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Institutional work mainly focused on the purposive action of rational actors. However, the evolution of institution is not only affected by deliberate actions but also by emergent strategic patterns. Through a qualitative study of emergent aggression strategy in a Chinese leading private firm, Gome, this paper aims to explore the role of emergent strategy in institutional work. The paper finds that emergent strategy influences the normative and cognitive institution unconsciously and offers actors specialized identities. The present analysis also suggests that the emergent strategy-based institution needs a supporting and repairing system for maintenance.

This study primarily considers the micro aspect of emergent strategy and institutional work. It calls for detailed observation, interviews and archival materials which can make up a comprehensive in-depth picture. The authors remain skeptical to what people claim and try to get multiple sources of information. Also, the topic the authors deal with is relatively under-researched, and it is valuable to get explorative richness. Therefore, an interpretive qualitative approach is adopted to investigate actual events from “the native’s” perspective.

We found that an emergent strategy, which is realized but without previous plans, can also construct a “proto-type institution”, only in an unconscious way. The precondition is that the strategic resources of the focal firm are abundant enough for it to set the criteria of inter-organizational sanctions and rewards. In addition, the authors believe that supportive system and repairing system underpin the maintenance of established institutions.

First, by combining the research on emergent strategy to institutional work, the authors extend the scope of the latter by adding unconscious institutional work. Even if the agent-based view is adopted, rational actors can still influence the institution. Second, the authors explored the institutional outcome of emergent strategy, which fills the paucity of strategy process research. Third, aggression, the specific emergent strategy in this paper, can be turned into “plans for the future”. Its prevalence in the emerging market will attract more academic attention.

The purpose of this paper is to present a unified approach to uncertainty and sensitivity analysis for camera calibration.

The approach is based on the fact that camera calibration is a problem of parameter estimation and the parameters of interest are given by the optimal solution of a least‐squares problem.

A system of linear equations relating the errors of the extracted feature points to the errors of the estimated parameters is derived, and the expression of the covariance matrix of the estimated parameters is given. Also, a system of linear equations characterizing the influence of the uncalibrated parameters on the calibrated ones is presented. Simulation results show that the camera's position and orientation are less sensitive to the lens distortion than the offset of the image center.

The models developed can be applied to optimize the layout of the calibration marks and design multiple‐stage calibration algorithm. The rationale can also find applications in image registration and robot calibration.

A generic approach is proposed to perform uncertainty and sensitivity analysis for camera calibration. By using the optimality condition for an unconstrained optimization problem, two mathematical models are developed in a unified framework.

The purpose of this study is to propose extended potentials and investigate the applicability of extended Finnis–Sinclair (FS) potential to Cr with the unit cell structure of body-centered cubic (BCC Cr).

The parameters of each potential are determined by fitting the elastic constants, cohesive energy and mono-vacancy formation energy. Furthermore, the ability of the extended FS potential to describe the crystal defect properties is tested. Finally, the applicability of reproducing the thermal properties of Cr is discussed.

The internal relationship between physical properties and potential function is revealed. The mathematical relationship between physical properties and potential function is derived in detail. The extended FS potential performs well in reproducing physical properties of BCC Cr, such as elastic constants, cohesive energy, surface energy and the properties of vacancy et al. Moreover, good agreement is obtained with the experimental data for predicting the melting point, specific heat and coefficient of thermal expansion.

In this study, new extended potentials are proposed. The extended FS potential is able to reproduce the physical and thermal properties of BCC Cr. Therefore, the new extended potential can be used to describe the crystal defect properties of BCC Cr.

Drawing on conservation of resources (COR) theory, this study aims to explore the influencing mechanism of exploitative leadership on knowledge hiding. Specifically, this study focuses on the mediating role of psychological distress and the moderating role of hostile attribution bias in affecting the mediation.

Data were collected from 324 employees of a high-technology company in China by a three-wave questionnaire survey. Hierarchical regression analysis and bootstrapping approach were employed to test hypotheses.

This study found that exploitative leadership was positively related to knowledge hiding and that psychological distress mediated this relationship. Moreover, the results revealed that the positive relationship between exploitative leadership and psychological distress and the indirect effect of exploitative leadership on knowledge hiding via psychological distress were stronger when hostile attribution was high rather than low.

The findings of this study offer guidance for managers to better undermine the negative effects of exploitative leadership.

First, this study extends the literature on exploitative leadership by verifying the positive effect of exploitative leadership on knowledge hiding. Second, this study enriches one’s understanding of the “black box” underlying the link between exploitative leadership and its consequences by demonstrating the mediating role of psychological distress. Third, by verifying the moderating role of hostile attribution bias, this study provides insights into the boundary conditions of the impact of exploitative leadership.

Servitization and research and development (R&D) innovation provide new developmental opportunities for transformation in the construction industry. This study aims to explore the transformative impact of servitization and R&D innovation on the value added of the construction industry, offering new insights into industry transformation and growth.

This study utilizes panel data from Chinese listed construction companies from 2014 to 2022 to empirically investigate the relationship among servitization, R&D innovation and value added in the construction industry. The data analysis is augmented by incorporating text mining techniques to rigorously investigate the interplay among servitization, R&D innovation and the value added within the construction industry.

