Structural Equation Modeling Approach Research Articles

Determinants of managerial accounting technique adoption in manufacturing enterprises: a structural equation modeling approach

Purpose This paper aims to examine the mediating effect of Contingent and Upper-Echelon factors on the relationship between Managerial Accounting Techniques (MAT) and the financial performance of manufacturing enterprises. Based on Upper-Echelon theory, it is hypothesized that executive characteristics such as age (AG) experience (ES), gender of CEO and CFO (GCEO/ GCFO), education of CEO and CFO (ECEO/EDCFO) and the involvement of accountants in strategic decision-making play an important role in this mediation. In line with the Contingency theory, factors such as firm size, production technology (PT), production sector (PS) and environmental (EN) conditions are considered key determinants influencing the use of MAT and their impact on the financial performance of manufacturing enterprises. Design/methodology/approach A quantitative, deductive approach was adopted, using a sample of 155 small, medium and large manufacturing enterprises in Kosovo. Structural equation modeling was used to explore the relationships between latent constructs and their impact on MATs use and enterprise financial performance. Findings The study found that accountant involvement in strategic decision-making, female CEO leadership, enterprise size and advanced production technology significantly increase the use of MATs of Stages 3 and 4. MAT usage positively impacts profitability, with CEO experience further enhancing profitability. CFO experience and environmental uncertainty showed no significant effects, and the production sector was not a determinant. In contrast, CEO education and experience positively impact profitability, while CFO education and experience have no effect. The model explains 63.1% of the variance in MAT usage and 10.8% in profitability. Research limitations/implications The study focuses exclusively on the manufacturing sector to ensure accuracy in assessing the use of MATs, acknowledging that different sectors may use varying techniques. Future research should expand the sample to include companies from other sectors. Originality/value This study offers valuable insights into the application of managerial accounting techniques in manufacturing enterprises within a developing emerging economy, contributing to understanding their influence on financial performance.

How do adverse childhood experiences influence non-suicidal self-injury among Chinese adolescent patients? A structural equation modeling approach

How do adverse childhood experiences influence non-suicidal self-injury among Chinese adolescent patients? A structural equation modeling approach

Empirical validation of a developmental model for binge-eating disorder in adolescents: a structural equation modeling approach

Loss of control (LOC) eating is characterized by a reported sense of being unable to control food intake, regardless of the amount of food consumed. It is the hallmark feature of binge-eating episodes, which involve consuming an unusually large amount of food within a discrete time frame, accompanied by a sense of LOC over eating. Some studies investigating the progression of LOC-eating symptoms in children and adolescents suggest that LOC-eating may be a precursor to binge-eating disorder (BED) in adults. To explain the progression from LOC-eating in childhood and adolescence to BED in adulthood, Tanofsky-Kraff and her colleagues developed a theoretical model highlighting three main constructs: negative affectivity, reward sensitivity, and executive functioning. However, a thorough empirical validation of this model has not yet been performed. The current study aims to empirically test Tanofsky-Kraff and her colleagues’ model via structural equation modeling (SEM) and explore potential gender and age differences within this framework. We surveyed 969 adolescents aged 12 to 18 years from the Quebec City area who completed self-report questionnaires. Our findings revealed that both negative affectivity and reward sensitivity are significantly associated with binge-eating symptomatology, whereas self-reported executive functioning is not significantly associated with binge-eating symptomatology. These results support several key components of the proposed model and provide insights into the interactions between the variables when tested simultaneously. Additionally, our study underscores the importance of considering individual factors such as age and gender in understanding binge-eating symptomatology.

