Researchers: Dating Sites Have It All Wrong (Consumer Affairs, 12/9/13)
While it is true that some people successfully find good, lasting relationships on online dating sites, it is also true that many end up frustrated and disappointed.
Rochelle, a Match.com user from Irvine, Calif., says she has found a troubling pattern with the men she has met online: they aren't telling the truth, she says.
"I've noticed that a lot of men are lying about their age," Rochelle writes in a ConsumerAffairs post. "I set my age limit at 45 and about a quarter of the men contacting me are no way even close to 45. Try 55-65! Also, a lot of men use very old pics. Sorry, but any picture older than 2-3 years is irrelevant."
Researchers at the University of Iowa (UI) think Rochelle might unknowingly be onto something. Not that people are dishonest when they use an online dating site but there's a disconnect—what they say doesn't really match what they truly want.
Kang Zhao, assistant professor of management sciences in UI's Tippie College of Business, and UI doctoral student Xi Wang are part of a team that has developed an algorithm for dating sites that uses a person's contact history to recommend partners with whom they may be more romantically compatible.
It's similar to the model Netflix uses to recommend movies users might like by tracking their viewing history. For example, you might not pick a particular movie to watch but Nexflix, analyzing the movies you've watched in the past, says "hey, you might like this one." In a way, it's putting the computer in computer dating.
Dating sites are taking notice. Zhao says he's had preliminary discussions with two dating services who have expressed interest in learning more about the model. Since it doesn't rely on profile information, Zhao says it can also be used by other online services that match people, such as a job recruiting or college admissions.
The system was developed with the help of a popular commercial online dating company whose identity is being kept confidential. The research team looked at 475,000 initial contacts involving 47,000 users in two U.S. cities over a 196-day span. Of the users, 28,000 were men and 19,000 were women, and men made 80 percent of the initial contacts.
The data showed that just 25% of those initial contacts were actually reciprocated. To improve that results, Zhao's team developed a model combining two factors to recommend contacts: a client's tastes, determined by the types of people the client has contacted; and attractiveness/unattractiveness, determined by how many of those contacts are returned and how many are not.
Zhao believes those two factors, taste and attractiveness, do a better job of predicting successful connections than relying on information that clients enter into their profile, because what people put in their profile may not always be what they're really interested in. And from Rochelle's observation, they could also be intentionally misleading.
Zhao goes a step further, suggesting the average user of an online dating site might not really know themselves well enough to know their own tastes in the opposite sex. A man who says on his profile that he likes tall women may in fact be approaching mostly short women, even though the dating website will continue to recommend tall women.
"Your actions reflect your taste and attractiveness in a way that could be more accurate than what you include in your profile," Zhao says.
Another way of saying, actions speak louder than words. Zhao says that eventually, the algorithm will notice that while a client says he likes tall women, he keeps asking out short women, and will change its recommendations to start suggesting that he contact short women.
If it works for movies, it should work for dates, Zhao says.
UI Researchers: Netflix-Style Tracking Can Increase Online Dating Success (Des Moines Register, 12/4/13)
Online daters looking for a virtual love connection can look no further than Netflix's recommendations feature.
University of Iowa researchers say the algorithm that gives viewers suggestions on the popular movie site could help them find a potential mate online.
Assistant professor Kang Zhao and student Xi Wang have created a model that would use someone's contact history to recommend more compatible partners, according to a news release. Netflix recommends movies to users based upon viewing history.
The conclusion came after a study used data from 47,000 users of an undisclosed popular dating website to seek a better solution.
"Your actions reflect your taste and attractiveness in a way that could be more accurate than what you include in your profile," Zhao said.
The new approach takes into account what a user does, which Zhao says is not always the same as what a person puts on his or her personal profile.
For the complete study, which was coauthored by Mo Yu of Penn State University and Bo Gao of Beijing Jiaotong University, see below. To see the complete news release, visit the University of Iowa's news website.
Love Connection (12/4/13)
Most online dating users don’t choose a potential mate the same way they choose a movie to watch, but new research from the University of Iowa suggests they’d be more amorously successful if that’s how their dating service operated.
Kang Zhao, assistant professor of management sciences in the Tippie College of Business, and UI doctoral student Xi Wang are part of a team that recently developed an algorithm for dating sites that uses a person’s contact history to recommend more compatible partners. It’s similar to the model Netflix uses to recommend movies users might like by tracking their viewing history.
Zhao’s team used data provided by a popular commercial online dating company whose identity is being kept confidential. It looked at 475,000 initial contacts involving 47,000 users in two U.S. cities over a 196-day span. Of the users, 28,000 were men and 19,000 were women, and men made 80 percent of the initial contacts.
Zhao says the data suggests that only about 25 percent of those initial contacts were actually reciprocated. To improve that rate, Zhao’s team developed a model that combines two factors to recommend contacts: a client’s tastes, determined by the types of people the client has contacted; and attractiveness/unattractiveness, determined by how many of those contacts are returned and how many are not.
