Partial Least Squares Structural Equation Modeling Analysis Research Articles

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.

SERVICE QUALITY AND POSITIVE WOM INCREASING CUSTOMER SATISFACTION: PURCHASING DECISION AS INTERVENING VARIABLE

This study examines the service quality of Bakso Rusuk Joss restaurant in Depok and Positive WOM for customer satisfaction through purchasing decisions. As part of the research survey methodology, questionnaires were sent to restaurant customers. The final data sample was obtained on Bakso Rusuk Joss with 245 respondents who made purchases twice or more. Hypothesis testing was carried out using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach. PLS-SEM analysis is carried out in two steps. The first step is the reliability and validity analysis, while the second step is the estimation and verification of path coefficients and performance of structural models. Hypothesis testing with SEM using PLS-SEM 2.3.9 software. The results of this study show that service quality has a direct positive and significant effect on customer satisfaction and purchasing decisions. Positive WOM has a direct and significant impact on customer satisfaction. Purchase decisions have a direct and significant impact on customer satisfaction.

Effects of digital readiness on digital competence of AEC companies: a dual-stage PLS-SEM-ANN analysis

ABSTRACT To what extent does a firm’s digital readiness influence its competence in implementing digital initiatives? This study employs a deep-learning-based dual-stage approach using Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN) to demonstrate and quantify this relationship. Data were sourced from a questionnaire survey involving 428 architecture, engineering and construction (AEC) firms in New Zealand. The PLS-SEM analysis confirmed the positive correlation between the digital readiness of an organization and its competence towards seven types of DT, including immersive technologies, sensing technology, robotics, 3D printing, digital fabrication, artificial intelligence and big data. The ANN analysis further quantified the importance of the investigated readiness indicators in influencing digital competence. The results highlighted four most significant readiness attributes influencing the digital competence of AEC firms: (1) organizational culture, (2) perception of the leadership team, (3) hardware & software systems and (4) strategy plans. The findings can serve as a baseline for developing effective change management strategies and contribute to reducing the digital divide within AEC organizations, facilitating the effectiveness of organizational digital transformation.

Prediction Model of Sacha Inchi Crop Development Based on Technology and Farmers’ Perception of Socio-Economic Factors

Background: The sacha inchi plant contains nutrients that are beneficial for health, cosmetics, and food products, so it has the potential to be developed economically. The development of sacha inchi involves agricultural technology, which includes the treatment of fertilizer types that need to be studied in maintaining production and productivity. Objectives: This study aims to analyze the optimal type of fertilizer treatment on crop yields and the influence of farmers’ perceptions of socio-economic factors in the development of sacha inchi plants so that an optimal sacha inchi development prediction model is formed. Methods: The partial least squares structural equation modeling (PLS-SEM) method was applied in the study to analyze the effect of perception of socio-economic factors, and the adaptive neuro-fuzzy inference system (ANFIS) method was applied to predict the optimal fertilizer treatment model. Findings: The results of the PLS-SEM analysis showed that farmers’ perceptions of sacha inchi cultivation considered economic factors at a percentage of 50.66% and social factors at a percentage of 49.33% and had a linear relationship with the economic development of sacha inchi with a value of 0.832, although simultaneously, 77.7% was influenced by economic factors and social factors, and 22.3% was influenced outside these two factors. The ANFIS prediction results reinforced the results of the analysis, which stated that fertilizer treatment based on sacha inchi plant waste in the form of seed shells produced greater harvest weight compared with goat manure fertilizer. If farmers wanted to use a combination fertilizer, the used composition was 80% sacha inchi seed shell waste and 20% goat manure fertilizer or other materials; if the used composition was otherwise, the yield tended to decrease. This research contributes to the theory of production sustainability by integrating the optimal fertilization factor as a decision support unit in the model. Practically, this study recommends the application of fertilizer from the basic ingredients of sacha inchi seed shells to create a sustainable sacha inchi processing industry that ensures production stability, strengthens the agribusiness ecosystem, and develops the economic potential of sacha inchi and reduces the operational costs of sacha inchi farming by reducing the cost of purchasing fertilizer and supporting the circular economy model.

Safety climate and safety behaviors: Adapting and validating a positively worded safety climate scale through the time-lagged approach.

