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The purpose of this paper is to identify specific drivers of value creation in secondary buyouts. While this type of private equity deal has risen in importance in recent years, it is not yet well understood. Through an in-depth analysis of the acquisition of Brenntag by BC Partners, we develop propositions on the value creation profile of secondary buyouts.

We use a single case study design to explore the information-rich context of a secondary buyout. The Brenntag case epitomizes the development of a company from forming part of a large conglomerate to being private-equity owned after the primary and secondary buyout, to its final disposition of public listing. Our analysis is based on ten semi-structured interviews with key protagonists and observers, as well as analysis of primary company data and additional secondary data sources.

We propose that even if the investment management and monitoring skills of the primary and secondary private equity group are similar, there is still potential to realize operational improvements in a secondary buyout, due to either early exit of the primary private equity group or measures that further enhance management incentives. In addition, the Brenntag case shows that low information asymmetries can lead to higher leverage and that opportunities for multiple expansions are limited in secondary buyouts.

While a secondary buyout has become a common exit route in recent years, we are the first to undertake an in-depth case analysis of a secondary buyout. Our study helps researchers and practitioners enhance their understanding of drivers behind the value creation profile of secondary buyouts.

This paper aims to review, systematize and map the extant literature on private equity (PE) and study the underlying research agenda for investment selection and value creation in portfolio firms of PE investors. The PE investment process entails the preinvestment stage, where PE investors screen the target firms, and the postinvestment stage, where PE investors monitor the funded firms. With the motive to understand both stages, this review consolidates the findings of existing literature.

This research adopts a systematic literature review approach to study the underlying themes in PE investment literature. To adequately profile the key research areas, the authors have adopted citation classics in addition to keyword search and drawn the most significant papers in this field of research based on citation metrics.

The review presents a heterogeneous set of themes by encapsulating the relevant PE literature and identifies significant and emergent themes within the broad research area of investment and performance. The foundational themes found are selection determinants for PE investments, value creation in PE investments and selection vs value-adding effect of PE investors. While the emergent themes are the relative performance of PE investments; sources of value creation; skill, luck and social capital in PE; and resource dependency vis-à-vis PE. Each theme or subtheme chalks out the underlying research agendas for future researchers.

To build an understanding of the selection determinants and value creation, this review addresses the need to synthesize and align the PE literature concerning pre and post investment stages. PE is a fertile research area that is systematically captured in this review by identifying themes, subthemes and avenues for future research.

With multiple-related organizations, worldwide infections, deep economic recession and public disorder, and large consumption amount of anti-epidemic resources, the coronavirus disease 2019 (COVID-19) has been defined as a public health emergency of international concern (PHEIC). Nowadays, Wuhan has recovered from the pandemic disaster and reentered normalization. The purposes of this study are to (1) summarize organization collaboration patterns, successful experience and latent defects under across-stage evolution of Wuhan's cooperation governance mode against the pandemic, and on the basis, (2) reveal how the COVID-19 development trends and organizations' collaborative behaviors affected each other.

Detailed content analysis of online news reports covering COVID-19 prevention and control measures on the website of Wuhan Municipal Government was adopted to identify organizations and their mutual collaborative interrelationships. Four complex network (CN) models of organization collaboration representing the outbreak, preliminary control, recession and normalization stages, respectively, were established then. Time-span-based dynamic parameter analyses of the proposed networks, comprising network cohesiveness analysis and node centrality analysis, were undertaken to indicate changes of global and local characteristics in networks.

First, the definite collaborative status of Wuhan Headquarters for Pandemic Prevention and Control (WHPPC) has persisted throughout the period. Medical institutions and some other administrations were the most crucial participants collaborating with the WHPPC. Construction-industry organizations altered pandemic development trends twice to make the situation controllable. Media, large-scale enterprises, etc. set about underscoring themselves contributions since the third stage. Grassroots cadres and healthcare force, small and medium-sized enterprises (SMEs), financial institutions, etc. were essential collaborated objects. Second, four evolution mechanisms of organization collaboration responding to the COVID-19 in Wuhan has been proposed.

First, universality of Wuhan-style governance experience may be affected. Second, the stage-dividing process may not be the most appropriate. Then, data source was single and link characteristics were not considered when modeling.

This study may offer beneficial action guidelines to governmental agencies, the society force, media, construction-industry organizations and the market in other countries or regions suffering from COVID-19. Other organizations involved could also learn from the concluded organizations' contributions and four evolution mechanisms to find improvement directions.