Those combinations of taste and attractiveness, Zhao says, do a better job of predicting successful connections than relying on information that clients enter into their profile, because what people put in their profile may not always be what they’re really interested in. They could be intentionally misleading, or may not know themselves well enough to know their own tastes in the opposite sex. So a man who says on his profile that he likes tall women may in fact be approaching mostly short women, even though the dating website will continue to recommend tall women.
“Your actions reflect your taste and attractiveness in a way that could be more accurate than what you include in your profile,” Zhao says. Eventually, Zhao’s algorithm will notice that while a client says he likes tall women, he keeps contacting short women, and will change its recommendations to him accordingly.
“In our model, users with similar taste and (un)attractiveness will have higher similarity scores than those who only share common taste or attractiveness,” Zhao says. “The model also considers the match of both taste and attractiveness when recommending dating partners. Those who match both a service user’s taste and attractiveness are more likely to be recommended than those who may only ignite unilateral interests.”
While the data Zhao’s team studied suggests the existing model leads to a return rate of about 25 percent, Zhao says a recommender model could improve such returns by 44 percent.
When the researchers looked at the users’ profile information, Zhao says they found that their model performs the best for males with “athletic” body types connecting with females with “athletic” or “fit” body types, and for females who indicate that they “want many kids.” The model also works best for users who upload more photos of themselves.
Zhao says he’s already been contacted by two dating services interested in learning more about the model. Since it doesn’t rely on profile information, Zhao says it can also be used by other online services that match people, such as job recruiting or college admissions.
Zhao’s study, “User Recommendation in Reciprocal and Bipartite Social Networks—A Case Study of Online Dating,” was coauthored by Mo Yu of Penn State University and Bo Gao of Beijing Jiaotong University. It will be published in a forthcoming issue of the journal IEEE Intelligent Systems and is available online at arxiv.org/pdf/1311.2526v1.pdf.
University of Iowa Professor Advises on Disaster Relief Logistics (The Gazette, 11/16/13)
Disasters like the super typhoon that bowled over the Philippines last week, killing thousands and displacing hundreds of thousands, are at the heart of University of Iowa professor Ann Campbell's research.
As a management sciences associate professor with the Tippie College of Business, Campbell studies transportation logistics—specifically focusing on finding more efficient ways to transport relief supplies to disaster zones.
And her research has taught her just how hard it can be to get help to those who most desperately need it.
"It's different when it involves a disaster," Campbell said.
There's a lot more at stake, and a lot more to overcome, according to Campbell. Not only are there traditional logistical hurdles—like finding efficient routes—but transportation, communication, and supply issues can become insurmountable, Campbell said.
Traditional supply chains take years to coordinate and perfect—consider Walmart's efforts to supply its stores with product every day.
"They did not develop that over night," she said. "But when what happened in the Philippines happens, you have to figure it out over night. There is zero in place."
Aid workers have to find suppliers, communicate with recipients, and operate around infrastructure damage to save people desperately needing food, water, and shelter.
"Speed is a big issue," she said
And so is communication, with disasters like Typhoon Haiyan wiping out cellular infrastructure. Campbell said the Philippines' coastal location also makes aid response a challenge—necessitating functioning airports and boats to even get close to the devastated regions.
"Hurricane Katrina was terrible, but at least you could load up an 18-wheeler and start driving down supplies from Iowa," Campbell said. "How do you get supplies to the Philippines when they have one airport serving a lot of people? The complexity and logistics just get worse and worse."
Typhoon Haiyan, which struck the Pacific island nation on Nov. 8, reportedly killed more than 4,400 people, injured more than 12,100 people, displaced more than 900,000 and left more than 1,000 missing. A week after the deadly typhoon, international responders on Friday still were battling clogged airports, blocked roads, and lack of manpower, according to news reports.
Campbell, through her research, said there are some new ideas on how to mitigate the complexities that come with getting aid to disaster zones. She is developing a way to use mathematical modeling and high-powered computing to develop quicker and more efficient ways to route vehicles.
The process aims to inform disaster relief drivers on which roads remain usable and which roads are impassable to speed up delivery times. Campbell said it also can be helpful—although not traditionally efficient—to send out multiple trucks at once in hopes of reaching more people quickly.
She said disasters should teach us to prepare and pre-stock supplies—like the American Red Cross does during hurricane season in the United States.
"That's not something every government and every state does," she said. "But you can access things faster if you do that."
Campbell became interested in disaster relief logistics after the Indonesian tsunami in 2004, and her research became increasingly relevant when Hurricane Katrina hit the Gulf Coast in 2005 and again when Haiti was devastated by an earthquake in 2010.
The Haitian disaster taught us, among other things, that disaster aid should be prioritized.
"Haiti had one airport, and they were letting some planes land that didn't have the most important things on them," she said.
