SHS Web Conf.
Volume 74, 2020The 19th International Scientific Conference Globalization and its Socio-Economic Consequences 2019 – Sustainability in the Global-Knowledge Economy
|Number of page(s)
|Economic Sustainability in Emerging Markets
|10 January 2020
Evaluation of Globally Operating Salesforce Staff by Multiple Attribute Decision Making Methods
VSB-Technical University of Ostrava, Faculty of Economics, 70200 Ostrava, Czech Republic
* Corresponding author: Gabriela.email@example.com
Business managers, globally sales executives operating worldwide, representing brands and good reputation of international companies are a special group of staff needing especially flexible working conditions to do their job all over the world. The evaluation and rewarding of their performance is globally linked to achieving business targets. How evaluate results of all involved staff working on different international markets as one set of so many variants and criteria with ensuring transparency, objectivity and fairness? The solution is found in multiple attribute decision methods (MADM). The aim of the paper is to evaluate a group of salesforce staff making international business world-wide by using MADM to identify and reward the best sales executives and at the same time manage to make them to feel be valued for their well-done work, efforts and achievements. Two methods of multiple attribute decision making were used for this evaluation – the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Weighted Sum Approach (WSA). The results of both methods were compared and the more suitable method for this universal application practicable world-wide in terms of the processing complexity and the user friendliness was chosen and recommended. The bonus scheme is based on a healthy competition for sales executives, on a motivation to grow up and gain better results to get additional special bonus beyond the standard rewards for meeting performance targets. Part of this papers is the proposal of flexible bonuses for reached positions in the ranking of evaluated employees.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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