuitive visualization dashboards, these leaders can promptly comprehend the current state of their services, pinpoint areas requiring improvement, and make informed decisions to bolster these services. This research illuminates the potential for data analytics, machine learning, and AI to significantly upgrade urban service management in smart cities, fostering sustainable and livable communities. Moreover, our findings contribute valuable knowledge to other cities aiming to adopt similar strategies, thus aiding the continued development of smart cities globally.

This study investigates the direct influence of ambidextrous leadership on employees’ innovation behaviour, the mediating role of innovative self-efficacy and harmonious work passion, and the moderating role of Zhong-Yong thinking.

The authors conducted a series of questionnaire surveys to collect data in three time periods and from multiple sources; 332 supervisor–subordinate matched samples were obtained. The hypothesised relationships were tested using structural equation modelling and ProClin.

Ambidextrous leadership is positively associated with employees’ innovation behaviour, while innovative self-efficacy and harmonious work passion play mediating roles. The analysis further confirms that innovative self-efficacy and harmonious work passion play a chained double-mediating role between ambidextrous leadership and employees’ innovation behaviour, while Zhong-Yong thinking plays moderating roles between ambidextrous leadership and innovative self-efficacy and between ambidextrous leadership and harmonious work passion.

This study demonstrates the influence of ambidextrous leadership on employees’ innovation behaviour, specifically the role of ambidextrous leadership, and extends the relationship’s theoretical foundation. It is also expected to provide inspiration and serve as a reference for local Chinese management.

This study aims to investigate dynamic relations among office property price indices of 10 major cities in China for the years 2005–2021.

Using monthly data, the authors adopt vector error correction modeling and the directed acyclic graph for the characterization of contemporaneous causality among the 10 indices.

The PC algorithm identifies the causal pattern, and the linear non-Gaussian acyclic model algorithm further determines the causal path from which we perform innovation accounting analysis. Sophisticated price dynamics are found in price adjustment processes following price shocks, which are generally dominated by the top tier of cities.

This suggests that policies on office property prices, in the long run, might need to be planned with particular attention paid to the top tier of cities.

The purpose of this study is to investigate the effect of nano ZrC particles on the mechanical and electrochemical corrosion properties of FeCrAl alloys, providing a beneficial reference basis for the development of high-performance carbide reinforced FeCrAl alloys with good mechanical and corrosion properties in the future.

Nano ZrC reinforced FeCrAl alloys were prepared by mechanical alloying and spark plasma sintering. Phases composition, tensile fractography, corrosion morphology and chemical composition of nano ZrC reinforced FeCrAl alloys were analyzed by X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy, respectively. Microhardness and tensile properties of nano ZrC reinforced FeCrAl alloys were investigated by mechanical testing machine and Vickers hardness tester. Electrochemical corrosion properties of nano ZrC reinforced FeCrAl alloys were investigated by electrochemical workstation in 3.5 wt.% NaCl solution.

The results showed that addition of nano ZrC can effectively improve the mechanical and corrosion properties. However, excessive nano ZrC could decrease the mechanical properties and reduce the corrosion resistance. In all the FeCrAl alloys, FeCrAl–0.6 wt.% ZrC alloy exhibits the optimum mechanical properties with an ultimate tensile strength, elongation and hardness of 990.7 MPa, 24.1% and 335.8 HV1, respectively, and FeCrAl–0.2 wt.% ZrC alloy has a lower corrosion potential (−0.179 V) and corrosion current density (2.099 µA/cm2) and larger pitting potential (0.497 V) than other FeCrAl–ZrC alloys, showing a better corrosion resistance.

Adding proper nano ZrC particles can effectively improve the mechanical and corrosion properties, while the excessive nano ZrC is harmful to the mechanical and corrosion properties of FeCrAl alloys, which provides an instruction to develop high-performance FeCrAl cladding materials.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

The study explores the relationship between the breadth of external pressures facing leaders of small and medium-sized enterprises (SMEs) and the entrepreneurial stance they adopt for their firm, that is, entrepreneurial orientation (EO).

Blending attention theory with EO literature, we argue that increasing breadth of external pressures will challenge leaders' attentions with implications for how they seek innovation, risk-taking and bold acts. We highlight an inflection point after which a negative relationship between the breadth of external pressure and EO will turn positive. We use data from a survey of 125 small-sized wineries in France to test this and capture a range of 15 external pressures on entrepreneurs.

The main tests and additional robustness tests provide support. It is the breadth of external pressures – as opposed to intensity of any one specific form of pressure – that plays a fundamental role in shaping leaders' adoption of EO in small enterprises over and above internal characteristics.

While the results may be context-dependent, they provide support for an attention-based view of entrepreneurial responses by leaders of SMEs under pressure.

SME leaders and entrepreneurs should be aware of how their attention is challenged by breadth of pressures from external sources, as this can influence the EO they adopt for their SME.

This nonlinear perspective on external pressures influencing the EO of small firms has not been taken in the EO literature to date, despite some recent work that considers only a small range of external pressures.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

The advent of the postpandemic era has brought renewed attention to the development of business tourism. However, the existing research on business tourism is fragmented, and there are gaps in the current understanding of the subject. This study aims to identify the intellectual structures, current hotspots and research directions in the business tourism field from 1994 to 2023.

