Partial Least Squares Path Modeling Research Articles

Rhizobium Inoculation Enhances the Resistance of Alfalfa and Microbial Characteristics in Copper-Contaminated Soil.

Some studies have reported the importance of rhizobium in mitigating heavy metal toxicity, however, the regulatory mechanism of the alfalfa-rhizobium symbiosis to resist copper (Cu) stress in the plant-soil system through biochemical reactions is still unclear. This study assessed the effects of rhizobium (Sinorhizobium meliloti CCNWSX0020) inoculation on the growth of alfalfa and soil microbial characteristics under Cu-stress. Further, we determined the regulatory mechanism of rhizobium inoculation to alleviate Cu-stress in alfalfa through plant-soil system. The results showed that rhizobium inoculation markedly alleviated Cu-induced growth inhibition in alfalfa by increasing the chlorophyll content, height, and biomass, in addition to nitrogen and phosphorus contents. Furthermore, rhizobium application alleviated Cu-induced phytotoxicity by increasing the antioxidant enzyme activities and soluble protein content in tissues, and inhibiting the lipid peroxidation levels (i.e., malondialdehyde content). In addition, rhizobium inoculation improved soil nutrient cycling, which increased soil enzyme activities (i.e., β-glucosidase activity and alkaline phosphatase) and microbial biomass nitrogen. Both Pearson correlation coefficient analysis and partial least squares path modeling (PLS-PM) identified that the interactions between soil nutrient content, enzyme activity, microbial biomass, plant antioxidant enzymes, and oxidative damage could jointly regulate plant growth. This study provides comprehensive insights into the mechanism of action of the legume-rhizobium symbiotic system to mitigate Cu stress and provide an efficient strategy for phytoremediation of Cu-contaminated soils.

Extracellular Enzyme Stoichiometry and Microbial Metabolism Limitation During Vegetation Restoration Process in the Middle of the Qinling Mountains, China

Clarifying the characteristics of soil microbial nutrient limitation and its driving mechanisms during vegetation restoration after farmland abandonment has important implications for revealing soil nutrient cycling and maintaining ecosystem stability. To determine the limitation of soil microbial nutrients and its relationship with soil properties along a chronosequence of abandoned farmland in the middle of the Qinling Mountains, the soil physicochemical properties and five enzyme activities (β-1,4-glucosidase (BG), cellobiohydrolase (CBH), β-1,4-N-acetylglucosaminidase (NAG), leucine aminopeptidase (LAP), and acid phosphatase (AP)) were measured, and models of extracellular enzymatic activity were applied. The results showed that the activities of BG, CBH, NAG, LAP, and AP were significantly increased following farmland abandonment. With the increasing years of abandonment, the ratios of (BG+CBH)/(NAG+LAP) and (BG+CBH)/AP significantly decreased, whereas the ratio of (NAG+LAP)/AP increased. Correlation analysis showed that most soil physicochemical properties were significantly correlated with extracellular enzyme activities and extracellular enzymatic stoichiometry. The vector length of extracellular enzymatic stoichiometry decreased with the increase in abandonment years, indicating that the limitation of soil microorganisms on carbon (C) was reduced. Moreover, the vector angles (>45°) showed a decreasing trend, indicating that microbial metabolisms were limited by phosphorus (P) and gradually decreased. Regression analysis showed that the C and P limitations were significantly related to total nutrients, available nutrients, nutrient ratio, and soil physical properties. Partial least squares path modeling (PLS-PM) revealed that the C and P limitations were directly regulated by nutrient ratio. PLS-PM further showed that soil total nutrients indirectly affected soil microbial C and P limitations by affecting nutrient ratio, and nutrient ratio affected the soil metabolism limitation via available nutrients and pH. Our study suggests that the characteristics of microbial metabolism during the vegetation restoration process reflect the mechanism of microorganism-mediated soil nutrient cycling, which provides a theoretical basis for revealing the community dynamics and stability during the vegetation restoration process and maintaining the regional ecological environment security in the Qinling Mountains.

