A cross-cultural analysis of ridesharing intentions and compliance with COVID-19 health guidelines: The roles of social trust, fear of COVID-19, and trust-in-God

Ridesharing services such as Uber and Lyft have been substantially affected by the ongoing COVID-19 pandemic. Drawing on social capital theory, the current research investigates how social trust relates to three types of trust in compliance with COVID-19 guidelines and consumers' ridesharing intentions. Analyzing data from two economically and culturally distinct countries, the results suggest that social trust positively affects trust in platform companies' compliance with COVID-19 guidelines (TPC), but not (or to a lesser extent) trust in drivers' (TDC) and other riders (TRC) compliance with COVID-19 guidelines in both the United States and Bangladesh. Importantly, TPC, TDC, and TRC are positively related with consumers' ridesharing intentions in the United States but not in Bangladesh. Furthermore, the analysis reveals two counterintuitive moderating effects of fear of COVID-19 and trust in God. The results provide important insights on factors affecting the ridesharing industry in the context of the COVID-19 pandemic, and they emphasize the importance of considering cultural context in understanding consumers’ intentions to engage in the sharing economy.

Determinants of academic achievement: How parents and teachers influence high school students' performance

This study explores the contribution of various drivers of attainment in secondary education in Portugal. We propose a model explaining the influence of students, teachers, and parents' traits on high school achievement, measured by the self-reported Math and Portuguese final grades of 220 students. Using PLS-SEM, we show that previous achievement predicts current achievement in both subjects; however, noteworthy differences were found. Portuguese grades are significantly better for students whose parents have post-secondary education and communicate higher expectations about their offspring's school careers. At the same time, Math achievement is influenced by students' perception of teachers' involvement but not by parents' expectations or education. Previous retention and receiving educational allowance impair Math achievement, but not Portuguese. Results and implications are discussed.

Understanding and predicting the determinants of blockchain technology adoption and SMEs' performance

Purpose

The success of SMEs' financial and market performance (MAP) depends on the firms' level of blockchain technology adoption (BCA) and identifying the crucial antecedents that influence SMEs' adoption. Therefore, this research attempts to develop an integrated model to understand and predict the determinants of BCA and its effect on SMEs' performance. The purpose of this paper is to address this issue.

Design/methodology/approach

The theoretical foundations are the technology–organization –environment (TOE) framework and the resource-based view (RBV) perspective. The authors distributed a survey to SMEs in South Africa and received 311 responses. The covariance-based structural equation modeling (CB-SEM) followed by the artificial neural network (ANN) technique was used for the data analysis.

Findings

The SEM results showed that SMEs' relative advantage, compatibility, top management support (TMS), organizational readiness (ORD), competitive pressures (COP), external support, regulations and legislation significantly influence SMEs' BCA. However, complexity negatively impacts SMEs' BCA. The analysis results also revealed that SMEs' BCA significantly influences the financial performance of the firms, followed by MAP. Furthermore, model determinants were input to an ANN modeling. The ANN results showed that TMS is the most critical predictor of SMEs' BCA, followed by ORD, COP, external support, and regulations and legislation.

Practical implications

The results provide valuable information for SMEs when maneuvering their adoption strategies in the scope of blockchain technology. Additionally, from the perspective of an emerging market, the study has successfully contributed the TOE framework and the RBV.

Originality/value

This study is the first work to explore the determinants of BCA in the context of SMEs from a developing country. This paper is also one pioneer in attempts to develop a causal and predictive statistical model for predicting the determinants of BCA in SMEs' performance.

A Unified Neural Network Framework for Extended Redundancy Analysis

Component-based approaches have been regarded as a tool for dimension reduction to predict outcomes from observed variables in regression applications. Extended redundancy analysis (ERA) is one such component-based approach which reduces predictors to components explaining maximum variance in the outcome variables. In many instances, ERA can be extended to capture nonlinearity and interactions between observed and components, but only by specifying a priori functional form. Meanwhile, machine learning methods like neural networks are typically used in a data-driven manner to capture nonlinearity without specifying the exact functional form. In this paper, we introduce a new method that integrates neural networks algorithms into the framework of ERA, called NN-ERA, to capture any non-specified nonlinear relationships among multiple sets of observed variables for constructing components. Simulations and empirical datasets are used to demonstrate the usefulness of NN-ERA. The conclusion is that in social science datasets with unstructured data, where we expect nonlinear relationships that cannot be specified a priori, NN-ERA with its neural network algorithmic structure can serve as a useful tool to specify and test models otherwise not captured by the conventional component-based models.

Brand orientation, employer branding and internal branding: Do they effect on recruitment during the COVID-19 pandemic?

Over the last twenty-five years, employer branding has been a subject of increasing attention among HRM scholars and practitioners. However, very limited research has explored the link between employer branding and HRM performance. To address the gap, in this study we explored how employer branding orientation impacted recruitment outcomes during the COVID-19 pandemic. In addition we combined both the brand orientation and internal branding concepts to better empirically explain their impact on building employer brand orientation. Based on cross-sectional data collected from 233 companies operating on Russian labor market, we found the positive relationships between brand orientation and employer branding orientation, between employer branding orientation and the employer branding programs, which are positively related to recruitment outcomes. However, the moderating effect of internal branding was negative. We also found moderating effects of COVID-19 in the relationship between employer branding orientation, employer branding programs, and recruitment outcomes.

