Northern University of Malaysia

International audience

Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.

Determining an appropriate sample size is vital in drawing realistic conclusions from research findings. Although there are several widely adopted rules of thumb to calculate sample size, researchers remain unclear about which one to consider when determining sample size in their respective studies. ‘How large should the sample be?’ is one the most frequently asked questions in survey research. The objective of this editorial is three-fold. First, we discuss the factors that influence sample size decisions. Second, we review existing rules of thumb related to the calculation of sample size. Third, we present the guidelines to perform power analysis using the G*Power programme. There is, however, a caveat: we urge researchers not to blindly follow these rules. Such rules or guidelines should be understood in their specific contexts and under the conditions in which they were prescribed. We hope that this editorial does not only provide researchers a fundamental understanding of sample size and its associated issues, but also facilitates their consideration of sample size determination in their own studies.

In this paper, the use of TF-IDF stands for (term frequencyinverse document frequency) is discussed in examining the relevance of key-words to documents in corpus. The study is focused on how the algorithm can be applied on number of documents. First, the working principle and steps which should be followed for implementation of TF-IDF are elaborated. Secondly, in order to verify the findings from executing the algorithm, results are presented, then strengths and weaknesses of TD-IDF algorithm are compared. This paper also talked about how such weaknesses can be tackled. Finally, the work is summarized and the future research directions are discussed.

Purpose The ESG factor, which consists of environmental, social, and governance factors, represents the non-financial performance of a company. United Nations Principles for Responsible Investment invites investors to consider ESG issues when evaluating the performance of any company. Moreover, nowadays, the contribution of corporations towards sustainable development is a major concern of investors, creditors, government, and other environmental agencies. Therefore, the purpose of this paper is to examine the impact of ESG factors on the performance of Malaysian public-limited companies (PLC) in terms of profitability, firm value, and cost of capital. Design/methodology/approach A total of 54 companies are selected from Bloomberg’s ESG database that has complete ESG and financial data from 2010 to 2013. This study conducted panel data regressions such as the pooled OLS, fixed effect, and random effect. Findings Based on the regression results, there is no significant relationship between individual and combined factors of ESG and firm profitability (i.e. ROE) as well as firm value (i.e. Tobin’s Q ). Moreover, individually, none of the factors of ESG is significant with the cost of capital (weighted average cost of capital, WACC), but the combined score of ESG positively and significantly influences the cost of capital (WACC) of a company. Practical implications As this is a new study on Malaysia, the findings of this study will be useful to investors, SRI analysts, policy makers, and other related agencies. Originality/value To the best of the authors’ knowledge, this study is among the first empirical study to examine the impact of ESG factors on the performance of Malaysian PLC in terms of profitability, firm value, and cost of capital.

This study examines the relationship between green finance and carbon dioxide (CO2) emissions in the top ten economies that support green finance (Canada, Denmark, Hong Kong, Japan, New Zealand, Norway, Sweden, Switzerland, the United Kingdom, and the United States). This study uses quantile on quantile regression (QQR), introduced by Sim and Zhou (2015), to examine the dependence structure between different quantiles of green finance and CO2 emissions. Our overall findings confirm the negative impact of green finance on CO2 emissions; however, this relationship varies across the different quantiles of the two variables. This variation might be due to green finance market conditions (e.g., bearish or bullish) and country-specific market conditions. The findings in the study confirm that green finance is the best financial strategy for reducing CO2 emissions.

