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This research aims to understand the smartphone security behavior using protection motivation theory (PMT) and tests the current PMT model employing statistical and predictive analysis using machine learning (ML) algorithms.

This study employs a total of 241 questionnaire-based responses in a nonmandated security setting and uses multimethod approach. The research model includes both security intention and behavior making use of a valid smartphone security behavior scale. Structural equation modeling (SEM) – explanatory analysis was used in understanding the relationships. ML algorithms were employed to predict the accuracy of the PMT model in an experimental evaluation.

The results revealed that the threat-appraisal element of the PMT did not have any influence on the intention to secure smartphone while the response efficacy had a role in explaining the smartphone security intention and behavior. The ML predictive analysis showed that the protection motivation elements were able to predict smartphone security intention and behavior with an accuracy of 73%.

The findings imply that the response efficacy of the individuals be improved by cybersecurity training programs in order to enhance the protection motivation. Researchers can test other PMT models, including fear appeals to improve the predictive accuracy.

This study is the first study that makes use of theory-driven SEM analysis and data-driven ML analysis to bridge the gap between smartphone security’s theory and practice.

Construction activities generate overwhelming waste that is typically disposed of in landfills, which has significant environmental consequences and hinders national progress. However, with the appropriate competencies, there is an opportunity to identify construction activities that produce recyclable materials, offering a path to a sustainable future. This study aims to assess the competencies for identifying construction activities that produce recyclable materials. To attain that aim, the study seeks to identify the key competencies and assess the index level of the competencies.

A systematic literature review was conducted, and 20 competencies were identified and categorized into knowledge, skills, and abilities. A questionnaire survey was developed based on the competencies and completed by 101 individuals. The collected data were analyzed using normalized mean analysis, confirmatory factor analysis, and fuzzy synthetic evaluation (FSE).

The results revealed that the key competencies are problem-solving skills, communication skills, skills in providing vocational training, and knowledge of the environmental impacts of construction activities. The FSE ranks the constructs in order of skills, knowledge, and abilities. Also, the FSE illustrated that the overall index level is inclined to be important.

This study leads to saving natural resources, using raw materials efficiently, protecting from environmental pollution, and mitigating resource depletion by providing the index level of the competencies.

The findings can guide professionals in effective waste management, policymakers in creating new policies and regulations, and researchers in compiling a list of competencies for identifying construction activities that produce recyclable materials.

China–Pakistan Economic Corridor (CPEC) is a framework of regional connectivity in which employees have to work in a cross-cultural environment. This study has extended the leader-member exchange theory by investigating the mediating role of employee commitment (EC) between the relationship of leader-member exchange (LMX) and employee's work-related behaviors.

PLS-SEM technique was used to test the model by utilizing a multi-wave/two-source data collected from employees and their supervisors (n = 500) working in different energy projects of CPEC.

According to the results/findings, LMX has a significant positive impact on employee commitment, employee performance (EP) and open-minded discussions, but insignificant impact on innovative work behaviour (IWB). Mediating role of employee commitment was significant between the relationship of LMX with EP and open-minded discussions, but insignificant with the IWB.

The study contributes empirical evidence to understanding the leader-member exchange relationship among Chinese managers and Pakistani workers. It also contributes to the LMX theory literature by investigating the effect of LMX on followers' outcomes (employee performance, IWB, open-minded discussions) through employee commitment.

This study aims to differentiate crime-related characteristics (such as the number of cases filed against current convictions and criminal history) based on the criminal thinking prevailing among convicts. However, because of the low reliability of subscales and poor structural validity of indigenous and translated versions of international instruments, a new instrument criminal attitude measure (CAM) was extracted to measure criminal thinking patterns among convicts incarcerated in central prisons of Punjab.

A cross-sectional research design was used. Data was collected from 1,949 male convicts (extracting mutually exclusive data from 649 respondents for EFA and 1,300 respondents for confirmatory factor analysis [CFA]). Both data samples were collected from convicts incarcerated in the nine (all) central jails of Punjab, Pakistan.