Reviewer Resources: Confirmatory Factor Analysis

Confirmatory factor analyses (CFA) are widely used in the organizational literature. As a result, understanding how to properly conduct these analyses, report the results, and interpret their implications is critically important for advancing organizational research. The goal of this paper is to summarize the complexities of CFA models and, therefore, to provide a resource for journal reviewers and researchers who are using CFA in their research. The topics covered in this paper include the estimation process, power analyses, model fit, and model modifications, among other things. In addition, this paper concludes with a checklist that summarizes the key points that are discussed and can be used to evaluate future studies that incorporate CFA.

Role of corporate governance in quick response to Covid-19 to improve SMEs’ performance: evidence from an emerging market

This paper aims to evaluate the role of corporate governance on performance of the small and medium-sized enterprises by exploring the mediating role of social responsibility engagement and environmental responsibility engagement between corporate governance and firm performance in the context of an emerging market. The paper follows a quantitative approach. The study sample was composed of 495 responses covering top executives, managers, and experts. The Analysis of a moment structures (AMOS version 20) was used to analyze the small and medium-sized enterprises data in an emerging economy in Southeast Asia in the year 2021. Our findings revealed that corporate governance has a significant and positive relationship with firm performance, social responsibility engagement and environmental responsibility engagement. In addition, social responsibility engagement and environmental responsibility engagement are found to mediate the relationship between corporate governance and firm performance. To the best of our knowledge, this is the first research that explores the mediating role of social responsibility engagement and environmental responsibility engagement between corporate governance and firm performance for the small and medium-sized enterprises. This study has novel contributions by providing important insights into the effective corporate governance mechanism and how corporate governance contributes to improving firm performance towards sustainability through engaging in social and environmental responsibility. Additionally, its application to food the small and medium-sized enterprises in the current context of an emerging economy in Southeast Asia reinforces the originality of this study. This study contributions are of great interest to academics, experts, business practitioners, and policymakers.

The mechanism of anger and negative affectivity on the occurrence of deviant workplace behavior: An empirical evidence among Malaysian nurses in public hospitals

Background

Employees' work experience significantly impacts their cognition and workplace actions. Anger and negative affectivity are two personality traits that have been linked to workplace deviant behavior conduct.

Objective

This study aimed to empirically analyze the deviant workplace behavior and its antecedents among Malaysian nurses in public hospitals.

Methods

A cross-sectional design was employed in this study. The survey questionnaires were distributed proportionately to staff nurses in six government hospitals in 2020, with a total of 387 nurses selected using a simple random sampling. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for data analysis.

Results

Trait anger triggered deviant workplace behavior in Malaysian nurses, thus supporting the argument that the personality trait could increase deviant behavior (β = 0.245, p = 0.000). At the same time, there was no evidence that negative affectivity could influence deviant behavior in the workplace among nurses in selected public hospitals in Malaysia (β = 0.074, p = 0.064).

Conclusion

The Malaysian nurses had positive affectivity, related to positive emotions like happiness, work interest, and attentiveness. On the other hand, the nurses were suffering from high levels of emotional tiredness. Further research should highlight a deeper understanding of Malaysian nurses' work experiences and workplace stress affecting their physical and mental health.

Online accounting courses: digital loyalty for an inclusive and open society

Purpose

Online education can facilitate inclusive societal development. In emerging countries with low investment per capita in school and universities, it helps students overcome infrastructure constraints to continue their learning and reach their full potential, and it helps educational institutes to save costs and improve quality of learning. This study aims to develop and empirically evaluate a conceptual model for predicting digital loyalty (DL) among participants in online accounting courses, as a key lever to execute an inclusive societal development agenda and ensure sustainability of education in an emerging country.

Design/methodology/approach

The study used quantitative primary data collected from survey questionnaires administered to 167 respondents in India and employed partial least squares structural equation modelling (PLS SEM) to analyse the data.

Findings

We observed that perceived learning (PL) significantly mediated the relationship between learning performance (LP) and digital loyalty to an online accounting programme.

Research limitations/implications

Students’ attitudes and preferences have changed remarkably in recent years. Online education encourages participants to complete their courses, learn new and relevant skills, improve their quality of life and recommend online education to others. This facilitates an inclusive, open society with opportunities for all. The results of this study have certain implications. First, as a novel extension of Abrantes et al.’s (2007) work, the DL construct added a new key dimension to the model. Second, the use of PLS Predict introduced methodological rigour to measures such as R2 and blindfolding processes, improving the understanding of the PLS Predict algorithm’s application to prediction studies.

Practical implications

The study established PL as a mediating variable in the associations between LP and DL and between pedagogical affect (PA) and DL. These findings have practical implications for course design and execution programmes in educational institutes, especially those aiming to democratise education and ensure inclusivity. Online education service providers should focus on equipping students with updated, cross-functional and integrated skills.

Originality/value

Online education can foster an inclusive and open society by overcoming the twin limitations of geographical distance and infrastructure constraints resulting from scarce learning resources, especially in emerging markets, such as India. The study makes an original contribution by collecting participant data for online accounting courses in India to establish clearly the antecedents of DL. This study empirically demonstrates the role of LP as the most significant antecedent of PL and DL.

