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The purposes of this paper are to find out the correlations between the changes of food companies’ environments and the strategic reactions of food companies after the media disclosed that there were food safety incidents out there in the food markets.

This paper uses a randomly sampling survey of 139 food enterprises in China. After statistical significance and statistical power were examined, canonical correlation analysis was used as the main data analysis technique of this research.

Based on the environment-strategy paradigm, the authors found that the changes of the competition environment, resource environment, and institution environment in the food industry have significant association with food companies’ strategic reactions such as public relations, networking with firms and futurity after food safety incidents in the food market were disclosed.

The paper is the first to quantitatively examine the relationships between the changes of food companies’ environments and the strategic reactions of food companies after the media disclosed that there were food safety incidents in the food markets. The findings of this paper send novel and important messages to government decision makers and the public, evidencing how food companies strategically respond to external environmental changes, and suggesting that the institution-builder as well as the media have more work to do in the aftermath of food safety incidents.

Wayfinding efficiency is an extremely influential factor to improve users' library interior experience. However, few research has studied the different functions of various wayfinding signages for university library users through mobile visual experiment. To fill this gap, the purpose of this paper is to explore the relationship between university library signage system design and patrons' wayfinding behavior features.

In this article, an eye movement tracking method was introduced to record eye movement data during the wayfinding process of participants in the library interior, targeting the cognition and psychology of library users in the wayfinding signage system. The visual guiding usability of landmarks, informational signages and directional signages were quantitatively tested, and the fixation on the signage system between orientation strategy users and route strategy users was compared. This study also investigated the effects of library users' spatial anxiety and environmental familiarity on their fixation on the area of interest of the wayfinding signage system using the differential test and regression.

This paper observed that informational signage had the best visual navigating competence. The difference of fixation duration and searching duration between patrons used various wayfinding strategies was significant. The informational signage was most attended by the route strategy users, and the orientation strategy users rarely focused on the directional signage. And participants with high anxiety tended to ignore the visually auxiliary function of the landmarks but paid attention to the directional signage. The participants with low anxiety could capture the landmarks that could not be easily found by the route strategy users. And participants less familiar with the environment were more sensitive to the landmarks. Furthermore, this paper offers optimization measures for university library wayfinding signage system, from the perspectives of informational signage understandability improvement, directional signage physical specification design and wayfinding assistant system with automatic landmark technology.

This article adds to the relatively sparse literature on university library user wayfinding experimental study in China. The experimental findings of this paper also have important practical implications for academic libraries' wayfinding system evaluation. The whole process could be seen as a repeatable and standard framework and methodology to inspect university library's wayfinding signage system usability and user wayfinding behavior performance.

This paper aims to propose a calibration model for kinematic parameters identification of serial robot to improve its positioning accuracy, which only requires position measurement of the end-effector.

The proposed model is established based on local frame representation of the product of exponentials (local POE) formula, which integrates all kinematic errors into the twist coordinates errors; then they are identified with the tool frame’ position deviations simultaneously by an iterative least squares algorithm.

To verify the effectiveness of the proposed method, extensive simulations and calibration experiments have been conducted on a 4DOF SCARA robot and a 5DOF drilling machine, respectively. The results indicate that the proposed model outperforms the existing model in convergence, accuracy, robustness and efficiency; fewer measurements are needed to gain an acceptable identification result.

This calibration method has been applied to a variable-radius circumferential drilling machine. The machine’s positioning accuracy can be significantly improved from 11.153 initially to 0.301 mm, which is well in the tolerance (±0.5 mm) for fastener hole drilling in aircraft assembly.

An accurate and efficient kinematic calibration model has been proposed, which satisfies the completeness, continuity and minimality requirements. Due to generality, this model can be widely used for serial robot kinematic calibration with any combination of revolute and prismatic joints.

To gain accurate support for large aircraft structures by ball joints in aircraft digital assembly, this paper aims to propose a novel approach based on visual servoing such that the positioner’s ball-socket can automatically and adaptively approach the ball-head fixed on the aircraft structures.

Image moments of circular marker labeled on the ball-head are selected as visual features to control the three translational degrees of freedom (DOFs) of the positioner, where the composite Jacobian matrix is full rank. Kalman–Bucy filter is adopted for its online estimation, which makes the control scheme more flexible without system calibration. A combination of proportional control with sliding mode control is proposed to improve the system stability and compensate uncertainties of the system.

