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Semiconductors are an important electronic component and play a central role in many industrial fields, whose production system is spread all over the world, involving trade in many raw materials, mechanical equipment, and finished products. Comprehending a broad global production picture of the semiconductor industry can be an arduous task. To tackle this complexity, the social network analysis method was used to capture the flows of products between economies in the semiconductor industrial chain. This study analyzed the evolution of the trade pattern of four key commodities in the semiconductor industrial chain, with a focus on identifying the status of major economies in the global semiconductor trade system. Additionally, the influencing factors of the formation of the trade networks were explored by using the Exponential Random Graph Model. The results showed that: (1) From 2001 to 2019, the import and export trade pattern of four key commodities in the semiconductor industrial chain has shown the characteristics of "rising in the east and decreasing in the west", but the change range shows strong commodity heterogeneity, the change of the spatial pattern of integrated circuits trade is the most significant, and the integrated circuits trade proportion of Asian economies has increased hugely with more than 80%. (2) The trade connectivity of various commodities in the semiconductor industrial chain has increased, upstream support products with high technical requirements such as wafers and equipment have the lowest average degree and weak trade liquidity, and the average degree of trade network of packaging materials and integrated circuits is relatively high, with strong trade liquidity and closer and more prosperous trade connections. (3) From 2001 to 2019, the "core-periphery" system of global semiconductor industry trade has changed significantly, with the core circle undergoing obvious iterative reorganization. for example, China and Singapore have achieved status improvement to the core circle in the base materials trade network, while Malaysia has been squeezed into the semi-peripheral circle. (4) The formation of trade networks of various commodities in the semiconductor industrial chain was driven by three aspects: network self-organization, exogenous endowment attribute, and exogenous network embeddedness. Among them, the influence of the technological innovation level of economies on different commodity trade networks showed heterogeneous. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the impact of corporate diversification and growth opportunities on the performance of real estate investment trusts (REIT) in Malaysia and Singapore before and during the pandemic. Design/methodology/approach: The sample consists of 33 public-listed REITs across Singapore and Malaysia. A dynamic panel system generalized method of moments (DPS-GMM) estimation is used to account for unobservable factors and a relatively short sample period (2009–2022). Findings: Results indicate that the impact of diversification is contingent on the market where the REIT is based and other institutional factors. The estimates also show that diversified REITs are better able to weather period of economic uncertainty. Practical implications: We provided a definitive answer as to why corporate diversification leads to conflicting outcomes – market and institutional factors, strategic intent and the overall economic environment. We also show that the impact of typical firm controls (i.e. free cash, size) can differ. Future firm-level work should thus study similar phenomenon more contextually and carefully consider these varying effects. Originality/value: The literature is divided on the impact of diversification on firm performance. By using a two-country sample, we show conclusive evidence that this contradictory outcome is due to market and institutional factors. We also show evidence that strategic intent is an important factor that influences the outcomes of diversification, regardless of market. We also infer that excess cash aids the resilience of the firm, contrary to the negative perception of excess cash during normal times. Firm size, in contrast, does not contribute to firm performance during a crisis. [ABSTRACT FROM AUTHOR]

Vector-borne infectious disease such as dengue fever (DF) has spread rapidly due to more suitable living environments. Considering the limited studies investigating the disease spread under climate change in South and Southeast Asia, this study aimed to project the DF transmission potential in 30 locations across four South and Southeast Asian countries. In this study, weekly DF incidence data, daily mean temperature, and rainfall data in 30 locations in Singapore, Sri Lanka, Malaysia, and Thailand from 2012 to 2020 were collected. The effects of temperature and rainfall on the time-varying reproduction number (Rt) of DF transmission were examined using generalized additive models. Projections of location-specific Rt from 2030s to 2090s were determined using projected temperature and rainfall under three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585), and the peak DF transmissibility and epidemic duration in the future were estimated. According to the results, the projected changes in the peak Rt and epidemic duration varied across locations, and the most significant change was observed under middle-to-high greenhouse gas emission scenarios. Under SSP585, the country-specific peak Rt was projected to decrease from 1.63 (95% confidence interval: 1.39–1.91), 2.60 (1.89–3.57), and 1.41 (1.22–1.64) in 2030s to 1.22 (0.98–1.51), 2.09 (1.26–3.47), and 1.37 (0.83–2.27) in 2090s in Singapore, Thailand, and Malaysia, respectively. Yet, the peak Rt in Sri Lanka changed slightly from 2030s to 2090s under SSP585. The epidemic duration in Singapore and Malaysia was projected to decline under SSP585. In conclusion, the change of peak DF transmission potential and disease outbreak