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The research analyzes the influence of three environmental triggers, i.e. awareness, concern and knowledge on environmental attachment and green motivation that affect tourists' pro-environmental behavior in the Pakistan’s tourism industry. Furthermore, this study has analyzed the moderating role of moral obligation concerning environmental attachment and green motivation on tourists' pro-environmental behavior.

Data were gathered via a structured questionnaire by 237 local (domestic) tourists of Pakistan. Furthermore, the data were examined by employing SmartPLS.

Findings demonstrate that all three environmental triggers have a positive and significant relationship with environmental attachment and green motivation. Accordingly, environmental attachment and green motivation promote tourists' pro-environmental behavior. Furthermore, the moderating role of moral obligations has also been incorporated in the study. The finding reveals a strong and positive relationship among environmental attachment and tourists' pro-environmental behaviors during high moral obligations. In contrast, moral obligations do not moderate association between green motivation and tourists' pro-environmental behavior. Therefore, competent authorities should facilitate tourists to adopt environmentally friendly practices; which will ultimately promote pro-environmental behavior.

This study provides useful insights regarding the role of tourism in fostering environmental attachment and green motivation that sequentially influence tourist pro-environmental behavior. Secondly, this research has employed moral obligations as a moderator to identify the changes in tourists’ pro-environmental behavior based on individuals' ethical considerations. Hence, the study provides an in-depth insight into tourists' behavior. Lastly, the present research offers effective strategies for the tourism sector and other competent authorities to increase green activities that can embed the importance of the environment among individuals.

This research paper aims to explore asymmetric market efficiency of the 13 Euro countries, i.e. Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Netherland, Portugal, Slovakia, Slovenia and Spain, concerning the period before global financial crisis (GFC), after GFC and period of COVID-19 pandemic.

Multifractal detrended fluctuation analysis (MF-DFA) is applied to examine the persistence and anti-persistency. It also discusses the random walk behavior hypothesis of these 13 countries non-stationary time series. Additionally, generalized Hurst exponents are applied to estimate the relative efficiency between short- and long-run horizons and small and large fluctuations.

The current study results suggest that most countries' markets are multifractal and exhibit long-term persistence in the short and long run. Moreover, the results with respect to full sample confirm that Portugal is the most efficient country in short run and Austria is the least efficient country. However, in long run, Austria appeared to be highly efficient, and Slovakia is the least efficient. In the pre-GFC period, Greece is said to be the relatively most efficient market in the short run, whereas Austria is the most efficient market in the long run. In the case of Post-GFC, Netherland and Ireland are the most efficient markets in short and long run, respectively. Lastly, COVID-19 results indicate that Finland's stock market is the most efficient in short run. Whereas, in the long run, the high efficiency is illustrated by Germany. In contrast, the most affected stock market due to COVID-19 is Belgium.

This study will add value to the present knowledge on efficient market hypothesis (EMH) with the MF-DFA approach. Also, with the MF-DFA approach, potential investors will be capable of ranking the stock markets of Eurozone countries based on their efficiency in the period before and after GFC and then specifically in the period of COVID-19.

本研究旨在探討13個歐元區國家在環球金融危機前後, 以及2019新型冠狀病毒病肆虐時期之不對稱市場效率; 這13個國家包括: 奧地利、比利時、芬蘭、法國、德國、希臘、愛爾蘭、義大利、荷蘭、葡萄牙、斯洛伐克、斯洛維尼亞和西班牙。

研究人員使用多重分形去趨勢波動分析法、來探討持續性與反持續性。這分析法也用來討論正在研究中的13個國家的非平穩時間序列的隨機漫步假說; 而且, 廣義赫斯特指數被用來估算長期/短期投資與大/小波動之間的相對效率。

研究結果間接表明了大部份國家的市場都是多重分形的; 而且, 它們無論以短期抑或以長期來審視觀察, 均能展示持久性。再者, 就整體樣本而言, 研究結果確認了在短期來看, 葡萄牙是效率最高的國家, 而奧地利則效率最低。唯以長期來審視觀察, 奧地利則似乎效率很高, 而效率最低的則是斯洛伐克。在環球金融危機爆發前, 就短期而言, 希臘被認為是相對效率最高的市場, 而長期而言, 效率最高的則是奧地利。至於在環球金融危機爆發後, 就短期而言, 荷蘭是效率最高的市場, 而就長期而言, 效率最高的則是愛爾蘭。最後, 2019新型冠狀病毒病的結果顯示, 就短期而言, 荷蘭的股票市場是效率最高的, 而長期而言, 德國則展示了其高效率性。而受疫情影響最大的股票市場則是比利時。

研究採用了多重分形去趨勢波動分析法、來探討股票市場的效率, 並以此分析法來討論有關國家的非平穩時間序列的隨機漫步假說, 這使我們對效率市場假說有進一步的認識; 就此而言, 本研究為有關的探討增添價值; 而且, 有意投資者在使用多重分形去趨勢波動分析法下, 能夠基於歐元區國家的股票市場在環球金融危機前後, 以及更明確地在2019新型冠狀病毒病肆虐時期的效率, 來把這些股票市場分等級。

環球金融危機、2019新型冠狀病毒病、效率市場假說、多重分形去趨勢波動分析.

