Partial Least Squares Structural Equation Modeling Analysis Research Articles

The Moderating Role of Supply Chain Agility on the Relationship Between Strategic Flexibility and Organizational Market Performance in Nigerian Pharmaceutical Industry

The pharmaceutical industry is key to the survival of the human race, but equally becoming increasingly susceptible to global disruptions. In Nigeria, records have shown that the industry is plagued with several problems, inclusive of low employee productivity, poor market share, low innovation performance, poor and marginal sales growth and low profitability, which are likely a result of a lack of strategic flexibility in the face of increasing environment turbulence and intense competition. Despite efforts from researchers, the moderating role of supply chain agility has been largely overlooked in the literature. Therefore, this study examines the moderating role of supply chain agility on the relationship between strategic flexibility (resource flexibility, coordination flexibility, proactive flexibility, reactive flexibility and futurity) and organisational performance. A survey research design was used to collect data from 642 management and senior staff employees of six pharmaceutical companies listed on the Nigerian Exchange Group. A total enumeration method was adopted for the study, with a well-structured adapted questionnaire, having Cronbach’s alpha reliability coefficients ranging from 0.725 to 0.945. Partial Least Squares Structural Equation Modeling (PLS-SEM) was chosen to achieve the research goal. The PLS-SEM analysis revealed that strategic flexibility positively affects organizational performance (β = -0.093, p> 0.050, Q2 = 0.644). However, supply chain agility negatively moderates this effect, indicating that while agility is beneficial independently, it can counteract the positive impact of strategic flexibility when combined. The study recommended that the management of pharmaceutical companies in Nigeria should pay serious attention to strategic flexibility as an organizational capability that can enhance performance in the face of increasing uncertainties in and unpredictability nature of the business environment.

The Effect of Work Stress and Work Environment on Job Performance in Manufacturing Industry: A PLS-SEM Approach

Employee performance is a critical determinant of growth and success within manufacturing organizations, making it essential to understand the factors influencing it. This study delves into the effects of work stress and the work environment on job performance, specifically within the electronics manufacturing sector in Penang, Malaysia. The research addresses how role ambiguity and conflict can act as stressors and also explores how intrinsic and extrinsic motivation factors related to the work environment affect job performance. The study sample comprised 116 participants from five electronics manufacturing firms located in Bayan Lepas, Penang. Data collection was conducted through a structured questionnaire, and the analysis was performed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results confirmed that the measurement model was robust, providing a solid foundation for validating the structural model. The PLS-SEM analysis demonstrated that the model had significant predictive capability, revealing that both work stress and the work environment exert substantial effects on job performance within the electronics manufacturing industry in Penang. Specifically, role stressors such as ambiguity and conflict were found to negatively impact job performance, while a supportive and motivating work environment positively influenced it. The study's results align with the theoretical frameworks of role stressors and self-determination, suggesting that effective management of stressors and the cultivation of a motivating work environment are essential for optimizing employee performance in the manufacturing sector.

The impact of residential winter HVAC usage behavior on arthritis in older adults: A PLS-SEM analysis

Environmental factors like temperature and humidity have been shown to influence arthritis symptoms in older adults, and HVAC equipment can regulate indoor environmental parameters. This study aimed to explore the pathways and effectiveness of residential HVAC usage behavior during winter on arthritis conditions. Conducted across four major climate zones in China, this cross-sectional study involved 3579 older adults aged 60–74 years and collected data on demographics, residential environments, lifestyles, and health outcomes. Utilizing Partial Least Squares - Structural Equation Modeling (PLS-SEM), a complex structural equation model (SEM) and an HVAC-Health mediation model was developed to analyze the relationships among influencing factors and health outcomes. Results revealed that socio-economic status, building characteristics, lifestyles, HVAC usage behavior, and indoor environmental exposure significantly affect the frequency of arthritis flare-ups (p < 0.05). Specifically, lifestyles, indoor wet and cold exposures have strong direct effects on health outcomes, with path coefficients of 0.178, 0.155 and 0.143, respectively. Moreover, HVAC usage indirectly influences health through mediators, with cold exposure (β = 0.045, p < 0.001), air pollution (β = 0.025, p < 0.001), and wet exposure (β = 0.012, p = 0.001) ranked in terms of their mediating effects. This research underscores the crucial role of HVAC systems in mitigating arthritis symptoms in older adults, advocating for enhanced implementation of HVAC technologies in senior housing to promote health and well-being. The originality of this study lies in employing the PLS-SEM method to elucidate how the indoor environment—particularly under the premise of HVAC usage—affect arthritis symptoms in older adults.

