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Motivating users to self-disclose online is significant to the long-term development of social media. Therefore, research on emotional disclosure, a significant form of self-disclosure, is required. By developing a stimulus-organism-response model, this study aims to investigate the mechanisms by which the social media environment affects users' online emotional disclosure.

This paper proposes two dimensions of social media environments, the online interpersonal environment (tie strength and network size) and the online information environment (self-reference). They are hypothesized to stimulate users' internal psychological needs (image management and emotional expression) which in turn will influence their emotional disclosure intentions. Using data from 489 users of WeChat Moments, the authors conduct partial least squares analysis to validate the research model.

The findings show that users' intrinsic psychological needs are stimulated by social media environments, but network size is not correlated with the need for emotional expression. The user's need for emotional expression promotes both positive and negative emotional disclosure intentions. The need for image management has a positive impact on positive emotion disclosure intentions but has a negative impact on negative emotion disclosure intentions.

This study contributes to the understanding of online emotional disclosure. It can also help social media managers create efficient plans to encourage users to create content.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2022-0245.

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.

Under the rural revitalization, the effect of China's implementation of rural prefabricated housing is not obvious. Cost has become the biggest obstacle to its development. Therefore, it is necessary to study the factors influencing the cost of prefabricated buildings in villages and clarify the focus of cost control.

This paper focuses on the whole process of prefabricated housing construction in villages in China and uses grounded theory to identify and screen out 27 related factors that affect the construction cost of prefabricated buildings. A system dynamics model is used to dynamically analyze the influencing factors. The engineering examples in rural areas of southern Shaanxi are simulated. Finally, five key factors that influence cost are obtained. Based on this, cost control countermeasures are proposed for rural prefabricated housing in southern Shaanxi.

The results show that: the key factors affecting the cost of prefabricated buildings in villages include the selection of production methods, the degree of design standardization, the quality of construction personnel, the level of construction technology and the circulation cycle of molds. The cost of prefabricated housing in villages can be controlled through five aspects: mass production of components, design exchange and feasibility analysis, improvement of employee professionalism, strict selection of construction schemes and technologies and improvement of mold turnover rate.

The system dynamics model applied in this paper is based on the idealized state. The system boundary is narrow and has a certain subjectivity. It needs further detailed research to make it closer to the engineering practice. In addition, this paper applies the rural engineering example in southern Shaanxi to carry out a single case study, and the universality of the research results needs to be further tested. There are many village construction projects and building types, so the research results can be further enriched through large sample research.

Rural construction is an important step in the implementation of rural revitalization. Exploring the factors that affect the key costs of prefabricated buildings in villages and towns in view of the particularity of rural areas will help provide a reference for their cost control and help the rural development of prefabricated houses.

The research results of this paper can provide a reference for the development of prefabricated buildings in other rural revitalization areas.

Different from the traditional research on urban prefabricated buildings, this paper focuses on rural areas and explores the core factors affecting the cost of prefabricated buildings from the micro level. This study establishes a system dynamics model suitable for the cost control of prefabricated housing at the village level and provides methods for its cost control. Based on the identified key factors affecting costs, cost control measures were proposed for prefabricated housing tailored to the unique characteristics of villages.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.

There is growing scholarly interest in the use of penalty in employment contracts which reduce employees' pay if the employee's performance does not meet a pre-specified performance threshold. Prior accounting research has focused exclusively on the effect of penalty on employee performance. In this study, the authors extend earlier research by examining how penalty affects the employers' wage offers. Prior research suggests that employers' generous wage offers in employment contracts are normally translated as trust by employees who in turn reciprocate with higher effort. The authors present a theory that predicts penalty reduces employers' wage offers. Then, the authors propose unrestricted communication between employers and employees as a potential moderator for the negative effect of penalty on trust and reciprocity.

The authors implement a controlled lab experiment with a 2 × 3 experimental design (Penalty: Present and Absent; and Communication: None, One-Way and Two-Way).

The authors develop their predictions by utilizing insights from motivational-crowding and organizational communication theories. The authors hypothesize and find evidence that employers' ability to penalize employees can reduce employers' motivation to offer generous wages. As a result, reduced trust demotivates employees to provide high effort. However, the authors find that a two-way communication moderates the negative effect of penalties by restoring trust, thereby, increasing reciprocity. Finally, the authors find evidence that relationship-oriented messages explain the moderating effect of communication.

