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This study aims to introduce and prove the existence of negative rivalry in use, which should be an integral part of goods taxonomy, from the perspective of knowledge sharing and further present the critical role of knowledge sharing in the digital economy era by reviewing the literature, theoretical analysis and real-world cases. It also aims to open a new door for re-recognizing knowledge sharing through an interdisciplinary framework.

This study proves the existence of negative rivalry through both theoretical analysis (4-E model) and real-world cases, especially the cases of Tesla and ChatGPT, and puts up new reasons for knowledge sharing in the era of digital economy through interdisciplinary methods.

The authors find out that there are many new phenomena beyond the spectrum of current goods taxonomy, especially beyond the priori understanding of rivalry in use. Digital platforms such as ChatGPT should have been “used up” in no time, for they have attracted so massive users according to (positive) rivalry in use, or should have been unchanged at most according to non-rivalry in use. But what we see is their rapid upgrading with the help of billions of users. The reason is that negative rivalry in use has completely been neglected. The authors find out that the process of knowledge sharing unveils the unrecognized attribute of rivalry in use, i.e. negative rivalry in use, which serves as the fundamental driving force of the breathtaking growth of all kinds of digital platforms.

This study originally put up a 4-E model of goods’ rivalry in use, the brand new term, i.e. negative rivalry in use, and proves its existence and working mechanism from the perspective of knowledge sharing. With the introduction of negative rivalry in use, the traditional four-type goods classification model is extended into a six-type model, which may be a sound marginal contribution, to the best of the authors’ knowledge. The study may reshape people’s mindsets on goods usage, especially knowledge management, into a more open-sharing model because it shows that there is very likely a positive-sum game instead of a zero- or negative-sum game for shared knowledge per se and its platform in the process of knowledge sharing in the era of digital economy.

With the explosive growth of the Internet, online travel agents (OTAs) have gained an increasing market share in the online booking market. However, OTAs are facing fierce competition from hotels' direct booking channels, as well as competition among themselves. Therefore, there is a need for an understanding of the evolution of the OTA market from a dynamic perspective. The purpose of this study is to investigate the long-term effect of OTAs on the hospitality industry and to find whether an equilibrium of this effect exists in the context of e-commerce.

To gain a better understanding of the OTA market process, a mathematical framework is constructed on the basis of four assumptions. NetLogo 5.1.0 is used to perform a series of numerical simulations.

The results indicate the following: (1) the development of the OTA market helps to improve net social welfare, but hotels (especially economy hotels) have suffered as a result; (2) clever exploitation of both online and offline channels that are based on hotels' historical data may improve hotels' performance; (3) a scale-priority strategy can be more helpful than a profit-priority strategy for enabling OTAs to maintain their long-term competitiveness; (4) the timing of participation in online-channel competition is a crucial factor in determining whether OTAs can achieve business success.

In this study, it is shown how consumer habits have changed since the development of OTAs. The online channels provided by OTAs create a convenient, low-cost user experience, and they consequently improve the net welfare of customers. OTAs should be encouraged appropriately, although some economy hotels may suffer from the rise of OTAs.

In this empirical study, a mathematical framework is developed to describe the process of evolution in the OTA market, and it uses simulations as a means to validate prior research findings. Unlike previous studies, a dynamic perspective is used in this investigation to interpret the emergence of OTAs and to analyze their enormous impact on the hospitality industry. Thus, the findings of this study capture the competitive characteristics of online and offline channels in a network context and indicate potential strategies for the development of OTAs and which hotels may use OTAs to achieve better performance. In addition, the study findings could be easily extended to explain many of the classical economic phenomena regarding firms with intangible products.

This paper aims to propose a normal and tangential contact stiffness model to investigate the contact characteristics between rough surfaces of machined joints based on fractal geometry and contact mechanics theory considering surface asperities interaction.

The fractal geometry theory describes surface topography and Hertz contact theory derives the asperities elastic, elastic-plastic and plastic contact deformation. The joint normal and tangential contact stiffness are obtained. The experiment method for normal and tangential contact stiffness are introduced.

The relationship between dimensionless normal contact load and dimensionless normal and tangential contact stiffness are analyzed in different plasticity index. The results show that they are nonlinear relationships. The normal and tangential contact stiffness are obtained based on theoretical and experimental methods for milling and grinding machined specimens. The results indicate that the present model for the normal and tangential contact stiffness are consistent with experimental data, respectively.