Leveraging user-generated content (UGC) in pre-travel behavior: A PLS-SEM and necessary conditions analysis (NCA) approach

Online review reading is almost ritualistic before making any purchases. Building on social cognition theory, uses and gratification theory, and stimulus organism response theory, this study explores user-generated content (UGC) attributes affecting intentions to travel via a mediating variable (destination image). Using partial least squares structural equation modeling (PLS-SEM) analysis and necessary conditions analysis (NCA) on responses ( N = 392) collected online in India, the findings reveal that the perceived novelty of content (PNC) and perceived value of content (PVC) positively influence destination image and behavioral intention. Destination image mediates the relationship between PNC, PVC, and content users’ behavioral intentions. Perceived reliability of content (PRC) positively affects behavioral intention. The findings suggest that adequate PNC, PRC, and PVC levels are necessary to enhance destination image and generate intention to travel. This study contributes to the UGC literature and provides recommendations for stakeholders to improve user experience and enhance destination image perception.

Using PLS-SEM and XAI for causal-predictive services marketing research

Purpose This study aims to redefine approaches to metrics in service marketing by examining the utility of partial least squares – structural equation modeling (PLS-SEM) and eXplainable Artificial Intelligence (XAI) for assessing service quality, with a focus on the airline industry. Design/methodology/approach Using the Airline Passenger Satisfaction data set from Kaggle platform, this study applies PLS-SEM, facilitated by ADANCO software and XAI techniques, specifically using the SHapley Additive exPlanations TreeExplainer model. This study tests several hypotheses to validate the effectiveness of these methodological tools in identifying key determinants of service quality. Findings PLS-SEM analysis categorizes key variables into Delay, Airport Service and In-flight Service, whereas XAI techniques rank these variables based on their impact on service quality. This dual-framework provides businesses a detailed analytical approach customized to specific research needs. Research limitations/implications This study is constrained by the use of a single data set focused on the airline industry, which may limit generalizability. Future research should apply these methodologies across various sectors to enhance a broader applicability. Practical implications The analytical framework offered here equips businesses with the robust tools for a more rigorous and nuanced evaluation of service quality metrics, supporting informed strategic decision-making. Social implications By applying advanced analytics to refine service metrics, businesses can better meet and exceed customer expectations, ultimately elevating the societal standard of service delivery. Originality/value This study contributes to the ongoing discourse on artificial intelligence interpretability in business analytics, presenting an innovative methodological guide for applying PLS-SEM and/or XAI in service marketing research. This approach delivers actionable insights, not only in the airline sector but also across diverse business domains seeking to optimize service quality.

Professional Standards and Educational Leadership: Higher Secondary Teachers’ Behavioral Intention Towards Adopting New Teaching Technologies

Integrating new teaching technologies in education has transformed the traditional classroom environment, offering innovative methods for teaching and learning. With the rapid advancement in digital tools and platforms, educational institutions are increasingly adopting these technologies to enhance instructional practices, engage students, and improve learning outcomes. Therefore, this research aimed to investigate the higher secondary teachers’ behavioral intention towards adopting new teaching technologies in the context of professional standards and educational leadership. The study adopted a descriptive research design and utilized a quantitative research approach. A standardized questionnaire and a web-based purposive sampling method were used to collect 350 data from higher secondary teachers in Bangladesh. The data was assessed, and the hypotheses were analyzed using a process called partial least squares structural equation modeling (PLS-SEM). The PLS-SEM analysis identified a notable link among perceived ease of use, enjoyment, usefulness, and behavioral intention in the context of professional standards and educational leadership. This study is highly significant for educational institutions and policymakers that aim to enhance teacher job satisfaction and teachers’ quality. Educational technology should feature an interface that is easy to use, engage the user’s interest, and fulfill its intended function efficiently. Furthermore, it is imperative to tailor training programs to aid teachers’ assimilation of the technology. School administrators must enact professional development efforts, encourage the effective use of technology, establish support networks, and provide adaptable solutions to meet the unique needs of instructors. These variables can potentially increase the rate of acceptance and satisfaction with technology in educational institutions.

