A growing number of Czech construction companies now recognise the importance of supplementing traditional financial measurements with a wider range of non-financial measurements as well. A significant number of organisations are adopting different models of performance measurement to implement business improvement strategies. The main aim of our research was to elucidate the importance that Czech construction companies attach to the individual criteria used in measurement systems. Original data were collected using a questionnaire survey. The answers were quantified in terms of the frequency of occurrence and relative importance index. The results show that traditional measurement criteria such as time and cost are still the most important for construction companies measurement systems. Positive finding is that certain new areas of measurement are increasingly being incorporated into measurement practice and their importance for Czech construction companies is growing rapidly, especially in the area of measuring the productivity of workers and craftsmen together with the productivity of subcontractors. The environmental impact of construction is still one of the least important areas in the measurement systems of construction contracts in Czech construction companies.

Maintenance is a key manufacturing function that contributes to a company’s productivity, profitability and sustainability. Unfortunately, many aspects of the contribution of maintenance to sustainability in manufacturing remain unexplored, and many enterprises are not yet ready to assess the maintenance impacts on their sustainability. Maturity models are useful tools for assessing maintenance practices; however, no maintenance maturity model that allows the evaluation of the contribution of maintenance to sustainable performance was found in literature. This paper proposes a model for assessing the maturity and sustainability of maintenance processes. The model outputs are: a measure of the maintenance and sustainability maturity level; recommendations for improvement to undertake to enhance maintenance maturity and, thus, meet sustainability standards. The model was applied in three manufacturing enterprises: the calculation of their maintenance maturity and sustainability indices made the maintenance stakeholders more aware of the need to implement effective strategies for more sustainable maintenance performance.

The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature.