Partial Least Squares Path Modeling Research Articles

The Influence of Employee Engagement, Work Environment and Job Satisfaction on Organizational Commitment and Performance of Employees: A Sampling Weights in PLS path Modelling

Purpose- This paper explored the link between employee engagement, work environment, and job satisfaction on organizational commitment and employee performance in Ghana's Banking sector considering moderated-mediated interaction. Design/Methodology- Data were obtained from seven hundred and twenty (720) employees from selected financial banks in the Greater Accra Region of Ghana through simple random probability sampling. However, seven hundred (700) responses were deemed accurate and therefore used in the analysis. In the analytical process, Weighted Partial Least Squares (WPLS) and Partial Least Squares (PLS) based on Structural Equation Modeling (SEM) were employed. Findings- From the findings, the studied data for both WPLS-SEM and PLS-SEM models met internal consistency reliability, convergent, and discriminant validity. Also, organizational commitment fully mediated the link between work environment and employee performance in the WPLS-SEM model compared to PLS-SEM with partial mediation. It was statistically significant at p<0.01. Practical Implications- Based on the findings, it’s recommended that organizations and managers focus on developing the workers' workplace environment in numerous ways. This should entail valuing workers' contributions, communicating the company's progress and achievement to workers, thus instilling ownership in workers, providing them with a work-life balance, providing the requisite knowledge and tools for successful production, and providing a stable atmosphere. The workplace of all these factors could increase workers' morale and lead to increased productivity.

The Bottom-Up Impact of Proactive Personality on Employee Job Crafting: A Serial Mediation Model

Explanatory mechanisms of the positive impact of proactive personality on relevant individual outcomes have been thoroughly discussed in the literature. That being said, few studies have investigated the supervisor’s leadership style as an explanatory mechanism through which the outcomes of proactive individuals are affected. Drawing insight from Job Demands-Resources (JD-R) theory and followership theory, this paper examines a serial mediation model in which the relationship between proactive personality and two types of job crafting (approach role and resource crafting) is mediated by empowering leadership and work engagement. More specifically, we argue for the capacity of proactive individuals to increase their work engagement by influencing their leaders to embrace an empowering leadership style. Furthermore, empowering leaders are argued to increase employee approach role and resource crafting through increasing employee work engagement. A sample of 298 full-time workers, mainly from Saudi Arabia, participated in the study. The hypotheses were tested using Partial Least Squares Path Modeling (PLS-PM). The findings support the hypothesized relationships. A discussion of the findings, contributions, limitations, and future directions is provided.

Protective Effect of Intestinal Helminthiasis Against Tuberculosis Progression Is Abrogated by Intermittent Food Deprivation.

BackgroundTuberculosis (TB) is still a major challenge for humankind. Because regions with the highest incidence also have a high prevalence of helminthiasis and nutritional scarcity, we wanted to understand the impact of these on TB progression.MethodsWe have developed an experimental murine model for active TB in C3HeB/FeJ, coinfected with Trichuris muris and Heligmosomoides polygyrus nematodes, and exposed to an environmental mycobacterium (M. manresensis) and intermittent fasting. Cause-effect relationships among these factors were explored with Partial Least Squares Path modelling (PLSPM).ResultsPrevious parasitization had a major anti-inflammatory effect and reduced systemic levels of ADA, haptoglobin, local pulmonary levels of IL-1β, IL-6, TNF-α, CXCL-1, CXCL-5 and IL-10. Oral administration of heat-killed M. manresensis resulted in a similar outcome. Both interventions diminished pulmonary pathology and bacillary load, but intermittent food deprivation reduced this protective effect increasing stress and inflammation. The PLSPM revealed nematodes might have protective effects against TB progression.ConclusionsSignificantly higher cortisol levels in food-deprivation groups showed it is a stressful condition, which might explain its deleterious effect. This highlights the impact of food security on TB eradication policies and the need to prioritize food supply over deworming activities.