The role of social support in enhancing self-efficacy and learning satisfaction in online education among secondary school students

Purpose The purpose of this study is to explore how different forms of social support, namely, family, friends and teachers enhance students’ computer internet self-efficacy (CIS) and its subsequent impact on learning satisfaction. By understanding these relationships, this study aims to provide insights into how social interactions influence digital competency and self-directed learning (SDL). In addition, it seeks to assess the significance of course clarity (CC) in promoting a positive learning experience. These findings aim to guide educators and policymakers in improving online education by integrating effective social support structures and clear instructional strategies. Design/methodology/approach This study uses a structural equation modelling (SEM) approach to examine the role of social support in enhancing self-efficacy and learning satisfaction among secondary school students in India. Data were collected from a diverse sample of urban secondary school students across six major cities. The study investigates how social support from family, friends and teachers influences students’ CIS, subsequently impacting CC, SDL and overall learning satisfaction in online education settings. The analysis highlights key relationships between these factors, offering insights into the dynamics of digital learning experiences. Findings This study reveals that family and friend support significantly influence students’ CIS, which in turn enhances their confidence and ability to navigate digital learning tools. Peer support emerged as the most influential factor in fostering digital confidence, whereas teacher support (TS) was particularly crucial in online learning settings. Furthermore, CC was strongly associated with perceived satisfaction, highlighting the need for well-structured digital curricula. Students with higher self-efficacy were more likely to engage in SDL, emphasizing the importance of digital competency in fostering independent study habits and overall learning satisfaction. Research limitations/implications This study is limited to urban secondary school students in six major Indian cities. Future research should explore rural and international contexts to understand how social support influences self-efficacy and learning satisfaction in different educational settings. In addition, the study focuses on current digital learning environments and does not account for emerging technologies that may further impact student experiences. Expanding the research to include newer digital learning tools and platforms can provide a more comprehensive understanding of these dynamics. Practical implications The findings highlight the need for educational institutions to strengthen social support mechanisms, particularly peer and TS, to enhance students’ digital confidence. In addition, ensuring CC is essential for improving learning satisfaction. Schools and educators should focus on structured, well-organized course designs that facilitate easy navigation and comprehension. Training programmes for teachers on effective digital pedagogies and the role of social support in online education can also be beneficial. These insights can help shape policies aimed at improving student engagement and satisfaction in digital learning environments. Social implications This study underscores the importance of social interactions in online education, emphasizing the role of peer and TS in enhancing digital learning experiences. The findings suggest that fostering a supportive learning community can significantly improve students’ self-efficacy and engagement with digital tools. By promoting strong social networks in online learning, educators can help bridge digital divides and create inclusive learning environments. In addition, recognizing the role of family support in education can encourage policies that involve parents in their children’s digital learning experiences, ultimately contributing to better academic outcomes. Originality/value This research contributes to the literature by providing a nuanced understanding of how social support, self-efficacy and CC collectively influence learning satisfaction in online education. Although previous studies have examined these factors in isolation, this study integrates them to offer a more comprehensive perspective. The findings provide valuable insights for designing effective, supportive online learning environments. By emphasizing the significance of peer and TS, as well as structured course design, this research informs educational policies and practices that aim to improve digital learning experiences for secondary school students in India and beyond.

Associations Between Early Life Stress, Health Behaviors, and Risk-Taking in Adulthood: A Structural Equation Modeling Approach

Abstract Across various scientific fields, early life stress (ELS) has been associated with more detrimental health behavior, higher risk-taking as well as accelerated socio-sexual behaviors, and higher reproductive effort. Previous research has identified resource scarcity, unpredictability, harshness, neighborhood hazards, parental investment, and exposure to violence and aggression as crucial factors of ELS. This study used an online survey to collect responses from 371 adult US residents via MTurk (160 females, 210 males, one other gender; Mage=29.98). Retrospective and current self-report measures were used to build a structural equation model of early childhood environment, socio-sexual behavior, reproductive effort, and adult health- and risk-related behaviors. A second-order factor of ELS predicted lower behavioral investment in health and safety (β=-0.30, p<0.001), indicated by less preventative and more detrimental health behavior as well as higher risk-taking propensity. The model showed that these adult behavioral tendencies constitute a coordinated behavioral strategy that prioritizes short-term opportunities and rewards over investments in future health, well-being, and safety. Model fit was excellent (RMSEA=0.054 [90% CI=0.048; 0.059]; CFI=0.966; TLI=0.957). Results partly corroborate theory and part of the previous empirical evidence but also suggest that factors of ELS are highly interrelated. No reliable associations emerged between ELS and socio-sexual behaviors, reproductive effort, or between these outcomes and adult behavioral tendencies. The study’s insights have implications for the design of intervention and prevention programs, which could benefit from focusing on changing ultimate behavioral strategies that jeopardize future health and well-being, rather than individual health and risk-taking behaviors.

