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The purpose of this study is threefold. First, the authors will confirm the existence and the intensity of the latent “genius loci” within quality management systems. Second, the authors will confirm the extent of the genius loci with environmental sustainability. Finally, the authors will try to understand whether a quality management system's performance can be affected by its genius loci, and whether a quality management system's environmental sustainability performance can be affected by the extent of environmental sustainability in its genius loci.

The extent of the genius loci in quality management systems and the genius loci with environmental sustainability are tested through higher-order confirmatory factor analysis.

The findings of this study are as follows. First, genius loci partially exist in quality management systems. Second, the genius loci with the environmental sustainability concept also exist partially in certain respects. There is a lack of recognition and actions on environmental sustainability activities in organizations. The lack of recognition and actions leads to the unsatisfactory performance of quality management systems in environmental sustainability. As a result, business goals with environmental sustainability aspects cannot be fully supported and achieved.

The results of this study can help small- and medium-sized OEM and ODM computer accessories companies in Taiwan and Southern China to understand the level of genius loci within their quality management systems and the extent that genius loci are linked with environmental sustainability. This understanding can be beneficial to them in achieving successful quality management systems with environmental sustainability.

Women from many cultures have historically been closely tied to the land and the environment through their role as subsistence farmers. But as the more developed nations have shifted to commercial agriculture and improved technology, farming has become a male-dominated industry. China’s shift from traditional family-operated farms to government-controlled collectives required a system of incentives to encourage agricultural labor to remain and prevent mass exodus to the cities. Hukou was created in the 1950s as a system of governmental registration for restricting the internal migration of labor within China, identifying citizens’ residency by place of birth. Residents of rural or urban locations are classified agricultural or nonagricultural labor, respectively. But as China’s industrialization has grown and technology has reduced the need for human agricultural labor, the need and desire for urban employment has intensified. For women, relocating has changed marriage practices, influenced child rearing, and altered their right to land tenure in their home region. This paper examines the role of gender in the changing use of hukou in the development of China, focusing on the impact of women’s patterns of migration on land tenure. Although hukou policies are still changing and there is a lack of data on the most recent changes, initial studies show that there are few who wish to give up their rural hukou in order to obtain urban hukou. Changes over the past decade indicate that rural woman are not only taking on more of the agricultural workload as men are drawn to urban employment, but also that they are less likely to care about environmental degradation in China.

The purpose of this paper is to prove the importance of both cluster leadership and identification on cluster innovation.

The case studies presented in this study involve a cluster by micro-enterprises in Yilan, Taiwan. Data collected during interviews, observations and secondary data provide understanding and practices for the impact of cluster identification on cluster innovation.

This study proved: first, the importance of cluster identification on innovation by representing the need of consensus and collaboration of the members in conducting innovation actions; and second, the cluster identification is influenced by the cluster leadership by showing high satisfaction of the leader, close interaction between the members and high identification with the cluster.

This study predicts the ongoing cluster innovation activities will be achieved due to the transformational leadership and high cluster identification.

This study enriches the factors of cluster innovation accomplishment and proposes the important of cluster identification, which has not been discussed much in the past.

This study aims to investigate the impact of geopolitical risk (GPR) on supply chain concentration (SCC) and the roles of operational capabilities and resources in this relationship.

Secondary longitudinal data from multiple sources is collected and combined to test for a direct impact of GPR on SCC. We further examine the moderating effects of firms’ operational capabilities and resources (i.e. firm resilience, operational slack and cash holding). Fixed-effect regression models are applied to test the hypotheses, followed by a series of robustness tests to check the consistency of the results.

Consistent with the tenets of resource dependence theory, our analysis reveals a significant negative impact of GPR on SCC. Moreover, we find that this adverse effect is attenuated for firms with higher levels of resilience, more operational slack and greater cash holdings. Further analysis suggests that maintaining a diversified supply chain base during heightened GPR is associated with a firm’s improved financial performance.

This study contributes to the supply chain management (SCM) literature by integrating GPR into the supply chain risk management framework. Additionally, it demonstrates the roles of diversification and operational resources in addressing GPR-induced challenges.

Guanxi, an invisible aspect of many levels of interaction in economic life, has increased in importance in recent years; however, this subject has been underappreciated in high-tech industries. High-tech firms can choose to use guanxi with their partners as a key component of their competitive advantage or to view guanxi as necessary evil that is required to complete business exchanges. This paper aims to evaluate how guanxi contributes to or impedes a high-tech firm’s innovation performance.

This study proposes and tests a nonlinear model that explores the positive and negative impact of guanxi on the innovation performance using a sample of 184 high-tech firms located in Taiwan Science Park.

In contrast to the mainstream of findings in the previous literature, the authors find that guanxi is a competitive advantage in constructing new business networks; however, additional increase of guanxi may even decrease innovation performance. This view opens up new research avenues in the context of high-tech industries and suggests directions for future research and practice.