duration would vary across locations, particularly under middle-to-high greenhouse gas emission scenarios. Interventions should be considered to slow down global warming as well as the potential increase in DF transmissibility in some locations of South and Southeast Asia. Author summary: Climate change has a significant impact worldwide, including the proliferation of infectious diseases in tropical areas. While the warmer and more humid living conditions in these regions are generally considered favorable for the transmission of vector-borne diseases, we argue that the effects of climate change on DF infection may vary across different locations. Unlike previous studies focusing primarily on the disease incidence, this study aims to estimate changes in peak DF transmissibility and the duration of disease epidemics in the future. By analyzing data from 30 locations in four tropical countries, we have found that changes in DF transmissibility and epidemic duration exhibit variations both within and between countries, particularly under the scenarios of moderate to high greenhouse gas emissions. In light of these findings, we recommend conducting location-specific evaluations of DF transmissibility under the influence of climate change, as well as implementing targeted interventions to mitigate the potential increase in DF transmission rates in specific tropical locations. [ABSTRACT FROM AUTHOR]

When individual civil society organizations (CSOs) in autocracies act collectively to campaign for a particular cause, they are more likely to succeed in pressuring an incumbent autocrat enact liberalizing reforms or resist democratic erosion. Under what conditions do CSOs engage in collective action for political reform in autocracies? The article argues that CSOs are more likely to act collectively for political reform when public interest in political reform and public support for CSOs is high. High public interest and support provides psychological motivation for collective action, psychological immunity from autocratic repression, and material immunity from a reliance on state funding. Increased salience and publicity from collective action further generates greater public interest and support. A positive collaborative equilibrium among CSOs ensues. However, when public interest and support is low, CSO leaders demur from collective action for fear of provoking the authoritarian state. A disinterested public demotivates CSO leaders, resulting in a negative collaborative equilibrium. We demonstrate this argument through a controlled comparison of divergent collaborative equilibriums for political reform in Malaysia and Singapore, utilizing original interviews with civil society activists in the two countries supported by public opinion data from the Asian Barometer and the World Values Survey. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the conditional volatility of the Asian stock market concerning Bitcoin and global crude oil price movement. Design/methodology/approach: This study uses the newest Dynamic Conditional Correlation (DCC)-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the conditional volatility of the stock market for Bitcoin and crude oil prices in the Asian perspective. The sample stock market includes Chinese, Indian, Japanese, Malaysian, Pakistani, Singaporean, South Korean and Turkish stock exchanges, with daily time series data ranging from 4 April 2015−31 July 2023. Findings: The outcome reveals the presence of volatility clustering on the return series of crude oil, Bitcoin and all selected stock exchanges of the current study. Secondly, the outcome of DCC, manifests that there is no short-run volatility spillover from crude oil to the Malaysian, Pakistani and South Korean and Turkish stock markets, whereas Chinese, Indian, Japanese, Singapore stock exchanges show the short-run volatility spillover from crude oil in the short run. On the other hand, in the long run, there is a volatility spillover effect from crude oil to all the stock exchanges. Thirdly, the findings suggest that there is no immediate spillover of volatility from Bitcoin to the stock markets return volatility of China, India, Malaysia, Pakistan, South Korea and Singapore. In contrast, both the Japanese and Turkish stock exchanges exhibit a short-term volatility spillover from Bitcoin. In the long term, a volatility spillover effect from Bitcoin is observed in all stock exchanges except for Malaysia. Lastly, based on the outcome of conditional variance, it can be concluded that there was increase in the return volatility of stock exchanges during the period of the COVID-19 pandemic. Research limitations/implications: The analysis below does not account for the bias induced due to certain small sample properties of DCC-GARCH model. There exists a huge literature that suggests other methodologies for small sample corrections such as the DCC connectedness approach. On the other hand, decisive corollaries of the conclusions drawn above have been made purely based on a comprehensive investigation of eight Asian stock exchange economies. However, there is scope for inclusive examination by considering other Nordic and Western financial markets with panel data approach to get more robust inferences about the reality. Originality/value: Most of the empirical analysis in this perspective skewed towards the Nordic and Western countries. In addition to that many empirical investigations examine either the impact of crude oil price movement or Bitcoin performance on the stock market return volatility. However, none of the examinations quests the crude oil and Bitcoin together to unearth their implication on the stock market return volatility in a single study, especially in the Asian context. Hence, current investigation endeavours to examine the ramifications of Bitcoin and crude oil price movement on the stock market return volatility from an Asian perspective, which has significant implications for the investors of the Asian financial market. [ABSTRACT FROM AUTHOR]