Partial Least Squares Structural Equation Modeling Research Articles

Effects of fertilization on soil ecological stoichiometry and fruit quality in Karst pitaya orchard

Pitaya (Hylocereus undulatus) is a significant cash crop in the karst region of Southwest China. Ecological stoichiometry is an essential method to research biogeochemical cycles and limiting elements. The purpose of this study was to explore the stoichiometric characteristics of C, N, and P in Karst pitaya orchards and fruit quality and to elucidate the mechanism and process of nutrient cycling. The results showed that: (1) Fruit quality was highest under the combination of chemical and organic fertilizers. Compared to the control, the contents of per-fruit weight, vitamin C, and soluble sugar increased significantly by 55.5%, 60.7%, and 23.0%, respectively, while the content of titratable acidity decreased significantly by 22.0%. (2) The content of soil nutrients under fertilization stress showed a downward trend in general, as did microbial biomass and extracellular enzyme activities. (3) Different fertilization treatments significantly affected the soil-microbial stoichiometry C:N ratio, C:P ratio, with research areas being significantly limited by C and P. (4) Spearman and PLS-SEM (partial least squares-structural equation model) analysis results showed that under the influence of fertilization, there was a significant positive effect between microorganisms and soil nutrients, but a significant negative effect between soil nutrients and quality. The results of this study offer an innovative perspective on pitaya quality research in Karst areas.

Examining tourists’ personality traits and dining-in/dining-out preferences. An approach-avoidance theory perspective

ABSTRACT Food and dining are integral to the travel experience for tourists. Despite this, there is a lack of research on how tourists choose between dining in and dining out. Furthermore, these choices may be influenced by the tourists’ personality traits. To address this gap, this study explores how the Big Five personality traits impact tourists’ preferences for dining in or dining out hospitality services. We gathered data from 790 tourists through an online survey and employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data. The results reveal that Openness to Experience is positively associated with the preference for dining in services but negatively associated with avoiding dining in or out. Conscientiousness is positively related to avoiding dining in or out. Extraversion is positively linked with the preference for dining in or out services, while Agreeableness has no association with either approaching or avoiding dining in/out. Neuroticism is positively associated with both approaching or avoiding dining in or out services. This study is not only one of the initial studies examining the influence of personality traits on tourists’ dining preferences but also help practitioners develop strategies via tourists’ personality traits to increase revenue for dining in/out services.

Study examining the significant role of intellectual property protection in driving radical technological innovation among national research project teams, employing PLS-SEM and ANN modeling.

This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspective. This study utilizes a sample of 336 national research project team members from various Chinese universities, research institutes, and corporations to analyze the theoretical model. Additionally, a two-stage hybrid partial least squares structural equation modeling (PLS-SEM) approach, combined with artificial neural network techniques (ANN), is employed to evaluate the hypotheses. The empirical findings of this study reveal a positive association between the intensity of IPP and RTI within national research project teams. Research and development investment intensity (R&DII) is identified as the primary predictor, while integrated leadership (IL) and group potential (GP) play crucial moderating roles. These groundbreaking findings extend the scope of innovation-driven and AMO theories, providing a proactive model for national research project teams to propose improvements to the IPP system, ultimately enhancing the realization of RTI.

Exploring public cooperation with police: the role of police accountability, police effectiveness, and public trust

ABSTRACT Public cooperation with the police is crucial because the public acts as the eyes and ears of the police. Moreover, research on public cooperation with the police, including crime-reporting behaviours and willingness to cooperate with law enforcement agencies, remains scarce in post-conflict countries like Somalia. Therefore, this study investigates the roles of perceived police accountability and effectiveness in fostering public cooperation with the police in Somalia via the underlying mechanisms of public trust in the police. Data were collected from a sample of 470 respondents in Mogadishu, Somalia. The analysis employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed model. The study found that police accountability has indirectly and positively impacted public cooperation via public trust in police. Moreover, public trust in police positively and significantly impacts public cooperation with the police. The findings also revealed that police effectiveness, directly and indirectly, impacts public cooperation with the police.

Using the UTAUT-TPACK model to explain digital teaching behaviour of elementary school mathematics teacher

ABSTRACT The appropriate use of digital technology in the classroom is very helpful to improve mathematics teaching in elementary school. However, the current situation of elementary school mathematics teachers’ digital teaching behaviour is not optimistic. This study analysed the factors influencing elementary school mathematics teachers’ digital teaching behaviour. A revised unified theory of acceptance and use of technology (UTAUT) model with technological pedagogical content knowledge (TPACK) was used to understand elementary school mathematics teachers’ digital teaching behaviour. A questionnaire survey was conducted in Hunan province of China. Three hundred elementary school mathematics teachers provided valid questionnaire data. The partial least squares structural equation modelling (PLS-SEM) approach was used to analyse the data. It was found that TPACK and facilitating conditions positively and significantly affected digital teaching behaviour of elementary school mathematics teachers, and TPACK was the biggest influential factor. The research results have important implications for improving digital teaching behaviour of elementary school mathematics teachers and promoting digital transformation of elementary school mathematics education.