This study adds to the current theoretical knowledge body by verifying the feasibility and effectiveness of investigating cooperation governance in public emergencies from the perspectives of analyzing the across-stage organization collaboration CNs.

Big 4 professional services firms increasingly lay claim to recruiting and including staff of diverse genders, cultures, ages and sexualities. Drawing on Foucauldian insights, this study explores how LGBTIQ+ staff navigated shifting technologies of client power, at the time marriage equality was legislated in Australia.

This article explores changing experiences of LGBTIQ+ staff and allies, through 56 semi-structured interviews undertaken through 2018–2019.

Technologies of client power were central to shaping workplace experiences for LGBTIQ+ staff. However, each firm was also keen to carve unique and bold responses to changing societal attitudes regarding sexuality and gender. These progressive moves did not sit comfortably with all clients, and so this article provides insight into the limitations of client privilege within professional services firms. For staff, this increasing complexity of sometimes opaque, contradictory and shifting technologies of client and firm power, enabled agency to explore a sense of self for some, but continued to exclude others.

Little attention has been directed to exploring challenges for staff of sexual and gendered diversity within professional services firms, or to exploring how staff navigate changing perceptions of client power.

The purpose of this paper is to explore the factors that influence migrant workers' household registration transfer willingness at both individual and urban levels and to provide empirical evidence on adjusting the household registration system to accommodate economic development and migrant workers' imbalances.

This paper adopts a hierarchical nonlinear model and examines individual and urban influencing factors of migrant workers' household registration transfer willingness, based on the data from China Migrants Dynamic Survey (CMDS) and the Urban Statistical Yearbooks.

This paper shows that: (1) multi-factors, such as age, education, marital status, household demographics, industry and migrant workers' contract coverage, have significant effects on migrant workers' household registration transfer willingness; (2) The urban public service equalization indicators, such as regional economic, educational resources, medical care and ecological quality, have significant effects on migrant workers' willingness to transfer household registration; (3) The heterogeneity of migrant workers' willingness to transfer household registration is significant in central, eastern and western China.

The authors provide a fresh perspective on population migration research in China and other countries worldwide based on the pull–push migration theory, which incorporates both individual and macro (urban) factors, enabling a comprehensive examination of the factors influencing household registration transfer willingness. This hierarchical ideology and approach (hierarchical nonlinear model) could be extended to investigate the influencing factors of various other human intentions and behaviors.

Micro approaches (individual perspective) have dominated existing studies examining the factors influencing migrant workers' household registration transfer willingness. The authors combine individual and urban perspectives and adopt a more comprehensive hierarchical nonlinear model to extend the empirical evidence and provide theoretical explanations for the above issues.

The study focuses on influential factors of collaboration on government data security by the Chinese government.

The article explores the case of e-government in the Chinese centralized unitary state system context, using a structured–pragmatic–situational (SPS) approach and the boundary theory as an analytical lens.

The findings indicate that e-government operates in highly interconnected environments where the safe flow of government data requires collaborative and cross-boundary strategies. Any organization is a potential “weakest link”. In addition, collaboration is fragmented by ambiguous accountability and organizational inertia across government departments, resources differences and limited visibility and measurability of security efforts across government levels and conflicts and uncertainties in principal–agent relationships. The solutions for those obstacles are also discussed from the multi-function, multi-level and multi-actor dimensions, respectively. A multi-dimensional overarching security model for the flow of government data is proposed.

The study advances the technology-oriented micro-analysis of previous studies on government data security to cross-organizational revealing at the macrolevel by connecting streams of research in information systems and public administration. These findings will contribute to making the safe flow of government data more resilient in the transformation of e-government.

Construction projects in Malaysia are often delayed and over budget due to heavy reliance on labor. Linear regression (LR) models have been used in most labor cost (LC) studies, which are less accurate than machine learning (ML) tools. Construction management applications have increasingly used ML tools in recent years and have greatly impacted forecasting. The research aims to identify the most influential LC factors using statistical approaches, collect data and forecast LC models for improved forecasts of LC.

A thorough literature review was completed to identify LC factors. Experienced project managers were administered to rank the factors based on importance and relevance. Then, data were collected for the six highest ranked factors, and five ML models were created. Finally, five categorical indices were used to analyze and measure the effectiveness of models in determining the performance category.

Worker age, construction skills, worker origin, worker training/education, type of work and worker experience were identified as the most influencing factors on LC. SVM provided the best in comparison to other models.

The findings support data-driven regulatory and practice improvements aimed at improving labor issues in Malaysia, with the possibility for replication in other countries facing comparable problems.