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The construction industry is an industry which has gained notoriety when it comes to both physical and mental health problems. Compared to other industries, the construction sector has a higher prevalence of many stressors and mental health concerns. This calls for mechanisms to cope with these concerns. One coping mechanism propounded to help cope and adapt in the face of pressures and challenges is “Mental Toughness (MT)”. While mental toughness has been widely studied in various fields, there is a paucity of comprehensive research examining its significance among construction professionals. Thus, the motivation of this study is to establish the mental toughness characteristics among construction professionals in Ghana.

The construction industry is an industry which has gained notoriety when it comes to both physical and mental health problems. Compared to other industries, the construction sector has a higher prevalence of mental health concerns. One coping mechanism propounded to help cope and adapt in the face of pressures and challenges is “Mental Toughness (MT)”. While mental toughness has been widely studied in various fields, there is a paucity of comprehensive research examining its significance among construction professionals. Thus, the motivation of this study is to establish the mental toughness characteristics among construction professionals.

the study's findings revealed 13-factor model characteristics of mental toughness with 43 variables for mentally tough performers in the construction environment. These 13-factor models include Pressure Management (PM), Motivation (M), Emotional Intelligence (EI), Interpersonal self-belief (SB), Tough Attitude (TA), Job-related self-belief (SBB), Ethical Values (EV), Commitment (C), Focus (F), Optimism (OP), Expertise and Competence (EC), Imagery Control (IC) and Resilient (R).

The outcome of this study has significant practical implications for various stakeholders. For construction professionals the identified factors provide valuable insights into the psychological attributes and behaviours that contribute to mental toughness among construction professionals. Understanding these characteristics can empower professionals to develop strategies for coping with stress, maintaining focus, and fostering resilience in challenging construction environments to achieve optimum performance levels consistently.

The originality of this study's findings stems from the fact that it is among the first to provide greater insight into mental toughness characteristics considered by professionals (quantity surveyors, construction managers, engineers, project managers, architects, estate managers) in the construction industry.

This study aims to investigate the factors influencing the adoption of data analytics in performance management. By examining the role of organizational and environmental contexts, this study contributes to the existing literature by proposing a novel and detailed technology-organization-environment (TOE) model for the complex interplay between firm characteristics and the adoption of data analytics. The results offer valuable insights and practical implications for organizations seeking to leverage data analytics for effective performance management.

The research draws upon a data set encompassing over 21,869 companies operating across all European Union member states. A multilevel logistic regression model was developed to evaluate the influence of organizational and environmental factors on the likelihood of adopting performance analytics in organizations.

The findings indicate that the lack of awareness of the benefits of data analytics and its practical application to address specific business challenges is a significant barrier to its adoption. Organizational contexts, such as variable-pay systems, employee training, hierarchical structures and frequency of monetary rewards, also influence the adoption of data analytics.

The study informs managers about the strategic role of data analytics capabilities in performance management for improved business intelligence and driving data culture.

The study helps managers understand the strategic role of data analytics capabilities in performance management, leading to improved business intelligence and fostering a data-driven culture in five key areas: structural alignment, strategic decision-making, resource allocation, performance improvement and change management.

The study advances the TOE theory, making it a more detailed and complete framework, particularly applicable to the adoption of performance analytics. It identifies the main factors of adoption that play a crucial role in this process.