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Social engineering is crucial in today’s digital landscape. As technology advances, malicious individuals exploit human judgment and trust. This study explores how age, education and occupation affect individuals’ awareness, skills and perceptions of social engineering.

A quantitative research approach was used to survey a diverse demographic of Egyptian society. The survey was conducted in February 2023, and the participants were sourced from various Egyptian social media pages covering different topics. The collected data was analyzed using descriptive and inferential statistics, including independent samples t-test and ANOVA, to compare awareness and skills across different groups.

The study revealed that younger individuals and those with higher education tend to research social engineering more frequently. Males display a higher level of awareness but score lower in terms of social and psychological consequences as well as types of attacks when compared to females. The type of attack cannot be predicted based on age. Higher education is linked to greater awareness and ability to defend against attacks. Different occupations have varying levels of awareness, skills, and psychosocial consequences. The study emphasizes the importance of increasing awareness, education and implementing cybersecurity measures.

This study’s originality lies in its focus on diverse Egyptian demographics, innovative recruitment via social media, comprehensive exploration of variables, statistical rigor, practical insights for cybersecurity education and diversity in educational and occupational backgrounds.

Means, medians and SD for available socio‐economic status (SES) black‐white differences are here substituted for those of IQ in a between‐groups model published by the author over a decade ago. The goodness of fit of the SES variables used is compared with that for the earlier IQ data. Even when SES variables are relatively successful this can be viewed as additional evidence of the importance of IQ differences to black‐white differences in delinquency.

This experimental study investigates the connotative (measured) meaning of the concept “auditor independence” within three audit engagement case contexts, including two acknowledged in the literature to represent significant potential threats to independence. The study’s research design utilises the measurement of meaning (semantic differential) framework originally proposed by Osgood et al. (1957). Findings indicate that research participants considered the concept of independence within a two factor cognitive structure comprising “emphasis” and “variability” dimensions. Participants’ connotations of independence varied along both these dimensions in response to the alternative experimental case scenarios. In addition, participants’ perceptions of the auditor’s independence in the three cases were systematically associated with the identified connotative meaning dimensions.

Economic globalization is leading large companies to focus on international strategic management. Nowadays, the assets referred to as “corporate intangibles,” such as corporate reputation, are becoming increasingly important because they are considered a key factor for the viability of an organization, and companies therefore need to incorporate them into their scorecards for management. The problem is that their measurement is subjective and latent. These two characteristics impede direct international comparison and require demonstrating the accuracy of comparison via a minimum of two tests – construct equivalence and metric equivalence. As regards corporate reputation, construct equivalence was verified by Naomi Gardberg (2006). However, the subsequent studies did not address metric equivalence. Based on the results of a survey provided by the Reputation Institute (n = 5,950, 50 firms evaluated in 17 countries in the Americas, Europe, Asia and Australia), the degree of RepTrak metric equivalence has been tested, using two different methodologies, multigroup analysis (structural equation model), and a new technique from 2016, the Measurement Invariance of Composite Model procedure from the Partial Least Square Path Modeling family. As one would expect from other cross-cultural studies, reputation metrics do not meet the full metric equivalence, which is why they require standardization processes to ensure international comparability. Both methodologies have identified the same correction parameters, which have allowed validation of the mean and variance of response style by country.

It is generally recognized that multinational enterprises must take into account country differences in deciding the degree to which it makes sense to localize their human resource management (HRM) strategies and organization cultures to fit with the host country or rather standardize HRM strategies and organization cultures across countries. However, an important vein of academic work assumes that country differences, especially in national culture, are so important that management is “culturally dependent” (Hofstede, 1983) and that “national culture constrains variation in organization cultures” (Johns, 2006). I critically evaluate the logical and empirical evidence (including methodological issues regarding effect size) used to support such constraint arguments and conclude that the evidence is much weaker than widely believed. One implication then is that organizations may be less constrained by national culture differences in managing workforces in different countries than is often claimed. A second implication is that researchers may wish to re-think how they study such issues. I provide suggestions for future research.

Using data for the period 1965–2016, we investigate whether there are systematic differences between the investment performance of Black fund managers and those of other races in South Africa and whether investors recognize these differences. The two-tailed test results show that there is no significant difference between the two means considering the 12 months yield return at a hypothesized mean difference of zero. There is no statistical difference at 5% level of significance implying that the performance of Black fund managers is as equally as that of managers of other races. Our results also show that the percentage of Black fund managers in South Africa is still too low even as the workforce gets diverse. There's no single explanation for what is happening in this industry. The findings cannot be explained by differences in fund characteristics such as age, total assets under management or expenses or from the performance lenses. The results seem hard to reconcile with an explanation of differences in portfolio characteristics such as return volatility or market, size, value and momentum exposures.