Exploring Determinants of and Barriers to Climate-Smart Agricultural Technologies Adoption in Chinese Cooperatives: A Hybrid Study

The loss of agricultural production due to climate change and natural disasters has attracted widespread attention. Climate-smart agricultural technologies (CSATs) are attracting attention as a solution to address climate change while achieving sustainable agricultural development. However, in the Chinese context, research on cooperatives’ intention to adopt such technologies is relatively limited. This study investigated the factors influencing the behavioral intentions of Chinese farmers’ cooperatives to adopt CSATs using a behavioral reasoning theory (BRT) framework. A structured questionnaire was administered to 308 participants using purposive sampling techniques. For data analysis, an artificial neural network (ANN) and fuzzy set qualitative comparative analysis (fsQCA) complemented the disjointed two-stage partial least squares structural equation modeling (PLS-SEM) approach to ensure the robustness of the results and provide important practical insights. The results suggest that values (perceived value of government environmental concern, value of openness to change) shape the determinants of and barriers to CSAT adoption by cooperatives, but do not have a direct impact on behavioral intentions. The “determinants” all positively influenced adoption behavioral intentions, with “agricultural extension and advisory service” having the greatest impact on behavioral intentions, followed by “opinion leaders’ recommendation” and “policy support”. Among the “barriers”, only “perceived risk” and behavioral intention were negatively correlated. Behavioral intention to adopt CSATs by cooperatives has a positive effect on willingness to pay, which motivated cooperatives to pay more to acquire the technology. Based on the findings, this study provides theoretical insights for researchers and policy implications for governments, agricultural organizations, policymakers, and agri-technology companies.

Awareness, acceptance, and adoption of Gen-AI by K-12 mathematics teachers: an empirical study integrating TAM and TPB

In the 21st century, the variety of instructional media for mathematics has significantly diversified. Generative AI (Gen-AI) is one technology that K-12 teachers can utilize for teaching mathematics. However, as a new instructional medium, Gen-AI presents its own set of usage challenges. Research into the factors influencing mathematics teachers’ usage behavior of Gen-AI is crucial. This study integrates the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), incorporating a factor of AI awareness to explore the determinants of teachers’ usage behavior in employing Gen-AI for mathematics instruction. Data from 230 mathematics teachers who agreed to participate were analyzed using the partial least squares structural equation modeling (PLS-SEM) approach. The results indicate that teachers’ attitudes toward Gen-AI, subjective norms, and perceived behavioral control (PBC) have a direct effect on mathematics teachers’ usage behavior. AI awareness was found to directly affect perceived usefulness (PU), perceived ease of use (PEOU), and attitudes, and it also has an indirect effect on mathematics teachers’ usage behavior. This research provides new insights into enhancing the adoption of Gen-AI as an instructional medium by improving mathematics teachers’ attitudes toward Gen-AI, with AI awareness playing a pivotal role in this enhancement.

