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The purpose of this study is to explore the competitive source of Chinese firms in an industrial sector of complex product systems. It helps to reveal the organizational innovation developed by Chinese firms in coping with international competition and technological challenges.

The study uses a qualitative method of research. The evidences are mainly collected through interviews, field observation and document analysis.

A pattern of engineer-centered organization is the source of competitiveness of Nanrui (NR) Electric (NREC) in this study. The firm equips its front project teams, and now its overseas branches with developmental human resources and authorizes them the power of decision-making to leverage R&D projects. It is an emerging challenge to the traditional multi-national companies (MNC) pattern, and enables the Chinese firms to build their capabilities on context-based knowledge.

As a single-case study paper, there are limitations about the external validity of its argument. Through the in-depth discussion of the NREC case, this paper aims to generate some clues for future study in the relevant academic community, which can be a useful step to formal theorizing and modeling. That is why the authors develop the paper on a single case. As future directions of research, comparative studies covering more cases not only within the power system control and protection industry but also among different complex technology products industrial sectors are really needed.

For innovative firms from developing countries like China, they need to develop institutional arrangements to incentivize engineers in the frontline, which may help them to build competence upon successful interaction with customers. During the era of globalization, such a pattern may generate special competitiveness over giant multi-nationals or global production networks (GPNs).

The research provides an instructive case on the Chinese rise in industrial sectors of complex product systems. Its findings can not only provide enlightenment for industrial catch-up in developing countries through organizational innovation but also help to initiate a reconsideration of the traditional theorizing of MNC and GPN.

This study aims to investigate Feng Shui elements that can influence housing selection and property pricing in the Malaysian housing market.

A structured questionnaire encompassing 26 Feng Shui elements, which were shortlisted based on relevant previous studies, was distributed to prospective homebuyers in the Klang Valley region. The elements were inferred and ranked according to frequency, significance and importance scores. Kruskal–Wallis ANOVA tests were used to assess the ratings provided by the different respondent groups, while Spearman's rank correlation tests were utilised to measure the degree of agreement or disagreement among each pair of the ethnic group.

The results obtained indicate the following as the five most influential elements: orientation, main entrance, street location, house number and living room. Despite a multiethnic and multicultural society in Malaysia, Spearman's rank correlation tests showed that there are no differences in the prioritisation of Feng Shui elements between three distinct ethnic groups (Malay, Chinese and Indian). However, the distribution scores are statistically different between the groups. Comparing income level with Feng Shui inclinations, the three most frequently considered elements across the three income groups consistently include orientation, main entrance and street location.

The findings of this study are expected to provide guidance to property stakeholders (developers, real estate agencies, architects, local authorities) in their future development projects. For homebuyers, this study serves as a property Feng Shui checklist for home selection and investment.

This study explored the association of Feng Shui principles to housing selection and property pricing based on cultural and income factors. These findings provide useful insights for designing and positioning of residential properties in both primary and secondary housing markets in Malaysia and beyond.

The spherical hybrid sliding bearings (SHSBs) can be used in ultra-precision and heavy-duty machine tools. However, there is little related research for these bearings. The purpose of this study is to investigate the static characteristics and effect factors affecting SHSBs by fluid lubrication.

Based on the theories of fluid lubrication, the Reynolds equation of general Newtonian fluid is derived to obtain the steady-state lubrication equation. The system is solved by the finite difference method and the relaxation iterative method on the staggered grid to obtain the thickness and the pressure distribution of the oil film. The radial and axial load capacities of SHSBs are determined by the pressure field integration over the spherical surface.

The results show that the parameters such as oil supply pressure, bearing clearance, eccentricity ratio, rotating speed and orifices’ number affecting the static characteristics of bearings are significant and the cross-coupling effect exists.

The lubrication model of SHSB is established to analyze the pressure distribution with a variety of oil film thickness. The laws of oil supply pressure, bearing clearance, eccentricity ratio, rotating speed and orifices’ number on the load capacities are researched.

Seismic isolation, as an effective risk mitigation strategy of building/bridge structures, is incorporated into AP1000 nuclear power plants (NPPs) to alleviate the seismic damage that may occur to traditional structures of NPPs during their service. This is to promote the passive safety concept in the structural design of AP1000 NPPs against earthquakes.

In conjunction with seismic isolation, tuned-mass-damping (TMD) is integrated into the seismic resistance system of AP1000 NPPs to satisfy the multi-functional purposes. The proposed base-isolation-tuned-mass-damper (BIS-TMD) is studied by comparing the seismic performance of NPPs with four different design configurations (i.e. without BIS, BIS, BIS-TMD and TMD) with the design parameters of the TMD subsystem optimized.

Such a new seismic protection system (BIS-TMD) is proved to be promising because the advantages of BIS and TMD can be fully used. The benefits of the new structure include effective energy dissipation (i.e. wide vibration absorption band and a stable damping effect), which results in the high performance of NPPs subject to earthquakes with various intensity levels and spectra features.

Parametric studies are performed to demonstrate the seismic robustness (e.g. consistent performance against the changing mass of the water in the gravity liquid tank and mechanical properties) which further ensures that seismic safety requirements of NPPs can be satisfied through the use of BIS-TMD.

Online health communities can be both supportive and vulnerable and highly rely on stable engagement from core members. Understanding the factors affecting core member churn is vital. This study examines a hair-loss-related online health community, taking a meso-level community approach. It investigates how users’ potential social capital, proactive social engagement and received social support in the community influence their churn.

This study collected the complete dataset spanning 13 years from a hair-loss-related online health community in mainland China. It identified 4,270 core users with over ten posted messages each, along with their associated text. Social network analysis and survival analysis were then used to calculate user node centrality and create a hazard model for user churn.