This study is subject to limitations inherent in all experimental studies. The decisions in the study experiment are less complex than those found in practice. Moreover, there are significantly higher costs and potential benefits to shirk on effort in practice. The authors encourage future research on other organizational features that would influence the generalizability of their theory and results. Nonetheless, this study makes an important contribution to the literature on trust, reciprocity, gift-exchange contracts, managerial controls and communication.

This paper has several important implications for theory and practice. The authors show that the presence of penalty may not automatically result in increasing employees' effort level, contrary to traditional economic theory predictions. This effect is driven mainly by the crowding out effect of a penalty on employers' desire to signal trust. Therefore, the presence of an open communication channel may become an important tool to reverse the psychological effect of reduced trust when penalty is present. Therefore, the study's findings contribute to the trust–reciprocity literature on how management control system influences employers' and employees' behavior. These findings are especially germane given the trend in the workplace toward establishing open communication at different levels within the firm hierarchy. The study also contributes to the literature on trust–reciprocity as critical informal controls and social norms in accounting practices (Bicchieri, 2006; Stevens, 2019), shedding light on how firms may influence employees' reciprocity in management control practices and induce them to act in line with the firm's objectives by opening communication channels.

Prior accounting research document that penalty in employment contracts increases employee performance due to loss aversion. The study, however, demonstrates that the positive effect of penalty is not sustained in a gift-exchange contract. Specifically, the study's experimental results provide evidence that the availability of penalties can psychologically change the way employers perceive their decisions on offering generous wages (i.e. trust) and consequently reduce employees' reciprocation of high effort levels. Yet, the authors propose a two-way communication as a restorative mechanism for the lost trust. Implications for theory and practice are discussed.

This study aims to explore the role of urban streets as transitional edges in coordinating socio-spatial interactions within the urban environment. It will focus on how streets can revitalize their surrounding environments and shape sustainable urban living through their characteristics.

Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, this study systematically reviewed 67 international research articles published from 2013 to 2023. It delved into the functionalities of urban streets as transitional edges under various social and physical interactions, covering the multidimensional impacts of streets at the social, spatial and individual levels.

The results demonstrate that the physical and social dimensions of streets, through their characteristics as transitional edges, not only complement each other but also effectively promote social space interactions and sustainable urban development. As a key public space at the interface of social and physical realms, streets influence residents' daily lives and balance the socio-spatial environment.

Although this study deepens the understanding of urban streets as transitional edges, it faces limitations due to the scarcity of literature related to transitional edges, which may affect the depth and breadth of the research. Future studies are required to further verify theoretical findings through field research and case studies and to explore practical applications of street design to enhance data comprehensiveness and availability.

The originality of this article lies in defining urban streets as dynamic transitional edge spaces, redefining their dual role in urban design to connect physical forms and social functions. Through a comprehensive literature review, this study provides theoretical support for urban planning and design practices, emphasizing their application value in promoting urban social interaction and sustainable development.

The study aims to devise a comprehensive evaluation model (CEM) for evaluating spatial equity in the layout of elderly service facilities (ESFs) to address the inequity in the layout of ESFs within city center communities characterized by limited land resources and a dense elderly population.

The CEM incorporates a suite of analytical tools, including accessibility assessment, Lorenz curve and Gini coefficient evaluations and spatial autocorrelation analysis. Utilizing this model, the study scrutinized the distributional equity of three distinct categories of ESFs in the city center of Xi’an and proposed targeted optimization strategies.

The findings reveal that (1) there are disparities in ESFs’ accessibility among different categories and communities, manifesting a distinct center (high) and periphery (low) distribution pattern; (2) there exists inequality in ESFs distribution, with nearly 50% of older adults accessing only 18% of elderly services, and these inequalities are more pronounced in urban areas with lower accessibility, and (3) approximately 14.7% of communities experience a supply-demand disequilibrium, with demand surpassing supply as a predominant issue in the ongoing development of ESFs.

The CEM formulated in this study offers policymakers, urban planners and service providers a scientific foundation and guidance for decision-making or policy amendment by promptly assessing and pinpointing areas of spatial inequity in ESFs and identifying deficiencies in their development.