The assessment of poultry welfare using partial least squares-path modelling (PLS-SEM): a modeling the effects of physical activity and stress on growth

Poultry welfare is closely related to human health and animal production which is a sensitive process. While several statistical methods are available to measure observed variables (stocking density), unobserved (latent) variables such as emotional, psychological situations are typically analyzed using factor analysis. In recent years, structural equation modeling (SEM) has been used effectively in many fields such as agriculture and livestock. SEM provides an estimation of relationships between latent variables that cannot be measured directly. Most of the studies published on poultry welfare highlighted the need to determine causal relationships between latent variables (growth, physical activity, biological stress). Here, we demonstrate that PLS-SEM analysis was used to examine the relationship between biological stress, physical activity, and growth in livestock. A three-factor model was conducted with 96 animals. The PLS-SEM results revealed that 65.2% of growth can be predicted by the independent variables (R2 = 0.652), and that physical activity (γ = 0.698) was found to have more effect than biological stress (γ = 0.176) on growth. Also, physical activity was determined as the main variable for the evaluation of biological stress (γ = 0.546, R2 = 0.298) and growth. Overall, the research showed the suitability of SEM for the assessment of growth and biological stress.

Soft Modeling of Military Expenditure, Income Inequality, and Profit Rate, 1988–2008

Abstract This paper investigates the nexus of military expenditure, income inequality, and profit rate, applying the non-parametric technique of Partial Least Squares Path Modeling (PLS-PM) to 21 countries for 1988–2008. The findings suggest that military expenditure has a positive effect on income inequality while income inequality has a positive impact on profit rate. In contrast, military expenditure has a (relatively small) positive effect on profit rate. However, these results change significantly once unobserved heterogeneity is considered. Accordingly, based on four segments, although the positive effect of income inequality on profit rate remains the same for each segment, for some segments, the effect of military expenditure on income inequality and profit rate become negative.

Examining the antecedents and consequences of mobile travel app engagement.

How and why customers engage with mobile travel apps is vital to mobile marketing of travel-related companies. This paper discusses the antecedents and consequences of mobile travel app engagement. Specifically, this study aims to understand how travel app attributes stimulate mobile travel app engagement and lead to purchase intention. A research model is established based on the Stimulus-Organism-Response (S-O-R) model and the model is tested by Partial Least Squares Path Modeling (PLS-PM). The results show that ease of use, compatibility, and UI attractiveness positively influence mobile travel app engagement, and in turn, affect purchase intention. Furthermore, a multi-group analysis shows that the attributes affecting mobile travel app engagement differ across different customer groups. This paper discusses some theoretical and practical implications.

Effects of long-term cropping regimes on SOC stability, soil microbial community and enzyme activities in the Mollisol region of Northeast China

Retaining carbon in cultivated soils is an important mechanism to mitigate climate change and to maintain the sustainability of agricultural ecosystems. Characterization of the soil microbial community was an early means to quantify the increase in soil organic carbon (SOC) content and stability under different cropping systems. However, the effects of different cropping systems on the soil microbial community and enzyme activity and the driving force for increasing the SOC content remain unclear, especially the differences between continuous maize (Zea mays L.) cropping and rotation systems containing legumes. We used a long-term field experiment (30 years) in the Mollisol region of Northeast China. The field experiment was undertaken in split-plot design comprised of four treatments: i) farmland fallow (FALL), ii) continuous soybean cropping (CSC), iii) maize-soybean rotation (MSR), iv) continuous maize cropping (CMC). Fluorometric assays and phospholipid fatty acid analysis (PLFA) were used to determine the biological characteristics of the soil. The SOC chemical composition was characterized using Cross Polarization/Magic Angle Spinning solid-state 13C-nuclear magnetic resonance (13C NMR) spectroscopy. Principal component analysis (PCA), redundancy analysis (RDA) and the partial least squares path model (PLS-PM) were used to explore the coupling mediation of these parameters further. Our results suggested that soil microbes in the four systems were not limited by C and N, but co-limited by P. But compared with the FALL system, the CMC system significantly alleviated the phosphorus limitation of the microorganisms. The CMC system also significantly increased soil nutrient content, especially SOC content (40.8%), available phosphorus (117%), available potassium (30.3%), NO3−-N (148%), and increased microbial community abundance and enzyme activities. Compared with the CMC system, the MSR system held relatively lower Gram-positive: Gram-negative ratio and higher fungi: bacteria ratio, which indicated that the soil microbial community structure is more conducive to improving the SOC stability. Meanwhile, more evidence supporting data that SOC stability was enhanced in MSR soils was provided by the 13C NMR spectra and higher-quality indices (A / AO, AI, HI and LCI). Moreover, strong correlations and RDA analysis confirmed that SOC is the main factor affecting microbial communities and enzyme activities.