The normal and tangential contact stiffness models are constructed by using the fractal geometry and the contact mechanics theory considering surface asperities interaction, which includes fully elastic, elastic-plastic and fully plastic contacts deformation. The present method can generate a more reliable calculation result as compared with the contact model no-considering asperities interaction.

With the increasing use of small unmanned aircrafts (SUAs), many countries have enacted laws and regulations to ensure the safe use of SUAs. However, there is a lack of industry-specific regulations accounting for the unique features of construction-related SUA operations. Operating SUAs in the construction industry is attributed to specific risks and challenges, which should be regulated to maximize the utility of SUAs in construction. This study, therefore, aims to develop a multi-dimensional regulatory framework for using SUAs in the construction industry.

A combination of quantitative and qualitative methods was used to compare seven selected national/regional SUA regulations to identify the applicability of implementing the existing regulations in construction. The interview surveys were then conducted to diagnose the challenges of construction-related SUA operations and gather interviewees' suggestions on the regulatory framework for SUA uses in construction.

The research found that some challenges of construction-related SUAs operations were not addressed in the current regulations. These challenges included the complex and time-consuming SUA operation permit, lack of regulation for special SUA operations in construction, insufficient regulatory compliance monitoring and a lack of construction-related remote pilots' training. A regulatory framework was then developed based on the findings of comparative analysis and interview surveys.

This study mainly compared seven representative countries/regions' regulations, leading to a small sample size. Further research should be carried out to study the SUA regulations in other places, such as South Africa, South America or Middle East countries. Besides, this study's respondents to the interviews were primarily concentrated in Hong Kong, which may cause the interview results to differ from the construction industry in other countries/regions. A large-scale interview survey should be conducted in other places in the future to validate the current findings.

The proposed regulatory framework provides a reference for the policy-makers to formulate appropriate industry-specific SUA regulations and improve the applicability of SUA regulations in the construction industry. It sheds light upon the future of SUA regulations and the development of regulatory practice in this area.

This study is the first to propose a multi-dimensional regulatory framework for operating SUAs in construction by comprehensive policy comparisons and interviews. The regulatory framework offers a fresh insight into the unexplored research area and points out the direction for subsequent studies on SUA regulations in the construction industry.

This paper aims to explore the influence of social support and the repatriation intention of expatriates in international constructions in the postpandemic era of COVID-19. Furthermore, test the mediation effect of team climate and individual resilience in this relationship.

A survey of 347 expatriates in international construction projects was conducted. A cross-level chain mediation model was employed to test the moderating effect of social support and repatriation intention. Then, statistical analysis with a bootstrap sample was used to test the mediation effect of the model.

The empirical results support that team climate, individual resilience and the chain mediating effect of team climate to individual resilience is significant among the influences of social support on repatriation intention. Social support can enhance the team climate of construction expatriates, promoting their resilience to reduce the repatriation intention further.

This study provides guidelines for international construction enterprises and managers to decide when and which expatriates should return home and formulate a series of policies to support expatriates and maintain a good team climate.

This study contributes to expatriate management literature by establishing the relationship between social support and repatriation intention. It provides a better understanding of how team-level factors impact individual thought. It takes team climate as one of the protective factors affecting individual psychological resilience. Also it takes social support as the antecedents of team atmosphere in case of emergencies.

Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack contributes to establishing an appropriate road maintenance and repair strategy from the promptly informed managers but still remaining a significant challenge. This research seeks to propose practical solutions for targeting the automatic crack detection from images with efficient productivity and cost-effectiveness, thereby improving the pavement performance.

This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features for enhancing automatic identification. Afterward, the detected cracks are used to quantify morphological features from five indicators, such as length, mean width, maximum width, area and ratio. Those analyses can provide valuable information for engineers to assess the pavement condition with efficient productivity.

In the training process, the TransUnet is fed by a crack dataset generated by the data augmentation with a resolution of 224 × 224 pixels. Subsequently, a test set containing 80 new images is used for crack detection task based on the best selected TransUnet with a learning rate of 0.01 and a batch size of 1, achieving an accuracy of 0.8927, a precision of 0.8813, a recall of 0.8904, an F1-measure and dice of 0.8813, and a Mean Intersection over Union of 0.8082, respectively. Comparisons with several state-of-the-art methods indicate that the developed approach in this research outperforms with greater efficiency and higher reliability.

