Big data technologies have a strong impact on different industries, starting from the last decade, which continues nowadays, with the tendency to become omnipresent. The financial sector, as most of the other sectors, concentrated their operating activities mostly on structured data investigation. However, with the support of big data technologies, information stored in diverse sources of semi-structured and unstructured data could be harvested. Recent research and practice indicate that such information can be interesting for the decision-making process. Questions about how and to what extent research on data mining in the financial sector has developed and which tools are used for these purposes remains largely unexplored. This study aims to answer three research questions: (i) What is the intellectual core of the field? (ii) Which techniques are used in the financial sector for textual mining, especially in the era of the Internet, big data, and social media? (iii) Which data sources are the most often used for text mining in the financial sector, and for which purposes? In order to answer these questions, a qualitative analysis of literature is carried out using a systematic literature review, citation and co-citation analysis.

Purpose: The purpose of this paper is to draw on dynamic capability view and contingency theory to clarify the nature of the effect of environmental turbulence on the relationships between firm’s both product and process innovations and business performance.Design/methodology/approach: The authors developed and empirically tested two structural models using structural equation modeling approach. The first model deals with both product and process innovations as the mediators between environmental turbulence and business performance. The second model considers the moderating effect of environmental turbulence between innovation and business performance.Findings: The findings show that environmental turbulence does not moderate the relationship between innovation and business performance. The authors have found a clear role of environmental turbulence in boosting innovation rather than moderating the relationship between innovation and performance.Research limitations/implications: The data set is a cross-section of heterogeneous firms regarding the industry.Practical implications: Managers should be aware of the importance of the innovation for the environmental turbulence and dynamism counteracting. The results imply a negative influence of environmental turbulence on business performance. However, with the innovation in the equation, this influence can be positive, because it boosts firms to innovate and though to achieve better business performance.Originality/value: It contributes the management and innovation research and practice through offering insights into the role of environmental turbulence in product innovation, process innovation as well as organizational business performance through comprehensive analysis of mediation and moderation effects between the observed constructs.

This study investigates the impact of perceived formal, informal and regulatory support on entrepreneurial intention. In addition, entrepreneurial capacity and fear of failure are analyzed as predictors of the propensity toward entrepreneurship. An empirical analysis of students in B&H finds that informal support perceived as support of family and friends exert a significant positive influence on entrepreneurial intentions. Fear of failure has a significant adverse impact on entrepreneurial intentions while entrepreneurial capacity enhances entrepreneurial intention. The negative relationship between the fear of failure and entrepreneurial intention is moderated by informal support. In other words, support by family and friends dampens the negative relationship between fear of failure and entrepreneurial intention. The findings were confronted with an ex-post literature review.

Background: Many studies have considered knowledge as the most important strategic resource for ensuring firm’s competitiveness. Accordingly, learning is an important concept for firms whether it is individual or organizational learning. Objectives: To provide empirical support to the impact of individual organizational learning dimensions on a firm’s knowledge management. Methods/Approach: The questionnaire survey approach is used for data collection and structural equation modeling for hypotheses testing. Besides, PROCESS procedure is employed to estimate confidence intervals of indirect effects in the model. Results: Organizational learning dimensions are antecedents of knowledge management capability. Shared values and openness influence directly and positively knowledge management capability. However, the same was not found to be the case for managerial commitment and dialogue. On the other hand, the results suggest that managerial commitment and dialog influence knowledge management capability indirectly over shared vision. Conclusions: While there has been an underlying assumption about the role of organizational learning for knowledge management, this study provides evidence on how organizational learning dimensions such as management commitment, shared vision, openness and experimentation, and dialog may be adjusted to facilitate and enhance knowledge management processes.

Enterprise resource planning (ERP) systems have become the most important tool for integrating businesses and achieving the “once only” principle in data entry, which contributes to resource efficiency, the enhancement of numerous organizational processes and capabilities, and, ultimately, improved business performance. In this study, we examine the ERP system’s quality as the company’s dynamic capability, contributing to business performance according to the dynamic capability perspective. Thus, we incorporate theoretical mechanisms into the model of the ERP system’s dimensions as a function of financial and non-financial organizational performance. We hypothesized that companies with a better ERP system, with all three dimensions, information, system, and services, will achieve better non-financial and financial performance. The model was tested using primary data collected using a survey method in the environment of a developing country, where the digital transformation of companies is still at a lower level. Structural equation modeling was employed for data analysis, and the results suggest a positive relationship between ERP system quality and both types of organizational business performance. The results indicate that not all dimensions have the same effect. The quality of information and service is particularly important for business performance until the system’s technical characteristics have no significant effect.