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The aim of this study is to investigate how the demographics and appearance cues of potential social engineers influence the likelihood that targets will trust them and accept security risk.

Data were collected through an online survey of 635 participants, including 322 participants from Arab countries and 313 participants from the UK. The survey presented scenarios with 16 personas who offered participants the use of their mobile internet hotspot. These personas were characterized by combinations of age (young vs aged), gender (male vs female), ethnicity (Arab vs UK) and look formality (casual vs formal). The study measured both participants’ offer acceptance and trust in the persona.

Results indicated a higher likelihood of offer acceptance from female and aged personas, as well as a greater trust in these groups. Arab participants showed a preference for personas with Arabian ethnic features. In both samples, trust and acceptance were influenced by the persona’s appearance, which was found to be gender-dependent; with female personas in casual attire and male personas in formal attire being trusted more in comparison to female with formal attire and male with informal, respectively.

Findings highlight the importance of incorporating awareness of appearance-based biases in cybersecurity training, suggesting the need for culturally sensitive training programs to enhance defense against social engineering.

This study distinguishes itself by elucidating the influence of social engineers’ demographic and appearance cues on the likelihood of individuals to take security risks, thus addressing a significant gap in the literature which has traditionally emphasized the profiles of targets.

Sexual harassment is a worldwide and prevalent problem that can have severe consequences. The #MeToo movement has highlighted that sexual harassment is not an isolated event and is linked to misogynistic cognitions and other forms of sexual violence. However, there is a lack of research regarding the relationship between sexual harassment and its nomological network, particularly in the general population. Therefore, the purpose of this paper is to explore the nomological network of harassment.

The aim of this study was to explore the relationship between perception of harassment and rape myths (RMS), with paraphilia (fantasy and behaviour) as mediators. In addition, the prevalence of paraphilia in the general population was explored and gender difference was analysed. Frequencies, Pearson's r correlations, independent sample t-tests and mediation analyses were conducted on a sample of n = 254 participants from the general population.

Analyses revealed that half of the sample have engaged in at least one paraphilia behaviour. Furthermore, correlations between a more lenient perception of harassment, RM acceptance and paraphilia were found, as well as significant gender differences. Finally, mediation models revealed a strong relationship between RM acceptance and a more lenient perception of harassment, with paraphilia mediating this relationship.

This study has several implications, highlighting the role of misogynistic cognitions in predicting a lenient perception of sexual harassment, and thus, proposing a key focus for prevention and intervention models.

This research is mostly conducted on male samples in these areas; thus, this study aimed to collect data from a diverse sample that may provide a better overview of sexual harassment and its nomological network.

This study aims to evaluate the nutrient content and acceptable qualities of plant-based burger patties (PBBP) formulated with chickpea flour, defatted sesame cake (DSC) flour, coffee silver skin and pomegranate juice as colorant.

The chemical composition, energy value, cholesterol content, amino acid composition, cooking loss, pH, color characteristics and sensory attributes of PBBP were analyzed using official procedures and compared to beef burger. 

PBBP had a protein value of 16.0 g/100g, which is nearly close to the protein content of the beef burger (18.1 g/100g). The fat content of the PBBP was approximately three times lower than that of the beef burger. The fiber content in PBBP was approximately 23 times as high as that in beef burgers samples (p = 0.05). The raw PBBP samples supplies 178 Kcal/100g, whereas beef burger possessed 259 Kcal/100g. Neither the raw nor the cooked PBBP samples contained any cholesterol. Both the beef and PBBP displayed acceptability scores higher than 7.0, which suggests that PBBP was well accepted.

It is concluded that the PBBP sample exhibited a protein value of 16.0 g/100g, which is comparable to the protein level of beef burgers (18.1 g/100g). The fat level of the PBBP samples was significantly lower than that of the beef burger samples. Uncooked PBBP samples contained significantly higher fiber content compared to beef burger samples. No cholesterol was found in raw or cooked PBBP samples. Overall acceptance scores for both beef and PBBP samples exceeded 7.0, suggesting that the proposed product (PBBP) was received favorably.

