Maximum Likelihood Structural Equation Modeling Research Articles

Foreign ownership and product market competition's influence on firm performance: Mediating role of the corporate governance index

AbstractThis study examines the influence of foreign ownership and product market competition on firm performance in Vietnam's listed companies through the mediating role of the corporate governance index. Moreover, the study explores the moderating role of business strategy in the relationships between foreign ownership, product market competition, and firm performance. We use maximum likelihood structural equation modeling in Stata 14 software to analyze the data collected from 180 Vietnamese listed companies from 2015 to 2019. The results indicate that foreign ownership and product market competition positively influence firm performance by mediating the corporate governance index. Business strategy negatively moderates the relationship between product market competition and firm performance. This study has implications for managers focusing on foreign ownership and product market competition to improve corporate governance systems, enhancing firm performance. Additionally, managers may build business strategies when product market competition increases to avoid negative effects on firm performance.

Supply chain resilience as a system quality: survey-based evidence from multiple industries

PurposeExperiencing more frequent, system-wide disruptions, such as pandemics and geopolitical conflicts, supply chains can be largely destabilized by a lack of materials, services or components. Supply chain resilience (SCRES) constitutes the network ability to recover after and survive during such unexpected events. To enhance the understanding of SCRES as a system-wide quality, this study tests a comprehensive SCRES model with data from multiple industries.Design/methodology/approachThe study proposes a theoretical framework conceptualizing SCRES as system quality, extending the classical proactive/reactive taxonomy by multiple system states consisting of the supply system properties, behaviors and responses to disruptions. Underlying hypotheses were tested using an online survey. The sample consists of 219 responses from German industries. Maximum likelihood structural equation modeling (ML-SEM) and moderation analysis were used for analyzing the survey data. The study was particularly designed to elaborate on supply chain theory.FindingsTwo pathways of parallel SCRES building were identified: proactive preparedness via anticipation and reactive responsiveness via agility. Both system responses are primarily built simultaneously rather than successively. The present study further provides empirical evidence on the central role of visibility and velocity in achieving comprehensive SCRES, while flexibility only exerts short-term support after a disruption. The study additionally points to potential “spillover effects” such as the vital role of proactive SCRES in achieving reactive responsiveness.Originality/valueThe present study confirms and expands existing theories on SCRES. While stressing the multidimensionality of SCRES, it theorizes the (inter-)temporal evolution of a system and offers practical guidelines for SCRES building in various industrial contexts. It thus supports the transformation toward more resilient and viable supply chains, contributing to the increasing efforts of middle-range theory building to achieve an overarching theory. The study also points to potential future research avenues.

Bridging the adoption gap for cryptocurrencies: understanding the affordances that impact approach–avoidance behavior for potential users and continuation usage for actual users

PurposeWith the rise of cryptocurrency and its influence on the financial industry, this paper aims to explore cryptocurrency affordances that lead to approach–avoidance behavioral intentions for non-users (potential) and the intention to continue use for users (actual), drawing upon affordance theory and chasm theory.Design/methodology/approachThe authors collected data from 480 potential and actual users in Germany and used maximum likelihood structural equation modeling (ML-SEM) to analyze it. In particular, the data consisted of 301 cryptocurrency users in Germany\ the authors used ML-SEM to test the post-adoption model. Additionally, logistic regression was utilized to determine the dominant actual usage method (store of value or medium of exchange) for various cryptocurrency coins.FindingsAccording to the study's results, the perceived value benefits have a positive impact on the behavioral intention of potential users to adopt cryptocurrency, and they influence the intention of actual users to continue using it. However, both perceived volatility and financial risk tolerance are the most crucial factors hindering cryptocurrency adoption, whether in the pre-adoption or the post-adoption stage.Originality/valueThis is the first study to reveal cryptocurrency affordances and examine their effect on behavioral intentions toward cryptocurrency adoption based on the differences between non-users (potential) and users (actual). Furthermore, the authors explore how cryptocurrency holders perceive and invest in different coins (e.g. NFTs), which sheds light on factors such as financial risk tolerance that affect their decision making.