What makes tourists adopt smart hospitality? An inquiry beyond the technology acceptance model

Smart hospitality has become an attractive project in tourism. Extant research has studied smart technology as a contingency but has neglected to conceptualize smartness and investigate its consequences. This study conceptualizes and operationalizes smart hospitality and explores the relationships among smartness, perceived usefulness, perceived ease of use, overall image of a hotel and tourists' behavioral intention to stay in a smart hotel. The proposed model incorporated technology acceptance model (TAM) and image theory. With a sample of 348 respondents in Macau, this study tested the model using partial least squares path modeling (PLS-PM), which indicates that the proposed model fits the data. In spite of a high inter-construct correlation, the results showed that smartness does not have a direct effect on behavioral intention. According to mediation analysis, indirect effects made up of significant direct effects and assigned them to TAM, image theory, and a combination of both. This paper contributes to hospitality management theory by providing additional insight into smart hospitality, it demonstrates the applicability of PLS-PM with composite and common factor models in technological change research, and it suggests smartness as a business strategy that can change tourists' choices in practice.

A comparative study on the performance of maximum likelihood, generalized least square, scale-free least square, partial least square and consistent partial least square estimators in structural equation modeling

Structural equation modeling offers various estimation methods for estimating parameters. The most used method in covariance-based structural equation modeling (CB-SEM) is the maximum likelihood (ML) estimator. The ML estimator is typically used when fitting models with normally distributed data. The growth of partial least squares path modeling (PLS-PM), including consistent partial least squares (PLSc), has also been noticed by researchers in the SEM fields. The PLSc has elevated interest in the scholastic setting in measuring the performance of various estimation methods in structural equation modeling. The choice of estimation methods has substantial impact in yielding parameter estimates. There could be a trade-off among the estimation methods’ ability to deal with different types of data based on the model tested. Accordingly, this study aims to compare the performance of ML, generalized least squares (GLS), and scale-free least squares (SFLS) for CB-SEM as well as partial least squares (PLS) and consistent partial least squares (PLSc). Multivariate normal data were generated using Monte Carlo simulation with pre-determined population parameters and sample sizes using R Programming packages. To produce the estimated values, data analysis was performed using AMOS and SmartPLS for CB-SEM and PLS-SEM, respectively. The findings illustrate notable similarities between CB-SEM (ML) and PLS-SEM results when the true indicator loading is certainly high.

How can Strategy-as-Practice Enable Innovation under the Influence of Environmental Dynamism?

ABSTRACT Purpose: the objective of this study was to analyze innovation in Brazilian organizations when enabled through SIS, in the strategy-as-practice approach, on the influence of moderating environmental dynamism. Methods: we performed structural equation modeling using the statistical technique of partial least squares path modeling (PLS-PM) and post hoc analysis to identify unobserved heterogeneity, with a sample of 256 Brazilian companies from different sectors. Results: the results revealed that the SIS had a strong and significant influence on the innovation of exploitation and exploration. The environmental uncertainty of dynamism moderation was not present in the relationship between SIS and the innovation of exploitation. However, SIS showed a strong and significant influence on innovation of exploration in high levels of dynamism. The existence of unobserved heterogeneity was identified for two segments of the sample, demonstrating a strong path effect between SIS and innovation of exploration and exploitation on the high presence of dynamism in service companies with a size greater than 500 employees. Conclusions: the study contributed to the extension of the strategy-as-practice and innovation literature, by identifying SIS as an alternative in the planning process to enable innovation in the organization, in environments with a high rate of change and unpredictability.

How can Strategy-as-Practice Enable Innovation under the Influence of Environmental Dynamism?