Contemporary literature raises serious questions about the inclusion of negatively worded items in the safety climate scale. Despite these reservations, limited efforts have been made to address this shortcoming. The present study aims to adapt and empirically validate the ten-items group-level safety climate scale with the purpose of replacing negatively worded items with positively worded ones after a thorough validation process. The present study is one of the first to propose an empirically validated group-level safety climate scale that uses positive items to measure the safety climate construct. Study 1 was conducted using a sample of 135 participants. Study 2 used a time-lagged approach to validate the scale, with a sample of 173 production workers from six oil and gas organizations in Malaysia. The Partial Least Squares Structural Equation Modeling (PLS-SEM) method was used to test the hypothesized relationships. In Study 1, the results of the exploratory factor analysis showed good reliability for the revised scale. In Study 2, the results of the PLS-SEM analysis demonstrated a positive relationship between safety climate and safety behaviors, thereby validating the revised and translated scale of safety climate. The revised safety climate scale will not only improve data quality, but it will also increase response rates. Additionally, the revised scale will assist managers in understanding the true perceptions of safety climate in their organization, regardless of the cultural context in which the scale is used.

How Does Interactivity Shape Users' Continuance Intention of Intelligent Voice Assistants? Evidence from SEM and fsQCA.

With the rapid expansion in the use of intelligent voice assistants (IVAs) in people's daily lives, how to improve users' continuous intention is crucial for the sustainable development of intelligent voice technology. Utilizing the stimulus-organism-response (S-O-R) framework, we propose a theoretical model to examine how three dimensions of interactivity (ie, two-way communication, responsiveness, perceived control) impact individuals' affective reactions (ie, psychological ownership, subjective well-being) and continuance intention of IVAs and how that effect differs technology readiness. To validate the proposed model, 412 valid samples were collected in China and underwent analysis using a comprehensive approach that incorporated partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The findings from the PLS-SEM analysis indicate that three dimensions of interactivity have significant impacts on affective reactions to varying degrees, thus affecting users' continuance intention. Among these dimensions, responsiveness is the strongest predictor of affective reactions. Additionally, the impact of subjective well-being on continuance intention is stronger when users with high technology readiness. Finally, the results from fsQCA support the PLS-SEM findings and provide three configurations with different combinations of antecedents that sufficiently explain high continuance intention. Our findings reveal the internal mechanisms through which the three dimensions of interactivity impact users' continued usage of IVAs. This study is among the first to examine the effects of dimensions of interactivity on behavioral intentions, utilizing both symmetric (PLS-SEM) and asymmetric (fsQCA) methodologies to identify the most significant dimensions of interactivity and determine sufficient combinations of dimensions to predict users' intention to continue using IVAs. These findings offer valuable and fresh insights for both theoretical understanding and practical application.

An assessment of critical success factors in information security implementation in organizations in Ghana

Purpose This paper aims to identify the critical success factors in improving information security in Ghanaian firms. Design/methodology/approach Through an exploratory study of both public and private Ghanaian organizations. The study relied on a research model based on the technology–organization–environment (TOE) framework and a survey instrument to collect data from 525 employees. The data was analyzed using partial least squares-structural equation modeling (PLS-SEM). Findings The findings confirm the role of the technological, organizational and environmental contexts as significant determinants in the implementation of information security in Ghanaian organizations. Results from PLS-SEM analysis demonstrated a positive correlation between the technology component of information security initiative, organization’s internal efforts toward its acceptance and a successful implementation of information security in Ghanaian firms. Top management support and fund allocation among others will result in positive information security initiatives and positive attitudes toward securing the organization’s information assets. Research limitations/implications The authors discussed the implications of the authors’ findings for research, practice and policy. Social implications The results of this study will be useful for both governmental and non-governmental organizations in terms of best practices for increasing information security. Results from this study will aid organizations in developing countries to better understand their information security needs and identify the necessary procedures to address them. Originality/value This study contributes to filling the knowledge gap in organizational information security research and the TOE framework. Despite the TOE framework being one of the most influential theories in contemporary research of information system domains in an organizational context, there is not enough research linking the domains of information security and the TOE model.

