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Semantic classification of business ontology while migrating business

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Abstract

An increase in business growth and revenue is the main objective of any business. There are various tactics to answer the problems i.e., about the growth of business and revenue. For example, one has also to answer for revising the company policies, motivational sessions for the employees, increment in salaries, and migration of business to a new place. The difference between a good and great business depends on the place of business. The purpose of migration is to expand the business where infrastructure cost is less, easily achieving business goals and need a comfortable market accordingly. The challenges occurs while migrating a business. Businesspersons can face various issues and problems. For example, how to identify the business challenges and know the basic legal rights to invest in a foreign country? To answer the problem, we have constructed a Business Migration Ontology (BMO) model to integrate information on the web accordingly. Therefore, three training sets used to construct the BMO. The training sets are semantically classified to find similarities and differences during the construction of BMO. The BMO facilitates the businesspersons to select an appropriate jurisdiction for migrating business, according to their requirements and possibilities. The BMO has semantically classified the legal acts defined by a jurisdiction, accordingly. The BMO facilitates to identify the required fields that have significance for businesspersons. The businesspersons can than determine to invest at a certain jurisdiction, accordingly. The BMO provides a complete view of different legal aspects according to various jurisdictions, which is helpful for businesspersons in the better decision while migrating their business.

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Notes

  1. https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/international-business-support/deloitte-cn-ibs-sweden-tax-invest-en-2016.pdf

  2. https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Tax/dttl-tax-hongkongguide-2016.pdf

  3. https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Tax/dttl-tax-newzealandguide-2016.pdf

  4. https://old.datahub.io/dataset?q=Business&sort=score+desc%2C+metadata_modified+desc

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Authors and Affiliations

  1. Department of Computer Science, Bahria University, Islamabad, Pakistan

    Muhammad Asfand-e-yar, Ramis Ali & Samia Mushtaq

  2. Center of Excellence in IT, Intitute of Management Sciences, Peshawar, Pakistan

    Imran Ahmed

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  1. Muhammad Asfand-e-yar
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  2. Ramis Ali
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  3. Imran Ahmed
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  4. Samia Mushtaq
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Correspondence to Muhammad Asfand-e-yar.

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Asfand-e-yar, M., Ali, R., Ahmed, I. et al. Semantic classification of business ontology while migrating business. Multimed Tools Appl 79, 17903–17921 (2020). https://doi.org/10.1007/s11042-020-08770-4

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