Religious Service Attendance and Religious and Secular Organizational Engagement in the United Kingdom

AbstractThe study uses nationally representative data to examine whether the moral freighting Putnam and Campbell (2010) propose, based on American experiences, may apply to overall British society. Specifically, it tests whether religious service attendance increases religious or secular organizational activities, possibly due to moral freighting that encourages religious congregants to practice their faith, transcending ego boundaries and self‐interest. It is also necessary to determine if engagement in religious or secular organizational activities elevates the degree of religious service attendance, thus forming a bidirectional association. The study employs the maximum likelihood‐structural equation modeling (ML‐SEM) method to verify the proposed reciprocity. The empirical tests confirm that a synergistic reciprocal relationship is established between religious service attendance and religious organizational engagement, and that religious service attendance increases secular organizational engagement. However, secular organizational engagement does not make a bidirectional contribution to religious service attendance.

The explanatory power of the SKYTRAX’s airport rating system: Implications for airport management

This article presents a study of the explanatory power of SKYTRAX's airport rating system, using data from 423 airports for statistical analysis. The study utilizes ordinal regression and Maximum Likelihood Structural Equation Modeling (ML SEM) to propose and test several models. The study results show that only three service quality components based on SKYTRAX have significant explanatory power, i.e., terminal comfort, wayfinding signage, and airports' food and beverage outlets. The study findings have significant implications for airport management and key stakeholders. By prioritizing these service quality components, airport managers can improve operational efficiency and increase service quality, which can attract new investments. The study highlights the importance of addressing the vital elements of airport service quality, which can lead to time and cost savings in problem-solving processes and procedures. The findings also have implications for academia, providing a basis for further research on the importance of airport rating systems for customer satisfaction and service quality.

Inclusive leadership can improve nurses' psychological ownership and reduce their turnover intention under the normalization of COVID-19 prevention.

The COVID-19 pandemic continues to impact people's lives and professions worldwide. Chinese nurses face immense work pressure under the normalization of COVID-19 prevention and control, resulting in greater turnover intention. It is, therefore, crucial to study the mechanisms that influence the turnover intention of nurses in this situation. Many studies have examined the impact of leadership style on nurses' turnover intention; however, few researchers have investigated this influence during the COVID-19 pandemic. Based on the leader-member exchange theory, this study empirically studied the effect of inclusive leadership on turnover intention of nurses under the normalization of COVID-19 prevention and control in China, while assessing the mediating role of psychological ownership. Cross-sectional study with multi-center data. Two thousand, two hundred ninety-nine registered nurses from 17 hospitals in China were recruited from January to March, 2022, under the normalization of COVID-19 prevention and control in China. A demographic questionnaire and scales of inclusive leadership, psychological ownership, and turnover intention integrated into an online survey were sent to registered nurses of different hospitals. Maximum likelihood structural equation modeling (ML-SEM) was used to analyze data. Independent variable inclusive leadership has a significant effect on the overall turnover intention of nurses, p < 0.001. The direct effect path coefficient from inclusive leadership to psychological ownership is significant, p < 0.001. The direct effect path coefficient from psychological ownership to turnover intention is significant, p < 0.001. The indirect effect path coefficient from inclusive leadership to turnover intention is significant, p < 0.001. Psychological anxiety, burnout, turnover intention, and even suicidal thoughts were the main symptoms of Chinese nurses under the normalization of COVID-19 prevention and control in China. The absence of a mechanism to counteract these negative conditions may ultimately lead to personal psychological distress for nurses and collapse of the healthcare system. Inclusive leadership can improve nurses' psychological ownership level and reduce their turnover intention by treating them fairly, providing them with opportunities for self-development, paying attention to communication with them, and increasing their sense of belonging, self-efficacy, and self-identity.