The research findings indicate that the impact of servitization on value added follows a positive U-shaped relationship, while the influence of R&D innovation on value added exhibits an inverted U-shaped relationship. Additionally, innovation investment plays a negative moderating role in the relationship between servitization and value added.

This study reveals a fresh perspective on how construction companies can leverage servitization as a strategic pathway for transformation and competitive advantage. The research also lays a theoretical groundwork for future innovation investment strategies in the construction industry, emphasizing the need for a balanced approach to innovation investments to maximize value added.

As the market competition becomes increasingly intensive and the profit from traditional voice services margins gradually decline, 3G telecom operators must provide various value‐added services to enhance the ARPU (average revenue per user). The purpose of this paper is to recognize the factors infecting the adoption of 3G value‐added services.

The TAM (technology acceptance model) was used as the foundation to further understand consumer's behavioral intention to use 3G value‐added services. Structural equation modelling (SEM) was used to develop a conceptual model of customer adoption and nine important factors were proposed. The authors conducted a questionnaire investigation, using a large sample, in the Chinese 3G value‐added service market. SPSS and AMOS were applied to analyze the survey data.

The empirical findings are: security and social influence are two of the most important factors in 3G market; 3G value‐added services must be perceived as enjoyment and useful; using context should be friendly and compatible; and in a whole view, the influence from gender, ease of use and need for unique to adoption intention is not significant, but to separate as two models, the difference is huge – the female group considers more about price and usefulness, while the male group thinks about enjoyment and compatibility.

The sample of this study is limited at the range of empirical data; the development of 3G technology has not yet been perfected in China and this study fails to include all of the 3G value‐added services, some of which are still in the exploratory phase of development. At the same time, the cities in this study cannot be said to represent the present stage of the whole of China.

The paper develops a conceptual structural equation model on the area of 3G value‐added services in China. The findings in the paper would help 3G providers to improve their services.

The optimal payment in the whole operation and maintenance period of water environment treatment PPP projects has become the main approach to realize sustainable development of projects. This study is aimed at constructing an effective payment model for the whole life period of projects to achieve win-win among all stakeholders, so as to provide a theoretical reference and managerial implications for the public sector in the whole operation and maintenance period.

In the whole operation and maintenance period of water environment treatment PPP projects, this article investigates how the public sector optimizes the payment in the whole operation and maintenance period of projects. Firstly, the projects' whole operation and maintenance period is divided into several stages according to the performance appraisal period. And then, the multi-stage dynamic programming model is constructed to design the payment construct model for the public sector in each performance appraisal stage. The payment from the public sector is the decision variable, and the deduction from the private sector is a random variable.

The optimal payment model showed that the relatively less objective weight of public sector leaded to its relatively more total payment and vice versa. Therefore, the sustainable development of the projects can only be ensured when the objective weights both of them should be balanced. Additionally, the deduction from the performance appraisal of private sector plays an important role in the model construction. The larger deduction the private sector undertakes, the smaller profits private sector has. Since the deduction at each stage is a random variable, the deduction varies with the different probability distributions obeyed by the practical deduction in each stage.

The findings from this study have provided theoretical and application references, and some managerial implications are also given. First, the improvement of the pricing system of public sector should be accelerated. Second, the reasonable profit of the private sector must be guaranteed. While pursuing the maximization of social benefits, the public sector should make full use of the price sharing mechanism in the market and supervise the real income situation of the private sector. Third is increasing the public to participate in pricing. Additionally, it is a limitation that the deduction is assumed to conform to a uniform distribution in this study. Other probability distributions on deduction can be essentially further sought, so as to be more line with the actual situation of the projects.

The optimal payment in whole operation and maintenance period of the projects has become an important issue, which is a key to project success. This study constructs a multi-stage dynamic programming model to optimize payment in the whole period of projects. Additionally, this study adds its value through deeply developing the new theories of optimal payment to more suitable for the practical problems, so that to optimize the design of payment mechanism. Meanwhile, a valuable reference for public and private sectors is provided to ensure the sustainable development of the projects.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.

In this study the aim was to investigate under-deposit corrosion (UDC) behavior and the action effects of amino trimethylene phosphonic acid (ATMP) in the oxygen-contained solution.

Electrochemical methods and wire beam electrode techniques were used for the study of ATMP action effect for X65 steel under silica sand and CaCO₃ particle deposit. Electronic coupon technique was used for the study of galvanic effect caused by the deposits and the action effect of ATMP.

ATMP would cause localized corrosion for the silica sand-covered steel. However, it could inhibit the localized corrosion of the steel beneath CaCO₃ particle deposit. Galvanic effect test showed that the galvanic effect caused by the deposits was an important factor for the acceleration of UDC. ATMP had an obvious promotion effect for the galvanic current between bare coupon and silica sand covered coupon and different degrees of localized corrosion were observed beneath both deposits.

The authors believe that the paper may be of particular interest to the readers of the journal as the measurement methods for the UDC of X65 pipeline steel. The experiment they did in the laboratory found that the inhibitor ATMP has a good inhibition effect for bare steel, but it would accelerate the UDC. Different kinds of deposits would have different influences for the UDC behavior with inhibitor added.

Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper.

First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given.

Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance.

A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.