The Influence of Price Discounts and Hedonic Motivation on Impulse Buying During Shopping Festivals in Shopee

Many research have established that price discounts and hedonic motivations are influential factors in driving impulse buying, especially in the context of online shopping. However, limited research has explored how these factors specifically affect impulse buying on e-commerce platforms like Shopee during online shopping festivals, particularly with the role of positive emotion as an intervening variable. This study aims to analyze the influence of price discounts and hedonic motivation on impulse buying behavior during Shopee’s shopping festivals, considering positive emotion as an intervening factor. The research method used is quantitative with a sample of 105 respondents who live in the Jabodetabek area and have shopped on Shopee during online shopping festivals. Data were analyzed using Partial Least Squares (PLS) with a Structural Equation Modeling (SEM) approach. The study found that both price discounts and hedonic motivation have a significant effect on impulse buying, with positive emotion acting as an intervening variable that strengthens this relationship. These findings are expected to provide insights for shopee in designing promotional strategies to increase sales through impulse buying behavior during shopping festivals.

Antecedences and consequences of customer satisfaction in mobile telecom services using PLS-SEM and NCA: the moderating role of involvement with ICTs

Purpose This study aims to examine the antecedents [such as service quality (call), network quality (internet), perceived value, and corporate image] and consequences [such as electronic word of mouth (eWOM), customer loyalty and postpurchase intention] of customer satisfaction with mobile telecommunication services, as well as the moderating role of customer involvement with Information and Communication Technologies (ICTs) between customer satisfaction, eWOM, customer loyalty and postpurchase intention. Design/methodology/approach The authors collected 295 usable mobile service user questionnaires and analyzed the data with partial least square-structural equation modeling and necessary condition analysis (NCA). Findings Service quality (call), perceived value and corporate image significantly affect and are necessary conditions for customer satisfaction. In contrast, network quality (internet) is a necessary condition but does not have a significant effect on customer satisfaction. In addition, customer satisfaction influences eWOM, customer loyalty and postpurchase intentions but these are not necessary conditions. Finally, the results demonstrated that customer engagement with ICTs moderates the relationship between customer satisfaction and eWOM. Originality/value To the best of the authors’ knowledge, this is the first study to include the service quality of mobile phone calls and the network quality of the internet connection in the formation of customer satisfaction and its subsequent influence on eWOM, customer loyalty, and postpurchase intention through dual partial least squares structural equation modeling and NCA methodological approaches. In addition, the results indicate that customer engagement with ICTs moderates the relationship between customer satisfaction and eWOM.

Do Conspicuous Consumption Motives Explain Eco-Friendly Consumption Decisions? Evidence from Social Media Exposure Effects

While past research suggests that conspicuous consumption does not support the goals of sustainable consumer behavior, emerging evidence indicates that it can drive green product choices in online contexts. However, the online mechanisms that support this process remain unclear. This study employs a Partial Least Squares Structural Equation Modelling approach to examine how conspicuous consumption motives influence green purchase intentions when consumers are exposed to green content on social media. It hypothesizes that social media exposure, Fear of Missing Out (FOMO), and social comparison act as antecedents to green conspicuous consumption motives, with perceived quality moderating these relationships. Data was collected from 346 social media users in the U.S., U.K., and Canada. Results indicate that conspicuous consumption motives significantly mediate the relationship between FOMO, social comparison, and green purchase intentions. While perceived quality enhances the effect of social comparison on conspicuous consumption, it does not significantly impact the relationship between FOMO and conspicuous consumption. These findings highlight the role of social media in shaping green purchase decisions and suggest that businesses and policymakers can leverage conspicuous consumption motives to promote sustainable consumer behavior. By positioning green products as both environmentally responsible and status-enhancing, marketers can appeal to consumers’ desire for social validation.

ChatGPT as an Academic Writing Tool: Factors Influencing Researchers’ Intention to Write Manuscripts Using Generative Artificial Intelligence

This study examined factors driving the adoption of generative artificial intelligence tools like ChatGPT for research writing through an integrated framework combining the Technology Acceptance Model, Task Technology Fit, and Trust in Specific Technology. Responses from 564 researchers in 12 countries were analyzed using a structural equation modeling approach. Intriguingly, perceived usefulness and ease of use were insignificant despite being considered the strongest predictors of behavioral intention in countless studies. Instead, researchers prioritize trusting beliefs and the compatibility between a technology and a task when considering its use. It was also found that trust in the technology has greater explanatory power than task-technology compatibility, and this trust is influenced by beliefs that ChatGPT is a socially and academically accepted tool for manuscript writing. Overall, this study contributes new insights for researchers, funding bodies, publishers, policymakers, and the academic community as they navigate the evolving role of AI in scholarly writing.