Assessing the impact of sustainable logistics service quality on relationship quality: Survey-based evidence in Egypt

Logistics services support customer-relationship building in the supply chain and help the buying companies establish and maintain a sustainable competitive advantage. To empirically quantify the effect, we introduce the Sustainable Logistics Service Quality (SLSQ) scale and measure the impact of SLSQ on customer satisfaction and relationship quality in the Egyptian market. Our quantitative research builds on 421 responses collected from small and medium-sized enterprises in Egypt. The identified relationships are tested using maximum likelihood structural equation modeling (ML-SEM) and mediation analysis. The results show that customer satisfaction with SLSQ indeed positively affects single relationship quality second-order dimensions. We further tested the indirect relationships between customer satisfaction, dependence, trust, and commitment confirming the important mediating roles of dependence and trust for relationship quality building. While the study contributes to a better understanding of the underlying mechanisms to build relationship quality, it additionally provides recommendations to increase the performance of LSPs in emerging countries such as Egypt. Finally, the results are discussed against previous literature and concluded by showing limitations and potential future research avenues.

Common etiological architecture underlying reward responsiveness, externally driven eating behaviors, and BMI in childhood: findings from the Gemini twin cohort.

BackgroundStudies have reported that impulsivity predicts childhood BMI and that the association is mediated by eating behaviors. One aspect of impulsivity – potentially crucial in the obesity context – is reward responsiveness, which may predispose to responsiveness to palatable food cues. The behavioral susceptibility theory hypothesizes that genetic susceptibility to obesity operates partly via genetically determined differences in appetite regulation. Reward responsiveness may therefore be one of the neuro-endophenotypes that mediates genetic susceptibility to obesity.ObjectiveTo test whether reward responsiveness, eating behaviors and child BMI share common genetic architecture.MethodsWe examined reward responsiveness, eating behaviors and BMI in five-year-old children from Gemini, a UK birth cohort of 2,402 twin pairs born in 2007. All measures were collected by parent report. Reward responsiveness was derived from the Behavioral Approach System. Compulsion to eat and eating for pleasure was measured with the ‘food responsiveness’ scale of the Child Eating Behavior Questionnaire. Wanting to eat in response to environmental food cues was measured with the ‘external eating’ scale of the Dutch Eating Behavior Questionnaire. Maximum-likelihood structural equation modelling was used to establish underlying common genetic and environmental influences.ResultsThere were significant positive phenotypic correlations between all traits except for reward responsiveness and BMI. Genetic factors explained the majority of the association between food responsiveness and external eating (74%, 95%CI: 61, 87), whereas common shared environmental factors explained the majority of the associations between reward responsiveness with both food responsiveness (55%, 95%CI: 20, 90) and external eating (70%, 95%CI: 39, 100).ConclusionsOur study demonstrates the importance of common environmental factors in the shared etiology between reward responsiveness and childhood eating behaviors. However, the common etiology underlying both reward responsiveness and BMI is unclear, as there was no phenotypic correlation between reward responsiveness and BMI at this age. Further longitudinal research needs to detangle this complex relationship throughout development.

Instrumental Variables Two-Stage Least Squares (2SLS) vs. Maximum Likelihood Structural Equation Modeling of Causal Effects in Linear Regression Models

In the presence of omitted variables or similar validity threats, regression estimates are biased. Unbiased estimates (the causal effects) can be obtained in large samples by fitting instead the Instrumental Variables Regression (IVR) model. The IVR model can be estimated using structural equation modeling (SEM) software or using Econometric estimators such as two-stage least squares (2SLS). We describe 2SLS using SEM terminology, and report a simulation study in which we generated data according to a regression model in the presence of omitted variables and fitted (a) a regression model using ordinary least squares, (b) an IVR model using maximum likelihood (ML) as implemented in SEM software, and (c) an IVR model using 2SLS. Coverage rates of the causal effect using regression methods are always unacceptably low (often 0). When using the IVR model, accurate coverage is obtained across all conditions when N = 500. Even when the IVR model is misspecified, better coverage than regression is generally obtained. Differences between 2SLS and ML are small and favor 2SLS in small samples (N ≤ 100).