ABSTRACT Purpose: the objective of this study was to analyze innovation in Brazilian organizations when enabled through SIS, in the strategy-as-practice approach, on the influence of moderating environmental dynamism. Methods: we performed structural equation modeling using the statistical technique of partial least squares path modeling (PLS-PM) and post hoc analysis to identify unobserved heterogeneity, with a sample of 256 Brazilian companies from different sectors. Results: the results revealed that the SIS had a strong and significant influence on the innovation of exploitation and exploration. The environmental uncertainty of dynamism moderation was not present in the relationship between SIS and the innovation of exploitation. However, SIS showed a strong and significant influence on innovation of exploration in high levels of dynamism. The existence of unobserved heterogeneity was identified for two segments of the sample, demonstrating a strong path effect between SIS and innovation of exploration and exploitation on the high presence of dynamism in service companies with a size greater than 500 employees. Conclusions: the study contributed to the extension of the strategy-as-practice and innovation literature, by identifying SIS as an alternative in the planning process to enable innovation in the organization, in environments with a high rate of change and unpredictability.

Identity-Based Online Hate Content

The content which is expressed over the internet and its associated social media based on any of the protected characteristics like gender, religion, race, and disability is referred to as online hate content. This article aims to examine the user responses on online hate content and determine the predictors of online hate content. With an objective to identify the determinants of online hate content, the data has been collected from 716 internet users using a research instrument designed for the purpose. Both online and offline modes are used for collecting the data. A comprehensive analysis is made using partial least squares path modeling (PLS-PM) package from an open-source software R. The analysis of structural model revealed that the attitude and opinions towards different protected characteristics such as gender, religion, race, and disability are influencers of online hate content. Further, the analysis of measurement models revealed the role of measuring indicators.

Synergy of saprotrophs with mycorrhiza for litter decomposition and hotspot formation depends on nutrient availability in the rhizosphere

Plants acquire and recycle nutrients from soil organic matter, and these dynamics depend on a highly diverse array of microorganisms in the rhizosphere. Although functions of many microbial groups have been identified, how different groups interact to affect biogeochemical processes is still poorly understood. We investigated the interactive effects of saprotrophs and arbuscular mycorrhizal fungi (AMF) on Medicago sativa litter decomposition and spatial distribution of enzyme activity in the rhizosphere in nutrient poor and rich soils, using compartmented microcosms designed for zymography. In nutrient poor soils, co-inoculation of saprotrophic bacteria (Alcaligenes faecalis) or fungi (Phanerochaete chrysosporium) with AMF (Rhizophagus irregularis) resulted in faster litter decomposition and greater hotspot areas of enzymes in the rhizosphere compared to mono-inoculations. These positive effects were stronger in the interaction of AMF with saprotrophic bacteria than that with saprotrophic fungi. The synergy of saprotrophic bacteria with AMF for litter decomposition and enzymatic hotspot formation was weaker in nutrient rich soils than that in nutrient poor soils. In contrast, in nutrient rich soils, co-inoculation of saprotrophic fungi with AMF reduced litter decomposition. A partial least squares path modeling (PLS-PM) analysis indicated that faster litter decomposition and larger enzymatic hotspots increased overall plant growth. These findings suggest the existence of important synergistic relationships between these two microbial guilds for plant growth in nutrient poor soils. Specifically, AMF accelerated litter mineralization by increasing saprotrophic biomass and enzyme activities (i.e., nitrate reductase, urease and cellulase). At the same time, saprotrophs increased AMF colonization rate, which increased the hotspot areas of enzyme activities. These hotspots, in turn, broadened the nutrient mobilization zone around the roots - in the rhizosphere. Consequently, the synergistic interactions between saprotrophs and AMF for litter decomposition and the formation of enzymatic hotspots may be an important mechanism for promoting plant fitness under low soil nutrient availability.