Purpose – The purpose of this paper is to investigate the applicability of theory of planned behavior (TPB) with special emphasis on measuring the direct and moderating effects of subjective norms on attitude, perceived behavioral control and buying intention in context of buying organic food. Design/methodology/approach – Structured questionnaires were randomly distributed among academic staffs and students of two universities in southern Punjab, Pakistan. Structural equation modeling was employed to test the proposed model fit. Findings – Results of the study showed that subjective norms significantly moderate the relationship between attitudes and buying intention as well as between perceived behavior control and buying intention. Furthermore, subjective norms significantly influence attitude toward buying intention. Practical implications – The paper provides useful insights for the academics and marketers. Academics may further explore the role of subjective norms in order to have a better understanding of their effects on TPB components. Whereas, marketers can target the opinion leaders and reference groups to increase the demand of organic food. Originality/value – Majority of previous studies overlooked the role of subjective norms in determining the buying intentions with respect to organic food. The striking feature of this study is an in-depth emphasis on exploring the direct and moderating effects of subjective norms on the elements of TPB. Moreover, to the best of authors’ knowledge, this is a pioneer study that comprehensively examines the linkage of components of TPB with organic food purchasing in Pakistan.

A fiercer level of competition is becoming the most influential factor in the structure and activities of the banking system around the globe. Banks are competing not only with themselves, but also with other financial institutions within the financial industry. In a plural society such as in Malaysia, the competition is becoming fiercer with the existence of the Islamic bank, which was established specifically to cater for the needs of the Muslim population in the country. To attract more customers, both conventional and Islamic banks should have information on factors used by customers in selecting their banks. Investigates how Muslims and non‐Muslims select their banks and what services they use frequently. Results show that there are many similarities between Muslims and non‐Muslims in their selection of banks and utilization of services.

Internet shopping is a phenomena that is growing rapidly nowadays. A peep into the exponential growth of the main players in this industry indicates there is still a large reservoir of market potential for e-commerce. The conveniency of online shopping rendering it an emerging trend among consumers, especially the Gen Y. The prevalence of online shopping has raised the interest of the retailers to focus on this area. Therefore, this study was to determine the relationship between subjective norm, perceived usefulness and online shopping behavior while mediated by purchase intention. University students aged between 18 and 34 that currently pursuing their studies in University Malaysia Perlis were selected as the subject of analysis. 662 out of 800 sets of questionnaires distributed were valid for coding, analyzing and testing the hypothesis. Collected data were then analyzed using SPSS version 18.0 and AMOS version 16.0. Structural Equation Modeling to examine the model fits and hypothesis testing. The conclusion can be depicted that subjective norm and perceived usefulness significant positively influence online purchase intention but subjective norm insignificant influence shopping behavior in a negative way. It is interesting to note that perceived usefulness also insignificantly influence online shopping behavior. Finding also revealed that purchase intention significant positively influence online shopping behavior. For future research, sample from working adults and other variables that related to online shopping were to be included to minimise sampling bias.

The paper investigates the relationship between capital structure and firm performance. The investigation has been performed using panel data procedure for a sample of 237 Malaysian listed companies on the Bursa Malaysia Stock exchange during 1995-2011. The study uses four performance measures (including return on equity, return on asset, Tobin s Q and earning per share) as dependent variable. The five capital structure measure (including long term debt, short term debt, total debt ratios and growth) as independent variable. Size is a control variable. The data are divided into six sectors which are construction, consumer product, industrial product, plantation, property, trading and service. The results indicate that firm performance, which is measured by return on asset (ROA), return on Equity(ROE) and earning per share (EPS) have negative relationship with short term debt (STD),long term debt (LTD),total debt (TD), as independent variable. Moreover, there is positive relationship between the growth and performance for all the sectors. Tobin s Q reports that there are significantly positive relationship between short term debt (STD) and long term debt (LTD). It also reports that total debt (TD) has significant negative relationship with the performance of the firm which similar to the above analysis.

Human spatial behavior has been the focus of hundreds of previous research studies. However, the conclusions and generalizability of previous studies on interpersonal distance preferences were limited by some important methodological and sampling issues. The objective of the present study was to compare preferred interpersonal distances across the world and to overcome the problems observed in previous studies. We present an extensive analysis of interpersonal distances over a large data set ( N = 8,943 participants from 42 countries). We attempted to relate the preferred social, personal, and intimate distances observed in each country to a set of individual characteristics of the participants, and some attributes of their cultures. Our study indicates that individual characteristics (age and gender) influence interpersonal space preferences and that some variation in results can be explained by temperature in a given region. We also present objective values of preferred interpersonal distances in different regions, which might be used as a reference data point in future studies.

