This study investigates the symmetric and asymmetric linkages within environmental sustainability proxied by ecological footprint (EFP), natural resources (NRR), renewable energy consumption (REC), urbanization (URB), human capital (HC), and government effectiveness (GE) in 27 African countries divided into two subgroups (ecological deficit countries and ecological reserve countries) over the period 1990 to 2018. The study employs the auto-regressive distributed lag (ARDL) model to investigate the symmetric (linear) effect and the nonlinear auto-regressive distributed lag (NARDL) model to study the asymmetric (nonlinear) effects of the variables on EFP. Results of ARDL show that a 1% increase in REC is projected to reduce ecological footprint by 0.17 and 0.2% in ecological deficit and ecological reserve countries. A 1% increase in NRR is estimated to increase ecological footprint by 0.02% in ecological deficit countries but has no impact on the environment in countries with ecological reserves. Similarly, a 1% rise in GE is estimated to increase EFP by 0.04% in Africa but has no impact on the environment in ecological deficit countries. NARDL estimations decomposed REC into positive (negative) shocks, which show that a 1% increase (decrease) in REC is projected to decrease EFP by 0.16% (0.13%) in countries with ecological reserves. Similarly, a positive (negative) shock in NRR is expected to decrease EFP in ecological reserve countries and increase EFP in ecological deficit countries. Results of the Wald tests prove the existence of long-run asymmetry among the variables. The findings indicate that renewable energy consumption enhances environmental quality, while economic growth and natural resource rents reduce environmental quality in Africa over the sampled period.

Based on prior research on the relationship between personality and safety behavior, we construct a moderated mediation model that tests the effects of each of the Big Five personality traits (openness, conscientiousness, agreeableness, extraversion, and neuroticism) on the safety behavior of gold miners in Ghana. The model included safety competency as a mediator between the five personality traits and safety behavior. Management commitment to safety was used as a moderator to test the strength of the mediation of safety competency. Data was collected from 344 individuals employed across six large-scale gold mining companies in Ghana using a questionnaire survey. Amos 26 was used to conduct confirmatory factor analysis. The hypotheses were tested using Hayes PROCESS macros models 4 and 7 on SPSS 26. Findings show that openness and extraversion have an insignificant direct influence on safety behavior. Neuroticism negatively affects safety behavior. In contrast, conscientiousness and agreeableness positively affect safety behavior. Mediation analysis revealed that safety competency partially mediates the relationships between (1) conscientiousness and safety behavior and (2) agreeableness and safety behavior. The relationship between extraversion and safety behavior is fully mediated by safety competency. Additionally, we discovered that management safety commitment has a significant conditional indirect effect (Index of moderated mediation = 0.168 95% CI = [0.122;0.222]) on the relationship between conscientiousness and safety behavior through safety competency. Management safety commitment also significantly moderated (Index of moderated mediation = 0.075 95% CI = [0.021;0.120]) the relationship between agreeableness and safety behavior through safety competency.

Process mining has piqued the interest of researchers and technology manufacturers. Process mining aims to extract information from event activities and their interdependencies from events recorded by some enterprise systems. An enterprise system’s transactions are labeled based on their information content, such as an activity that causes the occurrence of another, the timestamp between events, and the resource from which the transaction originated. This paper describes a novel process of parsing event-log activities based on information content (IC). The information content of attributes, especially activity names, which are used to describe the flow processes of enterprise systems, is grouped hierarchically as hypernyms and hyponyms in a subsume tree. The least common subsume (LCS) values of these activity names are calculated, and the corresponding relatedness values between them are obtained. These values are used to create a fuzzy causal matrix (FCM) for parsing the activities, from which a process mining algorithm is designed to mine the structural and semantic relationships among activities using an enhanced gray wolf optimizer and backpropagation algorithm. The proposed approach is resistant to noisy and incomplete event logs and can be used for process mining to reflect the structure and behavior of event logs.