The 5S methodology is a very appropriate way to initiate and achieve the process of continuous improvement. This paper studies management practices in successful Japanese companies in order to determine what 5S principles are behind them. After visiting and conducting interviews at five different plants, a multi-case study analysis was developed to identify the key aspects of the success of the implementation of 5S in Japan. Although each of the companies studied is different, there are commonalities that provide for interesting learning. As a result, best managerial practices based on 5S principles are explained, and the most important principles associated with the success of the 5S method are described and discussed.

Purpose The purpose of this paper is to describe a readiness programme designed to increase employees’ awareness of order and cleanliness as a way of building the necessary foundation for implementing and sustaining continuous improvement processes. In this paper, the authors propose a new readiness programme based on the principles of 5S, with the aim of strengthening employees’ motivation and involvement prior to 5S being implemented. Design/methodology/approach The research is based on case study methodology, followed by a programme of four structured activities. The validity of the programme is shown through the implementation of the activities in two different organizations. Findings The readiness programme was applied before 5S was successfully implemented. The degree of awareness and motivation of the programme participants improved as a result of these activities. Moreover, the activities increased people’s motivation to participate in improvement activities. Originality/value Applying a readiness programme before implementing 5S can help organizations to achieve and sustain improvement activities, thus increasing worker commitment and motivation.

Purpose: The purpose of this paper is to analyze the conditions under which continuous improvement practices are developed and to determine what success factors and barriers affect the sustainability of these practices in order to establish strategies that reduce the risk of failure of improvement proposals in companies.Design/methodology/approach: The paper presents a rigorous review of the success factors and barriers in the implementation of continuous improvement models in companies and a multiple case study in which four successful companies located in Bogota, Colombia, were compared using Bessant's maturity model.Findings: The results suggest the existence of systematic improvement processes in the four companies analysed in favour of the improvement of business competitiveness. After a convergence exercise between the success factors identified in the literature and the routines of the evaluation model used to identify the maturity of the companies in terms of improvement, five strategic fronts were identified to achieve sustainable improvement proposals:(1)have management commit to the improvement and guarantee resources, (2) define a methodology to implement, (3) facilitate and systematize the information on the interventions, (4) design training programs and incentives to encourage employee involvement, and (5) generate a verification and control system to provide real-time feedback on the progress of the improvement actions.Research limitations/implications: This research paper was limited by the analysis of four large Colombian companies, which did not allow the generalizability of findings. Therefore, the study offers interesting insights on the empirical evidence on the lessons learned from continuous improvement practices in order to support managers on better decision making and for the academics on better understanding continuous improvement drivers.Originality/value: The present investigation provides a conceptual framework for future studies related to the sustainability of continuous improvement in industry, approaching this topic from a theoretical and practical perspective.

Hydrology has used traditional methods for flood level forecasting. However, this type of forecast can lead to accuracy issues, caused by the nonlinear behavior of floods and limitations by not including all variables, such as water flow, level and precipitation. Consequently, some scientists began to use unconventional methods based on artificial intelligence models, to forecast floods more precisely and rigorously. This paper compares the HEC-RAS one-dimensional flow transit model with an artificial intelligence model based on Artificial Neural Networks, developed in MatLab to predict floods. The results were analyzed using six statistical indicators: mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), square root of the MSE, Pearson correlation coefficient (CC), and concordance correlation coefficient (ρc). In addition, the efficiency coefficient was calculated, and used in a virtual tool called Hydrotest. The analysis shows that forecast models that use neural networks have accurate results, given their closeness to the real data: MAPE between 11.95 and 12.51, CC between 0.90 and 0.92, ρc between 0.84 and 0.87, and a coefficient of efficiency larger than 0.8. The study was conducted on a section of the upper Bogotá River, in Colombia, between the Florence Bridge and Tocancipá hydrological stations. Flow data was taken from the Regional Autonomous Corporation of Cundinamarca (CAR), from September 2009 to October 2013.

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