discussion questions:

1. How has NASDAQ'S business benefited from the use of information systems?

2. What risks do information systems pose for NASDAQ'S OMX'S business?

3. What types of information are handled through NASDAQ'S systems. What are the key characteristics of this information and how do nasdaq customers

use this information to create value?

4. What does the example of goldman sachs paying to locate its server in the Nasdaq data center say about the relationship to locate it's server in the Nasdaq

data center say about the relationship between information systems and physical operations?

26 Start with two inventory by item type. This of items and the total sellingwillPor -20. ACCESS APPLIC TO INFORMATION SYSTEMS and a Consignor Report. Theots ing a favorite place to shop. The an Access database to help manage is fast becom- and total sales value of each i and the total selling price and What other reports could ese ar repowne in the spreadsheet ChoIEx02 table database with two tables (Consignors that net selling price after he has paid the that would be useful to the o commission consignor. ng price anculated field ors and tes). sells all items. The Consi CASE STUDY #1 Nasdaq's Information requency Tradinghallenges:Facbook's Botched Public Opening and trading day, howetver During the first tew hours of the first he workd's largest "fRoorless" exchange handles of millions of trades every day. Buys and sells ast that each trade has to be time-stamped the change aNYS competes above all, a technology to be completed manually. The botched os, When most people think of an exchange, they think of NYSE's enor- day Buys and sells happen so glitches at Nasdaq caused many delays and had to switch to a secondary system. At to the nano- second. First launched in 2000, Nasdaq OMx is, above all a company and it successfully competes against the venerable Nevw oe Stock Exchange (NYSE) on its breathtaking trading speed venerable New York to lase millions, and the technical issues a pricing. at Nada for the traders on the floor insisting that the company put profits ahead of backup system rather than interrupt trading to s Critics blamed poor decision maki mous building on Wall Street, with loud-mouthed the hioor shouting orders, racing stock tickers, and giant LCD screens laden with Charts, numbers, and ticker symbots. In fact, most exchanges are in data s, not in neoclassical buildings. And they are also for-profit laden with example, Citigroup claimed that the decision to ask man Drob busi major mistake, one that was mainly driven rassment during such a high-profile event. by a desire to avoig ew stock Suffeedroppet sibility for the technical problems and is png th a migh-fing, race new stuoi bungled operin nesses that compete for companies to list their shares and for investors and brokers to conduct their trades. After the first days of trading, Facebook's share Speed matters, and Nasdag OMX technology can handle 1 milion messages per second. It matters so much that some heavy tradersw 18%, and those who purchased the n hug n Nasdag's data center, just to avoid the make amends. In 2015, the company agreed to pay investto nother looming problem for Nasdaq OMX is computer trad 1 million factors may have contributed to the bunglet Goldman Sachs, for example pay ocating their own server tiny communication delay Nasdaq OMx for the privilege of dtaq took respons Goldman offices. A trader's servers lion to settle a class action lawsuit can Instanty detect any delay and can then automatically check other Hligh-Frequency Trading exchanges to see if the trade can be rerouted. in other businesses, improved information systems and technol- ogy drve prices down, In the early 2000s, NYSE and Nasdaq OMX shared with one another to close the deal at the best price, trading vol 90% of the market, but competition pushed that igure down to 45% ket u kly. Humans use ther coment toe the mane algorithms, or "algo-trading. " With machines talking to ma can use other exchanges with cheaper prices, or they can buy rules: once in place, however, the systems can trigger frenzieg and sell stocks in "dark pools"private groups whose members trade of trading. with one another Some argue that these high-frequency trades make the m more efficient and equitable, so the big players on the tradi Nasdag's focus on technology and lightning-fast trading speed were don't have an advantage. While Nasdaq OMX and other en reasons Mark Zuckerberg chose to use that exchange to take Facebook compete for the growing number of algo-traders, analysts w Facebook's Public Offering in 2012 so people could invest in the company directly. The choice the sheer technological speed introduces serious risks competitive win for Nasdaq which also cames high-tech kets dropped a gut-wrenching 9% on one afternoon in 2 ies such as Apple, Google, Groupon, and Zynga. However, Nas- suspected a clumsy algo-trader who accidentally triggere to other exchanges for Yelp, Linkedin, and Pandora. Face- (Figure 1-23). Though the real cause of that roller-coaster public opening (PO) was expected to be one of the largest was never clear, such programmed trades were the cle was a major book's initial in history similar event back in 1987