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The purpose of this paper is to discuss the use of mixed methods research in a major three year project and focuses on the contribution of quantitative and qualitative approaches to study school improvement. It discusses the procedures and multiple data sources used in studying improvement using the example of a recent study of the role of leadership in promoting improvement in primary and secondary schools’ academic results in England. Although the definition of improvement used was based on robust analyses of data on students’ academic outcomes, the mixed methods design enabled a broader perspective to be achieved.

The study illustrates how the multilevel analysis of students’ national assessment and examination results based on national data sets for primary and secondary schools in England were used to investigate the concept of academic effectiveness based on value-added methodology. Using three successive years of national results a purposive sample of schools were identified that could be classified as both effective and improving over the period 2003-2005. In addition, surveys and interviews were used to gather evidence of the role of stakeholder perceptions in investigating school improvement strategies and processes.

National student attainment data sets were used for the identification of improving and effective schools and revealed the importance of considering their different starting points in their classification of three distinctive improvement groups. The combination of quantitative survey data from headteachers and key staff with qualitative case study data enabled a range of analysis strategies and the development of statistical models and deeper understanding of the role of leadership.

The limitations of a focus on only academic outcomes and “value-added” measures of student progress are discussed. The challenges and opportunities faced in analysis and integration of the different sources of evidence are briefly explored.

The study contributes to the knowledge base on the identification of school improvement and use of performance data. The findings on strategies and processes that support improvement are of relevance to policy makers and practitioners, especially school leaders.

The mixed methods design adopted in the study enabled the research to combine rigorous quantitative and in-depth qualitative data in new ways to extend and make new claims to knowledge about the role of school leadership in promoting school improvement based on the study of effective and improved schools’ experiences.

This study investigates lecturers’ challenges in guiding students’ final scientific work online during the COVID-19 pandemic. It explores the impact of lecturers’ digital technology proficiency on the students’ ability to compile their thoughts and produce scientific work independently.

The study involved 45 lecturers and 140 students. Data was collected through online surveys using the Google Forms application and focus group discussions. The data were analysed qualitatively and interpretively based on the surveys and interviews.

The findings reveal three modes of mentoring: online, mixed, and offline. Many lecturers’ reluctance to use digital technology for mentoring stems from their lack of proficiency, resulting in mixed mentoring methods. This digital inadequacy affects students’ ability to write scientific work independently, as they are not accustomed to self-directed learning. The pandemic has necessitated more independent work from students, with limited physical guidance from lecturers, leading to a decline in the quality of scientific writing.

This paper contains the latest information related to students' scientific writing activities. Student scientific writing activities are disrupted because supervisors do not have the skills to use technology in the remote student mentoring process. Lecturers are not skilled at using technology in carrying out online tutoring assignments.

This paper aims to examine different types of sharing platforms based on risk perceptions of product/service providers and users, and to illustrate appropriate platform regulation preferences.

A survey was used (N = 540) to collect data on platform participants’ risk perceptions and regulation preferences in the Chinese (N = 263) and the US markets (N = 277). Cluster analysis and multiple correspondence analysis were used to categorise platforms and match their regulation preferences with the risk characteristics.

The results show that i) four types of sharing platforms are categorised in terms of the risk perceived by the supply and demand side, and ii) four types of regulation preferences are clustered, drawing on the power and trust elements proposed from the slippery slope framework. Furthermore, coercive power regulation is favoured by participants of platforms with high supply risk and low demand risk, legitimate power regulation is preferred by actors of platforms with low supply risk and high demand risk, reason-based trust regulation is preferred by actors of platforms with high supply and demand risk, and implicit trust regulation is favoured by participants of platforms with low supply and demand risk.

This paper develops an empirical typology of platforms based on risk perceptions of providers and users, and advances our understanding about lateral exchange markets from a consumer perspective.

This paper provides implications for platforms to regulate transactions through two mechanisms – the power of platforms and trust in platform participants.

Regulating by power ensures transaction security while regulating by trust enhances transaction efficiency, so it is important to configure the power and trust elements in platform regulation in an appropriate manner. To the best of the authors’ knowledge, this paper is one of the first attempts at addressing platform regulation and shows how consumers’ risk perception of platforms can lead to important implications for theory and practice in marketing and better regulation of platform transactions.