Academics and practitioners know little about the unfavorable aspects of this variable. Future studies might develop specific measurement scales that capture the negative side of strong guanxi. Beyond the positive side of variables that have been amply studied, such as affection and kindness, other interesting negative side of variables that may be considered in future studies are blood (Tsang, 1998), extortion (Dunfee and Warren, 2001) and favoritism (Hwang et al., 2009).

The authors contribute to the research on guanxi and innovation performance, in that this study extends guanxi literature beyond the intuitive conclusion that innovation performance can be significantly enhanced in Asian countries’ business networks by leveraging guanxi as competitive advantage, and further demonstrating when and how guanxi can be harmful for high-tech firms’ innovation performance.

This study aims to theoretically hypothesize and empirically examine the impact of economic policy uncertainty (EPU) on firms' innovation performance as well as the contingency conditions of this relationship.

This study collects and combines secondary longitudinal data from multiple sources to test for a direct impact of EPU on firms' innovation performance. It further examines the moderating effects of firms' operational and marketing capabilities. A series of robustness checks are performed to ensure the consistency of the findings.

In contrast to the common belief that EPU reduces the innovativeness of firms, the authors find an inverted-U relationship between EPU and innovation performance, indicating that a moderate level of EPU actually promotes innovation. Further analysis suggests that firms' operational and marketing capabilities make the inverted-U relationship steeper, further enhancing firms' innovation performance at a moderate level of EPU.

This study adds to the emerging literature that investigates the operational implications of EPU, which enhances our understanding of the potential bright side of EPU and broadens the scope of operational risk management.

The safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system. Through voiceprint technology, the sounds emitted by the transformer can be monitored in real-time, thereby achieving real-time monitoring of the transformer’s operational status. However, the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer, severely impacting the accuracy and reliability of voiceprint identification. Therefore, effective preprocessing steps are required to identify and separate the sound signals of transformer operation, which is a prerequisite for subsequent analysis.

This paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique (REPET) algorithm to separate and denoise the transformer operation sound signals. By analyzing the Short-Time Fourier Transform (STFT) amplitude spectrum, the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold, effectively distinguishing and extracting stable background signals from transient foreground events. The REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period, then constructs a repeating segment model. Through comparison with the amplitude spectrum of the original signal, repeating patterns are extracted and a soft time-frequency mask is generated.

After adaptive thresholding processing, the target signal is separated. Experiments conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation effects.

A REPET method with adaptive threshold is proposed, which adopts the dynamic threshold adjustment mechanism, adaptively calculates the threshold for blind source separation and improves the adaptability and robustness of the algorithm to the statistical characteristics of the signal. It also lays the foundation for transformer fault detection based on acoustic fingerprinting.

In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

This empirical paper is an endeavor to explore the relationship between social media advertising (SMA) and customers' purchase intention (CPI) in three South Asian countries. SMA was further divided into three relevant dimensions: perceived relevance (PR), perceived informativeness (PI) and perceived credibility (PC). Furthermore, the authors incorporated a single mediator: customers' brand consciousness (CBC) to test the mediating effects on the direct relationships.

The authors purposively selected 1937 fashion-conscious individuals based on a cross-sectional survey design. The authors applied SPSS 25 for explanatory statistics and structural equation modeling (SEM) (through AMOS 25) for testing the hypothesized relationships.

Based on the responses and the application of statistical measures, the authors revealed that all of the three dimensions of SMA have significant positive relationships with CPI. CBC is also significantly and positively related to CPI. Regarding the mediating effects, CBC was identified to have full mediation effects on the relationships between PR and CPI and PI and CPI. On the contrary, the same variable was found to have partial mediation on the relationship between PC and CPI.

South Asia is a growing business hub and the largest consumer market in terms of population. This empirical study was undertaken to reveal the role of SMA on CPI in the three highly populated South Asian countries, which is rare in academia. The outcomes of this empirical study are expected to be useful for further research attempts regarding SMA and consumer behavior. Businesses and policymakers are also expected to benefit from formulating SMA-related strategies to retain present buyers as well as attract the prospective ones.

This paper aims to examine the effect of dividend regulation on cost stickiness (i.e. the asymmetric change in firm expense between sales increase and sales decrease) and explore the underlying mechanism.

Based on the quasi-natural experiment of the Guideline for Dividend Policy of Listed Companies issued by the Shanghai Stock Exchange (SSE) in 2013, the authors employ a difference-in-difference model to investigate the impact of dividend regulation on cost stickiness.

The authors find that the cost stickiness of treatment group firms has decreased significantly when compared with control group firms after the dividend regulation. Moreover, this effect is more pronounced among firms in lower marketization regions, in lower competition industries and those with less analyst coverage and lower cash flow levels. Further analyses show that dividend regulation reduces the cost stickiness of firms by mitigating agency problems. Finally, the conclusion holds after several robust tests, including controlling for firm fixed effect, propensity score matching (PSM), placebo test and reconstruction of expense variable.

This paper confirms that dividend regulation serves an important role in corporate governance, which reduces firms' agency costs and thereby decreases cost stickiness. The conclusions shed light on the dividend policies of listed companies and capital market regulation in the future.