Assembly of functional microbial communities in paddy soil with long-term application of pig manure under rice-rape cropping system

Organic farming is considered an efficient approach to improve soil fertility for sustainable agriculture. However, its soil micro-ecological effects and functions in intensive rice cropping systems are still obscure. Twelve soil samples were collected from a field experiment with four treatments such as M0 (no pig manure), M1 (1.6 t ha−1 pig manure), M2 (3.2 t ha−1 pig manure) and M3 (4.8 t ha−1 pig manure) after eight rice-oilseed rape rotation. Soil chemical property, enzyme activity and abundant/rare bacterial or fungal communities were analyzed to investigate the effect of conversion to organic farming with continuous pig manure application on soil microbiota. Stochastic processes controlled the assembly of abundant taxa, and deterministic processes dominated rare taxa. The composition and network construction of bacterial and fungal communities were significantly affected by pig manure, with changes in soil property and enzyme activity. Based on partial least squares path modeling (PLS-PM), pig manure application affected bacteria construction and enzyme activities by increasing soil carbon (C) and nitrogen (N). In summary, long-term pig manure application promotes specific microbial associations known to be involved in degrading complex organic compounds, and improving soil fertility such as soil enzyme activities. This research provides insight into understanding the processes behind changes in bacterial and fungal communities in paddy soil after conversion to organic farming.

Using PLS Path Modelling in Education System: A Model to Measure the Academic Performance Score

Partial Least Square (PLS) was used the path modelling. Latent variables such as staff, institution (administration, number of enrolments, quality of laboratories, rooms, etc.), incentive applied for research and Academic Performance Score (APS) were proposed. The indicators available on Brazilian universities were chosen for this article, they were tested and duly validated, as well as the reliability of these items and the variables represented by them. The result was the model explains satisfactorily well the Academic Performance Score (APS) with a R2 of 70.6%, with the Institution contributing the most to the model, for approximately 35.4%. Next, the incentive to research contributes 29.2%. In addition, the hypotheses generated in this article, except one, adequately support the model.

Identifying the paths and contributions of climate impacts on the variation in land surface albedo over the Arctic

Understanding historical changes in land surface albedo (ALB) is critical for projecting future climate changes over the Arctic. Previous studies have reported the important role of snow cover and vegetation growth in regulating Arctic land ALB, but their main influencing paths and separate contributions remain underexamined. In this study, the partial least squares path model (PLS-PM) and random forest model (RFM) are adopted to explore the dominant paths of three climate variables—temperature (Tem), precipitation (Pre) and wet days (WD)—in influencing the interannual variations in ALB (IVA) by regulating vegetation and snow cover. The results show that ALB in October and December exhibit significant (p < 0.05) upward and downward trends, respectively. ALB in the Northwest Territories, Victoria Island and Nunavut of the Arctic significantly (p < 0.05) increase in summer and October. The summer snow cover fraction (SCF) shows a significant positive correlation with ALB (R: 0.60‒0.78), while significant negative (R = -0.60) and positive (R = 0.50) relations are found between the enhanced vegetation index (EVI) and ALB during July and September, respectively. According to PLS−PM, the dominant paths that affect the IVA exhibit a prominent seasonal feature. Pre → EVI → ALB and Tem → SCF → ALB are identified as the main paths for ALB changes during spring, while in summer, the only significant path is Tem → SCF → ALB. In autumn, nonsignificant impacts on the variations in EVI and SCF (p > 0.05) are observed, while a significant path WD → SCF → ALB is found in winter. Based on RFM, the relative contribution (RC) of vegetation change to March IVA can reach 52.1 ± 9.2%, while snow variations play a dominant role in April and May, with contributions of 57.8 ± 8.4% and 68.4 ± 4.1%, respectively. Seasonally, summer IVA is mainly impacted by snow (RC from 50.5 ± 4.5% to 65.9 ± 4.5%), while vegetation exerts the dominant influence on IVA in autumn except for September. In winter, however, the dominant strength of vegetation is weakened except in December, with IVA mainly controlled by snow (RC above 50%).

