Background: The article presents an MCDM model based on the MEREC and WISPS methods for pallet truck selection. Purpose: The main purpose of the study was to apply a new MCDM model for pallet truck selection in the textile workshop. Study design/methodology/approach: This article presents a simplified adoption of the Simple Weighted Sum Product (WISP) method, the Simplified WISP (WISP-S) method. The proposed method has fewer computation steps than the regular WISP method. In addition, this study proposes a new hybrid MCDM model in the literature by combining the MEREC method and the WISPS method. Finding/conclusions: The obtained results can be achieved in a shorter time compared to regular WISP. The application of the new method is considered in this study. In order to check whether the WISPS method achieves accurate results, the results of the WISPS method and the results of the ROV and WASPAS methods were compared. As a result of the comparison of the results of the methods, it was observed that the WISPS method achieved accurate results. Limitations/future research: As a direction for future research, other MCDM models can be applied for solving the same problem. When it comes to the limitations of the proposed model, it can be mentioned that the MCDM model is based on the use of crisp numbers.

The main intention of this paper is to emphasize the crucial tour­ism products that will contribute to the tourism development of the Repub­lic of Serbia. With that aim, the Multiple-Criteria Decision-Making – MCDM approach is proposed based on the PIvot Pairwise RElative Criteria Impor­tance Assessment – PIPRECIA and the Simple Weighted Sum Product – WISP methods. PIPRECIA method is applied for defining the criteria weights, while the WISP method is used for ranking the considered tourism products. The final results are reliable and the tourism product City break is emphasized as the one with the greatest potential.

The task of the communal police is primarily reflected in the provision of assistance and services that have their own specifics. When it comes to the communal police in the Republic of Serbia, in that case the duties are reflected in the performance of supervision and control in accordance with the legal authorizations of the city regulations. Accordingly, the communal police, by performing tasks within their jurisdiction, ensures the performance of tasks within the jurisdiction of the City of Zajecar, in the areas of communal activities, environmental protection, people and goods, protection and maintenance of order in the use of land, space, local roads, streets and other public facilities, as well as the unhindered performance of certain tasks within the jurisdiction of the city, and so forth. Having in mind the specifics of the communal police, the aim of the research is to show the efficiency of the work of the Communal Police when providing assistance (2014-2019) through a systematic approach to the processing of data from archival materials, on the example of the service provided to the city authorities, which refers to providing assistance to PC Parking Service Zajecar.

The research was designed as a cross-sectional study in two time periods (2014 and 2019) on a selected sample in 12 cities of the Republic of Serbia. It aims to find out about the level of job satisfaction of employees in the municipal police (Official Gazette of the RS, No. 51/2009) - militia (Official Gazette of the RS, No. 49/2019). In order to obtain valid results from the respondents, the measurement of the degree of satisfaction was carried out by means of an anonymous standardized questionnaire for measuring job satisfaction - Job Satisfaction Survey (JSS). The collected data were processed by Descriptive statistical analysis (Macura, Kovacevic, 2018), determined is medium value, relationships and connections with categorical by division on the subscales and total scales For pleasure by work: dissatisfied, ambivalent and satisfied. T test of independent samples performed is a comparison of mean values on the job satisfaction scale and all its subscales. Standard multiple regression analysis of certain is mutual and influence and statistics the significance of the set variables on Employee Job Satisfaction. The results showed a statistically significant influence between the subscales on the job satisfaction scale, where the greatest influence on employee dissatisfaction in 2014 was the salary, promotion, benefits, rewards and the very nature of the job. The greatest influence on employee ambivalence was satisfaction with work procedures and satisfaction with communications in 2014, while in 2019 the greatest influence on employee ambivalence was satisfaction with co-workers, rewards, the very nature of work and communication.