Examining the linkages between digitalisation, public service delivery and corruption in Ghana

Purpose This study aims to examine the linkages between digitalisation, public service delivery and corruption in Ghana using survey data from 121 respondents in Ghana. The authors also examine the mediating role public service delivery offers on corruption. Design/methodology/approach This study relied on the capability theory as its theoretical lens and partial least squares structural equation modelling (PLS-SEM) as the data analysis technique. Findings Results from the PLS-SEM analysis show that public service delivery significantly reduces corruption, whilst digitalisation does not. However, public service delivery significantly mediated the relationship between digitalisation and corruption. Research limitations/implications This study’s limitation is that the data was collected from Ghana only. To enhance the generalisability of findings, future research could collect data from multiple countries. In addition, the study did not factor in the moderating effects of demographic variables such as information and communication technology (ICT) literacy. Future research could consider these variables, given the low ICT literacy level of individuals in developing countries. Finally, future researchers could triangulate results with interviews and focus groups to provide more value to the identified questionnaire-based data. Practical implications The findings of this study highlight the need for digitalisation to be included in Ghana’s national policy objectives and service delivery objectives. It is essential for the government to ensure broader public engagement with stakeholders, including citizens, to ensure that digitalisation goals are achieved. The study’s results indicate that digitalisation does not significantly influence corruption. This calls for the government of Ghana to consider raising the level of human capital for the successful planning and deployment of e-services. This includes raising citizen ICT literacy and adopting cutting-edge technology to fully realize the benefits of online services. Developing capabilities, e-government leadership, and public sector employees as enablers of online public services should go hand-in-hand. It is also important to build connected capacities in the country and enhance access to information and technology, along with increasing digital infrastructure. Originality/value To the best of the authors’ knowledge, this is the first study to examine and offer a dual perspective on the role of digitalisation on public service delivery and corruption whilst considering the mediating role public service delivery offers on corruption.

Investigating the role of human resource management practices on employee performance through PLS-SEM approach: a case study of academic libraries in India

Purpose The purpose of this study is to explore the association between select human resource management practices and employee performance in academic libraries in India. Design/methodology/approach The current study uses the quantitative method of research. Partial least squares-structural equation modelling (PLS-SEM) was used to analyse the results. The current study uses a cross-sectional approach by using a convenient sampling method. The sample size of the study was 163, which was adequate for conducting PLS-SEM analysis. Findings The study found a significant positive correlation between human resource management practices and employee performance in academic libraries. This suggests that the implementation of effective human resource management practices has a beneficial impact on various aspects of employee performance. Research limitations/implications The study’s cross-sectional design may limit the ability to establish causality or determine the direction of the relationship between human resource management practices and employee performance. The study may have limitations regarding the sample size and its representativeness. If the sample is small or limited to specific academic libraries in India, it may not be possible to generalise the findings to a broader population of academic libraries in the country or to libraries in other regions or countries. Practical implications The study has practical implications for academic libraries in India. By recognising the significant correlation between human resource management practices and employee performance, libraries can prioritise the implementation of effective human resource management strategies. This includes aligning human resources practices with organisational goals, focusing on employee development and engagement and adopting best practices in recruitment, training and performance management. Social implications This study can have broader social implications by promoting a supportive and productive work culture that positively impacts the academic library community. Originality/value The paper focuses on a quite important and largely unexplored area of human resource management within the academic libraries sector.

Beyond Pleasure, Desire for Meaningful Consumption and Peacefulness from Digital Entertainment Platforms; Extending UTAUT2 Model with Eudemonic Motivation and Tranquility

The landscape of entertainment consumption has undergone a profound shift, with the emergence of digital entertainment platforms becoming indispensable in satisfying consumers’ desire for convenience. This study examines the complex interaction between user motivations and the adoption of digital entertainment platforms, focusing on the desire for meaningful consumption and the pursuit of experiencing peacefulness by adopting digital entertainment platforms. We extend the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) by introducing eudemonic motivation (EM) and tranquility (TL) as constructs influencing users’ behavioral intention (BI) and actual use (AU) of digital entertainment platforms. Adopting a non-probability mixed sampling method consisting of convenience and snowball sampling, we collected data from 870 active users across five southern Indian states through online surveys. A quantitative study design was used to test the model by employing partial least squares–structural equation modeling (PLS-SEM). The result of PLS-SEM analysis indicated that BI is positively influenced by effort expectancy (EE), hedonic motivation (HM), habit (HA), EM, and TL. Social influence (SI) has no significant influence on BI. The findings reveal that consumers seek meaningful eudemonic experiences and a sense of peacefulness from their digital entertainment interactions. This study serves as a foundation for future research, emphasizing the significance on crafting technologies that resonate with users’ quest for meaning and inner peace in digital entertainment consumption.

