Chapter 2 Dissertation Paper Topic = Information technology Requirements and application for the E- commerce and M-Commerce Requirements Table of content Abstract Introduction Add subsections to the

INFORMATION TECHNOLOGY REQUIRMENTS AND APPLICATIONS.

Information technology requirements and applications for the E-commerce and M-commerce industry

The e-commerce and the m-commerce industries.

Under the E-commerce and m-commerce industries, the topic to be handled will be behavior and information technology. The behavior at the e-commerce and m-commerce industry setting will be based on the attributions from the IT systems operators as well as all the stakeholders involved. The benefits enjoyed from the IT systems at these companies will be a critical part of analysis.

The behavior will also be touching on the approaches of attending to different activities for the successful performances in both platforms. The strategies towards these outputs will also mark part of the behavior. The IT part will be based on the structure, existing security measures, vulnerabilities to the IT system and the general working of the IT towards value delivery on the e-commerce and m-commerce platforms. The rise of the e-commerce and the m-commerce industries towards the current popularity will be addressed as part of the behavior insights. The weaknesses and strengths from the e-commerce and m-mobile industries also forms part of the behaviors in the industries.

Tools/methods to be used in measuring the behavior at the e-commerce and m-commerce industries.

In designing the response, I will use the qualitative method as the basis of my research. In this case, I would consider various approaches to gain insights from different perspectives of performances. I would introduce the standardized job sampling approaches and then using the standardized outcomes from different systems. Through the rating systems, I would l also be able to understand the summary of the collected data. The basis of ratings based on the interview outcomes would be formed under the technique of using questionnaires to different operators under the e-commerce and m-commerce systems.

Generally, I would also apply survey approaches over different e-commerce and m-commerce platforms and their users. Since there are different individual and group users for the e-commerce and m-commerce platforms, I would design focus groups and assign related questions to the industrial behavior. The approaches of observations in the different e-commerce and m-commerce systems would also be a reliable technique. The social media tools for instance emails, Facebook among others would be of great assistance.

The attributes of the tools/ techniques.

The observational techniques would only be based on what could be see, encountered, or heard in the identified field and thus may limit the amount of research data that could be gained. It would be effective in an acquiring data from the social media platforms and the subsidiaries to the e-commerce without their involvement.

The focus groups would generate discussions among various groups on people regarding e-commerce and m-commerce. The interviews would support in acquiring firsthand information from the industry. The standardized job sampling would be facilitating in acquiring trustworthy data from different platforms and users.

References

Bailey, J. S., & Burch, M. R. (2017). Research methods in applied behavior analysis. Routledge.

Laudon, K. C., & Traver, C. G. (2016). E-commerce: business, technology, society.

Luo, J., Fan, M., & Zhang, H. (2015). Information technology, cross-channel capabilities, and managerial actions: Evidence from the apparel industry. Journal of the Association for Information Systems, Forthcoming, 2016-056.

Rahayu, R., & Day, J. (2015). Determinant factors of e-commerce adoption by SMEs in developing country: evidence from Indonesia. Procedia-social and behavioral sciences, 195, 142-150.

Zhou, M., Ding, Z., Tang, J., & Yin, D. (2018, February). Micro behaviors: A new perspective in e-commerce recommender systems. In Proceedings of the eleventh ACM international conference on web search and data mining (pp. 727-735).