Algorithmic Modelling of Financial Conditions for Macro Predictive Purposes: Pilot Application to USA Data

Aggregate financial conditions indices (FCIs) are constructed to fulfil two aims: (i) The FCIs should resemble non-model-based composite indices in that their composition is adequately invariant for concatenation during regular updates; (ii) the concatenated FCIs should outperform financial variables conventionally used as leading indicators in macro models. Both aims are shown to be attainable once an algorithmic modelling route is adopted to combine leading indicator modelling with the principles of partial least-squares (PLS) modelling, supervised dimensionality reduction, and backward dynamic selection. Pilot results using US data confirm the traditional wisdom that financial imbalances are more likely to induce macro impacts than routine market volatilities. They also shed light on why the popular route of principal-component based factor analysis is ill-suited for the two aims.

Green service production and environmental performance in healthcare emergencies: role of big-data management and green HRM practices

Purpose

This study aims to examine the impact of big data management on green service production (GSP) and environmental performance (ENPr) while considering green HRM practices (GHRM) in healthcare emergencies.

Design/methodology/approach

The authors collected primary data from major healthcare organizations in India by surveying healthcare professionals. The data analysis through structural equation modelling (PLS-SEM) reveals several significant relationships to extricate the underlying dynamics.

Findings

Grounded in the theories of service production and natural resource-based view (NRBV), this study conceptualizes GSP with its three dimensions of green procurement (GP), green service design (GSD) and green service practices (GSPr). The study conducted in India's healthcare sector with a sample size limited to healthcare professionals serving in COVID-19 identifies the positive and significant impact of big data management on GSP and ENPr that organizations seek to deploy in such emergencies. The findings of the study explain the moderating effects of GHRM on GSP-ENPr relationships.

Research limitations/implications

The study was conducted in the healthcare sector in India, and its sample size was limited to healthcare professionals serving in COVID-19. The practical ramifications for healthcare administrators and policymakers are suggested, and future avenues of research are discussed.

Originality/value

This paper develops a holistic model of big data analytics, GP, GSD, GSPr, GHRM and ENPr. This study is a first step in investigating how big data management contributes to ENPr in an emergency and establishing the facets of GSP as a missing link in this relationship, which is currently void in the literature. This study contributes to the theory and fills the knowledge gap in this area.

Organisational networks, organisational learning, organisational adaptability and role clarity among humanitarian organisations during relief delivery

Purpose

Organisations involved in relief delivery tend to have cross-boundary mandates, which cause ambiguity of roles during delivery of relief services to the targeted victims. Having no clear role, specialisation affects service timeliness and increases resource duplication among the relief organisations. The objective of this study is to understand how organisational networks and organisational learning as complex adaptive system metaphors improve both organisational adaptability and role clarity in humanitarian logistics.

Design/methodology/approach

Using ordinary partial least squares regression through SmartPLS version 3.3.3, the authors tested the study hypotheses basing on survey data collected from 315 respondents who were selected randomly to complete a self-administered questionnaire from 101 humanitarian organisations. Common method bias (CMB) associated with surveys was minimised by implementing both procedural and post statistics methods.

Findings

The results indicate that organisational networks and organisational learning have a significant influence on organisational adaptability and role clarity. The results also show that organisational adaptability partially mediates in the relationship between organisational networks, organisational learning and role clarity.

Research limitations/implications

The major limitation of the study is that the authors have used cross-sectional data to test this research hypotheses. However, this was minimised following Guide and Ketokivi's (2015) recommendation on how to address the limitations of cross-sectional data or the use of longitudinal data that can address CMB and endogeneity problems.

Practical implications

Managers in humanitarian organisations can use the authors’ framework to understand, first, how complex adaptive system competence can be used to create organisational adaptability and, second, how organisational adaptability can help organisational networks and organisational learning in improving role clarity among humanitarian organisations by collaboratively working together.

Originality/value

This research contributes to the existing body of knowledge in humanitarian logistics and supply chain management by empirically testing the anecdotal and conceptual evidence. The findings may be useful to managers who are contemplating the use of organisational networks, organisational learning and organisational adaptability to improve role clarity in disaster relief-related activities.

The Interplay among Organisational Learning Culture, Agility, Growth, and Big Data Capabilities

This paper examines how an organisational learning culture impacts organisational agility by developing a model based on dynamic capabilities. The model treats agility as a dynamic capability and explains how an organisational learning culture (OLC) triggers a chain reaction through its influence on organisational agility (OA) that ultimately results in company growth. This paper also investigates the role of big data capabilities in transferring learning outcomes into dynamic capabilities. The model is tested through data collected from a survey of 138 Australian companies. Partial least squares structural equation modeling is adopted to empirically demonstrate how agility fully mediates the impact of the learning culture on growth. In addition, this paper further sheds light on the moderating role of big data competencies on the effects of OLC on OA. After presenting the results with implications to theory and practice, the paper ends with suggestions for future studies.