Sharing economic responsibility: Assessing end user's willingness to support E-waste reverse logistics for circular economy

The increase in the generation of e-waste is a growing concern worldwide. However, due to the presence of precious metals, it could serve as a source of secondary raw materials. This is in line with the circular economy concept, which focuses on the reuse of resources. However, e-waste management/recycling may not always be profitable. Therefore, stakeholders should share the economic responsibility of e-waste management to achieve a circular economy and sustainable society. Building on the concept of 'polluters pay', the present study investigates end user's willingness to pay (WTP) for the recycling of e-waste they produce. Specifically, using the theory of planned behaviour (TPB), the study empirically examines the psychological factors that influence end user's willingness to pay for e-waste recycling. The proposed model is tested using survey data obtained from 382 Indian residents. The partial least square path modelling (PLSPM) approach is employed to determine the effect of various factors (attitude, subjective norms, perceived behavioural control, intention, environmental concerns, and awareness of consequences) on WTP. The results suggest that perceived behavioural control (PBC), awareness of consequences, and intentions to recycle e-waste are positive predictors of WTP. Additionally, attitude, subjective norms, and environmental concerns positively affect WTP through the intention to recycle e-waste. The policymakers and decision-makers may use the findings of this study to motivate end-users to share the financial responsibility of the e-waste generated by them, which could lead to a circular economy and sustainable society.

Food Security and the COVID-19 Crisis from a Consumer Buying Behaviour Perspective-The Case of Bangladesh.

Since COVID-19 was confirmed in Bangladesh in March 2020, the government have enacted stringent measures to prevent the spread of the coronavirus, which has had a significant impact on people’s lives. Food consumption habits of consumers have shifted as a result of declining grocery shopping frequency, negative income shock, and food prices shooting up. This paper aims to explore Bangladeshi consumers’ buying behaviour in association with the stress generated from a food supply shortage during the COVID-19 pandemic and the post-outbreak perception of the food industry, using a dataset with 540 online samples collected between July and August 2021. A two-stage cluster sampling method and self-administrated questionnaire techniques were adopted for collecting the data during the third wave of COVID-19. Using partial least squares path modelling (PLS-PM) and multivariate multiple ordered logit regression (MVORD) to reveal the pertinent structure between all the blocks, this study provides two key findings. First, a higher intensity of COVID-19 impact translates into higher food stress associated with income reduction and higher food prices. Second, food stress directly affects consumer buying and consumption behaviour. We strongly recommend connecting consumers with local producers and collective use of shared warehouses through institutions, policies, and reforms to prevent disruption in the food supply chain and to keep food prices stable. Additionally, food producers, distributors, stakeholders, and policy planners should strengthen the food supply chain to stabilize food security.

Modelling of threats that affect Cyano-HABs in an eutrophicated reservoir: First phase towards water security and environmental governance in watersheds

Cyano-HABs are proliferating around the world due to anthropogenic nutrient enrichment of freshwater bodies. This study seeks to obtain a holistic vision over the various threats that affect the Cyano-HABs of Umia basin and especially of A Baxe reservoir (Galicia, NW Spain), through the method of Partial least squares path modelling (PLS-PM). The A Baxe reservoirs is a fundamental source of drinking water supply to surrounding dwellings. This study identifies and quantify the variables that increase contaminant concentration and decrease ecological integrity, as well as how this scenario evolved over various hydrologic years. In this regard, the PLS-PM equations will be robust and powerful tools to predict changes in eutrophication and ecological integrity, as response to measures implemented in the basin that can improve water quality. The dependent latent variables are “Eutrophication” (chlorophyl-a, Microcystis sp.) and “Ecological Integrity” (METI Bioindicator). The independent latent variables are “SWP”, which represents surface water parameters (phosphorus, nitrogen and pH) and “Climatic Conditions” (temperature, precipitation). The PLS-PM results revealed that 51.0% of “Eutrophication” is predicted by the independent variables. The connections between latent variables are quantified through path coefficients (β). The “SWP” contributes by increasing “Eutrophication” (β = 0.235), the same occurring with the “Climatic Conditions” (β = −0.672). The variables “Eutrophication” (β = −0.217) and “SWP” (β = −0.483) lower the “Ecological Integrity”. On the other hand, different trophic scenarios, adapted to the temperature increase predicted for the study area, were tested, and it was found that ecological integrity would improve by 46% if the oligotrophic state were reached. Therefore, it is recommended to prevent pollution by means of water control and governance plans, as well as corrective and preventive measures, which guarantee the water security of the river basins. Despite the complex mathematics behind the PLS-PM models, their user-friendly development and application through interactive graphical interfaces make them easily transposable to other eutrophic reservoirs, widening the readership of these studies focused on multiple-geosphere assessment of environmental impacts.

