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The role of conventional contracts in achieving sustainability goals in public–private partnership (PPP) projects has been questioned. From the multifunctional perspective of contract theory, joint-contract functions that combine contractual control, coordination and adaptation may be a potential approach for improving PPP project sustainability performance. This research intends to investigate the link between the joint-contract functions and PPP project sustainability performance, and their underlying mechanism, by analyzing the mediating role of relationship quality and moderating roles of environmental uncertainty and behavioral uncertainty.

Based on 170 valid survey data collected from the Chinese PPP professionals, partial least squares structural equation modeling (PLS-SEM) was adopted to test the hypothesis.

The results reveal that joint-contract functions are positively associated with the PPP project sustainability performance. This relationship is strengthened by environmental and behavioral uncertainty. Moreover, the relationship between the joint-contract functions and PPP project sustainability performance is mediated by relationship quality.

This research extends contract governance theory and sustainability research in PPP projects. The research implications are as follows: (1) joint-contract functions are a second-order construct consisting of three first-order dimensions: control, coordination and adaptation and are positively associated with PPP project sustainability performance; (2) joint-contract functions enhance the sustainable benefits of PPP projects during environmental uncertainty and behavioral uncertainty; (3) informal relationships are a critical bridge connecting formal institutions with the sustainability performance of PPP projects.

In general, these findings guide project participants who aim to achieve sustainable outcomes in PPP projects. (1) Project participants should consider the process of contract design and sign contracts that focus on joint-contract functions. (2) Project participants should investigate the degree of uncertainty of a PPP project before designing contracts, and design the contracts with corresponding complexity. (3) Project participants should work to enhance PPP sustainable benefits by improving the relationship between partners, such as encouraging mutual trust and joint problem-solving.

This research verifies the relationship between joint-contract functions and PPP project sustainability performance, and the boundary and intermediary conditions between them.

The purpose of this study is to investigate the influence of texture on hydrodynamic lubrication performance of slide surface from the perspective of skewness and kurtosis.

Hydrodynamic lubrication theoretical model of textured surface was established based on two-dimensional Reynolds equation, and finite difference algorithm was used as the numerical approach in the paper. Skewness and kurtosis of surface were obtained by discrete calculation.

Numerical analysis results show that the influence law of texture types on skewness, kurtosis and hydrodynamic lubrication was the more negative skewness and higher kurtosis, the better hydrodynamic lubrication performance when texture cross section contour and geometric parameters were the same. Similarly, the same influence law of skewness, kurtosis and hydrodynamic lubrication performance by texture cross-section contour was observed. However, it was unable to evaluate the effect of texture angle on hydrodynamic lubrication performance of textured surface from the perspective of skewness and kurtosis.

This paper confirms the feasibility of evaluating influence of texture types and texture cross-section contour on hydrodynamic lubrication performance from the perspective of skewness and kurtosis and provides a way to optimize texture type and texture cross section.

This paper aims to examine the effects of managerial ability (MA) on the likelihood and the timeliness of goodwill impairment and explore whether the desirable effect of MA vary with the degree of agency problems.

The authors propose a unified framework to simultaneously examine the effects of MA on the likelihood and the timeliness of goodwill impairment by incorporating a market-based impairment indicator (denoted as BTM), MA and the interaction of BTM with MA to this study’s regression model to account for the likelihood of goodwill impairment. BTM addresses the timeliness of goodwill impairment.

This study finds that firms with higher MA have lower likelihood of goodwill impairment, and such firms are more likely to recognize goodwill impairment in a timely manner when the underlying value of goodwill is economically impaired. This desirable effect of MA is more pronounced in non-state-owned enterprise (SOEs) and firms without chief executive officer (CEO) duality.

Firms can reduce the losses arising from goodwill impairment by enhancing the ability of their management teams combined with improved corporate governance structure.

This paper provides novel insights on understanding the role of MA in not only reducing the likelihood but also enhancing the timeliness of goodwill impairment. The findings help advance the upper echelons theory by uncovering the heterogenous effects of executives with different levels of ability.

Nowadays, the global agricultural system is highly dependent on the widespread use of synthetic pesticides to control diseases, weeds and insects. The unmanned aerial vehicle (UAV) is deployed as a major part of integrated pest management in a precision agriculture system for accurately and cost-effectively distributing pesticides to resist crop diseases and insect pests.

With multimodal sensor fusion applying adaptive cubature Kalman filter, the position and velocity are enhanced for the correction and accuracy. A dynamic movement primitive is combined with the Gaussian mixture model to obtain numerous trajectories through the teaching of a demonstration. Further, to enhance the trajectory tracking accuracy under an uncertain environment of the spraying, a novel model reference adaptive sliding mode control approach is proposed for motion control.

Experimental studies have been carried out to test the ability of the proposed interface for the pesticides in the crop fields. The effectiveness of the proposed interface has been demonstrated by the experimental results.

To solve the path planning problem of a complex unstructured environment, a human-robot skills transfer interface is introduced for the UAV that is instructed to follow a trajectory demonstrated by a human teacher.