Genetic and environmental influences on food preferences in adolescence

Background: Food preferences vary substantially among adults and children. Twin studies have established that genes and aspects of the shared family environment both play important roles in shaping children’s food preferences. The transition from childhood to adulthood is characterized by large gains in independence, but the relative influences of genes and the environment on food preferences in late adolescence are unknown.Objective: The aim of this study was to quantify the contribution of genetic and environmental influences on food preferences in older adolescents.Design: Participants were 2865 twins aged 18–19 y from the TEDS (Twins Early Development Study), a large population-based cohort of British twins born during 1994–1996. Food preferences were measured by using a self-report questionnaire of 62 individual foods. Food items were categorized into 6 food groups (fruit, vegetables, meat or fish, dairy, starch foods, and snacks) by using factor analysis. Maximum likelihood structural equation modeling established genetic and environmental contributions to variations in preferences for each food group.Results: Genetic factors influenced a significant and substantial proportion of the variation in preference scores of all 6 food groups: vegetables (0.54; 95% CI: 0.47, 0.59), fruit (0.49; 95% CI: 0.43, 0.55), starchy foods (0.32; 95% CI: 0.24, 0.39), meat or fish (0.44; 95% CI: 0.38, 0.51), dairy (0.44; 95% CI: 0.37, 0.50), and snacks (0.43; 95% CI: 0.36, 0.49). Aspects of the environment that are not shared by 2 twins in a family explained all of the remaining variance in food preferences.Conclusions: Food preferences had a moderate genetic basis in late adolescence, in keeping with findings in children. However, by this older age, the influence of the shared family environment had disappeared, and only aspects of the environment unique to each individual twin influenced food preferences. This finding suggests that shared environmental experiences that influence food preferences in childhood may not have effects that persist into adulthood.

Variation and Heritability in Hair Diameter and Curvature in an Australian Twin Sample.

Hair diameter and curvature are two characteristics of human scalp hair used in forensic contexts. While previous data show that subjective categorization of hair curvature is highly heritable, the heritability of objectively measured curvature and diameter, and variability of hair characteristics within each individual have not yet been studied. The present study measured hair diameter and curvature using an optical fiber diameter analyzer in a sample of 2,332 twins and siblings. Heritability was estimated using maximum likelihood structural equation modeling. Results show sex differences in the magnitude of genetic influence for mean diameter and curvature, with the vast majority of the variance accounted for by genetic effects in males (diameter = 86%, curvature = 53%) and females (diameter = 77%, curvature = 61%). The consistency of diameter (variance within an individual) was also highly heritable, but did not show sex limitation, with 68% of the variance accounted for by genetic factors. Moderate phenotypic correlations were seen between diameter and consistency (r = 0.3) but there was little correlation between diameter and curvature (r = -0.13). A bivariate Cholesky analysis was used to estimate the genetic and environmental correlations between hair diameter and consistency, yielding genetic correlations of r gF = 0.27 for females and r gM = 0.25 for males.

Self-esteem, diet self-efficacy, body mass index, and eating disorders: modeling effects in an ethnically diverse sample.

Disordered eating patterns, particularly binge eating, are prevalent in Hispanic samples, yet the biopsychosocial risk factors remain understudied in minority populations. The relationship between diet self-efficacy and bulimic symptoms has been established in non-Hispanic white samples but not yet in Hispanics. This study sought to identify the direct role of diet self-efficacy on eating disorder risk and symptomology in a multicultural Hispanic sample, and to investigate the potential indirect relations among diet self-efficacy, self-esteem, body mass index (BMI), and eating disorder risk and symptomology in Hispanics and non-Hispanic whites. The present study surveyed 1339 college students from diverse ethnic backgrounds. Participants completed four standardized scales to assess acculturation, diet self-efficacy, global self-esteem, and eating disorder symptomology and risk. Self-reported height and weight were used for BMI calculations, and the data were analyzed in a robust maximum-likelihood structural equation modeling (SEM) framework. The findings highlighted diet self-efficacy as a predictor of eating disorder risk and symptomology. Diet self-efficacy partially explained the covariation between self-esteem and eating disorder risk and symptomology, and between BMI and eating disorder risk and symptomology for the entire sample. Diet self-efficacy emerged as an important construct to consider in developing eating disorder prevention and treatment models.

