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Negative brand engagement represents a pervasive and persistent feature of interactivity in online contexts. Although existing research suggests that consumer negativity is potentially more impactful or detrimental to brands than its positive counterpart, few studies have examined negative brand-related cognitions, feelings and behaviours. Building on the concept of brand engagement, this study aims to operationalise negative online brand engagement.

This paper presents the results of nine studies that contributed to the development and validation of the proposed scale. Building on the concept of engagement, Studies 1–3 enhanced the construct conceptualisation and generated items. Study 4 involved validation with an academic expert panel. The process of measure operationalisation and validation with quantitative data was completed in Studies 5–8. Finally, the scale's nomological validity was assessed in Study 9.

The results confirm the multidimensional nature of negative online brand engagement. The validated instrument encompasses four dimensions (cognition, affection, online constructive behaviour and online destructive behaviour), captured by 17 items.

Progress in understanding and dealing with negative online brand engagement has been hampered by disagreements over conceptualisation and the absence of measures that capture the phenomenon. This work enhances managerial understanding of negativity fostering strategies that protect brand engagement and improve firm performance.

The purpose of this paper is to investigate the possibility of using the iron nanoparticles and iron nanoparticles coated with copper layer as additives to base oils.

Fe and Fe+Cu nanoparticles were synthesized by a reduction modification method and added to mineral oil. The size and structure of prepared nanoparticles were characterized by SEM, TEM, XRF, AAS and XRD analysis. Tribological properties of modified lubricants were evaluated on a four‐ball machine in a model of sliding friction pairs.

Spectral and microscopy analysis evidently displayed the formation of Fe and Fe+Cu nanoparticles in suspensions of colloidal solutions and oil. The size of formed nanoparticles was in 15‐50 nm range. Tribological experiments show good lubricating properties of oils modified with Fe and Fe+Cu nanoparticles: higher wear resistance (55 per cent and 46 per cent accordingly) and lower friction coefficient (30 per cent and 26 per cent accordingly). The tests show that nanoparticles provide decreasing tendency of friction torque during the operation of friction pair.

The paper demonstrates that iron nanoparticles and iron nanoparticles coated with copper layer, not only reduce the wear and friction decrease of friction pairs, but possibly also can create layer in oil which separates two friction surfaces and have some self‐organisation properties.

This paper aims to study the effect of microcrystalline cellulose (MCC) on the mechanical property and shape memory property of water-borne epoxy (WEP).

In the present study, the MCC/WEP composites were successfully prepared by melt-blending, freeze-drying and hot-pressing. The mechanical property tests were performed using a tensile test instrument (Instron Corp, Norwood, Massachusetts, USA). dynamic mechanical analysis Q800 was performed to analyze the sample’s dynamic mechanics. The thermal–mechanical cycle tests performed on a thermal mechanical analysis (TMA) Q400 in dynamic TMA mode enabled to analysis of the shape memory properties of the MCC/WEP composites.

The results showed that the inclusion of 2 wt.% MCC led to significant improvements in tensile strength and modulus of the composites, with tensile strength increasing by 33.2% and modulus expanding by 65.0%. Although the inclusion of the MCC into WEP enhanced the shape memory property, the MCC/WEP composites still maintained good shape memory fixity and shape memory recovery ratio of more than 95.0%.

This study has a significant reference value for improving the mechanical properties of WEP and other water-borne shape memory polymers.

The purpose of this work is to design the wire beam electrode (WBE) of P110 steel and study its corrosion behavior and mechanism under high temperature and pressure.

Packaging materials of the new type P110 steel WBE and high pressure stable WBE structure were designed. A metallurgical microscope (XJP-3C) and scanning electron microscopy (EV0 MA15 Zeiss) with an energy dispersive spectrometer were used to analyze the microstructure and composition of the P110 steel. The electrochemical workstation (CS310, CorrTest Instrument Co., Ltd) with a WBE potential and current scanner was used to analyze the corrosion mechanism of P110 steel.

