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Open innovation (OI), by now one of the major concepts for the analysis of innovation, is seen as a methodology for collaboratively designing and implementing solutions by engaging stakeholders in an iterative and inclusive service design process. This paper aims to empirically investigate OI capacities, defined as a cooperative, knowledge-sharing innovation ecosystem, and to explore how it can lead to improved performance of firms in Central and Eastern European (CEE) and Southeastern European (SEE) countries.

The study builds on the World Bank/European Bank for Reconstruction and Development (EBRD’s) Business Environment Enterprise Performance Survey (BEEPS) dataset for 2009, 2013 and 2019. Primarily, the research model was estimated using log-transformed ordinary least squares (OLS). Taking into consideration that this method might produce substantial bias, yielding misleading inferences, this study is fitting Poisson pseudo maximum likelihood estimators with robust standard errors and instrumental variable/generalized method of moments estimation (IV/GMM) approach for comparative results. Secondarily, the research model was tested using structural equation modelling (SEM) to investigate the relationship between five OI capacities and firm performance.

The findings indicate that there is a significant positive relationship between most OI capacities and firm performance, except for innovation, which did not show a statistically significant relationship with firm performance. Specifically, research and development (R&D), knowledge and coopetition are statistically significant and positively associated with firm performance, whereas transformation is statistically significant but negatively associated with firm performance. The IV/GMM estimations’ findings support the view that the firm performance is significantly affected by OI capacities, together with some control variables such as size, age, foreign ownership and year dummy to have a significant impact on firm performance.

This paper fills an identified gap in the literature by investigating the impact of OI on firm performance executed in the specific CEE and SEE country context.

Lack of appropriate student support and drawbacks in academic progression signify the importance of enhancing assessment and feedback in higher education (HE). Although assessment and feedback are significant in HE, minimal empirical research holistically explores the best practices. This study aims to address the niche and develop a decisive guideline for enhancing assessment setting and feedback provision within HE curricula.

A systematic approach was taken to obtain data for the study: a literature review underpinning the thematic content analysis of study documents, followed by semi-structured interviews. Document analysis contained mid-module reviews/student feedback; rubrics used in assessment; and formative/summative feedback provided for the graded work. Documental analysis informed the key attributes of the semi-structured interview. Interpretive structural modelling (ISM) analysis identified the influence and reliance of each driver.

This study revealed 15 drivers – 4 fundamental, 6 significant and 5 important – for enhancing assessment and feedback. The level partitioning from the ISM analysis established that all assessment and feedback needs to be underpinned by the university policy and fed into the assessment regime and marking scheme. This study identified that National Student Survey results were significantly improved due to implementing said drivers compared with the national and sector benchmarks.

The developed drivers enable the best practices in assessment setting and feedback provision. The level partition diagram can be used as a decisive guideline or a provisional framework in assessment and feedback provision for quality assurance in HE.

This study is one of, if not the only, to develop a guideline for signposting drivers and their influence and reliance to enhance assessment and feedback in a holistic HE setting. The developed drivers and the level partition diagram bring novelty and add to the current body of knowledge.

The purpose of this study is to propose an improved framework for managing Private Participation in Infrastructure ICT (PPI-ICT) projects in the context of developing countries as the requirements to manage them are different in several aspects.

The framework has been proposed based on an exhaustive literature review and statistical analysis of the PPI-ICT projects’ data set using logistic regression, F-test and student’s t-test. The proposed framework was also applied to the PPI-ICT projects.

The framework is an extension to NTCP (novelty, technology, complexity and pace) approach by including extrinsic factors such as income of the country, climate risk, religious diversity, political stability, regularity quality and control of corruption. The proposed framework was used to analyze project characteristics and their external conditions in the context of developing countries. Based on the analyses, the authors have presented a detailed set of recommendations for project managers, practitioners and governments to improve the success rate of these projects.

The major contribution of this study is the framework, which encompasses the NTCP model as well as extrinsic characteristics of PPI-ICT projects. The proposed framework is meant to assist the project managers to comprehend the project characteristics and its external environment to identify an adequate approach for managing projects successfully.

The issue of quality assurance in vocational and technical education (VTE) programs identifies a perilous need to develop a conceptual framework for teaching and learning standards. This study aims to identify standard components for teaching and learning to ensure quality delivery for the achievement of VTE objectives. The quality assurance framework for teaching and learning is envisioned as a closed-loop management process that functions as an effective operational scheme to coordinate teaching processes that support the structure for quality assurance in VTE programs.

Survey data were collected through a questionnaire developed to examine the quality standards for teaching and learning in VTE from 259 respondents from colleges of education. The identified quality components for teaching and learning and their quality indicators were analysed.

The conceptual framework for teaching and learning with the 12 quality components and 62 quality indicators is the key standard for improving quality teaching and learning to meet the desired goals of VTE programs.

The framework proposed is flexible and can be applied to many other programs to ensure that teachers are professional enough to teach effectively to provide adequate learning outcomes.