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This paper analyses the importance of leadership and culture in combating corruption in Hong Kong SAR, Japan, Malaysia, New Zealand, Singapore and Taiwan.

This paper is based on the comparative analysis of the effectiveness of the anti-corruption measures in the studies of six selected countries/regions in this special issue of Public Administration and Policy. The contributors in this special issue were invited because of their publications on combating corruption in the six countries/regions.

The critical variable ensuring the effectiveness of combating corruption is the strong political will of the leadership in changing the culture of corruption in the country/region by implementing a zero-tolerance policy toward corruption, as shown in Singapore and Hong Kong. In New Zealand’s case, leadership plays a less important role because of the population’s emphasis on equality and egalitarianism and its reliance on the Ombudsman and Serious Fraud Office to curb corruption. However, the corrupt leadership of Tanaka Kakuei in Japan, Najib Rajak in Malaysia, and Chen Shui-bian in Taiwan, demonstrates clearly their insidious impact of consolidating their kleptocratic rule in these countries/regions.

As the role of leadership and culture in combating corruption has not been given sufficient attention in the literature, this paper attempts to rectify this neglect by demonstrating that the political leaders in Singapore and Hong Kong, and to a lesser extent, New Zealand, have succeeded in minimising corruption while their counterparts in Japan, Taiwan and Malaysia, have failed to do so.

Insurance companies exist to manage the risk of others, which is why they are perceived to be competitive in risk management (RM). Considering this, we investigate how different RM capabilities make insurers effective in RM. These capabilities include understanding risk and risk management (URRM), risk identification (RI), risk assessment and analysis (RAA) and risk monitoring (RMON) activities in insurance companies. In addition, the authors probe how these capabilities can jointly yield a competitive advantage for the insurance industry under the resource-based view (RBV) and dynamic capabilities perspective (DCP).

The authors present a latent variable RM model for the insurance industry and employ structural equation modeling (SEM) to test the hypotheses. Furthermore, the authors also conduct confirmatory factor analysis (CFA) and convergent and discriminant validity analysis for model fit and invariance testing, respectively.

The results show that insurers who investigated RM-related capabilities directly influence their risk management practices (RMPs). Moreover, improving these capabilities will make insurers more effective in managing the risks of others. Thus, RM as a business process will yield a competitive advantage for the insurance sector. The findings are supported by the theoretical insights presented by the RBV and DCP. Furthermore, the model also adheres to the convergent and discriminant validity cut-off values.

To the best of the authors’ knowledge, this is the first study examining insurers' RM practices as a source of a competitive advantage.

保險公司存在的目的是為其它公司或個人管理其風險；因此，保險公司在風險管理方面、被認為具有競爭能力。故此、我們擬研究不同的風險管理能力是如何能使保險公司有效地管理風險的呢？這些風險管理能力包括對風險及風險管理之了解、風險辨識、風險評估和分析，以及在保險公司內的風險監控活動。再者，我們探究這些風險管理能力如何根據資源基礎觀點及動態能力理論共同為保險業創造競爭優勢。

我們為保險業展示一個潛在變項風險管理模型，並使用結構方程模型，來測試我們的假設；而且，我們為模型適配度而進行了驗證性因素分析，又為不變性檢定而進行了驗證輻合及驗證區別效度分析。

研究結果顯示、若保險公司審査與風險管理相關之能力，這會直接影響其對風險管理之措施；而且，若保險公司能改善其風險管理之能力，這會使它們更有效地管理其它公司或個人的風險。因此，作為業務過程的一環、風險管理會為保險業創造競爭優勢。我們的研究結果，得到資源基礎理論及動態能力理論提供之理論見解所支持；而且，我們的模型從附驗證輻合及驗證區別效度的截止值。