Enhancing Tax Compliance in the Energy Sector: PLS-SEM Analysis of Tax Administration Strategies

The energy sector often constitutes a significant portion of a country's gross domestic product (GDP). It includes industries related to oil, gas, electricity, and renewable energy sources. The size of this sector means that it has a substantial economic impact, contributing to overall economic growth and, in turn, increasing tax revenue. In the context of revenue generation challenges faced by tax authorities, this research explores the pivotal role of tax administration strategies in enhancing tax compliance within the energy sector. Employing a quantitative research methodology with a survey design, this study utilizes structured questionnaires distributed to randomly selected individual taxpayers involved in the energy sector in Indonesia, collecting 178 samples. The research leverages Partial Least Squares Structural Equation Modeling (PLS-SEM) to rigorously test its hypotheses. The findings underscore the critical importance of effective tax administration for augmenting tax compliance within the energy sector and, consequently, increasing tax revenues. The findings empirically prove that tax education, the imposition of law enforcement, and administrative efficiency emerge as key drivers, significantly and positively influencing tax compliance in the energy sector. The findings emphasize the importance of educating individuals and businesses within the energy sector about their tax obligations. Energy companies and workers should be well-informed about tax laws and regulations to encourage voluntary compliance.

Can consumption of local food contribute to sustainable tourism? Evidence from the perception of domestic tourists

ABSTRACT The nexus of tourism and sustainability has emerged as a catchphrase in academic literature in recent years. The present study employed an integrated path model to investigate the increasing significance of sustainable tourism, which is attributed, in part, to the penchant of domestic tourists to consume locally sourced food. The investigation additionally ascertains the potential influence of local food products on the various dimensions of sustainability, including economic, cultural, social, and environmental aspects. Data is collected using a purposeful sample technique, with 462 responses from domestic tourists to the Kashmir Valley being screened and analyzed using SPSS and partial least squares structural equation modeling (PLS-SEM). The findings derived from PLS-SEM analysis demonstrate that the act of domestic tourists consuming locally produced food has a considerable and statistically significant influence on sustainability-focused tourism. Furthermore, the consumption of locally grown foods has a positive influence on various dimensions of sustainability, including the economic, social, cultural, and environmental aspects. The present study contributes to the existing scholarly literature on the subjects of regional gastronomy and sustainable tourism. In the current work, the authors aim to present the potential of local food to promote sustainable tourism in the tourist host regions. The outcomes of this research can be utilized by policymakers in the tourism sector to enhance their ability to effectively market indigenous cuisine, thereby sustaining the industry’s enduring viability.

Factors Affecting Teachers' Integration of Visualization Technology in Geometry: PLS-SEM Analysis

Visualization is identified as a crucial element that affects students' performance in Geometry. Technology plays an important role to assist weak students in visualizing concepts in Geometry. Teachers need proper planning in teaching to help their students in understanding the concepts. This study used partial least squares-structural equation modelling (PLS-SEM) to test the hypotheses to verify the effects of variables on teachers’ intention of integrating visualization technology in teaching geometry. The model consists of four constructs: teaching strategy, teaching activity, selection of media, tools and teaching aids, and assessment. The research instrument consisted of 30 survey questions for four main constructs: teaching strategy, teaching activity, selection of media, tools, and teaching aids and assessment. The questionnaires were distributed to 180 teachers who teach Mathematics in secondary schools. The study used a PLS-SEM modeling tool to analyze data for reliability and validity. Results show that teaching strategy, teaching activity, selection of media, tools and teaching aids, and assessment significantly influence the integration of visualization technology in Geometry. This finding is a reference for policymakers and implementers to improve the quality of teaching and learning in Geometry for secondary schools.

Exploring the impact of intelligent learning tools on students’ independent learning abilities: a PLS-SEM analysis of grade 6 students in China

The purpose of this study was to investigate the influence of interaction quality and information quality of intelligent learning tools on students’ satisfaction and intention to use these tools, as well as to examine the relationship between the intention to use intelligent learning tools and students’ independent learning abilities. The study utilized Smart-PLS 3, a Partial Least Squares Structural Equation Modeling (PLS-SEM), to analyze data collected from 384 Grade 6 students in China. The results of the study showed that (a) intention to use intelligent learning tools had a significant and direct impact on students’ independent learning abilities; (b) interaction quality did not have a significant impact on intention to use, but information quality and satisfaction with the tools did have an impact on intention to use; (c) interaction quality and information quality indirectly influenced intention to use through students’ satisfaction with the tools. Furthermore, this research provided valuable recommendations for improving the interaction quality and information quality of intelligent learning tools, which can ultimately enhance students’ independent learning abilities.

What complex factors influence sleep quality in college students? PLS-SEM vs. fsQCA.