The effect of workplace environment and compensation on employee performance with job satisfaction as an intervening variable; study on employees of Permuda Tirta Kanjuruhan Regency, Malang

This study analyzes the influence of work environment and compensation on employee performance with job satisfaction as an intervening variable in Perumda Tirta Kanjuruhan, Malang Regency. Using the Structural Equation Model (SEM) approach based on Partial Least Square (PLS) on 411 respondents, the results showed that the work environment had a significant positive effect on performance and job satisfaction. Compensation had a negative effect on performance but positive on job satisfaction . Job satisfaction acts as a significant mediator between the work environment and compensation on performance. The dominant factors of the work environment included leadership fairness and communication between colleagues , while compensation was influenced by performance-based appreciation. These findings indicate that compensation injustice and mismatch of employee expectations are the causes of performance declines, even though job satisfaction is able to mediate these negative effects. Research recommends improvements to a holistic work environment (physical, psychological, social) and a transparent and performance-based compensation system to improve organizational productivity. The study contributes to the literature by clarifying the crucial role of job satisfaction as a mediator in work environment relationships, compensation, and employee performance.

The influence of emotional intelligence on job satisfaction and organizational commitment in Tehran’s construction industry: a structural equation modeling approach

PurposeThe purpose of the study was to examine the role of emotional intelligence (EI) in enhancing job satisfaction (JS) and organizational commitment (OC) among construction project employees. This research aimed to uncover the direct and indirect effects of EI on JS and OC as well as the mediating role of JS, thus contributing to a deeper understanding of the interplay between these variables within the construction industry context.Design/methodology/approachIn this study, the relationship between emotional intelligence (EI), job satisfaction (JS), and organizational commitment (OC) was evaluated in the construction projects. The total of 424 employees were invited to participate in the research through email and face-to-face methods from top-rated construction companies in Tehran, Iran. The final 362 responses were collected and analyzed using Smart PLS 3 through structural equation modeling (SEM). The results showed a significant positive effect of EI on both JS (0.945) and OC (0.925), while JS had a moderate positive impact on OC (0.073). The study also highlighted the mediating role of JS in the relationship between EI and OC, with a total indirect effect of 0.069. These findings suggest the significant role of EI in the decisive satisfaction and commitment of employees within the distinctive environment of the construction industry.FindingsThe study employed a quantitative research methodology, utilizing a survey-based approach to collect data from construction project employees. Structural equation modeling (SEM) was used to analyze the relationships between EI, JS, and OC, providing robust statistical evidence on both the direct and indirect effects of EI on JS and OC. The findings revealed that EI has a significant positive effect on both JS and OC, with coefficients of 0.945 and 0.925, respectively. Additionally, job satisfaction (JS) was found to have a moderate positive impact on OC with a coefficient of 0.073. The study also highlighted the mediating role of JS in the relationship between EI and OC, with a total indirect effect of 0.069.Research limitations/implicationsThe research is limited to the construction industry in Tehran, Iran, which may restrict the generalizability of the findings to other regions or industries. Additionally, the study relied on self-reported measures, which could introduce bias.Practical implicationsFor construction companies, the findings suggest the value of developing and implementing programs aimed at enhancing employees’ emotional intelligence. Such initiatives could lead to increased job satisfaction and organizational commitment, ultimately improving overall organizational performance.Social implicationsImproving emotional intelligence within the workforce has broader social implications, as it can contribute to better work environments and enhanced employee well-being. A workforce that is more emotionally intelligent and satisfied is likely to experience lower turnover rates, leading to greater organizational stability.Originality/valueThe results of the research demonstrated that emotional intelligence has a significant influence on organizational commitment and job satisfaction of construction project employees. Additionally, the test results indicated that all EI dimensions, including self-awareness, self-management, social awareness, and relationship management, significantly affect organizational commitment and its components, namely, continuance commitment, affective commitment, and normative commitment. EI had the greatest impact on continuance commitment. Furthermore, considering JS as a mediating factor, the results revealed a significant effect on OC.