The ball-socket can accurately and smoothly reach its desired position in a finite time (50 s). Positional deviations between the spherical centers of ball-head and ball-socket in the X-Y plane can be controlled within 0.05 mm which meets the design requirement.

The proposed approach has been integrated into the pose alignment system. It has shown great potential to be widely applied in the leading support for large aircraft structures in aircraft digital assembly.

An adaptive approach for accurate support of large aircraft structures is proposed, which possesses characteristics of high precision, high efficiency and excellent stability.

This study investigates how downward envy affects interpersonal conflict, workplace ostracism and displaced aggression in the mentoring context. It seeks to deepen our understanding of how these dynamics influence a mentor–protégé relationship.

Employing a three-wave research design, this study uses a sample of 176 participants in mentoring relationships to test our proposed moderated mediation model.

Downward envy can increase interpersonal conflict, workplace ostracism and displaced aggression. A mentor’s social comparison orientation moderates these effects by amplifying the negative impacts of downward envy.

These findings have practical implications for both mentors and protégés.

These findings have practical implications for both mentors and protégés.

This study contributes to the literature by focusing on downward envy within the mentoring context, yielding valuable insights to navigate mentoring experiences at work.

Assembly variation analysis generally demands probability distributions of variation sources. However, due to small production volume in aircraft manufacturing, especially prototype manufacturing, the probability distributions are hard to obtain, and only the small-sample data of variation sources can be consulted. Thus, this paper aims to propose a variation analysis method driven by small-sample data for compliant aero-structure assembly.

First, a hybrid assembly variation model, integrating rigid effects with flexibility, is constructed based on the homogeneous transformation and elasticity mechanics. Then, the bootstrap approach is introduced to estimate a variation source based on small-sample data. The influences of bootstrap parameters on the estimation accuracy are analyzed to select suitable parameters for acceptable estimation performance. Finally, the process of assembly variation analysis driven by small-sample data is demonstrated.

A variation analysis method driven by small-sample data, considering both rigid effects and flexibility, is proposed for aero-structure assembly. The method provides a good complement to traditional variation analysis methods based on probability distributions of variation sources.

With the proposed method, even if probability distribution information of variation sources cannot be obtained, accurate estimation of the assembly variation could be achieved. The method is well suited for aircraft assembly, especially in the stage of prototype manufacturing.

A variation analysis method driven by small-sample data is proposed for aero-structure assembly, which can be extended to deal with other similar applications.

In order to make the construction industry develop in the direction of greening, this paper analyzes whether the application of intelligent technology in prefabricated buildings can achieve carbon emission reduction, starting from the problems of weak technology and insufficient encouragement policies in the prefabricated building industry. It also designs dynamic and adjustable incentives for the smart transformation of prefabricated buildings and makes recommendations to facilitate the transformation of assembly manufacturers into “smart factories”.

This paper takes the intelligent technology for carbon reduction, energy efficiency and policy design in the prefabricated buildings industry as the starting point. Based on in-depth expert interviews and questionnaire survey data, a linear multiple regression model is used to establish an association network of intelligent technology in the production and transportation, construction, operation and maintenance, demolition and scrapping stages. On this basis, an evolutionary game theory is used to construct a smart transformation and carbon reduction utility game model between the government and manufacturers, and relevant suggestions for smart empowerment of green construction development technology combinations and policy settings are proposed.

An assembly manufacturing plant with smart empowerment is an important way to achieve green and sustainable development in the construction industry. Among them, BIM and IoT have made a greater impact on carbon emission reduction of prefabricated buildings in all stages of the whole life cycle. The government’s proposed energy efficiency incentives and environmental tax amount will effectively increase companies' motivation for smart transformation of prefabricated buildings. However, when the environmental tax amount is low, the government should strengthen the regulation of the industry in order to increase the speed of smart transformation of assembly manufacturers. Therefore, a reasonable setting of the environmental tax rate and energy-saving incentives and flexible adjustment of the regulatory efforts can maximize the functional utility of the government in the process of smart transformation.

This paper focuses on the impact of intelligent technologies on the overall carbon emissions of the industry and provides an evolutionary analysis of the strategic game between the government and assembly manufacturers, the main players in the smart transformation process of prefabricated buildings. However, smart technologies for different categories of assembly manufacturing plants and strategic options for a wider range of stakeholders have not been examined in depth.