The results of this study showed poor model fit for both the indigenous criminal thinking scale and the translated version of criminogenic cognition scale. CAM was extracted through principal component analysis and proposed as a 15-item questionnaire with five factors extracted through varimax rotation. Those five factors are power orientation, mollification, entitlement, mistrust toward authorities and short-term orientation. The results of CFA for CAM confirmed the proposed five-factor structure for the construct. Findings based on MANOVA further found that CAM differentiates between the thinking patterns of recidivists, convicts with multiple charges filed against them in current convictions and convicts with a familial criminal record. The findings of this study showed that CAM is a practical, valid and reliable instrument for measuring criminal thinking among convicts.

In this study, using the survey method was inevitable because of the restrictions imposed by the granted permission. However, this time duration was extended because of the courtesy of the Superintendent and Deputy Superintendent of each jail. This study is focused on a male sample only, and the findings cannot be generalized to females. The phenomena proposed (based on large data sets) in this study can further be elaborated using qualitative research designs and methods (using a small sample with an in-depth study). So, it is also suggested to test this new instrument on a comparative study between prisoners and non-prisoners to explore whether scale can differentiate between these two groups.

A short-scale and easy-to-administer instrument was developed for assessing major criminogenic needs among convicts for prison management, i.e. assigning barracks, allocating treatment and also detecting changes in attitude after imprisonment.

To the best of the authors’ knowledge, this study is the first study to explore and validate the construct of criminal attitudes among convicts using both the EFA and CFA. A small and valid instrument facilitates the measurement of criminogenic needs among prisoners. Data was collected from all central jails in Punjab. This study explored comparatively less researched crime characteristics in a relatively large sample.

This study aims to explore the association among financial resources, renewable energy, environmental degradation and technological innovation in BRICS economies.

To estimate the long-run impacts between these variables, the AMG method of estimation, which incorporates cross-sectional reliance and slope homogeneity, is adopted in this research.

According to the empirical findings, the long-run coefficients of environmental degradation and technological innovation show a statistically significant and negative impact on renewable sources of energy. Furthermore, a 1% increase in environmental degradation reduces 0.32% of renewable sources of energy in BRICS economies. Whereas only the coefficient of GDP shows a positive and statistically significant impact on renewable sources of energy, which demonstrates that a 1% increase in economic growth causes a 0.02% incline in renewable sources of energy. Therefore, strong policy recommendations are provided to encourage green energy utilization in these economies.

The majority of the participating nations have inexpensive labor and an abundance of resources from nature, which strengthens their appeal. Given that population growth is still quite conservative, this presents a chance for GDP per capita to expand significantly.

This study aims to investigate the influence of green human resource management (Green HRM) on employee ecological behaviour (EEB) using the mediating role of green commitment.

Data were gathered using convenience sampling by surveying 308 academicians in five public research universities across Malaysia. Partial least squares structural equation modelling (PLS-SEM) tested the hypothesised model.

The results offered support for the hypotheses. Green HRM was related positively to EEB, and Green HRM influenced EEB indirectly via green commitment.

This study has significant implications for policymaking regarding higher education institutions that maintain an eco-friendly environment in Malaysia. The study offers guidelines to decision makers for enhancing EEB and environmental commitment in the workplace.

This study contributes to the current literature on green behaviour and Green HRM by examining these relationships and testing the mediation effect of green commitment from the developing economy of Malaysia. It also offers guidelines for policymakers and HR practitioners to promote environmental friendliness at work and create an environmentally friendly organisational culture.

Despite the vast potential of mobile phone use, grape smallholder farmers’ satisfaction with mobile phone use has attracted insufficient attention among scholars in Tanzania. The study examined factors influencing satisfaction with mobile phone use for accessing agricultural marketing information.

The study used a cross-sectional research design and a mixed research method. Structured questionnaire and focus group discussions were used to collect primary data from 400 sampled grape smallholder farmers. Data were analysed inferentially involving two-way analysis of variance, ordinal logistic regression and thematic analysis.

The findings indicate a statistically significant disparity in grape smallholder farmers’ satisfaction across different types of agricultural marketing information. Grape smallholder farmers exhibited higher satisfaction levels concerning information on selling time compared to all other types of agricultural marketing information (price, buyers, quality and quantity). Factors influencing grape smallholder farmers’ satisfaction with mobile phone use were related to perceived usefulness, ease of use, experience and cost.

This study contributes to scientific knowledge by providing actionable insights for formulating unique strategies for smallholder farmers’ satisfaction with agricultural marketing information.