Understanding Customers' Continuance Intention

The purpose of this study is to understand the difference between Internet users' continuing use behavior in the context of digital inequality. Data were collected through a survey of Internet users in the Ivory Coast. The structural equation modeling technique was used to test the research hypothesis. This study showed empirically that concern over information and communication technologies (ICT) access as an explanation for digital inequality should be toned down. This research suggests emphasizing alternative factors to explain Internet sustained use intention by underprivileged individuals, including normative beliefs. The results will help internet service providers, governments, and international aid agencies to better understand users' behaviors or reactions to ICT available to them. This understanding provides a foundational platform upon which viable and effective information technology-enabled solutions and policies can be conceptualized and implemented. This study is one of the few that integrate three salient beliefs to differentiate ICT use continuance intention in the context of digital inequality.

Evasive entrepreneurship: Circumventing and exploiting institutional impediments for new profit opportunity in an emerging market

Evasive entrepreneurship (circumvention and exploitation of institutions by entrepreneurs) is a prevalent practice in many developing economies. Extant literature on the topic falls short of providing adequate theories to explain its triggers, mechanisms, and consequences. Leveraging extensive survey data from the World Bank, we used structural equation modeling to examine the relationship between evasive entrepreneurial behavior-tax evasion and bribery-and the relative payoff of such practices. Of the 2599 Nigerian entrepreneurs in our sample, the majority admitted to engaging in evasive entrepreneurship. The data suggest that institutional factors thought to constrain entrepreneurship in emerging markets are counter-intuitively perceived by founders as opportunities to earn large rents and improve firm performance. Our results emphasize the urgent need to eliminate institutional constraints that paradoxically enable the growth of evasive entrepreneurship in emerging economies. Our results also suggest that prevailing local conventions involving evasive behavior may motivate nascent entrepreneurs to imitate bribery and tax evasion, normalizing malfeasance as 'best practice.'

Psychological empowerment and job satisfaction of accountants: the mediating effect of task performance

Purpose

This study aims to ascertain the mediating effect of task performance (TP) on the linkage between the psychological empowerment (PE) and job satisfaction (JS) of professional accountants.

Design/methodology/approach

Primary data was collected through a questionnaire-based survey of 132 professional accountants who were the units of analysis for the study. These accountants were domiciled in 11 Indian cities and worked in both service and manufacturing firms. The data was analyzed using the partial least squares structural equation modeling method.

Findings

The study found that TP mediated the linkage between PE and JS, although, contrary to observations in developed economies, one of its sub-constructs – competence – displayed no such mediation capability. Counterintuitively, it was empirically observed that the accountants’ gender had no bearing on the mediating effect of TP.

Originality/value

The study makes three distinct contributions. First, it empirically confirms that the intrinsic motivation theory applies to accountants in the context of operations in emerging markets. Second, the paper contributes to the accounting behavioral literature by observing that competence, as a sub-dimension of the PE construct, does not significantly impact the JS level of accountants. Finally, the study also contributes to the development of sound business practices by confirming that gender differences do not impact the satisfaction levels of accountants in emerging markets.

Factors Associated with Distress in Caregivers of People with Personality Disorders

The present study investigated how stressors experienced by caregivers of people with personality disorders relate to each other and psychological distress, using the Stress Process Model (Pearlin et al. in Gerontologist 30(5):583-594, https://doi.org/10.1093/geront/30.5.583 , 1990). A community sample of caregivers (N = 106) completed an online survey. Partial Least Squares Path Modelling revealed that caregivers who were male, younger, or residing with their loved one were more likely to experience stressors. Salient primary stressors included the caregivers' worry and care-receivers' levels of instrumental demands and interpersonal problems. Important secondary stressors included strains in the caregivers' schedules, family relationships, and health, as well as reduced mastery and caregiving esteem. The model provided preliminary support for a pathway from demographic and relationship characteristics, through primary and secondary stressors, to heightened psychological distress. The present study clarifies the way caregiving stressors give rise to psychological distress; directions for future research are discussed.

Human Values and Work Engagement: The Mediating Role of Authenticity Among Workers in a Spanish Religious Organization

Nowadays religious organizations play a leading role in the third sector, contributing to maintaining the welfare state in a large number of countries in sectors such as health, education or social services, among others. These organizations provide a service to their users, aiming to transmit the predominant values in their mission statement and simultaneously promote both authenticity and work engagement in their employees. Indeed, the purpose of this article is to evaluate the link between human values and work engagement, as well as the mediating role of authenticity in this relationship. To this end, 938 workers of a Catholic religious organization, which constitutes a relatively unexplored context, is employed. To test the research model and hypotheses, this investigation uses PLS (Partial Least Squares). It covers two notable research gaps. First, the results confirm the direct links between human values, authenticity and work engagement within the context of religious organizations. Second, they provide evidence of the mediating role exercised by authenticity in the relationship between human values and work engagement.

The moderating influence of national culture on female and male entrepreneurs’ social network size and new venture growth

Purpose

The purpose of this paper is to disentangle individual-level gender differences and norm-based gender roles and stereotypes to provide a finer-grained understanding of why female and male entrepreneurs experience different growth returns from their social networks across different national cultures.

Design/methodology/approach

This research uses a survey of 637 (278 female and 359 male) entrepreneurs across four nations varying on relational culture (importance of social relationships) and gender egalitarianism (importance of gender equality or neutrality in social and economic roles).