Different from existing research, this study focuses on exploring the strategic game between the government and assembly manufacturers in the smart transformation of prefabricated buildings. It provides an innovative explanation of the connection between intelligent technology and carbon emissions. The study develops an evolutionary game model for both parties, addressing the research gap on the combined effects of policy incentives and intelligent technology on carbon reduction and efficiency improvement in the prefabricated buildings industry. This research not only offers practical reference for the government in designing incentive mechanisms and establishing regulatory systems but also provides feasible practical guidance for the smart transformation and carbon reduction efforts of assembly manufacturing plants.

For the automatic drilling and riveting in panel assembly, gaps between the skin and strangers are inevitable and undesirable. At present, the determination of pre-joining schemes relies on workers’ experience, introducing excessive number and inappropriate locations of pre-joining. This paper aims to present a new method for the evaluation of residual clearances after pre-joining and the pre-joining scheme optimization, providing operation guidance for the workers in panel assembly workshop.

In this paper, an equivalent gap assembly model for pre-joining is proposed on the basis of the mechanism of variation. This model retains the essential elastic behavior of the key features during the pre-joining operation and calculates the residual clearances in the view of the potential energy. Subsequently, this method is embedded into a Pareto optimality-based genetic algorithm, and the optimal pre-joining schemes are achieved with the consideration of the total residual clearances and the permissive tolerances.

The equivalent gap assembly model has the capability to predict an acceptable degree of accuracy of the residual clearances and achieve the optimized pre-joining schemes with less number of pre-joining at the same level of residual clearances.

The optimized pre-joining schemes are given in the form of Pareto optimality set, and workers can select suitable results according to their inclination to the quality and efficiency.

The paper is the first to propose the equivalent gap assembly model for the pre-joining operation, which provides for the simplification of the calculation of residual clearances based on the constrained variation principles.

The riveting process is a metal forming process involving complex elastic-plastic deformation, which will induce a compressive residual stress field and cause local distortions in the connecting areas. Regarding to the aircraft panel assemblies with plenty of rivets, the global deformation is inevitable and undesired, leading difficulties to downstream assembly processes. This paper aims to present a new method for the local distortion calculation and the global deformation prediction of sheet panel assemblies during the automated riveting process.

In this paper, a simplified algebraic study is presented to analyze the local distortion of single countersunk rivet joint with the consideration of the barrel-like shape of the driven head and the through-thickness variations along the rivet shank. Then, an equivalent rivet unit is proposed based on the result of the algebraic study and embedded into the global-level model for the prediction of the overall distortions of riveted panels.

The algebraic study is able to reach a more precise contour of the deformed rivet than the traditional assumption of cylindrical deformations and rapidly determine the equivalent coefficients of the riveting unit. The result also shows an industrial acceptable accuracy of the prediction for the global deformations of the double-layered panel assemblies widely used in the aircraft panel structures.

A new local-global method for predicting the deformations of the riveted panel assembly based on the algebraic study of the local distortions is proposed to help the engineers in the early design stages or in the assembly process planning stage.

This paper aims to present a modeling and analysis approach for multi-station aircraft assembly to predict assembly variation. The variation accumulated in the assembly process will influence the dimensional accuracy and fatigue life of airframes. However, in digital large aircraft assembly, variation propagation analysis and modeling are still unresolved issues.

Based on an elastic structure model and variation model of multistage assembly in one station, the propagation of key characteristics, assembly reference and measurement errors are introduced. Moreover, the reposition and posture coordination are considered as major aspects. The reposition of assembly objects in a different assembly station is described using transformation and blocking of coefficient matrix in finite element equation. The posture coordination of the objects is described using homogeneous matrix multiplication. Then, the variation propagation model and analysis of large aircraft assembly are established using a discrete system diagram.

This modeling and analysis approach for multi-station aircraft assembly reveals the basic rule of variation propagation between adjacent assembly stations and can be used to predict assembly variation or potential dimension problems at a preliminary assembly phase.

The modeling and analysis approaches have been used in a transport aircraft project, and the calculated results were shown to be a good prediction of variation in the actual assembly.

Although certain simplifications and assumptions have been imposed, the proposed method provides a better understanding of the multi-station assembly process and creates an analytical foundation for further work on variation control and tolerance optimization.