Predictors of Sustainable Tourism Development during the Post-Pandemic Period in Bangladesh

The goal of this study was to examine the predictors of sustainable tourism development during the post-COVID-19 pandemic period in the context of Bangladesh. Quantitative-type research was applied, and this study used a descriptive research design. A standardized questionnaire was used to collect 302 data points from actual indigenous tourists using an online purposive sampling method. A partial least squares structural equation modeling (PLS-SEM) approach was used to evaluate the data and test the hypotheses. The results of the PLS-SEM analysis method demonstrate that environmental integrity, social equity, economic prosperity, and technological adaption had a positive relationship with sustainable tourism development during the post-COVID-19 pandemic period in Bangladesh. This research article provides practical guidelines for tourism authorities (BTB, BPC, and so on) and stakeholders on how to effectively impact environmental integrity, social equity, economic prosperity, and technological adaption on sustainable tourism development during the post-COVID-19 pandemic period in the context of Bangladesh. This study recommends that influential strategic factors be utilized to develop a sustainable tourism business in Bangladesh, positioning it as an emerging tourism destination.

Social environment, health cognition, and health behavior: how individuals with non-fixed employment end up with adverse health outcomes in China under the era of VUCA?-findings from PLS-SEM and fsQCA.

This article studied the single-factor causal relationships between the social environment, health cognition, and health behavior of the individuals with non-fixed employment and their adverse health outcomes, as well as the complex causal relationships of multiple factors on these outcomes. Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) are employed. Data is collected from the results of an open questionnaire Psychology and Behavior Investigation of Chinese Residents 2021. PLS-SEM analysis reveals that health risk behaviors and cognition play a mediating role in impact of the social environment on adverse health outcomes, indicating that individuals with non-fixed employment susceptible to adverse health outcomes. fsQCA analysis identifies that weak social support is a core condition leading to outcomes of depression and anxiety. There are shared configurations and causal pathways between the outcomes of physical health and depression. The study supports the social determinants theory of health and suggests that the fundamental reason for people being trapped in adverse health outcomes is the health inequality caused by social stratification, and the external shock of uncertainty in the era of VUCA (Volatility, Uncertainty, Complexity, and Ambiguity).

The hustle behind knowledge: role of workplace ostracism and knowledge hiding towards quiet quitting in knowledge-intensive organisations

Purpose Given the workplace’s reinvention to accommodate the global pandemic’s novel conditions, knowledge hiding (KH) behaviour in knowledge-intensive organisations must be examined from a fresh perspective. In this context, the relationship between workplace ostracism (WO) as KH’s antecedent and quiet quitting (QQ) as its consequence is undertaken via the mediating role of KH behaviour among knowledge workers (KWs). Design/methodology/approach Through stratified sampling, data from 649 KWs is obtained to test the model. Partial least squares structural equation modelling (PLS-SEM) using SMART-PLS 4.0. software establishes a significant influence of WO on KH and QQ. KH significantly mediates the relationship between WO and QQ, highlighting its critical intermediary role PLSPredict evaluates the model’s predictiveness. WO and KH’s effects on QQ are examined using necessity logic by collectively applying PLS-SEM and necessary condition analysis (NCA). Findings The model wherein WO plays a significant role in increasing KH and QQ, with KH as a partial mediator in the relationship, has high predictive relevance. Moreover, NCA confirms WO as the key predictor variable that provides variance in QQ, followed by KH. The Importance-performance map analysis technique supports the study’s managerial implications. Originality/value This study enriches QQ’s emerging literature by empirically identifying its antecedents-WO and KH. Methodologically, this paper gives a model for using PLS-SEM and NCA together in relation to QQ by identifying WO as its necessary condition. Evidence of selected constructs’ interrelationships may help organisations draft leadership programmes to curtail KH and QQ behaviour.