High heritability of posterior corneal tomography, as measured by Scheimpflug imaging, in a twin study.

Anterior corneal curvature shows significant heritability. Scheimpflug imaging also permits assessment of posterior tomography. We estimated heritability of posterior and anterior tomographic parameters. Oculus Pentacam images were obtained in twins from the TwinsUK cohort. Mean anterior and posterior radii of curvature (right cornea) were compared within twin pairs, and heritability calculated (maximum likelihood structural equation modeling, using OpenMx package). Heritability estimates also were calculated for other parameters (anterior and posterior elevation at apex and thinnest point; pachymetry at apex and thinnest point; average pachymetry progression index). Images from 138 twins were included (32 monozygotic [MZ] and 37 dizygotic [DZ] twin pairs). Mean (SD) age was 61 (11) years; 91% were female. Coefficients for intrapair correlation for MZ and DZ twins were, respectively, 0.89 and 0.42 for anterior curvature, and 0.93 and 0.46 for posterior curvature (P ≤ 0.0001 for differences between MZ and DZ correlations; Fisher r-to-z transformation). Heritability estimates (95% confidence interval [CI]) for anterior and posterior curvature were 89% (79%-93%) and 90% (83%-94%), respectively. Estimates for all other parameters were 75% or higher, except anterior apical elevation (61%). Point estimates for posterior parameters were consistently higher than anterior parameters, although CIs overlapped. Age-matching yielded similar estimates. Intereye correlations were high; correlations with age were weak (r < 0.30). This is the first study to explore heritability of a number of different parameters of corneal tomography, including posterior curvature. Almost all parameters appeared highly heritable, with a trend toward higher heritability estimates for posterior (versus anterior) parameters.

The heritability of dry eye disease in a female twin cohort.

We estimated the relative importance of genes and environment in dry eye disease (DED) using a classic twin study. A large sample of 3930 female monozygotic and dizygotic twins from the UK Adult Twin Registry (TwinsUK) was questioned about the presence of a DED diagnosis and about DED symptoms in the preceding 3 months. In addition, a subset of 606 twins was examined for several dry eye signs. Genetic and environmental effects were estimated using maximum likelihood structural equation modeling. All DED outcome variables showed higher correlation in monozygotic twin pairs than in dizygotic twin pairs, suggesting genes have a contributory role in DED. The DED symptoms showed a heritability of 29% (95% confidence interval [CI], 18%-40%). A clinician's diagnosis of DED with concurrent use of artificial tears showed a heritability of 41% (95% CI, 26%-56%). Estimates of the heritability of DED signs were 25% (95% CI, 7%-42%) for interblink interval, 58% (95% CI, 43%-70%) for Schirmer value, 40% (95% CI, 25%-53%) for tear osmolarity, and 78% (95% CI, 59%-90%) for the presence of blepharitis. The unique environment explained the remainder of the variance. We found no significant heritability for tear breakup time. Genetic factors contribute moderately to the diagnosis, symptoms, and the signs of DED. Compared to other ocular phenotypes, the lower heritability might reflect some of the difficulties in objective phenotyping of DED in a population-based sample. However, future genetic studies are now justified and may help in unraveling the pathophysiology of DED.