Productivity is often cited as a key barrier to the adoption of metal laser-based powder bed fusion (ML-PBF) technology for mass production. Newer generations of this technology work to overcome this by introducing more lasers or dramatically different processing techniques. Current generation ML-PBF machines are typically not capable of taking on additional hardware to maximise productivity due to inherent design limitations. Thus, any increases to be found in this generation of machines need to be implemented through design or adjusting how the machine currently processes the material. The purpose of this paper is to identify the most beneficial existing methodologies for the optimisation of productivity in existing ML-PBF equipment so that current users have a framework upon which they can improve their processes.

The review method used here is the preferred reporting items for systematic review and meta-analysis (PRISMA). This is complemented by using an artificial intelligence-assisted literature review tool known as Elicit. Scopus, WEEE, Web of Science and Semantic Scholar databases were searched for articles using specific keywords and Boolean operators.

The PRIMSA and Elicit processes resulted in 51 papers that met the criteria. Of these, 24 indicated that by using a design of experiment approach, processing parameters could be created that would increase productivity. The other themes identified include scan strategy (11), surface alteration (11), changing of layer heights (17), artificial neural networks (3) and altering of the material (5). Due to the nature of the studies, quantifying the effect of these themes on productivity was not always possible. However, studies citing altering layer heights and processing parameters indicated the greatest quantifiable increase in productivity with values between 10% and 252% cited. The literature, though not always explicit, depicts several avenues for the improvement of productivity for current-generation ML-PBF machines.

This systematic literature review provides trends and themes that aim to influence and support future research directions for maximising the productivity of the ML-PBF machines.

An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors detect the level of waste in the dustbin. The data collected by the IoT sensor is stored in the blockchain. Here, an adaptive deep Markov random field (ADMRF) method is implemented to determine the weight of the wastes. The performance of the ADMRF is boosted by optimizing its parameters with the help of the improved corona virus herd immunity optimization algorithm (ICVHIOA). Here, the main objective of the developed ADMRF-based waste weight prediction is to minimize the root mean square error (RMSE) and mean absolute error (MAE) rate at the time of testing. If the weight of the bins is more than 80%, then an alert message will be sent to the waste collector directly. Optimal route selection is carried out using the developed ICVHIOA for efficient collection of wastes from the smart bin. Here, the main objectives of the optimal route selection are to reduce the distance and time to minimize the operational cost and the environmental impacts. The collected waste is then considered for recycling. The performance of the implemented IoT and blockchain-based smart dustbin is evaluated by comparing it with other existing smart dustbins for e-waste management.

The developed e-waste management system is used to collect the waste and to avoid certain diseases caused by the dumped waste. Disposal and recycling of the e-waste is necessary to decrease pollution and to manufacture new products from the waste.

The RMSE of the implemented framework was 33.65% better than convolutional neural network (CNN), 27.12% increased than recurrent neural network (RNN), 22.27% advanced than Resnet and 9.99% superior to long short-term memory (LSTM).

The proposed E-waste management system has given an enhanced performance rate in weight prediction and also in optimal route selection when compared with other conventional methods.

Asteroids have the characteristics of noncooperative, irregular gravity and complex terrain on the surface, which cause difficulties in successful landing for conventional landers. The purpose of this paper is to study the trajectory tracking problem of a multi-node flexible lander with unknown flexible coefficient and space disturbance.

To facilitate the stability analysis, this paper constructs a simplified dynamic model of the multi-node flexible lander. By introducing the nonlinear transformation, a concurrent learning-based adaptive trajectory tracking guidance law is designed to ensure tracking performance, which uses both real-time information and historical data to estimate the parameters without persistent excitation (PE) conditions. A data selection algorithm is developed to enhance the richness of historical data, which can improve the convergence rate of the parameter estimation and the guidance performance.

Finally, Lyapunov stability theory is used to prove that the unknown parameters can converge to their actual value and, meanwhile, the closed-loop system is stable. The effectiveness of the proposed algorithm is further verified through simulations.

This paper provides a new design idea for future asteroid landers, and a trajectory tracking controller based on concurrent learning and preset performance is first proposed.