Sleep quality has a significant impact on the health-related quality of life, particularly among college students. This study proposes a framework for identifying factors that influence college students' sleep quality, including stress, self-control, bedtime habits, and neighborhood environment. The study employed a cross-sectional analytical approach on a convenience sample of 255 medical students from a private university in China during the 2021/2022 academic year, of which 80.39% (205) were women. Two complementary methodologies, partial least squares-structural equation modeling (PLS-SEM), and fuzzy sets qualitative comparative analysis (fsQCA), were utilized in the study. The results of the PLS-SEM analysis suggest that Stress and Self-control act as mediating variables in the model, with Bedtime habits and Neighborhood environment influencing sleep quality through these variables. Additionally, the fsQCA analysis reveals that Bedtime habits and Neighborhood environment can combine with Stress and Self-control, respectively, to influence sleep quality. These findings provide insight into how multiple factors, such as Stress, Self-control, Bedtime habits, and Neighborhood environment, can impact college students' sleep quality, and can be used to develop intervention programs aimed at improving it. Moreover, the use of both methodologies enables the expansion of new methodological approaches that can be applied to different contexts.

Modeling eco-friendly house purchasing intention: a combined study of PLS-SEM and fsQCA approaches

Purpose The urgency to address climate change and its devastating consequences has never been more pressing. As societies become increasingly aware of the detrimental impact of traditional housing on the planet, there is a growing demand for eco-friendly housing solutions that prioritize energy efficiency, resource conservation and reduced carbon emissions. Therefore, this study aims to investigate the factors that influence customers’ priority toward eco-friendly house purchasing intention. Design/methodology/approach This study collected 386 data using a quantitative research strategy and purposive sampling method. This study uses a hybrid analysis technique using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approaches to identify the influencing factors. Findings The PLS-SEM analysis found that attitude toward the eco-friendly house, subjective norms, performance expectancy, environmental knowledge and environmental sensitivity have a positive influence on eco-friendly house purchasing intention. However, perceived behavioral control and willingness to pay were found to have insignificant effect on customers’ intention to purchase eco-friendly houses. The fsQCA results further revealed complex causal relationships between the influencing factors. Practical implications This research will not only contribute to academic knowledge but also provide practical guidance to real estate developers, policymakers and individuals looking to make environmentally responsible choices. By understanding the factors that influence consumers’ intentions to purchase eco-friendly houses, we can pave the way for a more sustainable and resilient future. Originality/value This study has used a hybrid analysis technique, combining PLS-SEM and fsQCA, to enhance the predictive accuracy of eco-friendly house purchase intentions among individuals residing in densely populated and highly polluted developing countries, such as Bangladesh.

Use and acceptance of crypto currencies in India: an evaluation of block chain application in financial sector using PLS SEM and ANN approach

PurposeThis paper aims to create and evaluate a model for cryptocurrency adoption by investigating how age, education, and gender impact Behavioural Intention. A hybrid approach that combined partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) was used for the purpose.Design/methodology/approachThis study uses a multi-analytical hybrid approach, combining PLS-SEM and ANN to illustrate the impact of various identified variables on behavioral intention toward using cryptocurrency. Multi-group analysis (MGA) is applied to determine whether different data groups of age, gender and education have significant differences in the parameter estimates that are specific to each group.FindingsThe findings indicate that Social Influence (SI) has the greatest impact on Behavioral Intention (BI), which suggests that the viewpoints and recommendations of influential and well-known individuals can serve as a motivating factor to invest in cryptocurrencies. Furthermore, education was found to be a moderating factor in the relationship found between behavioral intention and design.Research limitations/implicationsPrior studies on technology adoption have utilized superficial SEM and ANN methods, whereas a more effective outcome has been suggested by implementing a dual-stage PLS-SEM and ANN approach utilizing a deep neural network architecture. This methodology can enhance the accuracy of nonlinear connections in the model and augment the deep learning capacity.Practical implicationsThe research is based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) and expands upon this model by integrating elements of design and trust. This is an important addition, as design can influence individuals' willingness to try new technologies, while trust is a critical factor in determining whether individuals will adopt and use new technology.Social implicationsCryptocurrencies are a relatively new phenomenon in India, and their use and adoption have grown significantly in recent years. However, this development has not been without controversy, as the implications of cryptocurrencies for society, the economy and governance remain uncertain. The results reveal that social influence is an important predictor for the adoption of cryptocurrency in India, and this can help financial institutions and regulators in making policy decisions accordingly.Originality/valueGiven the emerging nature of cryptocurrency adoption in India, there is certainly a need for further empirical research in this area. The current study aims to address this research gap and achieve the following objectives: (a) to determine if a dual-stage PLS-SEM and ANN analysis utilizing deep learning techniques can yield more comprehensive research findings than a PLS-SEM approach and (b) to identify variables that can forecast the intention to adopt cryptocurrency.

