People Analytics of Semantic Web Human Resource Résumés for Sustainable Talent Acquisition

Necula, Sabina-Cristiana; Strîmbei, Cătălin

doi:10.3390/su11133520

Cited by 22 publications

(15 citation statements)

References 35 publications

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“…Another aspect noticed by the researchers refers to the economic profitability of the project as a factor of extrinsic motivation reported to intrinsic motivation. Although rewards are an important incentive (Dikaputra et al, 2019 ), there is a wide variety of intrinsic incentives that determine individuals to get financially involved in supporting a project, such as peace of mind, altruism, reciprocity or benefits for the community via implementation of the projects (Yang et al, 2016 ; Necula and Strîmbei, 2019 ). Kuppuswamy and Bayus ( 2017 ) highlight the importance of prosocial behavior in the case of reward-based crowdfunding: the supporters of the projects wish to make a profit, while also contributing in turning an entrepreneur's idea into reality.…”

Section: Resultsmentioning

confidence: 99%

Psychological Determinants of Investor Motivation in Social Media-Based Crowdfunding Projects: A Systematic Review

et al. 2020

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Background: Using the power of Internet, crowdfunding platforms are currently changing the traditional landscape of fundraising. Social media-based IT platforms in particular are bringing the creators of crowdfunding projects closer than ever to potential investors. A large variety of factors function as determinants of individuals' intention to participate in crowdfunding and have an intertwined impact on funding as the ultimate project goal.Objectives: For a better understanding of investor behavior in social media-based crowdfunding projects, this paper covers identifying, analyzing, and classifying general and specific factors of investor motivation, based on the literature in the field.The main focus is the relationship between the affordances provided by social media-based crowdfunding platforms and the psychological determinants of investor motivation in innovative start-up projects.Methods: Using IEEE Explore, Clarivate Web of Science, ScienceDirect, and Scopus, we conducted a systematic review of the existing research on the emerging role of crowdfunding as a disruptive technology in financing the start-up innovative projects. The paper explores the main determinants of investor motivation and aims to streamline the success factors in crowdfunding campaigns.Results: A total of 1,216 publications were identified after searching the aforementioned databases and, upon refining the results, 515 articles were considered for the final sample. After reading the titles and abstracts, the sample was reduced to 78 articles that were read in-depth and synthesized in accordance with the defined research questions. The selected articles were clustered into three main categories: general studies, determinants of investor behavior, and success factors.Conclusions: In the new global economy, crowdfunding platforms have become the nexus between the emerging creators of innovative products and services and the necessary funding sources. This connection is possible via a cumulative collection of contributions from multiple investors recruited from the audience of the selected platform, without time or space constraints. However, the determinants of the investment decision are very different in the case of social media-based crowdfunding platforms compared to determinants in the mainstream environment. This paper surveys these motivators and reveals how platform features can be used to persuade individuals to make a financial contribution toward the success of a project.

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Section: Resultsmentioning

confidence: 99%

Psychological Determinants of Investor Motivation in Social Media-Based Crowdfunding Projects: A Systematic Review

et al. 2020

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“…According to the empirical equation, the number of neurons is in the range of [5,14]. Hence, the model with several neurons between [3,16] is trained and tested.…”

Section: Parameter Selectionmentioning

confidence: 99%

“…Abdullah et al (2020) designed an enterprise cloud-based HRMS with 16 standard modules to solve HR problems using the CodeIgniter Web framework, which was then launched and deployed on the Amazon Web Service elastic computing cloud and used for an efficient enterprise HRM [4]. Necula and Strı ˆmbei (2019) developed an architecture to semantically enrich data through data science and semantic web technology for talent training. The experimental results suggested that the classification effect of the proposed architecture was better than the commonly used regression analysis, Random Forest (RF), and Support Vector Machine (SVM), and the proposed architecture could effectively mark the resume data and use the semantic web to extract data information from the resume [5].…”

Section: Introductionmentioning

confidence: 99%

“…Necula and Strı ˆmbei (2019) developed an architecture to semantically enrich data through data science and semantic web technology for talent training. The experimental results suggested that the classification effect of the proposed architecture was better than the commonly used regression analysis, Random Forest (RF), and Support Vector Machine (SVM), and the proposed architecture could effectively mark the resume data and use the semantic web to extract data information from the resume [5]. Jawad (2020) proposed a website-based HRMS to manage employee activity information, such as salary, registration, and promotion.…”

Section: Introductionmentioning

confidence: 99%

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Design and interactive performance of human resource management system based on artificial intelligence

et al. 2022

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The purpose is to strengthen Human Resources Management (HRM) through information management using Artificial Intelligence (AI) technology. First, the selection criteria of the applicant’s resume during recruitment and the formulation standards of the contract salary are analyzed. Then, the resume information is extracted and converted into the data-type format. Besides, the salary forecast model in the HRM system (HRMS) is designed based on the Back Propagation Neural Network (BPNN), and network structure, parameter initialization, and activation function of the BPNN are selected and optimized. The experimental results demonstrate that the algorithm optimized by the Nadm has shown improved convergence speed and forecast effect, with 187 iterations. Moreover, compared with other regression algorithms, the designed algorithm achieves the best test scores. The above results can provide references for designing the AI-based HRMS.

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“…Sabina-Cristiana Necula [12][13][14][15][16] defined a data science architecture that can analyze and derive the data for finding the right employee with good technical skills. The semantic web technologies extract the data that are specified in the resume and various skills are identified using the supervised machine learning algorithms.…”

Section: Related Workmentioning

confidence: 99%

An Extensive Analytical Approach on Human Resources using Random Forest Algorithm

Papineni¹,

Reddy²,

yarlagadda³

et al. 2021

IJETT

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The current job survey shows that most software employees are planning to change their job role due to high pay for recent jobs such as data scientists, business analysts and artificial intelligence fields. The survey also indicated that work life imbalances, low pay, uneven shifts and many other factors also make employees think about changing their work life. In this paper, for an efficient organisation of the company in terms of human resources, the proposed system designed a model with the help of a random forest algorithm by considering different employee parameters. This helps the HR department retain the employee by identifying gaps and helping the organisation to run smoothly with a good employee retention ratio. This combination of HR and data science can help the productivity, collaboration and well-being of employees of the organisation. It also helps to develop strategies that have an impact on the performance of employees in terms of external and social factors.

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People Analytics of Semantic Web Human Resource Résumés for Sustainable Talent Acquisition

Cited by 22 publications

References 35 publications

Psychological Determinants of Investor Motivation in Social Media-Based Crowdfunding Projects: A Systematic Review

Psychological Determinants of Investor Motivation in Social Media-Based Crowdfunding Projects: A Systematic Review

Design and interactive performance of human resource management system based on artificial intelligence

An Extensive Analytical Approach on Human Resources using Random Forest Algorithm

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