The paper "E-Commerce Essentials" is an amazing example of a Business assignment. The needs and requirements of consumers keep changing, and the business environment is also changing. eCommerce has improved how business is done and has disrupted the traditional approach of doing business. The disruptive nature of eCommerce has improved the experiences of retailers and consumers. The paper discusses some common eCommerce technologies and their respective impact on retailers and consumers. The discussion uses numerous examples including Uber, 3D printing, and cloud computing among others to indicative the values and variables that contribute to the embracement of the technology. 1 The Value These Technologies Offer to Customers and Retailers 1.1 Uber Uber is a taxi service provider or provides the framework to advance the easiness in transportation requirements.
Uber is based on a mobile application that allows consumers to use a Smartphone to submit a trip request, and the Uber drivers are routed to the customers (Isaac, 2014). The Uber drivers use their own cars to move consumers from one location to the other. Uber's strategy is disruptive in nature because it does not use the traditional method of taxis since the persons having access to the application can fulfill the request and communication purposes (Olsen and McDarby, 2015).
The value that the Uber technology offers to the customers is high-quality services and flexible pricing. For example, the customer is requested to rate the services offered, and the easiness of the rating system determines whether the Uber driver would receive more customers or unable to receive the customers. The voluminous feedback enables the company to continue improving the services (Marx, Gans, and Hsu, 2014).
The strategy is different from the traditional approach in which consumers were required to complain to the fleet companies. The traditional approach takes time, and the information can be controlled. For example, taxi fleet management may limit the movement of information, which is different from the strategy of Uber.
Aguiar, L., and Waldfogel, J., 2015. Streaming Reaches Flood Stage: Does Spotify Stimulate or Depress Music Sales? (No. w21653). National Bureau of Economic Research.
Boccardi, F., Heath, R.W., Lozano, A., Marzetta, T.L. and Popovski, P., 2014. Five disruptive technology directions for 5G. Communications Magazine, IEEE, vol. 52, no. 2, pp.74-80.
Hahn, F., Jensen, S. and Tanev, S., 2014. Disruptive Innovation vs. Disruptive Technology: The Disruptive Potential of the Value Propositions of 3D Printing Technology Startups. Technology Innovation Management Review, no. 4, vol. 12.
Isaac, E., 2014. Disruptive Innovation: Risk-Shifting and Precarity in the Age of Uber.
Krammer, M., Bernoulli, T. and Walder, U., 2014, October. Beyond HTML5 geolocation: A flexible concept to enable and easily use advanced positioning technologies for mobile indoor location based service web applications. In Indoor Positioning and Indoor Navigation (IPIN), 2014 International Conference on (pp. 383-399). IEEE.
Kushida, K.E., Murray, J. and Zysman, J., 2015. Cloud computing: from scarcity to abundance. Journal of Industry, Competition and Trade, vol. 15, no. 1, pp. 5-19.
Marx, M., Gans, J.S. and Hsu, D.H., 2014. Dynamic Commercialization Strategies for Disruptive Technologies: Evidence from the Speech Recognition Industry. Management Science, vol. 60, no. 12, pp. 3103-3123.
Oliveira, T., Thomas, M. and Espadanal, M., 2014. Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & Management, no. 51, vol. 5, pp.497-510.
Olsen, M.A.K. and McDarby, K., 2015. Utility and Disruption: Technology for the Entrepreneurs in Hospitality: Highlights from the 2015 Technology Entrepreneurship Roundtable.
Sandström, C.G., 2016. The non-disruptive emergence of an ecosystem for 3D Printing—Insights from the hearing aid industry's transition 1989–2008. Technological Forecasting and Social Change, vol. 102, pp.160-168.
Schrock, A.R., 2014. HTML5 and openness in mobile platforms. Continuum, vol. 28, no. 6, pp. 820-834.
Yanggratoke, R., Kreitz, G., Goldmann, M. and Stadler, R., 2012, October. Predicting response times for the Spotify backend. In Proceedings of the 8th International Conference on Network and Service Management (pp. 117-125). International Federation for Information Processing.
Zhang, B., Kreitz, G., Isaksson, M., Ubillos, J., Urdaneta, G., Pouwelse, J. and Epema, D., 2013, April. Understanding user behavior in Spotify. In INFOCOM, 2013 Proceedings IEEE (pp. 220-224). IEEE.