Abstract This panel study investigates the relationship between green logistics indices, economic, environmental, and social factors in the perspective of Asian emerging economies. This study adopted Fully Modified OLS (FMOLS) Model and Dynamic OLS (DOLS) Model methods to test the research hypothesis, catering the problem of endogeneity and serial correlation. The results suggest that logistics operations, particularly LPI2 (efficiency of customs clearance processes), LPI4 (quality of logistics services), and LPI5 (trade and transport‐related infrastructure), are positively and significantly correlated with per capita income, manufacturing value added and trade openness, whereas greater logistics operations are negatively associated with social and environmental problems including, climate change, global warming, carbon emissions, and poisoning atmosphere. In addition, human health is badly affected by heavy smog, acid rainfall, and water pollution. The findings further extend and reveal that political instability, natural disaster, and terrorism are also a primary cause of poor economic growth and environmental sustainability with poor trade and logistics infrastructure. There is very limited empirical work presented in the literature using renewable energy and green ideology to solve macro‐level social and environmental problems, and this study will assist the policy makers and researchers to understand the importance of the green concept in improving countries' social, economic, and environmental performance.

This study investigates the roles of board independence and CEO duality on a firm’s performance relying on financial ratios, namely ROA, ROE, EPS and profit margin. This paper argues that if boards and leadership structure are well in place and conform to the practices in other developed countries, the long‐term shareholder value is expected to increase and shareholder interests are also well protected. To test the roles of board independence and CEO duality, data from the KLSE Main Board companies for the 1994‐1996 financial years were used. The 1994‐1996 financial years were chosen because, during this period, the issue of corporate governance in Malaysia was not as prominent as it was during, and after, the 1997/1998 financial crisis. Thus, this period could be considered as the period during which guidelines on the structure of the board of directors were not yet available in Malaysia. The findings, generally, suggest that neither board independence, leadership structure nor the joint effects of these two showed any relations with firm performance. Findings of this study, nonetheless, showed that Malaysian companies’ boards were generally dominated by outside directors and the majority of the companies in the study practiced non‐dual leadership structures. Thus, this evidence suggests that the structure of the boards of directors in Malaysia is largely independent of management and the absence of any dominant personality.

Partial least squares structural equation modeling (PLS-SEM) is one of the most widely used methods of multivariate data analysis. Although previous research has discussed different aspects of PLS-SEM, little has been done to explain the attributes of the various PLS-SEM statistical applications. The objective of this editorial is to discuss the multiple PLS-SEM applications, including SmartPLS, WarpPLS, and ADANCO. It is written based on information received from the developers via emails as well as our ongoing understanding and experience of using these applications. We hope this editorial will serve as a manual for users to understand the unique characteristics of each PLS-SEM application and make informed decisions on the most appropriate application for their research.

In this study, we developed a modified version of the CRiteria Importance Through Inter-criteria Correlation (CRITIC) method, namely the Distance Correlation-based CRITIC (D-CRITIC) method. The usage of the method was illustrated by evaluating the weights of five smartphone criteria. The same evaluation was repeated using four other objective weighting methods, including the original CRITIC method. The results from all the methods were further analyzed based on three different tests (i.e., the distance correlation test, the Spearman rank-order correlation test, and the symmetric mean absolute percentage error test) to validate D-CRITIC. The tests revealed that D-CRITIC could produce more valid criteria weights and ranks than the original CRITIC method since D-CRITIC yielded a higher average distance correlation, a higher average Spearman rank-order correlation, and a lower symmetric mean absolute percentage error. Besides, additional sensitivity analysis indicated that D-CRITIC has the tendency to deliver more stable criteria weights and ranks with a larger decision matrix. The research has contributed an alternative objective weighting method to the area of multi-criteria decision-making through a unique extension of distance correlation. This study is also the first to propose the idea of a distance correlation test to compare the performance of different criteria weighting methods.