The findings indicate that increased social capital and social support can help prevent churn. However, higher social engagement alone does not directly reduce users’ likelihood to withdraw. Instead, users are more likely to stay in the community when highly engaged if they also receive substantial social support. Social support emerges as a critical factor in this mechanism.

This study innovatively adopts a meso-level community perspective, investigating user churn within an online health community for individuals with a self-limiting condition – hair loss. The research probes the interactive effects of user engagement and social support on churn within the online health community. Advice on sustaining member participation is given based on the findings as well as Chinese culture.

The purpose of this paper is to propose a new population-based metaheuristic optimization algorithm, assimilation-accommodation mixed continuous ant colony optimization (ACACO), to improve the accuracy of Takagi-Sugeno-Kang-type fuzzy systems design.

The original N solution vectors in ACACO are sorted and categorized into three groups according to their ranks. The Research Learning scheme provides the local search capability for the best-ranked group. The Basic Learning scheme uses the ant colony optimization (ACO) technique for the worst-ranked group to approach the best solution. The operations of assimilation, accommodation, and mutation in Mutual Learning scheme are used for the middle-ranked group to exchange and accommodate the partial information between groups and, globally, search information. Only the N top-best-performance solutions are reserved after each iteration of learning.

The proposed algorithm outperforms some reported ACO algorithms for the fuzzy system design with the same number of rules. The performance comparison with various previously published neural fuzzy systems also shows its superiority even with a smaller number of fuzzy rules to those neural fuzzy systems.

Future work will consider the application of the proposed ACACO to the recurrent fuzzy network.

The originality of this work is to mix the work of the well-known psychologist Jean Piaget and the continuous ACO to propose a new population-based optimization algorithm whose superiority is demonstrated.

This paper aims to proposes and analyzes a novel recovery-based posteriori error estimator for the stationary natural-convection problem based on penalized finite element method.

The optimal error estimates of the penalty FEM are established by using the lower-order finite element pair P₁-P₀-P₁ which does not satisfy the discrete inf-sup condition. Besides, a new recovery type posteriori estimator in view of the gradient recovery and superconvergent theory to deal with the discontinuity of the gradient of numerical solution.

The stability, accuracy and efficiency of the proposed method are confirmed by several numerical investigations.

The provided reliability and efficiency analysis is shown that the true error can be effectively bounded by the recovery-based error estimator.

The purpose of this study is to examine how perceived fit between a line/brand extension and its parent brand moderates the evaluation of two economically identical promotions, i.e. buy one get one free (BOGOF) and 50 per cent off. A travel-sized painkiller is the product in this study.

A 2 (perceived fit: high or low) × 2 (promotion type: BOGOF or 50 per cent off) between-subjects design is used in this study. Participants, who are college students, are randomly assigned to the four experimental conditions.

The results indicate that parent brand attitude is more closely associated with line-extension attitude than with brand-extension attitude, line extension leads to lower perceived performance risk and higher stockpiling tendency than brand extension and BOGOF is preferred over 50 per cent off for line extension but 50 per cent off is preferred over BOGOF for brand extension.

For a low-price, non-conspicuous and stock-up product category such as painkillers, marketers should consider using BOGOF to promote a line extension and 50 per cent off to promote a brand extension. It is important to explore in future research as to how the findings can be applied to other product categories, other promotion types, other packages and non-student consumers.

This study is the first that examines how perceived fit of a line/brand extension moderates the evaluation of economically identical promotions. It integrates the literature of line/brand extension, perceived performance risk and prospect theory to advance the research on sales promotions for new products.

This paper aims to propose two parallel two-step finite element algorithms based on fully overlapping domain decomposition for solving the 2D/3D time-dependent natural convection problem.

The first-order implicit Euler formula and second-order Crank–Nicolson formula are used to time discretization respectively. Each processor of the algorithms computes a stabilized solution in its own global composite mesh in parallel. These algorithms compute a nonlinear system for the velocity, pressure and temperature based on a lower-order element pair (P₁b-P₁-P₁) and solve a linear approximation based on a higher-order element pair (P₂-P₁-P₂) on the same mesh, which shows that the new algorithms have the same convergence rate as the two-step finite element methods. What is more, the stability analysis of the proposed algorithms is derived. Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms.

Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms.

The novel parallel two-step algorithms for incompressible natural convection problem are proposed. The rigorous analysis of the stability is given for the proposed parallel two-step algorithms. Extensive 2D/3D numerical tests demonstrate that the parallel two-step algorithms can deal with the incompressible natural convection problem for high Rayleigh number well.

Hair loss is often overlooked but psychologically challenging. However, the emergence of online health communities provides opportunities for hair loss patients to seek social support through self-disclosure. Nevertheless, not all disclosures receive the desired support. This research explores what patients disclose within the community and how their health narrative (content, form and linguistic style) regarding self-disclosure influences the social support they receive.

This study investigated a 13-year-old online support group for Chinese hair loss patients with nearly 240,000 members. Using structural topic modeling, Linguistic Inquiry and Word Count, and a negative binomial model, the research analyzed the content of self-disclosure and the interrelationships between social support and three narrative dimensions of self-disclosure.

Self-disclosures are classified into 14 topics, grouped under analytical, informative and emotional categories. Emotion-related self-disclosures, whether in content or effective word use, receive deeper social support. Longer and image-rich posts attract more support in quantity, but not necessarily in quality, while cognitive words have a limited impact.

This study addresses the previously overlooked population of hair loss patients within online health communities. It employs a more comprehensive health narrative framework to explore the relationship between self-disclosure and social support, utilizing unsupervised structural topic modeling methods to mine text. The research offers practical implications for how patients seek support and for healthcare professionals in developing doctor-patient communication strategies.