Exploring the nexus of attitude, contextual factors, and AI utilization intentions: A PLS-SEM analysis among primary mathematics teachers in China

This study delves into the pivotal integration of Artificial Intelligence (AI) in primary mathematics education, examining the nuanced interplay between teachers’ attitudes toward AI, Contextual Factors (CFs), such as institutional support and resource availability, and their Intention to Use AI (IUAI) in teaching practices. With the advent of digital transformation in education, understanding the dynamics of AI adoption in primary settings becomes increasingly critical. Surveying 476 primary mathematics teachers in China, this research employs partial least squares structural equation modeling (PLS-SEM) to unravel the complexities influencing AI integration. The findings reveal that teachers’ attitudes significantly impact their IUAI, while CF, particularly institutional support and resource availability, play a crucial role in shaping these attitudes and directly influencing IUAI. This investigation not only bridges a vital research gap by offering empirical insights into the determinants of AI adoption in a primary education context but also provides a robust framework for educators, policymakers, and stakeholders to foster a conducive environment for AI integration. By aligning AI deployment with pedagogical strategies, this study contributes significantly to enhancing the quality and effectiveness of mathematics education, underscoring the transformative potential of AI in shaping future educational landscapes.

Understanding driving forces of food waste separation intention to enhance regional and local solid waste planning: application of PLS-SEM and multi-group analysis

This study extended the theory of planned behaviour (TPB) and applied it to analyse influencing factors of food waste separation intention (FSI) among households in central Vietnam. Partial least squares structural equation modelling (PLS-SEM) was employed to analyse the data. The heterogeneity of factors contributing to FSI in cities of three levels was examined using multi-group analysis (MGA). The results indicate that attitudes, subjective norms (SN), perceived behavioural control (PBC), awareness of benefit (AB), information publicity (IP), facility availability (FA), and trust significantly affected FSI of households. MGA results indicated the heterogeneity of impacts of PBC and attitude on FSI of households among three municipal levels. The results will serve as basic data for waste officers, solid-waste management project leaders, non-governmental organisations (NGOs), and other related stakeholders to lay the foundation of food waste management planning in terms of regional scale and local scale. This study will also aid the creation of a circular economy by providing a scientific base for enhancing food waste separation at source in central Vietnam.

Understanding AI Chatbot adoption in education: PLS-SEM analysis of user behavior factors

The integration of Artificial Intelligence (AI) into education is a recent development, with chatbots emerging as a noteworthy addition to this transformative landscape. As online learning platforms rapidly advance, students need to adapt swiftly to excel in this dynamic environment. Consequently, understanding the acceptance of chatbots, particularly those employing Large Language Models (LLM) such as Chat Generative Pretrained Transformer (ChatGPT), Google Bard, and other interactive AI technologies, is of paramount importance. Investigating how students accept and view chatbots is essential to directing their incorporation into Industry 4.0 and enabling a smooth transition to Industry 5.0's customized and human-centered methodology. However, existing research on chatbots in education has overlooked key behavior-related aspects, such as Optimism, Innovativeness, Discomfort, Insecurity, Transparency, Ethics, Interaction, Engagement, and Accuracy, creating a significant literature gap. To address this gap, this study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the determinant of chatbots adoption in education among students, considering the Technology Readiness Index and Technology Acceptance Model. Utilizing a five-point Likert scale for data collection, we gathered a total of 185 responses, which were analyzed using R-Studio software. We established 12 hypotheses to achieve its objectives. The results showed that Optimism and Innovativeness are positively associated with Perceived Ease of Use and Perceived Usefulness. Conversely, Discomfort and Insecurity negatively impact Perceived Ease of Use, with only Insecurity negatively affecting Perceived Usefulness. Furthermore, Perceived Ease of Use, Perceived Usefulness, Interaction and Engagement, Accuracy, and Responsiveness all significantly contribute to the Intention to Use, whereas Transparency and Ethics have a negative impact on Intention to Use. Finally, Intention to Use mediates the relationships between Interaction, Engagement, Accuracy, Responsiveness, Transparency, Ethics, and Perception of Decision Making. These findings provide insights for future technology designers, elucidating critical user behavior factors influencing chatbots adoption and utilization in educational contexts.