Due to increase in operational risk, banks are facing huge losses. In order to avoid losses, banks need to manage operational risk. This study aims to analyze the impact of operational risk management (ORM) processes, which include identification, assessment, analysis, monitoring and control in the presence of corporate governance (CG) that can also contribute to effective ORM practices.

Operational risk management processes are used to manage operational risk along with CG. Primary data are collected through questionnaire from (167) operational risk managers of commercial banks. Multiple linear regressions has been run to analyze the data.

Results indicate significant impact of CG and operational risk identification (ORI), monitoring and control on ORM practices in commercial banks of Pakistan.

The study suggests policy makers to improve the ORM framework by CG. Beside this, in order to lessen operational risk, proper identification, monitoring and control of operational risk could also contribute.

This study provides the critical masses (thresholds) at which the positive incidence of finance and economic growth will be dampened by the negative effects of income inequality and poverty on energy consumption in Sub-Saharan Africa for policy direction.

The study employed the two steps systems GMM estimator for 41 countries in Africa from 2005–2020.

The study found that for finance to maintain a positive effect on energy consumption per capita, the critical thresholds for the income inequality indicators (Atkinson coefficient, Gini index and the Palma ratio) should not exceed 0.681, 0.582 and 5.991, respectively. Similarly, for economic growth (GDP per capita growth) to maintain a positive effect on energy consumption per capita, the critical thresholds for the income inequality indicators (Atkinson coefficient, Gini index and the Palma ratio) should not exceed 0.669, 0.568 and 6.110, respectively. On the poverty level in Sub-Saharan Africa, the study reports that the poverty headcount ratios (hc$144ppp2011, hc$186ppp2011 and hc$250ppp2005) should not exceed 7.342, 28.278 and 129.332, respectively for financial development to maintain a positive effect on energy consumption per capita. The study also confirms the positive nexus between access to finance (financial development) and energy consumption per capita, with the attending adverse effect on CO₂ emissions inescapable. The findings of this study make it evidently clear, for policy recommendation that finance is at the micro-foundation of economic growth, income inequality and poverty alleviation. However, a maximum threshold of income inequality and poverty headcount ratios as indicated in this study must be maintained to attain the full positive ramifications of financial development and economic growth on energy consumption in Sub-Saharan Africa.

The originality of this study is found in the computation of the threshold and net effects of poverty and income inequality in economic growth through the conditional and unconditional effects of finance.

With the increasing acclaim of Wireless Sensor Networks and its diverse applications, research has been directed into optimising and prolonging the network lifetime. Energy efficiency has been a critical factor due to the energy resource impediment of batteries in sensor nodes. The proposed routing algorithm therefore aims at extending lifetime of sensors by enhancing load distribution in the network. The scheme is based on the chain-based routing technique of the PEGASIS (Power Energy GAthering in Sensor Information Systems) protocol and uses Ant Colony Optimisation to obtain the optimal chain. The contribution of the proposed work is the integration of the clustering method to PEGASIS with Ant Colony Optimisation to reduce redundancy of data, neighbour nodes distance and transmission delay associated with long links, and the employment an appropriate cluster head selection method. Simulation results indicates proposed method’s superiority in terms of residual energy along with considerable improvement regarding network lifetime, and significant reduction in delay when compared with existing PEGASIS protocol and optimised PEG-ACO chain respectively.

This study aims to test empirically the differences between Islamic and conventional banks in terms of impacts of the audit committees' quality on financial performance between Subprime and Corona crises.

The variables are articulated in four hypotheses tested by the GLS analysis. The data were collected via DATASTREAM and from banks' annual reports. The collected data covered four continents: America, Asia, Africa and Europe. The financial performance measures and audit committee's determinants of the conventional and Islamic banks concerned 112 banks of each type after the Subprime crisis and before the Corona crisis (2010–2019).

Results showed that the audit committee reduced the profitability of two bank types. Moreover, it harmed the conventional banks' efficiency, but reported an unclear effect within Islamic banks. Even so, the authors noticed that the audit committee had a positive impact for the conventional banks' liquidity, while the same effect was apparently ambiguous on the Islamic banks' liquidity. For solvency, the audit committee positively influenced conventional banks, while it affected that of Islamic banks.

Empirically, the authors’ results can serve as a reference for decision-makers allowing to clarify the data on the financial competitiveness of two bank types to facilitate the planning of strategic performance programs based on the audit committee quality. Theoretically, researchers found that the differences between the results are due to the audit committee quality of each bank type or to the financial performance evaluation method. However, there are further factors that are related to the research peculiarities, the methodology, the data and the interpretation.

Based on the comparative literature review between conventional and Islamic banks, this study is the first conditional and comparative research between the audit committee quality and the financial performance of conventional and Islamic banks in a specific period (after Subprime and before Corona crises).