Purpose: This research aimed to explore whether different project management approaches (traditional, agile or hybrid) differentiate concerning their impact on project success, taking project success as multidimensional phenomena. In addition to this, the authors wanted to explore if specific project characteristics moderate these effects.Design/methodology/approach: The authors empirically addressed these on a sample of 227 project professionals worldwide. The exploratory factor analysis (EFA) of project success dimensions was done to validate these factors' constitution concerning their manifest variables. The K-means cluster method was used to distinguish respondents' profiles among agile, hybrid and traditional project management approaches. To test the significance among research groups, the research hypotheses were tested with ANOVA tests.Findings: The authors evidenced that the agile approach has a more significant positive impact concerning the two out of five dimensions of project success, under analysis in this research (impact on the team and preparing for the future), over the traditional approach.Practical implications: The research is relevant for project management practitioners to tailor the success-oriented project management approach and for academics to develop project management contingency theory.Originality/value: The authors constructed a research framework to test the impact and effectiveness of different project management approaches (traditional, agile, hybrid) on the dimensions of project success in different contextual conditions (organization industry, project type, novelty, technology, complexity and pace). The paper's main contribution is to expand data on the impact of these approaches on project success and compare them with relevant results and findings of previous research.

Customer churn is a problem virtually all companies face, and the ability to predict it reliably can be a cornerstone for successful retention campaigns. In this study, we propose an approach to customer churn prediction in non-contractual B2B settings that relies exclusively on invoice-level data for feature engineering and uses multi-slicing to maximally utilize available data. We cast churn as a binary classification problem and assess the ability of three established classifiers to predict it when using different churn definitions. We also compare classifier performance when different amounts of historical data are used for feature engineering. The results indicate that robust models for different churn definitions can be derived by using invoice-level data alone and that using more historical data for creating some of the features tends to lead to better performing models for some classifiers. We also confirm that the multi-slicing approach to dataset creation yields better performing models compared to the traditionally used single-slicing approach.

Manufacturing firms engage in various innovation activities to achieve a sustainable competitive advantage. Although technological innovation is considered one of the key performance drivers, organizational innovation has become increasingly prominent. This study analyzes the relationship between organizational and technological innovation and examines their effect on firm performance in the manufacturing context. The empirical evidence is based on the European Manufacturing Survey (EMS)—Serbian data set gathered in 2018. Hypotheses on the relationship between organizational and technological innovations and firm performance are tested by structural equation modeling using data from 240 Serbian manufacturing firms. The results have shown that technological concepts strongly mediate the impact of organizational factors on firm performance (return on sales—ROS). Moreover, it could be said that, in contrast to the individual approach, to foster a ROS, a synergic effect of organizational and technological concepts is needed, implying the need for an integrative perspective in the process of innovation.

The pandemic of the Coronavirus 19 disease (COVID-19) has had significant impact on healthcare systems worldwide. The present study aims to investigate the service providers’ quality dimensions in public sector hospitals in the Republic of Serbia during the COVID-19 pandemic and to propose a sustainable model for healthcare improvement. The study was conducted from September 2021 to December 2021. A modified SERPERF quality measurement questionnaire was distributed to healthcare workers in nine secondary care public hospitals of the Serbian Autonomous Province of Vojvodina (APV). Six hundred one questionnaires were found to be complete in all aspects and compared to 528 questionnaires from the database of the Provincial Secretariat for Health Care obtained from healthcare workers before the COVID-19 outbreak. The present study suggests that supportive measures during the COVID-19 pandemic are effective and, from the providers’ perception, increase healthcare quality. Continual investment in healthcare would provide sustainable development of healthcare quality in the future, regardless of the pandemic conditions.