Green practices and economic performance: Mediating role of green innovation in Ethiopian leather, textile, and garment industries—An integrated PLS-SEM analysis

Incorporating green issues into business operations is indisputable, as this is mandatory in today's environmental era. The purpose of this study was to explore the structural link between green practices such as green manufacturing, green marketing orientation, green human resource management, green investment, and the economic performance of textile and leather firms in Ethiopia through green innovation. This study was carried out utilizing a quantitative method, and 201 surveys were used to gather the data from the top managers and general managers of medium and large textile and leather firms in Ethiopia using stratified random sampling. To test the hypothesis, partial least squares structural equation modeling (PLS-SEM) was used. The results of this study demonstrate that green practices, specifically green manufacturing practices (GMP), green marketing orientation (GMO), and green investment (GIV), have a positive and substantial contribution to firms' economic performance (EP) and green innovation (GIN). However, the advancement of GIN is not significantly affected by the adoption of sustainable human resources management (HRM). Moreover, green innovation facilitates the connection between economic success, GIV, and GMO. Nonetheless, when it comes to the relationship between GHRM, green manufacturing practices, and economic success, green innovation plays no mediating function. According to this research, a company's management ought to strengthen its green practices as lower expenses would boost its economic outcome.

Determinants of consumer intention to use smart food lockers during COVID-19: A multi-method approach

During the COVID-19 pandemic, increased demand for contactless services has triggered the restaurant industry to adopt smart food lockers. Based on service quality theory, we investigated factors associated with consumer intention to use smart food lockers. We collected 222 valid questionnaires for the study and analyzed the data using the partial least squares structural equation modelling (PLS-SEM) and the fuzzy-set qualitative comparative analysis (fsQCA) method. Results of the PLS-SEM analysis show that food safety, convenience, perceived security, perceived control, and perceived time pressure significantly impact consumer intention to use smart food lockers. An MGA analysis shows that perceived protection during COVID-19 enhances the positive relationship between food safety and intention to use smart food lockers. For a more comprehensive view of the study’s findings, the fsQCA provides five scenarios that lead to high user willingness to use smart food lockers. This study provides practical insights into platforms and governments.

Customer engagement in Saudi food delivery apps through social media marketing: Examining the antecedents and consequences using PLS-SEM and NCA

In this study, we (1) investigated the role of social media marketing (SMM) activities in predicting customer engagement in online food delivery applications (OFDAs); (2) predicted the influencing role of customer engagement in OFDAs on behavioral outcomes; (3) utilized the stimulus-organism-response (S–O-R) framework to assess subsequent customer behavior; and (4) empirically validated the theoretical model using partial least squares structural equation modeling (PLS-SEM) and necessary conditions analysis (NCA). We obtained valid data from 233 respondents using the survey-based approach, which was then utilized for PLS-SEM and NCA analyses. The study's PLS-SEM analysis revealed that perceived SMM activities, such as informativeness and word-of-mouth (WoM), positively influence customer engagement in OFDAs. This engagement, in turn, predicts important behavioral outcomes, including co-production value, customer referrals, purchase intention, and customer satisfaction. The NCA results further indicate that informativeness, trendiness, and WoM are essential for driving customer engagement in Saudi-based OFDAs. These findings provide valuable insights for enhancing customer engagement and behavioral outcomes in the field of OFDAs, utilizing both PLS-SEM and NCA methodologies.