IMPROVING PURCHASING DECISIONS THROUGH PRICE PERCEPTION AND PRODUCT QUALITY: THE MEDIATING ROLE OF BRAND IMAGE IN BOTANICA APARTMENT

This research examines the impact of brand impression through the mediators of pricing perception and product quality on a buying decision for a Botanical Apartment. This study used primary data from questionnaires with a purposive sampling technique and the PLS-SEM (Partial Least Squares - Structural Equation Modelling) method to investigate the stated hypothesis. Two sessions were used to complete the PLS-SEM analysis in two phases. The reliability and validity analysis is the first stage, and the estimate and validation of the path coefficients and the robustness of the structural models are the second and third stages, respectively. For statistical analysis, using a sample of 220 respondents was taken from residents living in The Botanica Apartment and applying Smartpls V.3.2.9 to test the hypothesis of the influence of variables simultaneously and partially. Research findings show that brand image influences purchasing decisions, product quality affects the brand image, product quality affects purchasing decisions, price perception affects the brand image, and price affects purchasing decisions. In addition, the study revealed that product quality impacts brand image indirectly through purchasing decisions, and price perception impacts brand image indirectly through buying decisions.

FTIR and multivariate analysis of total phenolic content, antioxidant and anti-amylase activities of extracts and milk of Glycine max L. and Phaseolus vulgaris L.

BackgroundAlpha-amylase is a digestive enzyme which hydrolyses the glycosidic bonds in polysaccharides into monosaccharides. Inhibition of α-amylase can help to retard carbohydrate digestion in the small intestine and decrease blood glucose level. The effect of solvent extraction and milk processing on total phenolic content (TPC), antioxidant and anti-amylase activities, and Fourier-transform infrared (FTIR) spectra of Glycine max L. and Phaseolus vulgaris L. were estimated by Principal Component Analysis (PCA) and Partial Least Squares Structural Equation Modelling (PLS-SEM). ResultsThe result showed that the aqueous extract of P. vulgaris L. had the greatest antioxidant activity and anti-amylase activity, while the ethanol extract of G. max L. showed the greatest TPC. Interestingly, the milk of P. vulgaris L. seed showed the greatest level of TPC, antioxidant activity and anti-amylase activity. Mixed milk of G. max L. and P. vulgaris L. (8:2 v/v) showed high anti-amylase activity, while the mixed milk (5:5 v/v) showed high TPC and antioxidant activity. The FTIR result showed five wavenumber ranges associated with functional groups of phenolic compounds. Moreover, the PLS-SEM result revealed a significant positive correlation between TCP and FTIR data (β = 0.335, t = 2.112, p-value < 0.05), and between TCP and antioxidant activity (β = 0.346, t = 2.150, p-value < 0.05). ConclusionsThe result indicated that the solvent types and cooked beans could affect the biological activities and chemical content. The application of chemical content, biological activities, and FTIR technique combined with PLS-SEM and PCA analysis could discriminate bean types, solvent types, and between raw and cooked beans.How to cite: Thummajitsakul S, Paensanit P, Saeieo T, et al. FTIR and multivariate analysis of total phenolic content, antioxidant and anti-amylase activities of extracts and milk of Glycine max L.and Phaseolus vulgaris L. Electron J Biotechnol 2023;64. https://doi.org/10.1016/j.ejbt.2023.04.001.

Subjective well-being and its impact on online game addiction

ABSTRACT This study examined how an individual's subjective well-being (SWB) affects their online game addiction levels, which, in turn, affect their happiness and overall health. Partial least squares structural equation modelling (PLS-SEM) was used to analyze the data. The results showed that SWB had a negative relationship with online game addiction but a positive relationship with happiness and life health. Additionally, online game addiction had a negative impact on both happiness and life health. Furthermore, there was a significant positive relationship between happiness and life health. Overall, the proposed model explained 1.60%, 51.60%, and 31.80% of the variance in online game addiction, happiness, and life health, respectively. PLS-SEM analysis provided evidence that the indirect effect of SWB on life health and happiness was fully mediated by online game addiction. These findings indicate that SWB has a significant indirect effect on life health and happiness through online game addiction.