In manufacturing environments, mobile radio frequency identification (RFID) robots need to quickly identify and collect various types of passive tag and active tag sensor data. The purpose of this paper is to design a robot system compatible with ultra high frequency (UHF) band passive and active RFID applications and to propose a new anti-collision protocol to improve identification efficiency for active tag data collection.

A new UHF RFID robot system based on a cloud platform is designed and verified. For the active RFID system, a grouping reservation–based anti-collision algorithm is proposed in which an inventory round is divided into reservation period and polling period. The reservation period is divided into multiple sub-slots. Grouped tags complete sub-slot by randomly transmitting a short reservation frame. Then, in the polling period, the reader accesses each tag by polling. When tags’ reply collision occurs, the reader tries to re-query collided tags once, and the pre-reply tags avoid collisions through random back-off and channel activity detection.

The proposed algorithm achieves a maximum theoretical system throughput of about 0.94, and very few tag data frame transmissions overhead. The capture effect and channel activity detection in physical layer can effectively improve system throughput and reduce tag data transmission.

In this paper, the authors design and verify the UHF band passive and active hybrid RFID robot architecture based on cloud collaboration. And, the proposed anti-collision algorithm would improve active tag data collection speed and reduce tag transmission overhead in complex manufacturing environments.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

Based on role theory, from the perspective of workplace behaviors (proactive behavior, in-role behavior and organizational citizenship behavior), this paper provides a perspective of matching process on the importance of fit in personnel selection.

Using a sample of 231 leader–employee dyadic in a two-wave survey, the hypotheses were demonstrated with hierarchical regression analyses.

The results presented that: (1) Employees' perceptions of implicit leadership prototype fit and leaders' perceptions of implicit followership prototype fit were positively related to employees' workplace behaviors; (2) Employees' perceptions of implicit leadership prototype fit and leaders' perceptions of implicit followership prototype fit increased person-supervisor fit; (3) The influence of the interaction between employees' perceptions of implicit leadership prototype fit and leaders' perceptions of implicit followership prototype fit on employees' workplace behaviors will be mediated, first by person-supervisor fit and then by work engagement.

This study introduces the perspective of matching process that reflects the relative importance of fit in personnel selection. The results also enriched role theory from the perspective of implicit prototype fit, which provides an important basis for managers to effectively use managerial cognition and inspire employees' positive workplace behaviors.

The purpose of this paper is to present an integrated data-driven framework for processing and analyzing large-scale vehicle maintenance records to get more comprehensive understanding on vehicle quality.

We propose a framework for vehicle quality analysis based on maintenance record mining and Bayesian Network. It includes the development of a comprehensive dictionary for efficient classification of maintenance items, and the establishment of a Bayesian Network model for vehicle quality evaluation. The vehicle design parameters, price and performance of functional systems are modeled as node variables in the Bayesian Network. Bayesian Network reasoning is then used to analyze the influence of these nodes on vehicle quality and their respective importance.

A case study using the maintenance records of 74 sport utility vehicle (SUV) models is presented to demonstrate the validity of the proposed framework. Our results reveal that factors such as vehicle size, chassis issues and engine displacement, can affect the chance of vehicle failures and accidents. The influence of factors such as price and performance of engine and chassis show explicit regional differences.

Previous research usually focuses on limited maintenance records from a single vehicle producer, while our proposed framework enables efficient and systematic processing of larger-scale maintenance records for vehicle quality analysis, which can support auto companies, consumers and regulators to make better decisions in purchase choice-making, vehicle design and market regulation.

This study aims to explore the perspectives of patrons and the underlying factors influencing luxury consumption in British Michelin-starred restaurants. While numerous studies have investigated consumers' purchase behavior of luxury items, there is limited research focusing on the utilization of premium restaurant services. Additionally, the hospitality literature has rarely addressed the emergence of discreet luxury consumption. Therefore, this research aims to examine the experiences of British Michelin-starred restaurants by incorporating online reviews from some of the most renowned establishments in the country. The initial objective of this study was to identify the predominant themes within British Michelin-starred restaurant experiences. Furthermore, the authors sought to analyze whether these main themes varied across different market segments based on guest types.

Using text mining tools, the authors analyzed a sample of 4,393 online reviews. Qualitative data analysis was conducted using the Leximancer program, which identified the dominant themes. Additionally, the authors performed an analysis to identify the major narratives associated with different types of guests.

The results of this analysis demonstrate that guests express a high level of satisfaction with their experiences at British Michelin-starred restaurants. The dominant themes within the narratives include food, wine, restaurant, time, reservation and innovation. It is important to note that these narratives vary depending on the type of guest.

Previous studies have highlighted the importance of market segmentation in Michelin-starred restaurants. This research addresses this need by specifically categorizing British Michelin-starred restaurants based on traveler type and the main concerns of their customers. The extensive data the authors collected and the authors' approach to utilizing guests' testimonials instead of traditional surveys contribute significantly to the field of academia and restaurant management.