We test the glass cliff hypothesis by employing conditional logistic regression (CLR). The approach enables the use of case/control style of analysis where White/majority fund managers are the control population and professional minorities are the case group. The selection of these as fund managers is our event or outcome variable. To test savior effect hypothesis, we employ analysis of variance (ANOVA). The technique enables us to compare variances between the groups: when a White male fund manager replaces a professional minority, when a White male fund manager replaces a White male fund manager and when a professional minority replaces a professional minority.

Our analyses so far have documented a woeful underrepresentation of Black fund managers in South Africa's mutual funds industry. We explore potential explanations for these trends. Our analysis is meant to be suggestive. Are Blacks, women, people of color and ethnic minorities finding success in the investment industry? Are they having rewarding and fulfilling careers? Or is the industry still homogenous (just a White man's world) with a thin veneer of diversity layered on for public relations effect? The percentage of Black fund managers in South Africa is still too low even as the workforce gets diverse. There is no single explanation for what is happening in this industry. The findings cannot be explained by differences in fund characteristics such as age, total assets under management or expenses or from the performance lenses. Also, the results seem hard to reconcile with an explanation of differences in portfolio characteristics such as return volatility or market, size, value and momentum exposures.

The two-tailed test results show that there is no significant difference between the two means considering the 12 months yield return at a hypothesized mean difference of zero. There is no statistical difference at 5% level of significance. Our results so far establish that, ceteris paribus, the performance of Black fund managers is as equally as that of managers of other races.

The two-tailed test results show that there is no significant difference between the two means considering the 12 months yield return at a hypothesized mean difference of zero. There is no statistical difference at 5% level of significance. Our results so far establish that, ceteris paribus, the performance of Black fund managers is as equally important as that of managers of other races.

The two-tailed test results show that there is no significant difference between the two means considering the 12 months yield return at a hypothesized mean difference of zero. There is no statistical difference at 5% level of significance. Our results so far establish that, ceteris paribus, the performance of Black fund managers is as equally important as that of managers of other races.

This paper investigates whether there are systematic differences between the investment performance of Black fund managers and those of other races in South Africa and whether investors recognize these differences. Our hypothesis is that due to Broad-Based Black Economic Empowerment (BBBEE) laws in the country and possibly, due to a perception of discrimination in the market, it is only Black fund managers with superior fund management skills that enter the profession. As such, we expect to find superior performance among Black fund managers. We also conjecture that investors recognize this phenomenon and reward Black fund managers with more fund flows and more investment mandates than others.

The purpose of this paper is to illustrate new methods of examining structural differences among segmented markets beyond comparing merely univariate variable mean scores, so as to help marketers and researchers gain better insights into segment differences for meaningful strategy development.

A comprehensive dataset covering various lodging market segments was constructed from Tripadvisor.com. The data then were sorted into lodging customer segments by star rating, type of operation, and level of price charged. Structural equation modeling with the −2 log‐likelihood difference test was conducted to illustrate how effectively the differences, if any, of market segments could be assessed in contrast to the traditional mean‐score comparison approach.

Guest satisfaction was influenced by the same performance variable to the same magnitude and direction across different lodging segments examined. Such stability in the amount of influence of performance on guest satisfaction was true even in the fact that the variable mean scores were significantly different across the market segments.

The traditional approach to examining segment differences via univariate mean scores could be one set of results, while the effect‐based difference assessments in this paper resulted in another. Developing marketing strategies based on the effect‐based segment differences, as illustrated in this paper, is considered more effective than the traditional mean‐based approach. One limitation of this paper could be use of a secondary dataset with limited scope of the model employed for an illustrative purpose. Another limitation is that the sample characteristics are unknown due to the nature of a secondary dataset. The examination of the market segments was also limited to those based on only three popular variables.

The paper is a fresh attempt to examine market segment differences through the effect of one variable on another. The paper advances the methods of hospitality and tourism research for examining segment differences beyond the traditional univariate mean‐based examination approach. The methodological illustration is applicable to a vast majority of different theoretical frameworks known in the hospitality and tourism field. Use of the assessment method illustrated in this paper also requires future market segmentation studies to rely more on theories than data.