Exploring the impact of family, school and society on the perception and reputation of vocational training in Pakistan:a statistical analysis

PurposeThe Technical Education and Vocational Training Authority (TEVTA) plays a crucial role in the socioeconomic development of a country. Still, it is often stigmatized as a secondary choice in the Global South. This study explored the interrelationships and impacts of factors such as family, school, and society on the perception and reputation of TEVTA.Design/methodology/approachBy employing quantitative methods, the analysis focused on how family, society, and school support influence these perceptions and reputations within TEVTA programs. Social Cognitive Theory is the theoretical underpinning of this study, in which 350 students from 13 TEVTA institutes participated by filling out questionnaires. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and IBM SPSS 28.FindingsThis study indicates that family and societal influences significantly shape students' perceptions, confirming their pivotal role in enhancing the reputation of these programs. School support also emerged as a critical factor, significantly impacting students' perceptions but not directly influencing the programs' reputation. The analysis underscores the importance of understanding the sociocultural context to develop effective strategies for the TEVTA sector in Pakistan. This clear understanding is essential for developing effective strategies to improve the reputation of TEVTA programs in this setting. Moreover, this research offers policy suggestions to make vocational education more attractive and accessible to diverse students, ultimately contributing to the country's socioeconomic development.Originality/valueThis study applied Social Cognitive Theory (SCT) to explore how individual thoughts, environmental influences (such as family, school, and society), and behaviors interact within the context of TEVTA programs. This approach fills gaps in current research and offers a clearer understanding of what affects TEVTA's perception and reputation.

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.

Determinant factors for online cash waqf intention among Muslim millennial generation

Purpose This study aims to examine the factors influencing the intention of Muslim Millennial Generation in Indonesia to donate cash waqf digitally. Design/methodology/approach A quantitative approach was employed, surveying 284 Muslim Millennial Generation in Indonesia. The study integrated the Decomposed Theory of Planned Behavior (DTPB) and Technology Acceptance Model (TAM) to investigate the key factors driving the intention to contribute to cash waqf digitally. The researcher analyzed data using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings The findings of this study indicate that all hypotheses related to the variables are supported, including both direct and indirect correlations, except for perceived religiosity. This study confirms that the decision of millennials to donate cash waqf online is influenced by various factors, including their attitudes, the environment they are in, their ability to control their behavior, their perception of the ease and usefulness of technology and the availability of suitable facilities. Knowledge of technology is also a decisive component. Nevertheless, this study yielded intriguing findings that the perceived level of religious devotion does not impact the millennials’ willingness to make online cash waqf donations. Practical implications This study’s findings offer valuable insights for waqf institutions, providing a better understanding of Muslim millennials’ characteristics and preferences regarding spending, donations and waqf activities. This understanding can be instrumental in enhancing innovative digital platforms for cash waqf in the digital economy era. Originality/value This study uniquely explores the determinants of digital cash waqf donations among Muslim Millennial Generation in Indonesia. Contributions include integrating the DTPB and the TAM for a comprehensive analysis. Cross-disciplinary perspectives from behavioral economics and digital marketing enrich the research. Comparative studies and potential longitudinal analysis enhance depth, providing nuanced insights into the dynamic factors shaping digital donation behavior among Muslim millennials.

Exploring post-usage behaviour in app-based ride-sourcing services: Evidence from Egypt

Despite numerous studies focusing on ride-sourcing services, most have concentrated on users' pre-usage behaviour. This study explores users' post-usage behaviour, aiming to identify significant factors affecting existing users' intentions to continue using app-based ride-sourcing services in Egypt. Integrating the Expectation-Confirmation Model (ECM), the Technology Acceptance Model (TAM), and the Technology Readiness Model (TRM), this research identifies key determinants influencing users' perceptions and continued usage intentions. An online questionnaire collected empirical data from 381 respondents, analysed using partial least squares structural equation modelling (PLS-SEM). The results highlight the essential roles of optimism, innovativeness, discomfort, and insecurity in shaping users' perceptions of ride-sourcing apps' usefulness. Additionally, perceived ease of use is determined by innovativeness and discomfort. Furthermore, users' continuance usage intention is significantly associated with satisfaction level, perceived usefulness, and perceived ease of use. This study's findings offer valuable insights for service providers, aiding their understanding of variables influencing users' decisions to continue using ride-sourcing apps and enabling them to retain and satisfy their current users effectively.

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.