According to the analysis of Nyquist plots at different temperatures, the corrosion resistance of P110 steel decreases with the increase of temperature under atmospheric pressure. In addition, R_p of P110 steel under high pressure is maintained in the range of 200 ∼ 375 Ωcm², while that under atmospheric pressure is maintained in the range of 20 ∼ 160 Ωcm², indicating that the corrosion products on P110 steel under high pressure is denser, which improves the corrosion resistance of P110 steel to a certain extent.

The WBE applied in high temperature and pressure environment is in blank. This work designed and prepared a WBE of P110 steel for high temperature and pressure environment, and the corrosion mechanism of P110 steel was revealed by using the designed WBE.

Using WeChat moments as an example, this article explores the impact of user role conflict on privacy concerns, social media fatigue and the three dimensions of discontinuous usage intention: control activities, short breaks and suspend usage intentions. Moreover, the moderating function of self-esteem in this process is examined.

The conceptual model includes role conflict, privacy concerns, social media fatigue, discontinuous usage intention and self-esteem. Three hundred and thirty-one questionnaires were collected using an online survey, and the data were analyzed with structural equation and hierarchical regression modeling.

The results show that (1) role conflict positively affects privacy concerns and social media fatigue; (2) privacy concerns also positively affect social media fatigue; (3) privacy concerns positively affect control activities intentions, although their impact on short breaks and suspend usage intentions is not significant, whereas social media fatigue significantly influences control activities, short breaks and suspend usage intentions; and (4) self-esteem negatively moderates the influence of role conflict on privacy concerns.

A key limitation of this research is that it is designed for WeChat. Therefore, the question of whether other social media platforms face role conflict or discontinuous usage problems should be explored in the future.

The article is interesting in that it focuses on the discontinuous usage of social media and identifies factors that contribute to the discontinuous usage of social media. The findings make some theoretical contributions to, and have practical implications for, research into social media usage.

The purpose of this paper is to empirically investigate the effect of lean manufacturing on productivity changes and to identify the root sources of productivity changes. Furthermore, the authors explore the moderating effects of research and development (R&D) to examine the relationship between lean manufacturing and productivity changes.

This paper employs the propensity score matching (PSM) model combined with the difference-in-difference (DID) estimation to overcome the selectivity bias. The Malmquist productivity index is used to capture productivity changes. By analyzing 671 Chinese manufacturing listed firms from 2009 to 2014, the moderating effects of R&D on the relationship between lean manufacturing and productivity changes are measured.

The results reveal that lean manufacturing implementation has non-significant effects on productivity changes in principle, while a detailed analysis indicates that lean manufacturing could improve scale efficiency significantly. While engaged in R&D could significantly improve the efficiency of technological changes for lean manufacturing implementation firms, there exist negative effects on pure technical efficiency.

This research only covers manufacturing listed firms in China. Further studies should extend the generalizability of the findings.

This study helps managers to identify the important role of R&D on the relationship between lean manufacturing and productivity changes and provides insights into how to improve the lean manufacturing performance.

This paper appears to be one of the earliest studies on the relationship between lean manufacturing and productivity changes by applying the PSM combined with DID estimation in Chinese manufacturing environment.

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational burden, the adaptive metamodel-based design optimization (AMBDO) approaches have been widely used. This paper aims to develop an AMBDO approach, a lower confidence bounding approach based on the coefficient of variation (CV-LCB) approach, to balance the exploration and exploitation objectively for obtaining a global optimum under limited computational budget.

In the proposed CV-LCB approach, the coefficient of variation (CV) of predicted values is introduced to indicate the degree of dispersion of objective function values, while the CV of predicting errors is introduced to represent the accuracy of the established metamodel. Then, a weighted formula, which takes the degree of dispersion and the prediction accuracy into consideration, is defined based on the already-acquired CV information to adaptively update the metamodel during the optimization process.