How do gender disparities in entrepreneurial aspirations emerge in Pakistan? An approach to mediation and multi-group analysis

This cross-sectional study sought to identify gender differences in individual behavioral attitudes, personal traits, and entrepreneurial education based on planned behavior theory. The Smart partial least squares (PLS) structural equation model and PLS path modeling were used. A survey design was used to collect data from 309 samples using quantitative measures. The model was tested for validity and reliability and showed variance (full, R2 = 58.9% and split, R2 = 62.7% and R2 = 52.7%) in male and female model predictive power, respectively. Subjective norms (SN), personality traits (PT), and entrepreneurial education (EE) significantly impacted the male sample's intention. Females' intentions toward entrepreneurship was less affected by attitude toward behavior (ATB), subjective norms (SN), perceived behavioral control (PBC), and entrepreneurship education (EE). Further, attitudes, social norms, and behavioral controls as mediation variables indicate a significant and positive role of male and female intentions. These findings imply that behavioral beliefs (ATB, PBC, and SN) influence entrepreneurial intention-action translation. The results significantly supported the designed hypotheses and shed light on individual personality traits (PT) and entrepreneurship education (EE) underpinning enterprise intention. The study determined that EE and PT are the strongest predictors of intention, thus highlighting the role of these motives in the entrepreneurial process. This study contributes to the growing body of knowledge on youth entrepreneurs, expands our understanding of entrepreneurship as a practical career choice, and offers a novel account differentiating male and female PT. The drive to evaluate the effects of entrepreneurial intention among budding disparities in Pakistan requires a more profound knowledge of the aspects that endorse entrepreneurship as a choice of profession and enhances youth incentive abilities to engage in entrepreneurial activities based on exploitation.

Factors Affecting Image and Trust in Private Universities

This research was conducted to reveal the factors that influence the image and trust through service marketing management and customer relations to the image of private universities and their implications for customer trust. The research method used is the explanatory survey method. The unit of analysis in this study is a private university located in North Sumatra Province which is in LLDIKTI I, totaling 222 private universities. The number of samples had taken as many as 73 PTS. Based on the distribution of questionnaires, only 50 private universities were willing and fully included in the unit of analysis so that the number of respondents was 550 people who were selected as the unit of analysis. Data analysis method using Partial Least Square-Path Modeling (PLS-PM).The results of hypothesis testing indicate that the university's image variable is a full intervening variable where it is proven that service marketing management and customer relations do not have a direct influence on customer trust but provide a significant indirect effect. The magnitude of the influence of service marketing management variables, customer relations, and university image shows that the largest influence on customer trust is given by service marketing management, followed by the second place is the image of the university and the third position is customer relations.

Impact of Artificial Intelligence on HR practices in the UAE

Social trends and information technology are creating pressure, resulting in organizations being forced to update and recreate themselves. Against this backdrop there is an increasing trend to adopt artificial intelligence technologies. This study aims to explore and investigate the effect of Artificial Intelligence (AI) on Human Resources (HR) practices in UAE companies with the help of mixed-method design. A mixed-method design was applied to explore and test the research questions. Semi-structured interviews and survey were conducted, respectively for both the study designs. AI and HR personnel were approached as sample participants for this study. Thematic analysis and PLS-SEM (Partial least squares path modeling) were used to analyze the data, respectively. Positive and significant effects of planned training and development process (0.231→0.021), tactical performance appraisal and integration of AI (0.719→0.000), and integration of AI and efficient HR practices (0.204→0.131) were shown. The moderating role of ease of use on integration of AI and efficient HR practices was negative and insignificant. AI plays an essential role in shifting the HR functions to enter the digitization era. The types of businesses and abilities require some activities such as training and development due to the increased use of technology.