Associated soil aggregate nutrients and controlling factors on aggregate stability in semiarid grassland under different grazing prohibition timeframes

Grazing prohibition is an effective measure in improving soil stability and ecological quality. However, only a limited number of studies have been published on the dominant factors that impact soil aggregate stability and their associated effects on nutrient distribution for different size soil aggregates under long-term grazing prohibition management. In this study, we investigated variation in soil aggregate stability and nutrient distribution characteristics in semiarid grassland sites under different grazing prohibition timeframes (0years [GP0], 11years [GP11], 26years [GP26], and 36years [GP36]). Results showed that organic carbon (C) and total nitrogen (TN) concentrations in soil aggregates decreased at GP11 before progressively increasing and reaching its highest value at GP36, and the total phosphorus (TP) concentration did not change significantly. Most nutrients accumulated in macroaggregates (> 0.25mm) under grazing prohibition, and the nutrient stoichiometry in soil aggregates increased after 26years. Compared to the control (GP0), the mean weight diameter (MWD) value of the soil stability index increased at GP11 (21.7%) and decreased at GP26 (18.9%). Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) also showed that the proportion of stable organic C-related functional groups (i.e., alkene-C and aromatic-C) in macroaggregates were higher at GP11 and GP36 than at GP26. Furthermore, principal component analysis (PCA), partial least squares path modeling (PLS-PM), and the relative importance of regressors all showed that glomalin-related soil proteins (GRSP) and nutrients indirectly improved aggregate stability in semiarid grassland through their influence on the GRSP accumulation potential and nutrient stoichiometry. Generally, after 26years grazing prohibition had a positive effect on soil aggregate stability and nutrient accumulation in the semiarid grassland sites investigated for this study. Results from this study provide a theoretical basis to select appropriate grazing prohibition timeframes under grassland management initiatives to optimize ecological quality measures in semiarid regions.

Evaluation of factors affecting arsenic uptake by Brassica juncea in alkali soil after biochar application using partial least squares path modeling (PLS-PM)

Biochar application to As-contaminated soil can alter various soil chemical properties, and it can affect available As, plant As uptake, and As phytotoxicity. Increased dissolved organic carbon (DOC) and P released from biochar affect As behavior in the soil system. In this study, we evaluated the effect of biochar application on the chemical properties of soil and phytotoxicity in Brassica juncea using correlation analysis and partial least squares path modeling (PLS-PM). Biochar application increased electrical conductivity (EC), DOC, available P and available As. However, the increased available As did not significantly affect As uptake by B. juncea due to the decrease in the relative ratio and effect of available As with increase in available P derived from biochar. Moreover, biochar application negatively affected soil chemical properties (pH, EC, DOC, available P, and available As) and As uptake by B. juncea. Therefore, correlation analysis and PLS-PM analysis are useful tools to interpret the interactions among influencing factors in the soil-plant system. An approach at the equivalent molecular level rather than concentration should be adopted in future studies.

Improvement of alfalfa resistance against Cd stress through rhizobia and arbuscular mycorrhiza fungi co-inoculation in Cd-contaminated soil.