Ten numerical examples with different degrees of complexity and an AIAA aerodynamic design optimization problem are used to demonstrate the effectiveness of the proposed CV-LCB approach. The comparisons between the proposed approach and four existing approaches regarding the computational efficiency and robustness are made. Results illustrate the merits of the proposed CV-LCB approach in computational efficiency and robustness.

The proposed approach exhibits high efficiency and robustness in engineering design optimization involving computational simulations.

CV-LCB approach can balance the exploration and exploitation objectively.

A fiber Bragg grating (FBG) sensor was designed to measure the door gap of automobile bodies.

The gap sensor was designed through a combination of the sliding wedge and cantilever beam, involving a magnetic force installation and arc structure of the force transmission point. Moreover, the sliding block adopted an anti-magnetic and wear-resistant material and the temperature compensation of the two FBGs was conducted. The magnetic force and contact stress of the sensor were examined to ensure that the sensor exhibited a certain magnetic attraction force and fatigue life. The performance of the gap sensor was examined experimentally.

The sensor could measure gaps with dimensions of 5 mm to 11 mm, with a sensitivity and measurement accuracy of 150.9 pm/mm and 0.0063% F.S., respectively. Moreover, the sensor exhibited a small gap sensitivity, with a repeatability error of 0.15%, anti-creep properties and magnetic interference abilities.

The sensor is compact and easy to install, as well as use for multiple sensor locations, with a maximum size of 43 mm, a mass of 26 g and installation type of magnetic suction. It can be used for high-precision static and dynamic measurements of the door inner clearance with a resolution of 0.013 mm to improve the efficiency of internal clearance on-line analysis and assembly quality inspection.

A multi-laser sensors-based measurement instrument is proposed for the measurement of geometry errors of a differential body and quality evaluation. This paper aims to discuss the aforementioned idea.

First, the differential body is set on a rotation platform before measuring. Then one laser sensor called as “primary sensor”, is installed on the intern of the differential body. The spherical surface and four holes on the differential body are sampled by the primary sensor when the rotation platform rotates one revolution. Another sensor called as “secondary sensor”, is installed above to sample the external cylinder surface and the planar surface on the top of the differential body, and the external cylinder surface and the planar surface are high in manufacturing precision, which are used as datum surfaces to compute the errors caused by the motion of the rotation platform. Finally, the sampled points from the primary sensor are compensated to improve the measurement accuracy.

A multi-laser sensors-based measurement instrument is proposed for the measurement of geometry errors of a differential body. Based on the characteristics of the measurement data, a gradient image-based method is proposed to distinguish different objects from laser measurement data. A case study is presented to validate the measurement principle and data processing approach.

The study investigates the possibility of correction of sensor data by the measurement results of multiple sensors to improving measurement accuracy. The proposed technique enables the error analysis and compensation by the geometric correlation relationship of various features on the measurand.

The proposed error compensation principle by using multiple sensors proved to be useful for the design of new measurement device for special part inspection. The proposed approach to describe the measuring data by image also is proved to be useful to simplify the measurement data processing.

This paper aims to propose hybrid global optimization based on multiple metamodels for improving the efficiency of global optimization.

The method has fully utilized the information provided by different metamodels in the optimization process. It not only imparts the expected improvement criterion of kriging into other metamodels but also intelligently selects appropriate metamodeling techniques to guide the search direction, thus making the search process very efficient. Besides, the corresponding local search strategies are also put forward to further improve the optimizing efficiency.

To validate the method, it is tested by several numerical benchmark problems and applied in two engineering design optimization problems. Moreover, an overall comparison between the proposed method and several other typical global optimization methods has been made. Results show that the global optimization efficiency of the proposed method is higher than that of the other methods for most situations.

The proposed method sufficiently utilizes multiple metamodels in the optimizing process. Thus, good optimizing results are obtained, showing great applicability in engineering design optimization problems which involve costly simulations.