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The authors introduce a new approach to estimate high-dimensional factor-augmented vector autoregressive models (FAVAR) where the loadings are subject to idiosyncratic regime-switching dynamics. Our Bayesian estimation method alleviates computational challenges and makes the estimation of high-dimensional FAVAR with heterogeneous regime-switching straightforward to implement. The authors perform extensive simulation experiments to study the finite sample performance of our estimation method, demonstrating its relevance in high-dimensional settings. Next, the authors illustrate the performance of the proposed framework for studying the impact of credit market disruptions on a large set of macroeconomic variables. The results of this study underline the importance of accounting for non-linearities in factor loadings when evaluating the propagation of aggregate shocks.

An accelerometer is a device that measures force due to gravity or a change in speed or direction of travel. This paper describes accelerometers and their application in other disciplines and, by way of an example, explores the utility of accelerometers for studying aggression. We end with a discussion of additional ways accelerometers might be used in group processes research.

We first review the use of accelerometers in other disciplines. We then present the results of four studies that demonstrate the use of accelerometers to measure aggression. Study 1 establishes the measure’s concurrent validity. Study 2 concerns its stability and representative reliability. Study 3 seeks to establish the measure’s predictive validity by associating it with an existing measure. Study 4 demonstrates the ability of accelerometers to address a sociological research question.

In Studies 1 and 2, we find that accelerometers can be used to differentiate between distinct levels of aggression. In Study 3, we find that men’s average peak acceleration correlates with a previously validated measure of aggression. Study 4 uses accelerometers to reproduce a well-established finding in the aggression literature.

We conclude that accelerometers are a flexible tool for group processes’ researchers and social scientists more broadly. Our findings should prove useful to social scientists interested in measuring aggression or in employing accelerometers in their work.

This chapter focusses on how qualitative research can capture the lived experiences of entrepreneurial individuals by exploring their subjective experiences. Traditional methods of data collection involve listening to what entrepreneurial individuals say and observing their actions, although particular attention to their feelings is often absent. To achieve data congruence and to gain a deeper understanding of their lived experiences, it is crucial to also take into consideration how they feel. This chapter will recount a confessional tale recorded during a recent field study in entrepreneurship that will shed light on the pivotal role that a researcher’s sensory processing sensitivity (SPS) trait can play during qualitative data collection in helping researchers becoming mindful of the feelings of entrepreneurial individuals, even when those feelings are not directly expressed by them. The introduction of the researcher’s SPS trait in promoting data congruence during qualitative data collection will be this chapter’s principal contribution.

To prevent malpractices, medical staff has adopted inventory time-outs and/or checklists. Accurate inventory and maintenance of surgical instruments decreases the risk of operating room miscounting and malfunction. In our previous study, an individual management of surgical instruments was accomplished using Radio Frequency Identification (RFID) tags. The purpose of this paper is to evaluate a new management method of RFID-tagged instruments.

The management system of RFID-tagged surgical instruments was used for 27 months in clinical areas. In total, 13 study participants assembled surgical trays in the central sterile supply department.

While using the management system, trays were assembled 94 times. During this period, no assembly errors occurred. An instrument malfunction had occurred after the 19th, 56th, and 73th uses, no malfunction caused by the RFID tags, and usage history had been recorded. Additionally, the time it took to assemble surgical trays was recorded, and the long-term usability of the management system was evaluated.

The system could record the number of uses and the defective history of each surgical instrument. In addition, the history of the frequency of instruments being transferred from one tray to another was recorded. The results suggest that our system can be used to manage instruments safely. Additionally, the management system was acquired of the learning effect and the usability on daily maintenance. This finding suggests that the management system examined here ensures surgical instrument and tray assembly quality.

This paper shows that the parsimoniously time-varying methodology of Callot and Kristensen (2015) can be applied to factor models. We apply this method to study macroeconomic instability in the United States from 1959:1 to 2006:4 with a particular focus on the Great Moderation. Models with parsimoniously time-varying parameters are models with an unknown number of break points at unknown locations. The parameters are assumed to follow a random walk with a positive probability that an increment is exactly equal to zero so that the parameters do not vary at every point in time. The vector of increments, which is high dimensional by construction and sparse by assumption, is estimated using the Lasso. We apply this method to the estimation of static factor models and factor-augmented autoregressions using a set of 190 quarterly observations of 144 US macroeconomic series from Stock and Watson (2009). We find that the parameters of both models exhibit a higher degree of instability in the period from 1970:1 to 1984:4 relative to the following 15 years. In our setting the Great Moderation appears as the gradual ending of a period of high structural instability that took place in the 1970s and early 1980s.

This paper aims to propose a multi-scale simulation approach for the concrete macro-mechanical damage caused by mixed micro-pore pressures, such as the coupled alkali–silica reaction (ASR) and freeze-thaw cycles (FTC).

The micro-physical events are computationally modeled by considering the coupling effect between ASR gel and condensed water in the mixed pressure and motion. The pressures and transport of pore substances are also linked with the concrete matrix deformation at macro-scale through a poro-mechanical approach, and affect each other, reciprocally. Once the crack happens in the nonlinear analysis, both the micro-events (water and gel motion) and the macro mechanics will be mutually interacted. Finally, different sequences of combined ASR and FTC are simulated.

