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Rising inflation in recent years has caused financial distress and many problems for companies. Most of these problems are affected by life cycle stages. One way out of these problems is to increase corporate social responsibility (CSR) performance. Therefore, our aim in this study is to investigate the effect of CSR performance on financial distress over the life cycle of the company for a period of 10 years. Data collection was done through the website of the Tehran Stock Exchange and related software for a sample of 112 companies during the period 2009 to 2019. The mathematical method (directional distance function) is used to evaluate the CSR performance, and the models of Berger et al., Almida, Campello, and Altman are used to measure financial distress. The research hypotheses are tested using panel data and fixed effects by multivariate regression statistical method. The results show that CSR performance alone does not affect financial distress. The combination of CSR and life cycle in the growth and maturity phases has a significant and negative effect on financial distress. The CSR performance and life cycle together reduce financial distress. The combination of CSR performance and life cycle in the recession phase has a positive and significant effect on financial distress and in the fall phase, does not affect it. Given that companies compete more in the phase of growth and maturity than other phases of the life cycle, they also pay more attention to CSR. Therefore, according to these results, it can be concluded that the life cycle of the company and the CSR performance together, reduce financial distress.

The impact of personal judgment on the assessment of an individual’s financial situation has been drastically reduced through the development of credit scoring. The systems are capable of deciding based on an applicant’s total score which is a combination of several factors and indicators. Over the past few decades, credit scoring has been considered an essential tool for evaluation in various institutions and has also been able to transform the industry as a whole. Most of the research conducted in the field has taken into account traditional credit scoring, but considering the ever-evolving technological world that we live in and the increasing emergence of new social media networks, such research has now become obsolete. Such technological advancements have not only paved the way for far more sophisticated credit scoring systems but also essentially rendered the previous generations useless. It should be noted that credit scoring and its features have widely been discussed across the globe but, considering the various aspects and models that have to be taken into account, no one best method has been designed or suggested for it so far. This study shows that social media channels tend to perform relatively well in predicting stock market trends when the overall index is growing positively. The research also illustrates that a higher number of days of activity and a large number of signals released do not necessarily mean that the channels can or have credited their offered stock return on a one-month time frame. The methodology used is "CRISP-DM," which consists of six steps. The main variables include social and financial variables that are examined for six months. In the research, we seek to identify, analyze and categorize active telegram channels in stock signals using the data mining model and the RFM method. The k-means algorithm is selected for this category. Then, in each cluster, the importance of social variables and the performance of the channels are extracted by the EXTRATREECLASSIFIER algorithm, and channel performance is measured by considering the changes in the total index.

Competitive advantages play a unique role in organizations' successes or failures because of customers' very speedy accessibility to suppliers and manufacturers. Indeed, this is competitive advantages which can make firms and organizations survive and grow in today's increasing competitive field attaining by creating and or improving their capabilities. The main goal of the study is to design a grounded theory model extracted from the transnational capabilities, but this required to explore the transnational capabilities aiming for the international markets entry. The statistical population of this qualitative research included experts and managers working in the steel pipe manufacturing companies of Iranian gas and oil industry. The data collected via interviews. The validity assured by counseling with the elites and university professors and the reliability verified by the Delphi technique. The findings revealed 496 open, 44 axial and 9 selective codes including: 1) Marketing, 2) Managerial, 3) Human Resources, 4) Financial, 5) Manufacturing, 6) Quality & Standards, 7) Research & Development 8) Logistics and 9) Interactions and counseling with the government. Finally, a new model extracted and represented from analysis of the axial coding process of the grounded theory. The model precisely clarified relationships among the components including casual conditions, context, actions/interactions (strategies), intervening conditions and consequences. Recognition of the relationships of the components will help better understanding of the capabilities. This will lead to attain the competitive advantages needed for successful entry into the international markets.