據我們所知，本研究為首個研究、去探討保險公司的風險管理措施如何為它們創造競爭優勢。

The purpose of this article is the effect of doping minor Ni on the microstructure evolution of a Sn-xNi (x = 0, 0.05 and 0.1 wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment. Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of interfacial layer was different due to the different mechanism of element diffusion of the two substrates. The PC Ni substrate mainly provided Ni atoms through grain boundary diffusion. The Ni₃Sn₄ phase of the Sn0.05Ni/PC Ni joint was finer, and the diffusion flux of Sn and Ni elements increased, so the Ni₃Sn₄ layer of this joint was the thickest. The SC Ni substrate mainly provided Ni atoms through the lattice diffusion. The Sn0.1Ni/SC Ni joint increases the number of Ni atoms at the interface due to the doping of 0.1Ni (wt.%) elements, so the joint had the thickest NiSn₄ layer.

The effects of doping minor Ni on the microstructure evolution of an Sn-xNi (x = 0, 0.05 and 0.1 Wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment was investigated in this study.

Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of the interfacial layer was different due to the different mechanisms of element diffusion of the two substrates.

In this study, the effect of doping Ni on the growth and formation mechanism of IMCs of the Sn-xNi/Ni (single-crystal) solder joints (x = 0, 0.05 and 0.1 Wt.%) was investigated.

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always been considered a superior technique for selecting the relevant subset features from highly dimensional data and thus reducing learning complexity. In the relevant literature, streaming feature selection refers to the features that arrive consecutively over time; despite a lack of exact figure on the number of features, numbers of instances are well-established. Many scholars in the field have proposed streaming-feature-selection algorithms in attempts to find the proper solution to this problem. This paper presents an exhaustive and methodological introduction of these techniques. This study provides a review of the traditional feature-selection algorithms and then scrutinizes the current algorithms that use streaming feature selection to determine their strengths and weaknesses. The survey also sheds light on the ongoing challenges in big-data research.

Although knowledge sharing in online communities has been studied for many years, little is known about the determinants for individuals' knowledge sharing in online health communities (OHCs) surrounding smoking cessation. Examining the determinants of knowledge sharing in such OHCs from the social capital perspective may prove particularly enlightening.

A questionnaire-based online user survey of two smoking cessation OHCs, one based in Finland and one based in China, was performed. Performing data analysis with partial least squares (SmartPLS 3.0), the authors developed a model conceptualizing the structural, cognitive and relational dimensions of social capital as drivers for knowledge sharing in smoking cessation OHCs, with users' stage in giving up smoking as a moderator.

The results show that structural capital (social ties) and relational capital (reciprocity) are important motivators behind knowledge sharing in smoking cessation OHCs, and the authors found a moderating effect of the stage in quitting on the antecedents' relationship with knowledge sharing in these OHCs.

The study enriches understanding of knowledge sharing in smoking cessation OHCs, contributing to theory and identifying practical implications for such groups' administration.

Due to the recent coronavirus (COVID-19) outbreak, a temporary interruption of education activities occurred all over the world. The sudden and quick shift from blended or face-to-face learning mode to the sole online learning mode affected the perceptions of students toward the Blackboard application and the usage. This study aims to investigate the perceptions of students toward the Blackboard application in the process of learning Preparatory Year (PY) English courses as the mere tool of learning and the impact of the students’ perceptions on the students’ use of Blackboard.

The results are based on a survey conducted with 228 of PY students: 1st level n = 126 and 2nd level n = 102 at Najran University. The data are analyzed to compare the two levels, as the students’ prior experience with Blackboard is not the same. The 2nd level students have prior experience of blended learning through Blackboard, whereas 1st level students have no prior experience of learning through Blackboard.

The data of the perceptions of both levels showed that 1st level students’ perceptions toward online learning of English via Blackboard were higher than 2nd level students. The data on the frequency of the use of the Blackboard application reflected the perceptions of students.

The findings suggest that the students’ prior experience of e-learning via Blackboard has an impact on the students’ perceptions.

The findings of the study contributed to the learning through the management systems research field and online learning of English during the COVID-19 outbreak.