IMPACT OF BRAND IMAGE, INFORMATION QUALITY ON ONLINE CONSUMER BUYING DECISION OF ONLINE FOOD INDUSTRY IN PAKISTAN

This study examines the key determinants influencing Online Consumer Purchasing Decision (OCPD) using a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. The research focuses on critical factors such as Ease of Use (EU), Price (P), Trust (T), Information Quality (IQ), Brand Image (BI), Promotion (Pr), and Security (S), analyzing their interrelationships and overall impact on consumer behavior. The findings reveal that Brand Image (BI) and Promotion (Pr) are the most significant predictors of OCPD, while Price (P) plays a crucial role in shaping perceptions of Information Quality (IQ). Interestingly, the study finds a negative relationship between Trust (T) and Information Quality (IQ), suggesting that excessive or misleading information can reduce consumer confidence. Moreover, while Information Quality (IQ) positively impacts Brand Image (BI), it does not directly lead to purchases unless combined with strong marketing and promotional efforts. The results underscore the importance of transparent information, strategic promotional activities, and a seamless online shopping experience in influencing consumer purchase behavior. This study provides valuable insights for businesses to enhance customer engagement, strengthen brand perception, and develop targeted marketing strategies to improve online sales and consumer trust. Future research should explore the evolving role of digital marketing and social media influence in shaping purchasing decisions. Keywords: Online Consumer Purchasing Decision, Brand Image, Promotion, Price, Information Quality, Trust, Ease of Use, Security, Digital Marketing.

Unraveling the effect of Social Media Advertising on Consumer Buying Behaviour in the Fashion Industry: Insights from a Structural Equation Modeling Approach

The study aims to know the effect of social media advertising on the consumer buying behaviour in fashion industry. An empirical approach using structural equation modeling (SEM) was used to know the cause-and-effect relationships in the proposed model of the consumer buying behaviour and social media advertising. The exploratory & descriptive research design was used in this study. Preliminary pilot study was performed on the 49 samples. The Cronbach alpha, KMO and % of variance were used under the scale development and tools standardization process. The nonprobability snowball sampling technique was used in this study. The sample size of this study was 490. The empirical results reveal that the corporate reputation of social media advertising, the attitude towards social media advertising, and the artificial intelligence-driven social media advertising had a substantial impact on the buying behaviour towards the fashion industry consumers in Uttar Pradesh.

Determining factors affecting the perceived quality of fire safety signage icons: A structural equation modeling approach.

Determining factors affecting the perceived quality of fire safety signage icons: A structural equation modeling approach.

Relationship of transition shock, adversity quotient, and work engagement: A structural equation modeling approach.

Relationship of transition shock, adversity quotient, and work engagement: A structural equation modeling approach.

Fan groups, family, and Chinese tourists' purchase intentions to cultural products: A structural equation modeling approach based on dimensional innovation.

Fan groups, family, and Chinese tourists' purchase intentions to cultural products: A structural equation modeling approach based on dimensional innovation.

Anthropogenic sources and transfer of trace metals from the environment to brown trout (Salmo trutta) in mountainous rivers.

Anthropogenic sources and transfer of trace metals from the environment to brown trout (Salmo trutta) in mountainous rivers.

Homestay experience and eWOM among Generation Z tourists: The role of guest delight, guest satisfaction, and the need for uniqueness.

Homestay experience and eWOM among Generation Z tourists: The role of guest delight, guest satisfaction, and the need for uniqueness.