CD4+ T-cell subsets are associated with chronic stress effects in newly diagnosed anxiety disorders

AimPrior research has indicated a connection between CD4+ T cells and the development of anxiety, but the specific CD4+ T cell subsets linked to anxiety disorders remain uncertain. Our study seeks to investigate the relationship between distinct CD4+ T cell subsets and anxiety, as well as to explore whether CD4+ T cell subsets mediate the effect of chronic psychological stress on anxiety. Methods56 eligible matched participants were recruited in Peking Union Medical College Hospital. The diagnosis was made based on DSM-5 diagnostic criteria. The severity of anxiety and depression symptoms was assessed using the Hamilton Anxiety Rating Scale and Hamilton Depression Rating Scale, respectively. The Life Events Scale (LES) evaluated the chronic stress level. CD4+ T cell subsets were characterized using multiparametric flow cytometry. To assess the impact of CD4+ T cells on the effect of chronic psychological stress on anxiety, Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis was employed. ResultsWe discovered fifteen notably distinct CD4+ T-cell subsets in anxiety disorder patients compared to healthy controls. Multiple linear regression analysis unveiled an association between anxiety severity and CD27+CD45RA− Th cells, CD27+CD28+ Tregs, and the total Life Events Scale (LES) score. The PLS-SEM analysis demonstrated that CD4+ T cell subsets and LES could explain 80.2% of the variance in anxiety. Furthermore, it was observed that CD27+CD28+ Th/Treg cells acted as inverse mediators of the effects of LES on anxiety (P = 0.031). ConclusionsDrug naïve anxiety disorder patients exhibited significant alterations in numerous CD4+ T-cell subsets. Specifically, the memory subset of CD27+CD45RA− Th cells and the naïve subset of CD27+CD28+ Treg cells were found to be independent factors associated with the severity of anxiety. Additionally, the CD27+CD28+ Th and Treg cell subsets played a significant mediating role in the influence of long-term psychological stress on anxiety.

Analysing the Adoption of Wealthtech by Individual Investors for Investment Services

This research investigates the adoption of Wealthtech among individual investors in India using Partial Least Squares Structural Equation Modeling (PLS-SEM). A convenience sample technique was employed, gathering data from 280 participants through an online survey. The study applies the Theory of Planned Behavior and the Technology Acceptance Model as the theoretical framework to examine the factors influencing the intention to use Wealthtech. Additionally, the role of perceived ease of use and perceived usefulness in shaping attitudes toward Wealthtech adoption is explored. The results from the PLS-SEM analysis show significant positive associations between Attitude and Perceived Behavioral Control with the intention to use Wealthtech. These insights can help financial institutions tailor Wealthtech platforms to meet investor preferences, fostering increased adoption among individual investors. Regulatory authorities can use these findings to enhance accessibility and acceptance of Wealthtech solutions by fostering a conducive environment for technological innovation.

Associations between Adverse Childhood Experiences and Gambling Severity in Youth Online Gamblers: The Mediating Roles of Internalizing, Attention and Externalizing Problems.

This study examined the association between Adverse Childhood Experiences (ACEs) and Gambling Severity (gambling severity), considering the mediating roles of internalizing, externalizing, and attention among youth online gamblers. 762 youth (agemean±SD= 15.03 ± 2.40; agerange = 10-18 years; 75.3% boys) completed the Persian Gambling Disorder Screening Questionnaire (GDSQ-P), Pediatric Symptom Checklist - Youth Report (Y-PSC), and Behavioral Risk Factor Surveillance System Questionnaire (ACE's section, modified by authors). The analysis was done using the SMART PLS software. The reliability and discriminant validity of the provided model were assessed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). According to the results of the PLS-SEM analysis, the present model demonstrated suitable levels of reliability and validity. Adverse Childhood Experiences (ACEs) significantly affected attention, internalizing, externalizing problems, and gambling severity. Additionally, the level of gambling was directly correlated with ACEs. Moreover, the indirect influence of the independent variable on the dependent variable via the mediators was found to be statistically significant (P < .001).These findings suggest that externalizing behaviors, attention problems, and internalizing symptoms mediate the effect of ACEs on gambling severity. Lastly, fitness indices indicated that our proposed model fit the data well (SRMR = 0.06, d_ULS = 1.15, Chi-square = 1291.461, and NFI = 0.71). Our study found that ACEs significantly influence gambling severity among youth online gamblers, with internalizing, externalizing, and attention problems mediating this relationship. Practical implications include integrating ACE screening and targeted interventions for associated mental health issues into youth gambling prevention programs to mitigate the risk of problematic gambling behavior.