Two new methods for estimating structural equation models: An illustration and a comparison with two established methods

The application of structural equation models (SEMs) is common in marketing and the behavioral sciences. Accordingly, the exploration of more effective methods to estimate SEMs is also a popular area of research. Croon (2002) and Skrondal and Laake (2001) have each proposed a new method for estimating SEMs, but since these proposals nearly a decade ago, these methods have been mostly overlooked by applied researchers. We suggest that reasons for this oversight may include not only a lack of guidance in implementing these new methods but also the absence of a formal comparison to review these new methods relative to the more familiar maximum likelihood structural equation modeling (MLSEM) and partial least squares (PLS). In this paper, our goal was to make the Croon and Skrondal–Laake (SL) methods more accessible to applied researchers. We first provide a step-by-step illustration of how to implement the Croon and SL methods. We also present the first comprehensive evaluation of the new methods relative to MLSEM and PLS. From this evaluation, we can better appreciate the circumstances under which these new methods are preferable to MLSEM and PLS. Thus, we intend to help readers understand how and when to apply these new methods.

The Posttraumatic Growth Inventory: an examination of the factor structure and invariance among breast cancer survivors

The present study tested the proposed five-factor structure and invariance of the Posttraumatic Growth Inventory (PTGI; Tedeschi & Calhoun, 1996) in a sample of physically active breast cancer survivors. A sample of breast cancer survivors (N=470, Mage=57.3, SD=7.8 years) completed the PTGI and a demographic questionnaire. The factor structure, factorial invariance, and latent mean invariance were tested using maximum likelihood structural equation modeling. Preliminary analyses showed acceptable reliability for the PTGI subscales (alpha<0.83). Confirmatory factor analysis (CFA) supported the five related factors corresponding to: relating to others, new possibilities, personal strength, spiritual change, and appreciation of life (chi(2) (179)=822.53, CFI=0.97, NNFI=0.96, SRMR=0.05, RMSEA=0.09). Multigroup CFA supported the invariance of the PTGI across age groups, treatment type, time since diagnosis, and time since last treatment. These findings provide support for (1) the multidimensional nature and factorial validity of the PTGI, and (2) the use of the PTGI in future research examining posttraumatic growth within samples of physically active breast cancer survivors.

Modeling the Relationships between Adult Attachment Patterns and Borderline Personality Disorder: The Role of Impulsivity and Aggressiveness

To obtain a better understanding of the associations among Borderline Personality Disorder (BPD), adult attachment patterns, impulsivity, and aggressiveness, we tested four competing models of these relationships: a) BPD is associated with the personality traits of impulsivity and aggressiveness, but adult attachment patterns predict neither BPD nor impulsive/aggressive features; b) adult attachment patterns are significant predictors of BPD but not of impulsive/aggressive traits, although these traits correlate with BPD; c) adult attachment patterns are significant predictors of impulsive and aggressive traits, which in turn predict BPD; and d) adult attachment patterns significantly predict both BPD and impulsive/aggressive traits. We assessed 466 consecutively admitted outpatients using the Structured Clinical Interview for DSM–IV Axis II Personality Disorders (V. 2.0), the Attachment Style Questionnaire, the Barratt Impulsiveness Scale–11, and the Aggression Questionnaire. Maximum likelihood structural equation modeling of the covariance matrix showed that model (c) was the best fitting model (χ2(21) = 31.67, p > .05, RMSEA = .023, test of close fit p > .85). This result indicates that adult attachment patterns act indirectly as risk factors for BPD because of their relationships with aggressive/impulsive personality traits.

A Monte Carlo Simulation of Observable Versus Latent Variable Structural Equation Modeling Techniques

In this study, three approaches commonly used by communication scientists to specify structural relationships using full-information maximum likelihood structural equation modeling are investigated. Specifically, a simulation study using Monte Carlo techniques was conducted to compare the structural paths generated by each of the three structural equation model types. Two of the three approaches utilized forms of latent variable modeling, and the third approach employed observed variables only. Of the three, the observed variable approach produced the most conservative structural path coefficients, whereas the hybrid latent variable approach generated the least attenuated coefficients. The appropriateness of each technique in modeling structural relationships is discussed and an argument is made for greater use of latent variable structural equation modeling in the field of communication.