Findings

The authors find evidence that male entrepreneurs in high relational cultures benefit the most in terms of growth in revenues from larger network size while women in low relational cultures benefit the least. In cultures with low gender egalitarianism, male entrepreneurs benefit more from their larger social networks than did the female entrepreneurs.

Practical implications

The study presents implications for female entrepreneurs’ behaviors to gain more benefits from their social networks, especially in cultural contexts where relationships are important or where there is equality in gender roles. In these contexts, they may need to develop other strategies and rely less on social networks to grow their ventures.

Social implications

This research suggests that female entrepreneurs still are disadvantaged in some societies. National policy may focus on developing more opportunities and providing more support to women entrepreneurs as a valuable contributor to economic growth of the nations.

Originality/value

The authors disentangle the effects of gender differences, norm-based gender stereotypes and networks on entrepreneurial outcomes.

The assessment of water erosion using Partial Least Squares-Path Modeling: A study in a legally protected area with environmental land use conflicts

Water erosion has historically been assessed by various methods, with the purpose to help reducing this phenomenon. However, application of models capable to handle complex relationships between large numbers of variables is still relatively scarce. The method of Partial Least Squares-Path Modeling (PLS-PM), used in this study, was able to expose complex causal paths between soil erosion and potentially related factors, namely "Surface Runoff", "Environmental Land Use Conflicts", "Soil Fertility" and "Relief Factors", within the Environmental Protection Area of Uberaba River Basin (EPA) located in Minas Gerais state, Brazil. In the context of PLS-PM, soil erosion (dependent) and the related factors (independent) are called latent variables and described by measured or estimated parameters. For example, the "Relief Factors" were described by measured drainage density and topographic slope. These were linked to the corresponding latent variables through weights and the later joined to each other through paths. During the PLS-PM runs, weights and paths were quantified and latent variables interpreted in regard to their importance for soil erosion and spatial incidence. The spatial incidence was used to prioritize areas for soil conservation. To test the model, data were obtained from soil samples (texture and fertility parameters) or digitally extracted from cartographic products (e.g., maps of soil loss, land use, brightness index, topographic slope, drainage density), at 37 sites within the EPA. The PLS-PM results revealed that 70.2% of soil erosion is predicted by the independent variables (R² = 0.702), and that "Soil Fertility" and "Environmental Land Use Conflicts" were the most influencing ones (β = -0.758 and β = 0.346, respectively). These variables can be managed by man, through implementation of effective soil conservation measures and respect for suitable land use. It is therefore urgent to act in these regard, considering the socioeconomic and environmental importance of the EPA.

Fusion Validity: Theory-Based Scale Assessment via Causal Structural Equation Modeling

Fusion validity assessments employ structural equation models to investigate whether an existing scale functions in accordance with theory. Fusion validity parallels criterion validity by depending on correlations with non-scale variables but differs from criterion validity because it requires at least one theorized effect of the scale, and because both the scale and scaled-items are included in the model. Fusion validity, like construct validity, will be most informative if the scale is embedded in as full a substantive context as theory permits. Appropriate scale functioning in a comprehensive theoretical context greatly enhances a scale's validity. Inappropriate scale functioning questions the scale but the scale's theoretical embedding encourages detailed diagnostic investigations potentially challenging specific items, the procedure used to calculate scale values, or aspects of the theory, but also possibly recommends incorporating additional items into the scale. The scaled items should have survived prior content and methodological assessments but the items may or may not reflect a common factor because items having diverse causal backgrounds can sometimes fuse to form a unidimensional entity. Though items reflecting a common cause can be assessed for fusion validity, we illustrate fusion validity in the more challenging context of a scale comprised of diverse items and embedded in a complicated theory. Specifically we consider the Leadership scale from the Alberta Context Tool with care aides working in Canadian long-term care homes.

An Assessment of Groundwater Contamination Risk with Radon Based on Clustering and Structural Models

There is currently some controversy in the scientific community regarding the efficiency of the water–rock interaction process in the contamination of radon in groundwater. In this study, some difficulties were found in the sampling phase. Many of the water collection points are used for human consumption. As such, some municipalities did not want to collaborate. When this natural contaminant is undetectable to the human sense and may cause pulmonary neoplasms in the long term, it is difficult to obtain collaboration from the municipalities concerned. To overcome this controversy, it is important to understand that geogenic, climatic, hydrological, and topographic features may contribute to the effective transfer of radon from rocks to groundwater. In brief, this new approach combines the radon transfer from the geological substrate to the groundwater circulation through hierarchic agglomerative clustering (HAC) and partial least squares-path modeling (PLS-PM) methods. The results show that some lithologies with higher radon production may not always contribute to noticeable groundwater contamination. In this group, the high-fracturing density confirms the recharge efficiency, and the physical-chemical properties of the hydraulic environment (electric conductivity) plays the main role of radon unavailability in the water intended for human consumption. Besides, the hydraulic turnover time of the springs can be considered an excellent radiological indicator in groundwater. In the absence of an anomalous radioactive source near the surface, it means that the high-turnover time of the springs leads to a low-radon concentration in the water. Besides linking high-risk areas with a short period required to free local flow discharges, this study exposes the virtues of a new perspective of a groundwater contamination risk modeling.