Rhizobia and arbuscular mycorrhiza fungi (AMF) are important symbiotic microbes that are advantageous to plants growing in metal-contaminated soil. However, it remains unclear how inoculated microbes affect rhizosphere microbial communities or whether subsequent changes in rhizosphere microbiomes contribute to improving plant resistance under metal stress. This study investigated the effects of rhizobia and AMF inoculation on alfalfa resistance to Cd stress. The response of rhizosphere microbial communities to inoculation and its role in increasing alfalfa' ability to cope with stress were further analyzed using high-throughput sequencing of 16S and ITS rRNA genes. Results showed that single rhizobia or AMF inoculation significantly improved alfalfa resistance to Cd stress, while their co-inoculation resulted in the greatest overall improvement. Improved resistance was reflected by the significant mitigation of Cd-induced lipid peroxidation and reactive oxygen species (ROS) stress caused by increases in antioxidant enzyme activities along with co-inoculation. Furthermore, co-inoculation significantly altered the rhizosphere microbial community structure by decreasing fungal community diversity and increasing bacterial community diversity. Results of partial least squares path modeling (PLS-PM) and variation partitioning analysis (VPA) showed that the rhizosphere bacterial community predominated over the fungal community with respected to improvements in resistance to Cd stress under the co-inoculation treatments. This improvement was specifically seen in the enrichment of certain key bacterial taxa (including Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi) induced by the rhizobia and AMF co-inoculation, enhancing alfalfa' ability to uptake rhizosphere nutrients and reduce its release of photosynthetically-derived carbon (C) into soil. Our findings revealed that the co-inoculation of multiple symbiotic microbes can assist plants to effectively cope with Cd stress, providing a greater understanding of rhizosphere bacterial taxa in the microbe-induced phytomanagement.

Machine Learning Data Imputation and Prediction of Foraging Group Size in a Kleptoparasitic Spider

Cost–benefit analysis is widely used to elucidate the association between foraging group size and resource size. Despite advances in the development of theoretical frameworks, however, the empirical systems used for testing are hindered by the vagaries of field surveys and incomplete data. This study developed the three approaches to data imputation based on machine learning (ML) algorithms with the aim of rescuing valuable field data. Using 163 host spider webs (132 complete data and 31 incomplete data), our results indicated that the data imputation based on random forest algorithm outperformed classification and regression trees, the k-nearest neighbor, and other conventional approaches (Wilcoxon signed-rank test and correlation difference have p-value from < 0.001–0.030). We then used rescued data based on a natural system involving kleptoparasitic spiders from Taiwan and Vietnam (Argyrodes miniaceus, Theridiidae) to test the occurrence and group size of kleptoparasites in natural populations. Our partial least-squares path modelling (PLS-PM) results demonstrated that the size of the host web (T = 6.890, p = 0.000) is a significant feature affecting group size. The resource size (T = 2.590, p = 0.010) and the microclimate (T = 3.230, p = 0.001) are significant features affecting the presence of kleptoparasites. The test of conformation of group size distribution to the ideal free distribution (IFD) model revealed that predictions pertaining to per-capita resource size were underestimated (bootstrap resampling mean slopes <IFD predicted slopes, p < 0.001). These findings highlight the importance of applying appropriate ML methods to the handling of missing field data.

The interplay of green servant leadership, self‐efficacy, and intrinsic motivation in predicting employees’ pro‐environmental behavior

AbstractEmployees' pro‐environmental behavior serves as a cornerstone in realizing organizations' sustainability initiatives. Leadership plays a vital role in shaping and nurturing the desired employee behaviors. Building upon social learning and self‐determination theories, we developed and tested a research model that investigated the mediating role of employees' green intrinsic motivation and the moderating influence of their green self‐efficacy on the relationship between green servant leadership and pro‐environmental behavior. Data were collected in two waves from 323 pairs of employee‐manager working in Pakistan's energy sector and analyzed with partial least squares path modeling (PLS‐PM). The findings endorsed that green servant leadership influences pro‐environmental behavior through the mediating mechanism of green intrinsic motivation. Further, green self‐efficacy played an interactive role with green servant leadership in shaping pro‐environmental behavior. This research responds to multiple calls for research and advances the knowledge on servant leadership and pro‐environmental behavior.

What difference does the gig mobility service make in the workers’ human needs structure?

This paper aims to compare and contrast the perceived psychological experience of the traditional versus gig mobility service workers with respect to their human needs structure. Gig mobility service here refers to on-demand transportation service enabled by an online platform. Both qualitative and quantitative research methods were used. Using the perspective of ERG (Existence, Relatedness and Growth) theory, we first explored the field using in-depth interviews and observations of both worker groups. Based on the qualitative findings, we formulated the quantitative measures for the corresponding constructs. The constructs’ relationship and paths differences between the two groups were analyzed statistically using partial least square path modeling (PLS-PM) method. The differences between the two groups were categorized into four quadrants, highlighting what both groups have and do not have, as well as what one group has but not the other. It was found that the gig mobility service resulted in not only more relationships among the constructs, but also generally higher perceived well-being for the workers. It seems that the gig mobility service has so far been promising in meeting workers human needs despite its long-term uncertainty. This study is among the few studies on understanding in which way the technology has changed the mobility service actors seen as workers, rather than sellers or users.

