This paper postulates that the effect of e-commerce on firm performance is not direct and needs to be examined using mediating factors. The Ordinary Least-Squares (OLS) model was employed with the data of the Flash Eurobarometer 439 Survey entitled The Use of Online Marketplaces and Search Engines by small and medium enterprises. The obtained findings provide support for the mediating hypothesis. To be more precise, while the relationship between e-commerce and firm performance is negative, it is positively mediated by certain types of internet sales channels. In particular, the benefits of e-commerce in terms of higher sales are more pronounced when firms use commercial websites and online marketplaces. On the other hand, the interaction between e-commerce and search engines has an insignificant effect on firm performance. This study advances research on e-commerce by emphasizing the importance of mediating effect.

Although a substantial body of literature has analysed the potential benefits of the circular economy, empirical evidence on the relationship between circular economy-related activities and firm performance is scarce. Rather than analysing only the effect of the circular economy on firm performance, we empirically examine the effects of the different phases of the adoption process of the circular economy on firm performance. Therefore, in this paper, a multiphase framework of circular economy adoption is developed. Employing a propensity-score-matching model on the sample of more than 4000 European SMEs, we show that the adoption of circular economy activities improves firm performance as measured by productivity. In addition, our findings reveal that the impact of circular economy activities on firm performance is dependent on the different phases of the adoption process. Taken together, this study enriches current research on the circular economy by contributing to a more nuanced understanding on the relationship between the different phases of the adoption process and firm performance.

The paper presents the results of the application of a practical approach for collecting data, which provides a simple, cost efficient, and easily reproducible method that was applied to obtain the necessary data for the status analysis of the Sustainable Urban Mobility Plan (SUMP) for Podgorica, the capital of Montenegro. Important data for the estimation of the existing condition of the traffic system were collected through desk research from the appropriate institutions and organizations. Several surveys and focus group interviews were conducted, in which about 5000 residents of Podgorica participated. In addition to answering questions, residents made numerous suggestions, confirming the correctness of a participatory approach in the new traffic planning paradigm that provides the SUMP with crucial advantages. A manual cordon count of traffic on five bridges for the traffic of the motor vehicles, as well as on two pedestrian-only bridges, was performed by students from the study program Road Traffic, and there are plans to repeat this in the coming years in order to enable more reliable monitoring and evaluation of the obtained data. Contemporary quality management tools such as BYPAD and ParkPAD were also used to assess the status of cycling and parking policy, respectively. It is especially important to emphasize that Podgorica is the first city in the West Balkans, and the fourth city in Europe, in which the ParkPAD tool was applied. A wide range of negative phenomena and trends was identified, like a rapid increase in the number of registered vehicles, an increase in the motorization rate and the number of traffic accidents, increased non-compliance with traffic rules, excessive use of passenger cars and auto-taxi vehicles, insufficient use of unattractive public transport, walking and cycling, etc. Based on the data collected, key challenges in status analysis in Podgorica were identified, which the SUMP should try to overcome.

Given the application of a multiple regression and artificial neural networks (ANNs), this paper describes development of models for predicting surface roughness, linking an arithmetic mean deviation of a surface roughness to a torque as an input variable, in the process of drilling enhancement steel EN 42CrMo4, thermally treated to the hardness level of 28 HRC, using cruciform blade twist drills made of high speed steel with hardness level of 64–68 HRC. The model was developed using process parameters (nominal diameters of twist drills, speed, feed, and angle of installation of work pieces) as input variables varied at three levels by Taguchi design of experiment and measured experimental data for a torque and arithmetic mean deviation of a surface roughness for different values of flank wear of twist drills. The comparative analysis of the models results and the experimental data, acquired for the inputs at the moment when a wear span reaches a limit value corresponding to a moment of the drills blunting, demonstrates that the neural network model gives better results than the results obtained in the application of multiple linear and nonlinear regression models.

The paper presents the results of tests and analysis of strength of traditional Montenegrin chair using FEM (The Finite Element Method) according to the procedure described in the relevant European standards. Stresses in the critical points of the structure were obtained and compared with values of permissible stresses for appropriate material. The influence of design parameters of chair on distribution and intensity of the stresses was considered, so it was selected the appropriate combination of parameters that presents the optimal solution from the aspect of the mentioned criterion. The obtained solution is compared with a volume equivalent model of usual chair with four legs. Based on the results we trained neural network in order to make it enable selection of design parameters of the traditional Montenegrin chairs that provide a satisfactory solution.