Social media interactivity creates consumer’s space of information seeking-sharing where its intensity could produce knowledge, creates new values and changes behavior. The aim of this study is to exploratory investigate the dual role of Generation Z’s information seeking-sharing behavior within green context through the interactive space of social media as a resource for the development of social media marketing strategy. The research employs mixed-method approach of qualitative-explorative data mining, quantitative cross-tabulation Chi-Square test, and integration. Two findings of this research are elaborated. First, consumer’s space of information-seeking leads to the process of green awareness rationalization, i.e., how environment-oriented actions can be rationalized. Second, consumer’s space of information-sharing leads to green social values, i.e., How environment-oriented actions can be socially recognized. The marketing implications of these two findings are business’ efforts to develop green-oriented strategic mindset through space of social media marketing “customer engagement” where the dual role of information seeking-sharing within green context is facilitated.

The management of Mediterranean mountains need to know whether or not the flora is adapted to respond to fire and, if so, through what mechanisms. Serpentine outcrops constitute particular ecosystems in the Mediterranean Basin, and plants need to make an additional adaptive effort. The objective of this study is to know the response to fire of the main members of the group of serpentine plants, which habit the Spanish Mediterranean ultramafic mountain, to help in their management. For this purpose, monitoring plots were established on a burned ultramafic outcrop, which was affected by fire in August 2012.They were located in the Mediterranean south of the Iberian Peninsula, Andalusia region. The dominant vegetation of this serpentine ecosystem had been studied previously to fire; it was a shrubland composed of endemic serpentinophytes (small shrubs and perennial herbs) included in Digitali laciniatae-Halimietum atriplicifolii plant association (Cisto-Lavanduletea class) in an opened pine forest. The post-fire response of the plants was studied in the stablished burned plots by field works through permanent 200 x 10 m transect methods, consisting on checking whether they were resprouters, seeders, both of them or if they showed no survival response. Additional information about fire related functional traits is provided for the studied taxa from other studies. Of the total of plants studied (23 taxa), 74% acted as resprouters, 30% as seeders, some of which also had the capacity to resprout (13%), and only 9% of the plants did not show any survival strategy. The presence of a resprouting burl was not high (17%), although serpentine small shrubs such as Bupleurum acutifolium and the generalist Teucrium haenseleri had this kind of organ. The herbaceous taxa Sanguisorba verrucosa, Galium boissieranum and Linum carratracense were seen to be resprouters and seeders. The serpentine obligated Ni-accumulator, Alyssum serpyllifolium subsp. malacitanum, did not show any survival strategy in the face of fire and therefore their populations need monitoring after fires. In the studied ecosystems no species had traits that would protect the aerial part of the plant against fire, although most of the species are capable of post-fire generation by below ground buds. Our results show that the ecosystem studied, composed of taxa with a high degree of endemism and some of them threatened, is predominantly adapted to survival after a fire, although their response capacity may be decreased by environmental factors.

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.

Personality traits refer to enduring patterns of emotions, behaviors, and thoughts that shape an individual’s distinct character, influencing how they perceive and engage with their environment. This quantitative study aims to underscore the influence of personal factors and the role of educational institutions in mapping sustainable green entrepreneurial intentions among university students in Saudia Arabia. To examine the impact of personality traits and entrepreneurship education on students’ green initiatives, the research employs a quantitative research method, collecting data through a structured questionnaire survey from 494 participants who enrolled in the entrepreneurship education at King Faisal University. Structural equation modeling via SmartPLS 3 is employed for data analysis. The study reveals significant associations between the need for achievement, proactiveness, risk-aversion, self-efficacy, and entrepreneurship education with green entrepreneurial intentions. Our research findings demonstrate that the inclusion of entrepreneurship education in the curriculum has a noteworthy and favorable influence on the intention to engage in green entrepreneurship (β = −0.105, t = 3.270, p < 0.001). Additionally, it is worth noting that the desire for achievement remains significantly associated with the intention to engage in green entrepreneurship (β = 0.120, t = 3.588, p < 0.000). Furthermore, the proactive behavior of individuals has a positive and constructive impact on the intention to engage in green entrepreneurship (β = 0.207, t = 4.272, p < 0.000). Similarly, the inclination to avoid risk is found to have a beneficial and significant influence on the intention to engage in green entrepreneurship (β = 0.336, t = 4.594, p < 0.000). Lastly, it is worth highlighting that individuals’ belief in their own abilities, referred to as self-efficacy, is positively and significantly linked to the intention to engage in green entrepreneurship (β = 0.182, t = 2.610, p < 0.009). The research carries social, economic, and academic implications by emphasizing the positive contribution of green entrepreneurs to the future. Practical recommendations for policymakers and decision-makers are provided.