Modeling teachers’ quality of work life: a partial least square approach

Purpose

The purpose of this paper is to examine the factors affecting quality of work life (QWL) of teachers working in Higher Education Institutions.

Design/methodology/approach

A cross-sectional study was conducted by sampling 347 teaching faculty members through questionnaires.

Findings

Fair communication plays the strongest role and social networks have the weakest role in shaping the QWL in higher educational institutions (HEIs) of Pakistan. The relationship of social networks and QWL negates the Hofstede’s view of Pakistan society to a great extent.

Research limitations/implications

A cross-sectional data set is used for tapping a small sample size. The direct effects of four factors were considered for examination. The examination of indirect effects for the factors having weak effects is recommended.

Practical implications

Decision makers having intentions to improve QWL in HEIs must adopt procedural justice and effective communication channels; they should have high respect for employees and should help them to develop networks within the HEIs.

Social implications

Inter-relationships at workplace are hampering due to weak social networks.

Originality/value

The study is an important landmark in highlighting the factors that must be available for higher QWL of faculty members of public sector HEIs.

Muscle Androgen Receptor Content but Not Systemic Hormones Is Associated With Resistance Training-Induced Skeletal Muscle Hypertrophy in Healthy, Young Men

The factors that underpin heterogeneity in muscle hypertrophy following resistance exercise training (RET) remain largely unknown. We examined circulating hormones, intramuscular hormones, and intramuscular hormone-related variables in resistance-trained men before and after 12 weeks of RET. Backward elimination and principal component regression evaluated the statistical significance of proposed circulating anabolic hormones (e.g., testosterone, free testosterone, dehydroepiandrosterone, dihydrotestosterone, insulin-like growth factor-1, free insulin-like growth factor-1, luteinizing hormone, and growth hormone) and RET-induced changes in muscle mass (n = 49). Immunoblots and immunoassays were used to evaluate intramuscular free testosterone levels, dihydrotestosterone levels, 5α-reductase expression, and androgen receptor content in the highest- (HIR; n = 10) and lowest- (LOR; n = 10) responders to the 12 weeks of RET. No hormone measured before exercise, after exercise, pre-intervention, or post-intervention was consistently significant or consistently selected in the final model for the change in: type 1 cross sectional area (CSA), type 2 CSA, or fat- and bone-free mass (LBM). Principal component analysis did not result in large dimension reduction and principal component regression was no more effective than unadjusted regression analyses. No hormone measured in the blood or muscle was different between HIR and LOR. The steroidogenic enzyme 5α-reductase increased following RET in the HIR (P < 0.01) but not the LOR (P = 0.32). Androgen receptor content was unchanged with RET but was higher at all times in HIR. Unlike intramuscular free testosterone, dihydrotestosterone, or 5α-reductase, there was a linear relationship between androgen receptor content and change in LBM (P < 0.01), type 1 CSA (P < 0.05), and type 2 CSA (P < 0.01) both pre- and post-intervention. These results indicate that intramuscular androgen receptor content, but neither circulating nor intramuscular hormones (or the enzymes regulating their intramuscular production), influence skeletal muscle hypertrophy following RET in previously trained young men.

A partial least squares - Path modeling analysis for the understanding of biodiversity loss in rural and urban watersheds in Portugal

The main purpose of this study was to use Partial Least Squares - Path Modeling (PLS-PM) to quantify the contributions of natural and human-induced threats to biodiversity loss in rural and urban watersheds. The study area comprised the Sabor and Ave river basins, located in northern Portugal. The Sabor is rural and sparsely populated while the Ave is urbanized, industrialized and densely populated. Within PLS-PM, threats are called exogenous latent variables while the ultimate environmental consequence (biodiversity loss) is termed endogenous latent variable. Latent variables are concepts represented by numerical parameters called formative variables. The selected latent variables were given the names "pressures", "contamination" and "ecological integrity". The most important "pressures" were the wildfire risk, the percentage of urban area in sub-catchments, the diffuse emissions of livestock nitrogen (N) and agriculture/forest phosphorus (P), and the point source emissions of urban N, P and biochemical oxygen demand, as well as of industrial N. The latent variable called "contamination" was primarily represented by stream water concentrations of phosphate, suspended solids and dissolved oxygen. And finally, the "ecological integrity" was represented by the he North Invertebrate Portuguese Index. The results unequivocally showed that point source emissions in the Sabor (except industrial N) and stream water contamination in the Ave determine biodiversity loss. These contrasting influences suggest that Ave basin has evolved from a catchment where man once produced localized negative effects on stream ecological integrity (a condition still observed in the Sabor basin) to a catchment where the dense human occupation has covered the entire area with urban contaminant sources, somewhat generalizing the local effects. The attribution of local effects to biodiversity loss in the rural catchment and of regional effects in the urban catchment is confirmed by the results of a study covering the entire planet.

