Cois11011—foundations Of Business Computing

COIS11011—Foundations of Business Computing The Questions: 1. Discuss the five IT Megatrends that shape the Digital Future. Source: Chapter 1 2. Of the five competitive forces presented in the Chapter 2 (Porter’s model), which is the most significant for an organisation in terms of making IS investment decisions? Why? Which is the least significant? Why? Source: Chapter 2 3. Internet access in the United States and throughout the world is continuing to grow steadily. In early 2016, nearly 50 percent of the world’s total population was accessing the Internet. In the United States, 88.5 percent of the population was accessing the Internet. Whereasmany western European countries are in the mid-90 percent range and slowly move toward 100 percent penetration, Iceland is still ranked as the only country having 100 percent of its population online. At the other end of the spectrum, many small and very poor countries are still struggling to gain access. In countries such as Guinea, Somalia, and Eritrea, less than 2 percent of the population is online. In between the bottom and the top, access varies widely. In Asia, about 50 percent of the population has access, while less than 10 percent of those living in Africa have access. (a) Search the Web for the most up-to-date statistics. (b) Discuss how these numbers will look in 5 years and 10 years. What changes have to be made to the global networking infrastructure? What issues/opportunities do you see arising? Source: Chapter 3 4. Describe social commerce and explain how companies can leverage consumers’ social networks.Source: Chapter 4 5. Explain the organisational issues associated with using social media applications strictly from the perspective of organisational hierarchies, technological inertia, and security concerns.Source: Chapter 5 6. Define a Database Management System (DBMS). What is an entity? Differentiate between records and attributes with example. Source: Chapter 6   Page 4 of 6 7. Write a short note on the rise of ‘Enterprise Systems’. Source: Chapter 7 8. Ethical Dilemma: When Algorithms Discriminate Promising companies the ability to get to know their customers and maximize the benefit gained from each one, CRM systems could be called a marketer’s dream. CRM software allows companies to look closely at customer behavior, drilling down to smaller and smaller market segments. Once so segmented, customers can be targeted with specific promotions. For the company, this process reaps the greatest returns from marketing efforts because only those customers are targeted who are likely to respond to the marketing campaign. From a customer’s perspective, CRM systems seem like a great idea. You finally stop receiving advertisements for things that don’t interest you. But what if a company uses its CRM software in a more discriminating way? Where do companies draw the line between using CRM data to offer certain clients customized deals and unethically discriminating against other customers? For example, lenders, which often segment their customers according to their creditworthiness, might use this credit risk data to target customers having a low credit rating with underhanded payday or subprime loans. Although these customers are riskier for the lender, the higher fees and interest charged for credit make these customers especially lucrative. CRM and all software contain countless algorithms for manipulating, aggregating, and summarizing data. Algorithms reflect a set of rules to be followed in calculations and other problem-solving operations. While there is a widespread belief that such algorithms must be objective and fair, CRM software, and the underlying algorithms, is not free of human bias. Instances of bias reported in the popular press include a report that Google’s online advertising system displayed an advertisement for high-income jobs for men more often than for women. Similarly, ads for accessing arrest records were significantly more likely to show up on searches for distinctively black names. In a similar way, CRM systems based on biased or discriminatory algorithms can potentially do more harm than good, destroying rather than building customer relationships. (a) Whose responsibility is it to ensure that algorithms are not discriminatory? Explain. (b) Google, Facebook, and many other widely used software platforms have been accused of using algorithms that present biased search results or news feeds. Should such platforms be bias free (at least as much as possible), or is it acceptable for platforms to reflect the biases of the developers? Explain. Source: Chapter 8