Machine Learning for Improved Management

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Table of Contents

Overview of Project
Theory and Hypothesis
Research Methodology
Analysis of Results and Limitations
Contributions and Outlets
Citations/References and Exhibits
Anticipated Challenges
Reference List

Overview of Project

The topic of machine learning and its role in the entire concept of managers’ work is essential today due to technological development. Various factories, manufacturers, and other businesses implement different innovations in their working processes to make them more accurate, fast, and productive (Choi, Jung & Noh 2015, p. 50). Nowadays, the profession of a manager is not as popular as it was several decades ago because machines and robots demonstrate better working results. The innovation outlined in the proposal will be examined at the meso-organizational level as the significant changes in managers’ occupations might be adopted by global companies that employ thousands of managers at the present moment. The method of using machine educational techniques is beneficial for many businesses that cannot afford to train their employees due to the possibility of a significant profit loss.

The problem of the proposed research is that some companies do not know whether it is better to invest their finances in informational technologies or it would be more advantageous to spend the same amount of money on their employees’ education. The purpose of the given study is to identify the role of information technologies and applications in modern production processes.

Theory and Hypothesis

The theoretical perspectives that will be used in the proposed study will discuss the question of information technologies’ impact on the management of professional activities and the world in general. The scholarly literature necessary for developing appropriate statements and thoughts for the given research will be taken only from reliable journals and books published and released by people who study the same topic for an extended period. Unfortunately, there are not many studies done in the area of machine learning in management as this approach to production processes is new, and still needs improvement (Jaiswal 2015, p. 74). One of the most important study questions is to determine whether managers might be deprived of their professional activities because of new technologies. The hypothesis is to evaluate whether new technologies and applications can replace people at the positions of managers.

Research Methodology

The primary research sampling will include approximately one thousand participants employed by an organization that requires particular management activities to be applied in the working process. The sample will be divided into two groups (five hundred people will work with applications, and other employees will be given recommendations by a professional manager). These people will be required to work in such conditions for three months. In the end, their productivity rates will be analyzed and compared with the help of such research instruments as questionnaires and observation.

Analysis of Results and Limitations

As it is mentioned above, the descriptive statistics data acquired during the research will be analyzed to support or refute its hypothesis. This method is appropriate as it is used by the majority of scholars with accurate study results and outcomes (Perles-Ribes et al. 2016, p. 693). However, some limitations might emerge due to the participants’ age differences. Some people might be more comfortable working with a manager as they are used to such a work organization.

Contributions and Outlets

Scholars who will do further researches in the sphere of machine learning might be interested in the results if this project. Various managers’ conferences would be the most appropriate outlet for sharing the study results. Also, professional journals that specialize in information technology might use the research data for one of their issues.

Citations/References and Exhibits

As it is mentioned above, only credible and scholarly sources will be cited in the study article. All of the references will be structured according to a certain citation style. Such exhibits as graphs and tables will help include particular statistical data.

Anticipated Challenges

Such challenges as gathering results and interviewing the study participants might be challenging due to a large sampling size. This issue will be addressed by a questionnaire that every member of the research will be asked to complete. According to the timeline, every employee will be required to work regular shifts during the first four weeks. The progress of both groups will be observed during the next four weeks. The participants will be asked to complete an interview to record precise results during the final month of the research.

Reference List

Choi, S, Jung, K & Noh, S 2015, ‘Virtual reality applications in manufacturing industries: past research, present findings, and future directions’, Concurrent Engineering, vol. 23, no. 1, pp. 40–63.

Jaiswal, S 2015, ‘Book review: common sense talent management: using strategic HR to improve company performance’, Vision: The Journal of Business Perspective, vol. 19, no. 1, pp. 73–75.

Perles-Ribes, J, Ramon-Rodriguez, A, Moreno-Izquierdo, L & Sevilla-Jeminez, M 2016, ‘Economic crises and market performance—a machine learning approach’, Tourism Economics, vol. 23, no. 3, pp. 692–696.

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