A Path Model of the Intention to Adopt Variable Rate Irrigation in Northeast Italy

Irrigated agriculture determines large blue water withdrawals, and it is considered a key intervention area to reach sustainable development objectives. Precision agriculture technologies have the potential to mitigate water resource depletion that often characterises conventional agricultural approaches. This study investigates the factors influencing farmers’ intentions to adopt variable rate irrigation (VRI) technology. The Technology Acceptance Model 3 (TAM-3) was employed as a theoretical framework to design a survey to identify the factors influencing farmers’ decision-making process when adopting VRI. Data were gathered through quantitative face-to-face interviews with a sample of 138 fruit and grapevine producers from the Northeast of Italy (Veneto, Emilia-Romagna, Trentino-Alto Adige, Friuli-Venezia Giulia). Data were analysed using partial least squares path modelling (PLS-PM). The results highlight that personal attitudes, such as perceived usefulness and subjective norm, positively influence the intention to adopt VRI. Additionally, the perceived ease of use positively affects intention, but it is moderated by subject experience.

Identifying agricultural areas with potential for city connections: A regional-scale methodology for urban planning

The main objective of this study was to characterize the spatial structure of periurban agriculture for the purpose of operational urban development, avoiding the use of cumbersome and costly surveys when the public action sphere is extended to a region or a country. On the basis of Partial Least Squares-Path Modeling (PLS-PM), the approach developed here uses data freely available in France and makes it possible to analyze complex relationships between the socio-economic structure of farms, demography, landscape structure, and landscape management and function. The results are used to identify spatial units of periurban farmland (USAP). Aggregated at the municipal level, they reveal municipalities under the influence of an urban pole whose agricultural areas have a greater possibility of developing short marketing chains towards the city and that could consequently justify public support for local supply options.

I Quit! Effects of Work-Family Policies on the Turnover Intention.

The retention of key human resources is a challenge and a necessity for any organisation. This paper analyses the impact of the existence and accessibility of work-family policies on the well-being of workers and their intention to leave the organisation. To test the proposed hypotheses, we applied a structural equation model based on the partial least squares path modelling (PLS-SEM) approach to a sample of 558 service sector workers. The results show that the existence and accessibility of work-family policies directly reduce the intention to leave the organisation. Moreover, this relationship also occurs indirectly, by mediating the well-being that is generated by these work-family policies. We also analysed the moderating role that gender and hierarchy could have in the above relationships. In addition to the above theoretical implications, this study has practical implications. The findings show that employees with family and work balance problems experience lower emotional well-being, more health problems and eventually higher turnover rates. To avoid these problems, management must focus not only on the implementation of work-family policies but also on their accessibility, without subsequent retaliation or prejudice to employees. Additionally, management should pay special attention to female managers, given their greater difficulty in balancing work and family life.

Using Composite Phenotypes to Reveal Hidden Physiological Heterogeneity in High-Altitude Acclimatization in a Chinese Han Longitudinal Cohort

Altitude acclimatization is a human physiological process of adjusting to the decreased oxygen availability. Since several physiological processes are involved and their correlations are complicated, the analyses of single traits are insufficient in revealing the complex mechanism of high-altitude acclimatization. In this study, we examined these physiological responses as the composite phenotypes that are represented by a linear combination of physiological traits. We developed a strategy that combines both spectral clustering and partial least squares path modeling (PLSPM) to define composite phenotypes based on a cohort study of 883 Chinese Han males. In addition, we captured 14 composite phenotypes from 28 physiological traits of high-altitude acclimatization. Using these composite phenotypes, we applied k-means clustering to reveal hidden population physiological heterogeneity in high-altitude acclimatization. Furthermore, we employed multivariate linear regression to systematically model (Models 1 and 2) oxygen saturation (SpO2) changes in high-altitude acclimatization and evaluated model fitness performance. Composite phenotypes based on Model 2 fit better than single trait-based Model 1 in all measurement indices. This new strategy of using composite phenotypes may be potentially employed as a general strategy for complex traits research such as genetic loci discovery and analyses of phenomics.