A bibliometric visual analysis using VOSviewer was conducted to assimilate the available knowledge from 136 business tourism-related articles collected in the WoS Core Collection database between 1994 and 2023.

The results indicate that the number of business tourism-related research fluctuates, but the overall trend is gradually increasing. It synthesizes four main research themes, which are tourist behavior, destination marketing, information technology and work-family interferences of business travelers.

To the best of the authors’ knowledge, this study is among the first to systematically review business tourism publications over the past 29 years. It assists scholars in gaining a more comprehensive understanding of business tourism research and informs future research directions.

后疫情时代的到来使得商务旅游的发展再次受到关注。然而, 目前的商务旅游研究是零散的, 我们对与这一主题的理解存在空白。本研究旨在确定1994至2023年商务旅游相关领域的知识结构、当前热点和研究方向。

本研究使用VOSviewer进行了文献计量学可视化分析, 以吸收从Web of Science（WOS）核心合集数据库中收集的136 篇1994年至2023年间的商务旅游相关文章中的可用知识。

结果表明, 与商务旅游相关的研究数量呈现出波动但总体逐渐增加的趋势。其中包括四个主要的研究主题, 分别是游客行为、目的地营销、信息技术和商务旅行者的工作与家庭。

本研究系统回顾了过去29年间与商务旅游相关的出版物。从而有助于学者们对商务旅游研究有更全面地了解, 并获得未来的研究方向。

El advenimiento de la era postpandemia ha renovado la atención prestada al desarrollo del turismo de negocios. Sin embargo, la investigación existente sobre el turismo de negocios está fragmentada y existen lagunas en la comprensión actual del tema. El presente estudio tiene como objetivo identificar las estructuras intelectuales, los focos actuales y las direcciones de investigación en el ámbito del turismo de negocios desde 1994 hasta 2023.

Se realizó un análisis visual bibliométrico utilizando VOSviewer para asimilar el conocimiento disponible en 136 artículos relacionados con el turismo de negocios recogidos en la base de datos WoS Core Collection entre 1994 y 2023.

Los resultados indican que el número de investigaciones relacionadas con el turismo de negocios fluctúa, pero la tendencia general es a aumentar gradualmente. Se sintetizan cuatro temas principales de investigación: el comportamiento del turista, el marketing de destinos, la tecnología de la información y las interferencias trabajo-familia de los viajeros de negocios.

Este estudio es uno de los primeros que revisa sistemáticamente las publicaciones sobre turismo de negocios de los últimos 29 años. Ayuda a los investigadores a obtener una comprensión más completa de la investigación sobre el turismo de negocios y sugiere futuras líneas de investigación.

This study aims to provide a precise understanding of how corporate sustainability information is used in socially responsible investing (SRI). The study is motivated by the lack of a recognised body of knowledge on this issue. This study, therefore, collates and reviews relevant studies (67 studies) to provide guidance to investors interested in SRI and identify a research agenda for academics desiring to contribute to this area.

This study conducts a systemic literature review employing recognised key words and searching the Web of Science. HistCite is utilised to ensure important cited studies are not missed from the collection. The review was conducted from two perspectives: (1) sources of sustainability information and (2) how the information is used in SRI.

The review identifies five major sources of sustainability information, including corporate reports, ESG ratings, industry affiliation, news and private communication with firms. These sources of information play different roles in the cross section of SRI strategies (i.e. negative and positive screening, active ownership and integration). This study provides guidance on how to use this information in SRI and provides recommendations for future research on how analysts interact with the information, how different informational characteristics impact implementation, ways to improve data quality, improvements to analysis methods and where data use needs to be extended into new strategies.

This review contributes to the SRI literature by inventorying studies of an important, yet omitted aspect, namely, sustainability information. This work also enriches the literature on corporate sustainability information by investigating how this information can be used for a specific purpose, namely, SRI. Given the increasing interest in SRI, this review will provide much-needed guidance for a range of practitioners, including investors and regulators.

This study argues that online user comments on social media platforms provide feedback and evaluation functions. These functions can provide services for the relevant departments of organizations or institutions to formulate corresponding public opinion response strategies.

This study considers Chinese universities’ public opinion events on the Weibo platform as the research object. It collects online comments on Chinese universities’ network public opinion governance strategy texts on Weibo, constructs the sentiment index based on sentiment analysis and evaluates the effectiveness of the network public opinion governance strategy adopted by university officials.

This study found the following: First, a complete information release process can effectively improve the effect of public opinion governance strategies. Second, the effect of network public opinion governance strategies was significantly influenced by the type of public opinion event. Finally, the effect of public opinion governance strategies is closely related to the severity of punishment for the subjects involved.

The theoretical contribution of this study lies in the application of image repair theory and strategies in the field of network public opinion governance, which further broadens the scope of the application of image repair theory and strategies.

This study expands online user comment research to network public opinion governance and provides a quantitative method for evaluating the effect of governance strategies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0269