Digital Transformation Driving SME Business Model Innovation

The purpose of this paper is to propose a research model to investigate the relationships between dynamic capabilities, business model innovation, and business performance. The moderating role of digital transformation in the research model is also examined. A total of 262 managers in Chinese small and medium-sized enterprises (SMEs) were enrolled via an online questionnaire. Data is scrutinized by partial least square structural equation modeling (PLS-SEM) using SmartPLS 3.0. The findings of this study reveal that dynamic capabilities can positively affect business model innovation and business performance. Furthermore, business model innovation partially mediates the relationship between dynamic capabilities and business performance. Meanwhile, digital transformation has a positive moderating role in the aforementioned relationships. These findings bridge the research gaps in extant literature and contribute to theoretical and practical implications for SMEs.

Enlightening the shadow dimensions of part‐time entrepreneurship: Navigating fear of failure and enhancing social status

AbstractPart‐time entrepreneurs—individuals acting simultaneously as entrepreneurs and employees—are often considered to be in a transitional stage towards becoming full‐time entrepreneurs. However, they can also exit a venture or remain hybrid entrepreneurs. Based on this evidence, we explore the influence of social norms (social status and shame of failing), the desire to create a company, entrepreneurial motivation, the need for achievement, risk propensity, and indirect shame on the entrepreneurial intention of part‐time entrepreneurs. A questionnaire was administered to 304 part‐time entrepreneurs residing in Brazil. The results of partial least squares structural equation modeling (PLS‐SEM) have shown that social status and entrepreneurial motivation positively influence the entrepreneurial intention of hybrid entrepreneurs, while the shame of failing has a negative effect on this dimension. We also found that the desire to create a company has a positive impact on entrepreneurial intention but negatively moderates the relationship between social status and entrepreneurial intention, that is, the direct relationship becomes weaker as the desire to create a company increases. Accordingly, this study provides evidence on the main drivers of entrepreneurial intention by focusing on the specific case of part‐time entrepreneurs. The uniqueness of this study, therefore, lies in its valuable contribution to empirical knowledge about hybrid entrepreneurship, a category often underestimated in research dedicated to the field of entrepreneurship.

The effects of AIoT-SC strategic alignment on SC intelligence and NPD performance

ABSTRACT The emergence of AIoT has profoundly influenced supply chain management (SCM) and new product development (NPD) performance. However, the AIoT and its strategic alignment with the supply chain (SC) strategy have not received equal attention in academia and industry. By incorporating concepts of strategic alignment, AIoT, and NPD from previous literature, this study proposes a new concept of AIoT-SC strategic alignment and examines its role in SC intelligence (SCI) and NPD performance. By using a partial least squares structural equation modelling (PLS-SEM) approach, the survey data results demonstrate that AIoT-SC strategic alignment in planning, making, delivery, sourcing, and return is positively related to SC intelligence regarding market intelligence quality (MIQ), SC partner intelligence quality (SCPIQ), and NPD performance. The study’s findings can guide managers in improving firms’ business functions through AIoT-SC strategic alignment. Furthermore, this research provides researchers with sound theoretical grounds/basis for further academic development of AIoT, SCM, and NPD.

Impact of expertise in standardization on business internationalization

ABSTRACT The European Union (EU) Strategy on Standardization stressed that Europe’s competitiveness will depend on how successful European actors are in standardization at the international level. It follows that companies with strong standardization-related skills and competencies may be more competitive in such competitions and eventually become more internationalized. Although the interplay between expertise in standardization and business internationalization seems to be evident, the literature still lacks a comprehensive analysis of the impact of the expertise in standardization on business internationalization. The study aims to address three research questions: (1) How does the expertise in standardization impact business internationalization? (2) How does the company size moderate the relationship between expertise in standardization and business internationalization? and (3) How does the country of origin moderate the relationship between expertise in standardization and business internationalization? We conducted a survey among owners and managers of European companies and applied the Partial Least Squares Structural Equation Modelling (PLS-SEM) analysis. Our results showed what is changing and what benefits European companies are not only standardization-related competencies; experience in developing standards makes a difference. Large companies from countries more active in standardization will create more advanced market entry strategies and use export and non-export entry modes more intensively.

Sustainable Brand Resilience: Mitigating Panic Buying through Brand Value and Food Waste Attitudes Amid Social Media Misinformation

This study investigates the relationship between user-generated content on social media and panic buying, with a focus on how attitudes towards food waste and brand value act as moderating variables. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), data from an online survey with 370 responses were analyzed. The findings show that user-generated content significantly contributes to the dissemination of inaccurate information, which in turn triggers panic buying. However, the impact of inaccurate information on panic buying is moderated by consumer attitudes towards food waste and brand value. Specifically, consumers with negative attitudes towards food waste and high brand trust are less likely to engage in panic buying when exposed to misinformation. These results suggest that promoting responsible consumption and leveraging brand value can mitigate the adverse effects of misinformation during crises. This study contributes to sustainability by providing insights into developing strategies for retailers and policymakers to manage consumer behavior, emphasizing the importance of accurate information and brand communication in reducing panic buying tendencies.

