This paper aims to appraise the influence of strategic control tactics on financial performance. The goal is to examine the mediating effect of the resource allocation process on the relationship between financial performance and five strategic control tactics. A quantitative hypothetico-deductive methodology was used in this study. A basic random sample of the Ministry of Finance–North Lebanon’s workforce was used to conduct an electronic questionnaire. A total of 232 valid responses were collected. Two statistical analysis methods, an exploratory and a confirmatory factor analysis, were implemented. The sample adequacy was confirmed by a KMO value higher than 0.7 before instigating the principal component analysis (PCA). The latter kept more than 60% of the initial data while structuring the data. The findings of the KMO and Barlett tests supported the adoption of PCA. The correlation matrix confirmed a statistically significant relationship between resource allocation, financial success, and strategic control techniques. The structural equation model (SEM) validated the linear correlations and statistical significance between the variables. The hypotheses were examined. Results confirmed that the model satisfactorily fits the data. The RMSEA is below the 0.05 threshold. The incremental indices are higher than 0.9. Results confirmed that the resource allocation process mediates the relationship between preventive control, operational control, special alert control, implementation control, and financial performance.

The massive development of technology has affected commerce and given rise to e-commerce and online shopping. Nowadays, consumers prioritize e-shopping over the brick and motor stores due to numerous benefits, including time and transport convenience. However, this progressive upsurge in online payment increases the number of credit card frauds. Therefore, defending against fraudsters’ activity is obligatory and can be achieved by securing credit card transactions. The objective of this paper is to build a model for credit card fraud detection using Machine learning techniques. An innovative approach to credit card fraud detection grounded on machine learning is proposed in this study. Machine learning (ML) is an artificial intelligence subfield comprising learning techniques from experience and completing tasks without being explicitly programmed. Three ML techniques have been used: Support vector machine, logistic regression, Random Forest, and Artificial Neural network. First, the most significant features that affect the type of transaction (fraud or not fraud) have been selected. After that, the ML model was applied. The performance of the proposed approach is tested using a confusion matrix, recall, precision, f-measure, and accuracy. The proposed method is tested using accurate data that consists of 284807 transactions. The result shows the efficiency of the proposed approach.

Changes in consumer behavior are influenced by green marketing and brand equity dimensions. Green marketing places high concerns on consumers’ environmental attitudes as a determinant of purchases and word of mouth. Green marketing increases brand awareness, fosters consumer loyalty and enhances reputation. The study aims to assess the influence of green marketing on consumers’ word of mouth through the mediating effect of brand equity dimensions. This descriptive causal research establishes a cause-and-effect relationship between variables, employing a quantitative research method. The questionnaire was deployed to collect the data and was pre-tested using a pilot test. 495 Lebanese consumers were included in the sample, which was collected using the convenience sampling technique. The results validated that green marketing reinforces consumers’ word of mouth (β = 0.663). It has a strong influence on brand equity (β = 0.899), brand loyalty (β = 0.772), brand trust (β = 0.663) and perceived quality (β = 0.353). The results corroborated that brand trust has the strongest mediating in this study (SE: 0.950; CR: 6.602; p < 0.01). Brand loyalty, while not a significant mediator in this relationship (SE: 0.012, CR: 0.872, p: 0.383 > 0.005), still plays a crucial role in brand management. This study concludes that giving brands a voice will appeal to the target audience and keep them committed. It highlighted the need for managers to review their loyalty strategies.

AI is an irreplaceable human resources technological tool in the era of new technologies. AI allows recruiters to face tense talent shortages and resignation peril. AI benefits include talent identification, working time optimization, productivity elevation, and empowerment. Machine learning and profound learning advances imply faster processing speeds for applications and efficient solutions endorsed by human-artificial intelligence collaboration. Artificial intelligence experts in artificial intelligence concluded that AI will never replace employees but will act as an intelligent assistant supporting them to attain the organization's mission. Therefore, the biggest challenge for AI adoption is not technical but human. Innovative technologies depend on experts to train employees to use these intelligent machinery and systems intelligently. AI and talented workforces are partners in supporting the human resources transformation. Ultimately, employees gain in productivity and use their expertise for strategic decisions.

This paper aims to assess the influence of emotional intelligence on organizational commitment. A quantitative survey was conducted among the academic staff of Lebanese universities to reach this objective. This research paper is an explanatory, descriptive, and confirmatory study. This cross-sectional study is based on a quantitative method to examine the validity of the theory or model. This research favors the deductive approach. This approach enables the deduction of a general conclusion from hypotheses. The structured questionnaire is constructed on the theoretical constructs of the mixed approach of the Goleman model, evaluating the following six components: self-awareness, self-control, internal motivation, empathy, leadership skills, and interpersonal relationship management. Empirical testing incorporates the plurality of causes and effects of interaction in this explanatory, descriptive research. Universities confront a lack of employee commitment. Emotional appreciation drives commitment to the organization. E.I. denotes the aptitude to detect, categorize, and use feelings to smooth rational decisions. The study verified that E.I. components significantly and positively influence organizational commitment, with internal motivation having the highest influence in Lebanese universities. Soft skills are essential abilities. Decision-makers and managers of Lebanese universities, conscious and attentive to the influence of employees' emotions, should integrate emotional intelligence into their managerial practices. To build and maintain organizational commitment, displaying appropriate emotions, interpersonal relationships, and communication are compulsory.