Relationships Among Knowledge Management, Organisational Innovativeness and Performance: Covariance-Based Versus Partial Least-Squares Structural Equation Modelling

The relationships among effective knowledge management (KM), organisational innovativeness (OI), market orientation (MO) and organisational performance (OP) have been explored in the literature. These constructs are generally analysed in pairs, such as the influence of KM on OI, or KM on OP, and other combinations, but the relationships among the full set of constructs in question are not fully understood yet. In the extant literature, the relationships among them are analysed for the most part with covariance-based structural equation modelling (CB-SEM). Partial least-squares (PLS) path modelling is a component-based approach to SEM that is not as widely used as CB-SEM, but it has the potential to allow increased flexibility in handling various modelling problems in comparison with CB models, particularly for predictive and exploratory purposes. This paper aims to verify whether the PLS method could confirm or reject the results of the more restrictive covariance-based method in modelling the relationships among KM, OI, MO and OP. The results indicate that both methods yielded convergent and discriminant validity for the constructs, displaying stability across model analysis and depuration. The PLS model revealed the influence of KM on MO, OI and OP. It also shows that OI is the main driving factor for OP. KM seems to have a direct effect on OP, which is greatly magnified when mediated by OI. The sample size, although borderline adequate for the CB method, was more than adequate for PLS, yielding excellent model stability.

Mediating and moderating influencers of firm performance

Purpose

The purpose of this paper is to conduct an exploratory study that will assist supply chain firms in the development of partner satisfaction, flexibility, and supply chain performance. The authors examine how the interaction of information exchange, partner interaction, knowledge sharing and flexibility as mediated through partner satisfaction effectuates firm performance. The goal of this research is to answer the supply chain managers’ need to better understand where to invest their time and effort to get improved firm performance.

Design/methodology/approach

The model was tested with panel data from 105 experienced, US-based supply chain managers. Structural equation modeling using partial least squares approach was utilized to conduct the analysis.

Findings

The results provide crucial evidence that simple information exchange among supply chain partners does not result in improvements in firm performance or partner satisfaction, but, when mediated through the flexibility construct, it does. Further, the use of integration tools has a moderating effect on the relationship between flexibility and firm performance. The results suggest that working closely with supply chain partners helps ensure improved relationship satisfaction, and can reduce issues that can impact firm performance.

Research limitations/implications

The empirical research presented requires additional validation though larger sample data from supply chain managers.

Practical implications

This study stresses on the importance of managers using information exchange, partner interaction, and knowledge sharing as a means of improving their firm’s indirect influence on firm performance through flexibility and integration tools.

Originality/value

This is one of the few studies in the supply chain literature that integrates flexibility as a mediator variable. Additionally, this study introduces the new construct of integration tools to the supply chain literature.

Establishment of Comprehensive Indicators in TCM Pectoral-qi Case Report Based on Experts Diagnosis and Self-test Technology

RATIONALE

To establish TCM Pectoral-qi comprehensive indicators and highlight the inner structure among different variables in an objective way, the article uses Partial Least Square Second-order Latent Variable Model (PLS-SLVM) and accomplishes 3 different comprehensive indicators based on both experts diagnosis and self-test data. SLVM includes a measurement model that defines the relationship between observed variables and latent variables and a structure model that imputes relationships between latent variables. The article focuses on PLS as the estimation method. Without normal distribution and independence assumptions, PLS uses objective weighting methods based on the data. Bootstrap method (B = 200) is used to calculate the mean value and standard errors of the PLS estimates. The article chooses the percentile interval to obtain the confidence interval of PLS parameters.

PATIENT CONCERNS

The patients were diagnosed by the means of experts diagnosis and self-test technology. On the one hand, the patients want to know the effect of self-test by wearing a kind of instrument. On the other hand, we want to establish TCM Pectoral-qi comprehensive indicators and highlight the inner structure among different variables in an objective way.

DIAGNOSES

The group of 59 subjects are the same no matter whether they were diagnosed through TCM Pectoral-qi Assessment Questionnaire of self-test technology.

INTERVENTIONS

The same group of 59 subjects keep wearing the instrument for hours and get the self-test data consequently.

OUTCOMES

As one of comprehensive indicator establishing methods, PLS-SLVM highlights the structure state among variables and improves the evaluation efficiency. Furthermore, it provides a new tool and method in TCM diseases prevention and health security.

LESSONS

As expected, PLS-SLVM is a useful tool due to its nonassumption of normal distribution and independence with consideration of correlation among different variables. Thus PLS-SLVM can be applied in ordinal data from assessment questionnaire and continuous data about physicochemical indexes for the same group of people. It displays that PLS-SLVM builds a connection between TCM experts diagnosis and the self-testing technology.

Bi-cultural dynamics for risk and protective factors for cardiometabolic health in an Alaska Native (Yup'ik) population

Alaska Native people experience disparities in mortality from heart disease and stroke. This work attempts to better understand the relationships between socioeconomic, behavioral, and cardiometabolic risk factors among Yup'ik people of southwestern Alaska, with a focus on the role of the socioeconomic, and cultural components. Using a cross-sectional sample of 486 Yup'ik adults, we fitted a Partial Least Squares Path Model (PLS-PM) to assess the associations between components, including demographic factors [age and gender], socioeconomic factors [education, economic status, Yup'ik culture, and Western culture], behavioral factors [diet, cigarette smoking and smokeless tobacco use, and physical activity], and cardiometabolic risk factors [adiposity, triglyceride-HDL and LDL lipids, glycemia, and blood pressure]. We found relatively mild associations of education and economic status with cardiometabolic risk factors, in contrast with studies in other populations. The socioeconomic factor and participation in Yup'ik culture had potentially protective associations with adiposity, triglyceride-HDL lipids, and blood pressure, whereas participation in Western culture had a protective association with blood pressure. We also found a moderating effect of participation in Western culture on the relationships between Yup'ik culture participation and both blood pressure and LDL lipids, indicating a potentially beneficial additional effect of bi-culturalism. Our results suggest that reinforcing protective effects of both Yup'ik and Western cultures could be useful for interventions aimed at reducing cardiometabolic health disparities.

