In order to adapt to ever-changing customer needs and satisfy them, good Business Process Management (BPM) in Small and Medium-sized Enterprises (SMEs) is crucial. The target group of this research is production SMEs whose BPM can be monitored respecting the values of key performance indicators (KPIs). This paper shows how improving the performance of the observed business processes can improve the level of customer satisfaction. This improvement should lead to the sustainability of SMEs in the market. In this paper, evaluation of business processes performance is defined as a multi-criteria decision problem. The relative importance of considered KPIs and their imprecise values are described by linguistic expressions, which are then modeled by triangular intuitionistic fuzzy numbers (TIFNs). Calculation of KPI weights is done by using the fuzzy analytic hierarchy process (FAHP). Evaluation of BPM success is conducted respecting the obtained KPI weights and KPI values. An optimal solution for BPM success improvement, respecting customer satisfaction indicators, is calculated using the Artificial Neural Network (ANN) and Genetic Algorithm (GA) approaches. By applying the proposed model, managers of production SMEs can determine the management initiatives that will improve their business and the sustainability of their companies.

The performance evaluation of business processes in uncertain environments has important consequences for investors, stakeholders and has critical importance for the improvement of business processes, which is one of the requirements of ISO 9001. In this paper, a new fuzzy model is proposed for evaluation and improvement of process quality. The fuzzy ratings of the Key Performance Indicators (KPIs) are stated as fuzzy pair-wise comparison matrices (by analogy to the AHP framework). By using the developed procedure, the fuzzy weights of KPIs are given. The KPI values are based on the assessment of decision makers. The developed solution, based on the genetic algorithm approach, is presented and tested on data from 53 Serbian manufacturing SMEs. The presented solution enables quality assessment of a purchasing process, the fuzzy ranking of KPIs, the selection of critical KPIs by using an exact approach, optimization and the provision of the basis for successful improvement of purchasing process quality.

The management of the electrical and electronic waste (WEEE) problem in the uncertain environment has a critical effect on the economy and environmental protection of each region. The considered problem can be stated as a fuzzy non-convex optimization problem with linear objective function and a set of linear and non-linear constraints. The original problem is reformulated by using linear relaxation into a fuzzy linear programming problem. The fuzzy rating of collecting point capacities and fix costs of recycling centers are modeled by triangular fuzzy numbers. The optimal solution of the reformulation model is found by using optimality concept. The proposed model is verified through an illustrative example with real-life data. The obtained results represent an input for future research which should include a good benchmark base for tested reverse logistic chains and their continuous improvement.

Improvement of the production process presents a very important management task for both researchers and practitioners and enables a better market position of the enterprise. Key Performance Indicators (KPIs) of the production process can provide useful information on the current state of the ongoing process. In this paper, the relative importance of KPIs and their values at the enterprise level were assessed by the experts and decision-makers. Their estimates are described by the linguistic variables which were modeled by intuitionistic fuzzy numbers. The weights vector of KPIs at the level of the considered enterprise is given by the Fuzzy Analytic Hierarchical Process (FAHP) with Triangular Intuitionistic Fuzzy Numbers (TIFNs). The rank of enterprises with respect to KPIs’ values and their weights was calculated using the modified TOPSIS with TIFNs. The developed model was tested on 30 enterprises from Serbia, belonging to the sector of small and medium-sized (SME) production enterprises. The improvement strategies of KPIs should be proposed at the level of each enterprise, separately, respecting the KPIs’ values of the first-ranked enterprise.