The multi-chemo mechanistic computation can reproduce complex events in pore structures, and further the macro-damages. The results show that ASR can reduce the FTC expansion for non-air-entrained concrete, but may increase the frost damage for air-entrained concrete. The simulation is examined to bring about the observed phenomena.

This paper numerically clarifies the strong linkage between macro-mechanical deformation and micro-chemo-physical events for concrete composites under coupled ASR and FTC.

The purpose of this paper is to analyse the development strategies of two Chinese global players in the high‐tech sectors.

The paper adopts a case‐study approach on Huawei Technology Co. Ltd (Huawei) and Jing‐Hua Optical and Electronics Co. Ltd (JOC).

While Huawei's first strategic decision was that of becoming a leader on the domestic market, the key choice for JOC was that of acquiring a European firm. However common features emerge: persistent investment in R&D, strategic collaboration with universities and presence of government supporting policies, even though the case studies suggest the existence of thresholds for firms to access the benefits of government policy.

The results pave the way for more general discussions on the emergence of champions of excellence in China. They reinforce the idea that Chinese industrial development is built on non‐conventional catching‐up processes at the country, local and firm level. They confirm that in order to fully catch the success of national Chinese champions the role of government policies should be better investigated.

Results highlight the importance of R&D investment and technology transfer also for SMEs in high‐tech sectors. As for policy makers, the practice of official institutional recognition – a well experimented form of rewarding used in China – might be an effective way to stimulate virtuous imitative processes.

The comparison of these two global players is itself original. Moreover there is a valuable attempt to understand from a national champion's perspective the importance of supra‐firms factors such as collaboration with other institutions and government policies.

The purpose of this paper is to review key academic literature on the characteristics of business firms' intellectual property (IP) strategy and to examine the implications for how Chinese firms can deal with today's business environment under the globalization.

A selection of peer‐reviewed articles from scholarly journals listed in major academic search engines is reviewed. The search results showed that ProQuest included 509 related articles and ScienceDirect included 121. The abstract of all the articles were reviewed. Finally, 26 articles were identified and comprehensively reviewed. The key characteristics of the role of internal and external contexts for IP strategy development were then analysed in terms of the challenges faced by Chinese firms.

The results show that IP strategies involve IP identification/generation, valuation, utilization and enforcement. Its effectiveness depends on both internal (i.e. company size, ownership of firms, business strategies and the value of the IP) and external factors (i.e. industry structure, level of competition, and novelty of technology). Given that many Chinese firms are developing new innovative capabilities and need to protect their IP in domestic or international markets, there is a need for these firms to align their emerging IP strategy with future business strategies.

The study focuses on the IP strategies and management in business organizations, and therefore excludes the articles from law and economics literature.

The paper suggests a conceptual framework and provides managerial implications on IP management at firm level, particularly relevant for Chinese business firms.

This paper aims to assess the fatigue life characteristics of vehicle coil spring under random strain load in the time domain. Cyclic random road loads caused fatigue failure for automotive components during their operating condition. .

The coil spring model is developed through finite element analysis software. The critical region and fatigue life cycle of coil spring is evaluated through finite element analysis. The experimental is set up to capture the random strain signal of the rural, highway and campus road. The sampling rate of the random strain signals data captured were 500 Hz in 150 s. Then, fatigue life is assessed through Goodman, Brown-Miller, Fatemi-Socie, Wang-Brown fatigue life models. Goodman model is evaluated through finite element analysis in order to compare with fatigue experimental results.

The fatigue life was estimated for Brown-Miller model is the highest (4.32E4, 4.10E4, and 3.73E4 cycles/block for rural, highway and campus respectively) followed by Goodman model, Brown-Miller, Fatemi-Socie and Wang-Brown models respectively. The conservative fatigue life 1:2 and 2:1 data scattering approach is proposed in order to determine the acceptability of the data.

Hence, the proposed fatigue life models can be used to assess multiaxial fatigue under random strain signals for the automobile coil spring.

This study assessed the heterogeneous impact of the Anchor Borrower Program (ABP) on the welfare distribution of rice farming households in Nigeria.

Self-selection bias and treatment endogeneity were accounted for by employing the Instrumental Variable Quantile Regression (IVQR) model. The estimates obtained from the IVQR model were further compared with those from the conventional quantile regression, and quantile regression using Propensity Score Matching. This was to highlight the extent to which endogeneity bias has been purged from the treatment, in order to establish a consistent causal link between participation in the ABP and the welfare of a cross-section of rice farming households.

ABP farmers had significantly higher rice yields across all quantiles of the yield distribution under treatment exogeneity assumption, and in only two quantiles upon controlling for observable confounders. However, this yield gain did not translate to higher Per capita Consumption Expenditure (PCE). The estimates of the more robust IVQR model provided further evidence that the rice yield and PCE of ABP farmers are not statistically different from that of non-ABP farmers across all quantiles of the welfare distribution.

The negligible impact of ABP was relatively higher for lower-yielding households. Thus, implying that, although the ABP is a pro-poor development intervention, the program has not been sufficiently implemented to significantly improve the welfare of the dominant resource-poor farming households in Nigeria.

This study assessed the impact of ABP beyond the conventional potential mean outcome framework by accounting for heterogeneity in treatment effect.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0083