The developed approach combines TransUnet with an integrated quantification algorithm for crack detection and quantification, performing excellently in terms of comparisons and evaluation metrics, which can provide solutions with potentially serving as the basis for an automated, cost-effective pavement condition assessment scheme.

This study explores how factors arising from supply chain (SC) network and complexity work together in supply chain learning (SCL) behavior.

Fuzzy set qualitative comparative analysis, which is an emerging configurational analysis method, was adopted to examine the complex combination of five influencing factors. The data were collected using a two-stage survey. First, the authors selected seven typical firms with an awareness of SCL. Second, questionnaires were sent to the partners of the seven selected firms, and 156 valid questionnaires were obtained from 76 firms.

Drawing on emergent insights from the initiative, the authors find that multiple configurations of SC network and complexity lead to high SCL. Specifically, weak ties are necessary conditions of such learning, while strong ties are also conducive to this. Moreover, a moderate SC complexity is conducive to SCL.

This study enriches the understanding of SCL and provides new insights for SC management practitioners to take measures to improve it.

This study addresses the lack of in-depth understanding of the antecedent conditions of SCL in the literature. It establishes an integrated and comprehensive theoretical framework of such learning based on contingency theory. Additionally, this study incorporates ambidextrous SCL (i.e. creation capability and dispersion capacity). An overall prototype of SCL capability is proposed on SC network and complexity theory.

The purpose of this paper is to provide additive manufacturing-based solutions for preparation of elastomeric foam with broaden compressive stress plateau.

Mechanic models are developed for obtaining designs of foam cell units with enhanced elastic buckling. An experimental approach is taken to fabricate the foams based on direct ink writing technique. Experimental and simulation data are collected to assist understanding of our proposals and solutions.

A simple tetragonal structured elastomeric foam is proposed and fabricated by direct ink writing, in which its cell unit is theoretically designed by repeating every four filament layers. The foam exhibits a broader stress plateau, because of the pronounced elastic buckling under compressive loading as predicted by the authors’ mechanic modeling. A two-stage stress plateaus as observed in the foam, being attributed to the dual elastic buckling of the cell units along two lateral directions of the XY plane during compression.

Future work should incorporate more microscopic parameters to tune the elastomeric foam for mechanic performance testing on linear elastic deformation and densification of polymer matrix.

Additive manufacturing offers an alternative to fabricate elastomeric foam with controlled cell unit design and therefore mechanics. Our results comment on its broad space for development such superior cushioning or damping material in the fields of vibration and energy absorption.

This work has contributed to new knowledge on preparation of high performance elastomeric foam by providing a better understanding on its cell structure, being printed using direct ink writing machines.

This study examines the effect of political networking capability (PNC) and strategic capability on exploratory innovation/exploitative innovation through the mediation of absorptive capability (AC).

Using empirical survey data collected from 153 traditional manufacturing firms (TMFs) in China, the authors apply partial least squares structural equation modeling (PLS-SEM) combined with mediation analyses to test hypotheses.

PNC has a higher impact on exploratory innovation than exploitative innovation through AC. The authors thus provide novel empirical insights into independent variables of firms' ambidextrous innovation and their implementation mechanisms.

The authors highlight a unique situation of China and contribute to the literature on PNC and AC. The findings demonstrate that AC plays an important role in configuring government-obtained external resources into new products, thus influencing ambidextrous innovation strategic decisions.

TMFs' executives should enhance PNC to obtain more resources to conduct exploratory and exploitative innovation. Government officials and policymakers should strengthen the supervision of TMFs' innovation activities and adopt effective measures to ensure that TMFs could conduct more exploratory innovation as governments expected.

This study provides new insights by bridging research gaps in the literature and advances the insights of how TMFs' PNC/strategic capability directly and indirectly fosters exploratory and exploitative innovation via the mediating role of AC in China.

This paper aims to systematically review the literature on quality management in agri-food supply chains (SCs) and propose an integrated conceptual framework.

A systematic literature review that analyses 93 papers in peer-reviewed academic journals published from 1996 to November 2021 is conducted. A conceptual model is advanced.

Based on a hierarchy of capabilities perspective, the authors develop an integrated conceptual framework in which SC quality (SCQ) management practices promote three levels of SC dynamic capabilities, which in turn lead to agri-food SCQ performance.

The authors propose a hierarchy of capabilities perspective of quality management in agri-food SCs and develop a conceptual framework. Furthermore, a number of propositions based on dynamic capabilities and the review findings are provided. Four future research directions are presented.