The influence of corporate social responsibility on students' emotional appeal in the HEIs: The mediating effect of reputation and corporate image

AbstractThe purpose of this paper is to study the influence of corporate social responsibility (CSR) over higher education institutions' (HEIs) students' emotional appeal and the effect of two mediating variables, corporate image, and reputation. A sample of 211 students surveyed was obtained, and the study was conducted using partial least squares path modeling (PLS‐SEM) technique. The results showed that emotional appeal is influenced by corporate reputation, corporate image, and CSR practices. These effects are not only direct and positive but significant indirect effects are also obtained, which allow the positive effects of CSR to be heightened. This paper contributes to the literature on CSR considering mediating effects of corporative image and reputation in the relationship between CSR and emotional appeal. The findings provide important implications for theory and practice, indicating consistent strategies for competitive advantage in HEIs by achieving stakeholder engagement and new lines of research in terms of emotional marketing.

Components to foster organizational resilience in tourism SMEs

PurposeSmall- and medium-sized enterprises (SMEs) mainly rely on their structure and internal networks to achieve their goals and remain competitive. However, their limited internal capabilities and complex environments can hinder their stability. Thus, this study evaluated the relationships among specific factors toward fostering organizational resilience (OR) in tourism SMEs.Design/methodology/approachA multi-methodological approach was adopted to address this research study, including (1) social network analysis (SNA) to formulate the conceptual model and (2) construct validation through partial least squares path modeling (PLS-PM).FindingsThe six proposed hypotheses were supported. These results suggest that addressing these variables and relationships after considering management style and people development as critical factors can foster OR in tourism SMEs.Research limitations/implicationsThe ideas that were developed were constrained to the organizational domain. Although the results apply to the Mexican context, this limitation can be offset by extending the proposal to other emergent regions or organizations. This can also increase the generalization of the results and foster improvements in the approaches applied.Practical implicationsAcademics and managers must rethink resilience as the final state generated by multiple factors. This requires reconfiguring inner organizational interactions, providing more autonomy to operative units, reinforcing business intelligence and improving feedback mechanisms.Originality/valueThis research study contrasts previous studies because it proposes that SNA be exploited to avail of the advantages it confers in designing the conceptual model. In this regard, we present new relationships to promote OR and provide new avenues in order to improve the analysis of adaptation processes.

Influence of arbuscular mycorrhizal fungi on selenium uptake by winter wheat depends on the level of selenate spiked in soil

Selenium (Se) deficiency has been a public health concern for years. Arbuscular mycorrhizal fungi (AMF) play an essential role in improving Se uptake in crops, but related mechanisms still remain unclear. To explore the influence of AMF on uptake of Se in winter wheat, a pot experiment was conducted to inoculate wheat with Funneliformis mosseae (F.m) or not under different levels of selenate in soil. The present results indicated that inoculation of F.m significantly (p < 0.05) increased Se concentration in shoots and roots of wheat under low level of selenate (≤5.0 mg kg−1) treatments, while the contrary pattern was recorded under high level of selenate (15 and 20 mg kg−1) treatments. Moreover, inoculation of F.m significantly increased concentration of available Se in soil by 4.68–34.05%. Under selenate ≤5 mg kg−1 treatments, the expression of TaeSultr1;1 and TaeSultr1;3 in roots of mycorrhizal wheat was significantly up-regulated by 3.06–5.53 and 0.63–5.12 times, while reached saturation under selenate >5 mg kg−1 treatments. In addition, partial least squares path modeling (PLS-PM) showed that inoculation of AMF directly affected the expression of sulfate transporter and that both sulfate transporter and soil Se fractions played a significant positive effect on plant Se content. The present study indicated that AMF on Se concentration in winter wheat depends on the level of selenate spiked in soil and added to our understanding of the functions and applications of AMF on crop Se absorption.