Uso Pessoal das Tecnologias no Trabalho: Motivadores e Efeitos à Distração Profissional

Resumo Apesar dos inúmeros benefícios que as Tecnologias de Informação (TI) - proporcionam a seus usuários, os efeitos adversos da utilização indiscriminada dos dispositivos tecnológicos pessoais no ambiente de trabalho é um tema pouco explorado. Este estudo analisa os aspectos individuais motivadores do uso particular de Tecnologias de Informação no trabalho e a relação da Distração Digital como um componente significativo sobre a perda de atenção dos profissionais durante a execução de suas atividades. A pesquisa evidencia que os aspectos ligados à dependência tecnológica são as principais causas do Uso Pessoal das Tecnologias no ambiente de trabalho. Entre esses motivadores, a perda do Controle do Impulso de uso da TI é o fator mais significativo ao Uso Pessoal das Tecnologias em ambientes profissionais, comparada a outros fatores analisados. A pesquisa também revela que a Distração Digital provoca significativa perda de concentração dos profissionais e que a Utilização Pessoal da TI no ambiente de trabalho é reflexo direto da redução do Engajamento do profissional no seu trabalho. Além disso, o estudo revela que o uso particular das aplicações que promovem interação social não é subterfúgio dos profissionais que manifestaram fraco Suporte Social dos seus pares no local de atuação profissional.

Authenticity and Subjective Wellbeing within the Context of a Religious Organization

Although authenticity has a long history as a philosophical and psychological idea, this concept has received scarce attention in the business literature until very lately. Nevertheless, scholars belonging to a broad array of disciplines have pointed out the escalation in the individuals’ search for authenticity within developed societies. Hence, the purpose of this paper is to assess the link between authenticity and subjective wellbeing within the rarely explored context of faith-driven organizations, where the management of emotions attains a particular significance. Specifically, this study links authenticity with subjective wellbeing among the distinct groups that shape a large international Catholic organization. This study uses Partial Least Squares (PLS) to test our research model and hypotheses. This paper covers two noteworthy research gaps. On the one hand, it provides evidence of the relationship between authenticity and subjective wellbeing within the context of religious organizations. On the other hand, our results suggest that this relationship is not homogeneous among the distinct groups that shape the organization. Implications of the research are finally discussed.

Triggering Innovation Through Mergers and Acquisitions

In this article, we analyze how shared team and task mental models, developed prior to an acquisition, affect exploration and exploitation activities in the postacquisition phase, and how these effects are dependent on relative size. With a sample of 101 transactions of acquirers from the German-speaking part of Europe, we provide empirical evidence that both shared team and task mental models positively influence exploitation activities following an acquisition, whereby only shared team mental models (TMMs) are beneficial for exploration. We provide empirical evidence that shared mental models in terms of task and team are an important informal source for enhancing exploration and exploitation innovation activities. However, this source of informal coordination is contextual. Although the relationships on exploitation are stable, the beneficial effect of TMMs on exploration is sensitive and devitalized by an increasing relative size. Implications for further research and management practice are given.

Improving supply chain performance through industry standards use and community socialization

Purpose

The purpose of this paper is to examine how use of industry standards and community socialization contribute to the operational, strategic and environmental performances of supply chain partners.

Design/methodology/approach

Survey data were collected from 216 firms in China that have implemented RosettaNet standards. Structural equation modeling was used to test the hypotheses forming the research model.

Findings

The empirical analysis suggests that use of industry standards and community socialization is central to achieving greater supply chain performances. The results show that the use of industry standards and community socialization enhance inter-organizational knowledge sharing and trust, which eventually improve performances of supply chain partners.

Originality/value

The study makes several contributions to the literature. First, it highlights the importance of standards consortia, which not only develop and promote industry standards, but also improve community socialization. Second, the research examines how use of industry standards could influence the operational, strategic and environmental performances of supply chains, and thus fills the research gap in related literature. Third, this paper explores how industry standards can be used as boundary objects to span organizational boundaries and enable greater supply chain partnerships.

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

Antecedents and Consequences of Fairness Perceptions in Personnel Selection

Drawing on Gilliland’s selection fairness framework, we examined antecedents and behavioral effects of applicant procedural fairness perceptions before, during, and after a personnel selection procedure using a six-wave longitudinal research design. Results showed that both perceived post-test fairness and pre-feedback fairness perceptions are related to job offer acceptance and job performance after 18 months, but not to job performance after 36 months. Pre-test and post-test procedural fairness perceptions were mainly related to formal characteristics and interpersonal treatment, whereas pre-feedback fairness perceptions were related to formal characteristics and explanations. The impact of fairness attributes of formal characteristics and interpersonal treatment diminished over time, whereas attributes of explanation were only associated with pre-feedback fairness. Results are discussed in terms of theoretical implications for fairness research and for hiring organizations.