Does Copyright Imitation Impact Purchase Behaviour in the Entertainment Industry: A PLS-SEM Analysis of Gen Z’s Brand Recognition in Africa?

The entertainment industry has experienced remarkable growth, driven by technological advancements and changing consumer preferences, with revenue soaring to $31.23 billion in 2023 and anticipated growth at a Compound Annual Growth Rate (CAGR) of 10.64% through 2027. However, the industry’s significant sustainability issue is the widespread practice of copyright imitation, with Africa’s accommodated 2.5 billion unauthorised image imitations daily representing 1.48% global imitation index, causing substantial damages, notably affecting Gen Z with estimated losses of €532.5 billion, with Egypt experiencing the highest incidence of cases in Africa. This research delves into how copyright infringement impacts brand recognition, as a construct of purchase behaviour, among Gen Z in the African entertainment industry. By relying on post-positivism paradigm and planned behaviour theory, the research used questionnaire and collected 352 responses (92% sample rate) from tech-savvy Gen Z respondents, derived using Borden sampling model. The PLS-SEM (Partial Least Squares Structural Equation Modelling) model reveals that copyright infringement substantially affects brand recognition, explaining 64.7% of the variance in consumer behaviour. Specifically, imitated corporate names, product ideas, and promotional tactics impact brand recognition by 11.1%, 9%, and 6.2% respectively, which refutes the initial assumption. Research recommendations include implementing stricter management protocols within the industry, fostering deeper community engagement, and differentiating products by using unique, high-quality materials. The study acknowledges potential biases in data collection due to unequal online access among Gen Z music enthusiasts in Africa, by possibly not fully reflecting the broader diversity of Gen Z behaviour across the continent in the world, considering the varying cultural, economic, and social dynamics that influence purchasing behaviours.

The reflective measurement model of adherence to non-pharmaceutical interventions (NPIs) in accordance with normalization process theory (NPT) in coherent and convenient social subgroups: PLS-SEM analysis.

Non-pharmaceutical interventions (NPIs) decrease COVID-19 transmission. Reliability and validity of adherence to NPIs in accordance with normalization process theory (NPT) in coherent and convenient social subgroups using reflective measurement model assessment has not been evaluated. In February 2021, a sample of medical students and people with substance use disorders in treatment as coherent (based on continuous probability distribution) vs. convenient groups (based on convenience, not equal probability) composed of travellers and COVID-19 suspected persons from Split-Dalmatia County (SDC) (n = 656) in the Mediterranean completed self-administered surveys. Partial least squares structural equation modelling (PLS-SEM) was used to measure reflective model assessment of adherence to NPIs according to NPT. PLS-SEM reflective model assessment provided two-group specific factors in inverse relationships which determined adherence to NPIs with excellent goodness-of-fit [χ2 = 1.292, df = 1; P = 0.297, CFI = 1, TLI = 0.997, RMSEA = 0.011 (90% CI 0-0.105), RMSEA P = 0.604, SRMR = 0.008, Hoelter CN (α = 0.05) = 2322.757]. Significant negative factors covariance estimate (-0.716) revealed an inverse relationship between first (adherence to NPIs and internal locus of control (LoC) (0.640)) and second factor; young adulthood age (≤25) and highest level of education (1362). As the first factor increased the second tended to decrease. LoC is expected potential mechanism by which sex (MLsex = -0.017, SE = 0.007, P < 0.016) and belonging to coherent subgroups (MLgroup = -0.008, SE = 0.003, P = 0.015) can produce indirect effect of adherence to NPIs. Coherent subgroups had a more pronounced tendency toward integration of NPIs in everyday life. Group factors that facilitate the normalization were higher educated younger adults with a tendency toward external LoC.