Impact of self-efficacy and mediating factors on Fintech adoption in the VUCA era

This paper aims to understand the impact of factors affecting the relationship between intention and using Fintech in the VUCA era, which stands for volatility, uncertainty, complexity, and ambiguity. A cross-sectional design was employed in this study. The data was collected via questionnaires, with 1,411 usable responses received through the survey. Partial least squares structural equation modeling (PLS-SEM) was employed to assess the process with SmartPLS 4. Our research did figure out the positive impact of Perceived Usefulness and Perceived Ease of use on behavioral intention and the positive impact of Intention on Using Fintech behavior. Simultaneously, we indicated that Financial literacy could moderate the relationship between Intention and Using Fintech behavior, and Financial self-efficacy would be a mediator of the association between Financial literacy and Using Fintech behavior. Based on the results, we make some recommendations for Fintech developers in Vietnam.

Investigating How Chinese E-Commerce SMEs Would Adopt AI Live-Streaming via a Dual Analysis

This study aims to delve into the adoption of AI live-streaming technology by Chinese e-commerce SMEs. We employed a robust analytical approach, synergizing Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Networks (ANNs). A comprehensive survey was conducted with 260 e-commerce SMEs, examining the key factors that may influence the adoption of AI live-streaming under the Technology-Organization-Environment (TOE) framework. With this model we evaluated six detailed variables for technological readiness, organizational readiness, and environmental influence. The empirical results reveal that such factors - perceived ease of use, perceived usefulness, management support, employee competency, and market trends – may significantly influence the adoption of AI live-streaming in Chinese e-commerce SMEs. The findings help enrich the existing body of knowledge in technology adoption in an increasingly digitalised era.

A valid and reliable explanatory model of learning processes in heritage education

BackgroundThe main challenge in heritage education is to identify the verbs—and their hierarchical relations—that explain heritage learning as based on empirical evidence. The Heritage Learning Sequence (HLS) selects seven verbs (Knowing-Understanding-Respecting-Valuing-Caring-Enjoying-Transmitting) on the basis of (a) theoretical studies, (b) analyses of international standards, and (c) evaluation of heritage education programs. The study has the following objectives: (a) to clarify the heritage learning process; (b) to test a theoretical model that groups the verbs that make up the Heritage Learning Sequence (HLS), as well as the relationships between them; (c) to identify possible sub-models that explain the different heritage learning itineraries.MethodsThe Q-Herilearn scale (previously calibrated using SEM and IRT models) was administered to N=1454\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N = 1454$$\\end{document} individuals, focusing on seven factors (corresponding to each HLS verb) that measure heritage learning. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used as a general analytical strategy.FindingsThe results obtained provided sufficient guarantees to validate the HLS and showed the adequate explanatory and predictive power and general fit of the proposed model (Heritage Learning Model); all twelve hypothesized direct influence relations between the main verbs that define heritage learning were confirmed. The statistical significance values suggested the existence of other internal subsequences that could be explored in further studies.ContributionLearning modeling provides a key structural framework for (a) the design of effective, efficient, and comprehensive tools to measure heritage learning and (b) their operationalization in heritage education designs.

Combining effects of submerged macrophytes and lanthanum-modified bentonite on sediment enzyme activity: Evidence from mesocosm study

Lanthanum-modified bentonite (LMB) combined with submerged macrophytes (SM) has been a conventional means of eutrophication management in lakes in recent years, and is one of the most important methods for P removal. However, trends in nutrients and sediment enzymes at the water-sediment interface during this process have not been systematically assessed, and there are still some gaps in how abiotic properties drive changes in enzyme activity. Here, we show changes in aquatic environmental conditions under the action of different ratios of modified bentonite (0, 10%, 20%, and 30%) in combination with SM (Vallisneria natans, Potamogeton lucens, and Hydrilla verticillate) and quantify their effects on sediment enzyme activities. The results showed that the nutrient cycling at the water-sediment interface was facilitated by the combined effect of SM and LMB, which effectively reduced the overlying water nutrient concentration, increased the sediment enzyme activity and enhanced the N cycling process. Partial least squares structural equation model (PLS-SEM) showed that sediment parameters strongly influenced changes in enzyme activity, with NO3–N as the main controlling factors. Our study fills in the process of changing environmental conditions in lake water under geoengineered materials combined with macrophyte measures, especially the changes in biological properties enzyme activities, which contributes to a clearer understanding of nutrient fluxes during the management of eutrophication in lakes.