This editorial is dedicated to moderation analysis. Similar to what we did with the earlier editorial about mediation analysis, this editorial addresses seven key issues related to moderation and provides guidelines to justify the inclusion of moderator(s) and perform the analysis. Specifically, it discusses identification, conceptualization, usage, analysis, and reporting of moderating variables. Additionally, it also explains several approaches pertaining to moderation analysis and highlights the key differences between a simple moderation analysis and a multi-group analysis. We hope that this editorial will be useful to academics and research students to conduct moderation analysis with rigor.

Abstract The objective of this research is to examine the role of economic growth, technology innovation, and renewable energy in reducing transport sector CO 2 emission in China by using the annual data of 1990–2018. An application of the QARDL approach discloses that economic growth, technology innovation, and renewable energy significantly influence CO 2 emission in the transportation sector in China. Both renewable energy consumption and innovation show a negative impact on emissions of CO 2 related to transport. It depicts that due to the increase in renewable energy and innovation, the CO 2 emission in the transport sector is likely to decrease; however, an increase in the GDP of a country will upsurge the emission of CO 2 in the transportation sector. However, China should make new policies to introduce innovation in the transportation sector to minimize the emission of CO 2 .

Dynamic and causality interrelationships from municipal solid waste recycling to economic growth, carbon emissions, and energy efficiency using a novel bootstrapping autoregressive distributed lag

The coronavirus disease 2019 is a new pandemic that spreads primarily through contact with an infected person when they cough or sneeze. The outbreak of COVID-19 is starting in China then spreading to worldwide that contributes to large number of deaths (40,598 deaths, 1 st April 2020). The COVID-19 is a disease causes respiratory illness with symptoms such as a cough, fever, and in more severe cases, difficulty breathing. To preventing spreading of this pandemic, many countries implementing lockdown procedure to stopping the chain of infection for this new disease. The government-ordered lockdowns have disrupted life for billions and in the same time creates economic collapse scenario. The country with the most COVID-19 infections reported a record surge in unemployment. Therefore, this research calculates the effect of COVID-19 to tourism industry for affected countries in the worldwide. This study evaluated the impact using supply and demand curve to detect the economic changes in tourism industry. The result shows COVID-19 CREATES panic among public that contributes to lower demand in tourism industry. This is one of effect because of disease spreading including lockdown approach that implemented in current situation. This scenario, contributes to lower demand price by customer. Therefore, according to market equilibrium of supply-demand theory, the price of tourism sector is keep decreasing parallel with decrement in demand. The finding of this study is very important to government in preventing and stopping decrement demand in tourism industry. The government need to introduce a mechanism that economy and in the same time developing anti-virus for COVIC-19. If the action of prevention is not mange properly, the tourism industry will face more decremental effects that creates economic collapse.

Abstract In terms of attaining the objectives of Sustainable Development Goals (SDGs), the Asian economies are considered as laggards, and one of the major problems faced by these economies is the issue of environmental degradation. For addressing this pertaining issue, a policy-level reorientation might be necessary. In this view, this study aims to explore the impact of urbanization, renewable energy consumption, financial development, agriculture, and economic growth on CO2 emissions in 15 Asian economies over 1990–2014. The empirical evidence demonstrates that urbanization, financial development, and economic growth increase CO2 emissions, renewable energy consumption reduces CO2 emissions, and the impact of agriculture is insignificant. Impulse response function and variance decomposition techniques are used to test the causality among the variables. Based on the study outcomes, a comprehensive SDG-oriented policy framework has been recommended, so that these economies can make progression toward attaining the objectives of SDG 13 and SDG 7. This study contributed to the literature by recommending this SDG-oriented policy framework, which encapsulates economic growth and its drivers.