Powder bed density is a key parameter in powder bed additive manufacturing (AM) processes but is not easily monitored. This research evaluates the possibility of non-invasively estimating the density of an AM powder bed via its thermal properties measured using flash thermography (FT).

The thermal diffusivity and conductivity of the samples were found by fitting an analytical model to the measured surface temperature after flash of the powder on a polymer substrate, enabling the estimation of the powder bed density.

FT estimated powder bed was within 8% of weight-based density measurements and the inferred thermal properties are consistent with literature findings. However, multiple flashes were necessary to ensure precise measurements due to noise in the experimental data and the similarity of thermal properties between the powder and substrate.

This paper emphasizes the capability of Flash Thermography (FT) for non-contact measurement of SS 316 L powder bed density, offering a pathway to in-situ monitoring for powder bed AM methods including binder jetting (BJ) and powder bed fusion. Despite the limitations of the current approach, the density knowledge and thermal properties measurements have the potential to enhance process development and thermal modeling powder bed AM processes, aiding in understanding the powder packing and thermal behavior.

This research aims to explore perceptions of subjective well-being (SWB) in public relations (PR) practitioners, focusing on dimensions of job satisfaction, networking, relationships and work–life balance, while addressing the under-researched area of gender and age – related to stages of life – disparities in SWB within the PR industry.

Employing a mixed-methods sequential explanatory design, this study utilised a survey, followed by semi-structured interviews to investigate SWB among PR professionals in Portugal, considering gender and stages of life differences.

Using a gendered and stages of life lens, this study found nuanced perceptions of SWB among Portuguese PR professionals. Older women showed higher emotional well-being but lower work evaluations than men, while young professionals exhibited less gender disparities in SWB. Men reported greater job satisfaction, emphasising passion, while women faced challenges like work overload and valued recognition. Gender differences were seen in networking, with men favouring teamwork and women valuing friendships for career advancement. Work–life balance issues, especially among older women, related to mental health.

This study contributes to filling the research gap regarding SWB in the PR industry, particularly in Portugal, offering insights into gender and stages of life dynamics that influence SWB perceptions, thereby informing strategies for enhancing well-being and productivity in PR workplaces.

Even the greatest developed countries have capitulated to the destructions imposed on the global supply systems, as the COVID-19 pandemic has revealed. The purpose of this study is to explore human resource sourcing strategies for managing supply chain performance during the COVID-19 outbreak. There are six human resource sourcing strategies such as outsourcing, near sourcing, integration, the requirement of suppliers, joint ventures and virtual enterprise that are considered to measure supply chain performance.

Based on collecting data from the potential respondents of Indian manufacturing companies, the elevation of human resource sourcing strategies to supply chain performance is measured considering the multiple regression analysis techniques.

The results of the study revealed that four of the six hypotheses have a significant and positive relationship with supply chain performance during the COVID-19 outbreak while two hypotheses are partially supported that lent good support to this study.

In this critical situation, this study will enable managers and practitioners to support the business in giving customers the best services on time.

The novelty of this study is to identify the key human resource sourcing strategies by using multiple regression analysis methods, considering the case of Indian manufacturing companies to measure their supply chain performance during the COVID-19 outbreak era.

The purpose of this paper is to investigate and review the impact of the use of statistical quality control (SQC) development and analytical and numerical methods on average run length for econometric applications.

This study used several academic databases to survey and analyze the literature on SQC tools, their characteristics and applications. The surveys covered both parametric and nonparametric SQC.

This survey paper reviews the literature both control charts and methodology to evaluate an average run length (ARL) which the SQC charts can be applied to any data. Because of the nonparametric control chart is an alternative effective to standard control charts. The mixed nonparametric control chart can overcome the assumption of normality and independence. In addition, there are several analytical and numerical methods for determining the ARL, those of methods; Markov Chain, Martingales, Numerical Integral Equation and Explicit formulas which use less time consuming but accuracy. New ideas of mixed parametric and nonparametric control charts are effective alternatives for econometric applications.

