Purpose: To identify the duties and responsibilities of project managers by analysing the content of online job advertisements. Design/methodology/approach: Job advertisements were automatically downloaded for 63 countries/areas available on Indeed. A text mining analysis of fragments of the advertisements describing the scope of duties was carried out. The text mining analysis included initial text processing, creating corpora of the documents, creating a document-term matrix, and using classic methods derived from data mining. Findings: The research established the most frequently used words and n-grams in job advertisements. They have been presented in the form of figures. The 2-grams are also presented in the form of a net, a directed graph. The LDA algorithm identified abstract topics describing the duties and responsibilities of project managers. The most frequent words, n-grams, and topics identified by the LDA algorithm were used to identify the duties and responsibilities of project managers. Research limitations/implications: Only job advertisements written in English were analysed. The postings were downloaded only for six days. An attempt to automatically identify the responsibilities section did not yield the expected results. Therefore, it was carried out manually for random advertisements, which reduced the number of analysed documents. The content of the job advertisements was not analysed by country/area. Practical implications: The method applied can be used by organisations training future project managers, to modify and better adapt curricula to the needs of the labour market. Originality/value: Studies have shown that text mining of job advertisements can help determine the duties and responsibilities of project managers.
Purpose: An attempt to identify the duties and responsibilities of the project manager by analysing job offers from a job website. An attempt to determine whether there were any changes between 2018 and 2019. Design/methodology/approach: Text mining was performed for fragments of job offers, describing the duties and responsibilities. The text mining analysis consisted of initial processing of the text, creation of a corpus of analysed documents, construction of a word frequency matrix and use of classical methods from the data mining are. Findings: The most common words in job offers are presented, as well as their correlation with other words. With the use of the Topic modeling algorithm, hidden topics describing the analysed job offers have been generated. These topics can also be used to identify the duties and responsibilities of a project manager. Research limitations/implications: Only the job offers meeting the following conditions were analysed: (1) they concerned the job of „project manager”; (2) the content was in Polish; (3) they were provided by www.pracuj.pl website; (4) they were collected from 09 to 11 April in 2018 and 2019. Practical implications: This method can be used by organizations training project managers, in order to modify and better adjust the curriculum to the needs of the labour market. Originality/value: Research has shown that text mining can be used to determine the responsibilities of a project manager by analysing job offers.
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Through past decades, globalization of many industries was pushing them into virtual collaboration. Recent advances in technology are enabling increased efficiency of such interaction. Virtual teams are able to share documents, discuss various issues and quickly exchange information in the blink of an eye. However, lack of physical contact among the team is still an issue disorganising work and slowing down the progress. 16 factors behind this states were presented recently. Ensuring control over all those risk factors may be overwhelming for a project manager, therefore author of this paper proposes a systematic solution for successful virtual collaboration. It is based on gamification, method of increasing engagement of stakeholders by introducing game elements into the process, which gained popularity recently. This paper proposes the model, based on real virtual project and presents the evaluation method which will be used to assess its efficiency.
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