ECONOMIC ANALYSIS CHILD LABOR BASED HOUSEHOLDS IN BENGKULU CITY

The purpose of this study was to analyze the influence of father characteristics, mother characteristics, household characteristics, child labor characteristics, and community, on work time of child labor in Bengkulu City. This research uses primary data. Sampling was done by incidental method. Data collected through interviews and questionnaires. The analytical method uses PLS-PM (Partial Least Square-Path Modeling). The results showed that the variables of father characteristics, mother characteristics, household characteristics and community had a negative and significant effect on the working hours of child labor. While the variable child labor characteristics had a positive and significant influence on working hours of child labor. If the father characteristics, the mother characteristics, the household characteristics, and the community are getting better, then the working hours for child labor will be reduced. While, if the child labor characteristics are getting better (the more it fits the criteria, namely male sex, the lower the education, and not going to school), then the work time of child labor will increase. The indicators on the father characteristic variables, that most determine are father's income and father's education. Indicators on the mother characteristics that most determine are mother's income, mother's education and mother's occupational status. The most determine indicators of household characteristics are household assets, number of family members, number of children, number of working family members, and parents' income. Indicators on the most determine characteristics of child labor are the gender of child labor, the education of child labor and the status of child labor. The most determine indicators in the community are market availability and school availability.Keywords: Child labor, Household, Working Hours, Indonesia, BengkuluJEL Classifications: J01, J13DOI: https://doi.org/10.32479/ijefi.9827

The role of intrinsic and extrinsic motivations in sharing economy post-adoption

PurposeThe purpose of this paper is to examine use and sharing economy (SE) continuance intention, and the mediation effects of use between individuals' motivations and SE continuance intention. A theoretical model is developed to explain use and SE continuance intention as intrinsic and extrinsic motivated behaviour, as proposed by self-determination theory. Factors are derived from SE context and supported by published research on SE.Design/methodology/approachThe partial least squares path modelling (PLS-PM) technique is used to test the model in a quantitative study involving 256 users of SE services.FindingsFindings suggest that use and SE continuance can be explained by concurrent intrinsic and extrinsic motivations. Moreover, high environmental concerns may restrain the use of SE services. Findings show that continuance intention is influenced by current use of SE services. Moreover, the study emphasizes the mediation effect of use between intrinsic and extrinsic motivation and SE continuance intention.Research limitations/implicationsThe analysis of use behaviour should be complemented with other measures of use and with data provided by qualitative methods of research. Further research should also consider the effect of different control variables and mediation effects.Practical implicationsBrand managers and companies providing services through digital platforms should address individuals' needs in order to stimulate voluntary engagement in persistent SE practices.Social implicationsThis study informs the consumer in general so that the SE can develop its potential alongside an economy based on the ownership of private property.Originality/valueThis study extends findings on continuance intention research by offering internal motivation factors as predictors of post-adoption behaviour and emphasizes the role of use on SE continuance intention.

The Spatial-Temporal Heterogeneity of Understory Light Availability in a Temperate Forest of North China

The spatial-temporal variation of understory light availability has important influences on species diversity and community assembly. However, the distribution characteristics and influencing factors of understory light availability have not been fully elucidated, especially in temperate deciduous, broad-leaved forests. In this study, the understory light availability was monitored monthly (May–October) in a temperate deciduous, broad-leaved forest in Henan Province, China. Differences in the light availability among different months and habitat types were statistically analyzed using Kruskal–Wallis method, respectively. Partial least squares path modeling (PLS-PM) was used to explore the direct and/or indirect effects of stand structure, dominant species and topographic factors on the light environment. Results showed that there were differences in light environments among the four habitat types and during the studied six months. The PLS-PM results showed that the stand structure and the dominant species were negatively correlated with the light environment, and the path coefficient values were −0.089 (P = 0.042) and −0.130 (P = 0.004), respectively. Our result indicated that the understory light availability exhibit a distinct spatial and temporal heterogeneity in temperate deciduous, broad-leaved forest of north China. The characteristics of woody plant community, especially the abundance of one of the dominant plant species, were the important factors affecting the understory light availability.