In terms of mixed nonparametric control charts, this can be applied to all data which no limitation in using of the proposed control chart. In particular, the data consist of volatility and fluctuation usually occurred in econometric solutions. Furthermore, to find the ARL as a performance measure, an explicit formula for the ARL of time series data can be derived using the integral equation and its accuracy can be verified using the numerical integral equation.

The purpose of the study is to examine how risk factors contribute to the occurrence of defects in a process. By analyzing these risk factors in relation to process quality, the study aims to help organizations prioritize their resources and efforts toward addressing the most significant risks. These challenges, integrated with the emerging concept of Quality 4.0, necessitate a comprehensive risk assessment technique.

Fuzzy logic integrated with an analytic network process is used in the process failure mode and effects analysis for conducting risk identification and assessment under uncertainty. Through a mathematical model, the linkage of risk with Six Sigma is established and, finally, a value–risk matrix is developed for illustrating and analysing risk impact on process quality.

A case study on fused filament fabrication demonstrates the proposed methodology’s applicability. The results show its effectiveness in assessing risk factors’ impact on Six Sigma metrics: defects per million opportunities/sigma level.

By integrating qualitative assessments and leveraging available data, this approach enables a more comprehensive understanding of risks and their utilization for an organization’s quality improvement initiatives.

This approach establishes a risk-centric Six Sigma assessment method in accordance with the requirement of ISO 9001:2015 and in the context of Quality 4.0.

This study examines the direct and indirect effects of organizational environmental orientation (EO)/culture, quality management practices (QMP) and sustainability experience (SE) on the relationship between organizational green practices (GP) and the triple bottom line (TBL) of sustainability performance (SuP).

To test the seven hypotheses, a structured questionnaire was used to collect data. The responses of 365 managers from various USA businesses in the service industries were analyzed using IBM SPSS and structural equation modeling (SEM)-AMOS.

The empirical results indicate that positive SuP in the economic, environmental and social dimensions and organizational GP can be improved by a strong culture of EO, effective QMP and substantial SE.

This research fills the gap in existing research between important organizational and environmental priorities and SuP. Consequently, the study provides managers with important strategic guidance: for environmental practices to achieve profitability and sustainability success, companies must promote an environmental-mindful culture and strategically invest in integrated QM systems.

This research is one of the first that explores how organizational environmental culture and QMP affect directly and indirectly the relationship between GP and SuP. These results provide empirical evidence to support the claim that environmental culture and QMP have significant direct and indirect effects on the relationship between GP and SuP dimensions.

Drawing on the integrative perspective of the technology acceptance model (TAM) and theory of planned behaviour (TPB) and extending it further by examining the role of organisational facilitators and perceived HR effectiveness in this integrative perspective, we examine HR professionals’ AI-augmented HRM (HRM^(AI)) acceptance in this research.

The data (N=375) were collected from HR professionals working in different organisations in India. Structural equation modelling (SEM) was employed to analyse the data.

The results of the study suggest that along with organisational facilitator antecedents to the relevant components of both TAM and TPB, perceived HR effectiveness also enhanced the HRM^(AI) acceptance levels of HR professionals.

The research findings are expected to contribute to the understanding of the factors that influence the acceptance of AI-augmented HRM in organizations. The results may also help organisations to identify the facilitators that can enhance the adoption and implementation of AI-augmented HRM by HR professionals. Finally, the study provides a composite TAM-TPB theoretical framework that can guide future research on the acceptance of AI-augmented HRM.

To the best of our knowledge, this is one of the first attempts to factor in the effect of contextual factors (i.e. organisational facilitators and perceived HR effectiveness) in the TAM and TPB equations.