Typhoon Haiyan poses its own set of challenges, she said, also highlighting the need to have prepared and flexible leaders.
"The fact that it's only accessible by boat and a few airports makes it so much harder," she said. "You have to have the right people in charge."
Getting Aid to Philippines Is Challenging, Costly (KCRG, 11/13/13)
Don Fields and his wife Sandee, who operate a warehouse for Kids Against Hunger, are preparing to send what they call "medicine in a bag" to victims of Typhoon Haiyan. The warehouse is packed with boxes of food ready to be shipped overseas.
"Each one of these boxes has 36 bags of food, and each bag will feed a family of six for one day," Fields explained.
It's a soy and rice mix that Fields says is formulated to kick-start the digestive system of a person going hungry. But getting this precious cargo—two shipping containers worth—to the Philippines will be costly.
"To ship from my warehouse to the Philippines, a 40-foot container, which is 18 pallets, is $4,000," said Fields.
Which is why many experts say that unless you're part of an organization like Kids Against Hunger, one equipped with the resources to ship large quantities of food or water, the best way to help is to donate money.
Associate Professor Ann Campbell with the University of Iowa said that's because items like boxes are much more expensive to put to good use.
"You have to come up with suppliers, because people were self-sufficient before, in terms of food and water, and you've got to figure out who is going to donate what," said Campbell. "You've got to deal with infrastructure damage."
Campbell, who researches transportation and logistics, says vehicle supply chains are usually set up to maximize profits, but in a disaster, it's no longer about making money.
"Food , shelter, water is priority one," said Campbell. "We're not maximizing profit; it all becomes about speed, and some of the things that maximize profit do not maximize speed."
But Fields is up to the challenge. He'll be communicating with non-government organizations in the Philippines to make sure that this food gets to the people who need it most.
"They have the capability of tracking the food," Fields told us. "We track it all the way over there, we know when it gets to port, we know who unloads it, who picks it up, where it goes, and what warehouse it's stored in, and then people can come in and distribute it."
Mathematics Turned to Helping Disaster Relief After Philippine Typhoon (UPI, 11/12/13)
Mathematics and logistics can improve relief efforts like those under way after Typhoon Haiyan plowed through the Philippines, a U.S. scientist says.
Management sciences Associate Professor Ann Campbell at the University of Iowa is an expert on transportation logistics and has turned to researching more efficient methods for governments, agencies, and businesses to transport relief supplies to disaster areas where roads, ports, and airports are all but destroyed.
Her specialty—vehicle routing—uses mathematical and computer modeling to develop quicker, more efficient ways to move supplies and personnel from one place to another.
Although her research normally is aimed at business supply chains and commercial activities, she says the same research tools can meet the challenge of disaster logistics.
"Commercial supply chains are focused on quality and profitability," Campbell said. "Humanitarian supply chains are focused on minimizing loss of life and suffering, and distribution is focused on equity and fairness much more than in commercial applications."
Campbell's current research is focused on helping drivers in the Philippines learn what roads are still usable and which have become impassable as a result of the disaster, so that emergency workers will know before setting out which path is least likely to be damaged.
"We want to give drivers a recommended path and some back-up options in case they encounter road failures," she said. "In a disaster, it is important to recognize that information on road conditions is slow to come in. Also, cell phones usually don't work, so it is important to give drivers as much information as possible before they leave the depot with supplies."
Typhoon Haiyan Highlights Disaster Relief Logistics (11/12/13)
Typhoon Haiyan’s trail of destruction in the Philippines last weekend is drawing attention to the difficulty of providing relief services in a place where roads, ports, and airports are all but destroyed.
Ann Campbell, a professor of management sciences in the University of Iowa’s Tippie College of Business, is an expert on transportation logistics, and one of her research focuses is finding more efficient methods for governments, agencies, NGOs, and businesses to transport relief supplies to disaster areas.
Campbell is using the tools of her trade to find a better idea. Her specialty—vehicle routing—uses mathematical modeling and high-powered computing to develop quicker, more efficient ways to move something from one place to another.
Most of her research is aimed at helping businesses build supply chains that reduce transportation costs and increases profits. But few transportation logistics problems are as challenging as disaster logistics, which deal in many more unknown factors and turns the objective of supply chain management—maximizing profit—on its head.
“Commercial supply chains are focused on quality and profitability,” she says. “Humanitarian supply chains are focused on minimizing loss of life and suffering, and distribution is focused on equity and fairness much more than in commercial applications.”
Campbell started studying disaster logistics after the Indonesian earthquake and tsunami in 2004 wiped out a portion of Aceh Island and killed hundreds of thousands of people. For weeks, governments and international agencies struggled to bring relief supplies to a remote corner of a remote island where the disaster had taken out most transportation infrastructure.
The question took on added urgency when Hurricane Katrina hit the Gulf Coast in 2005 and Haiti’s capital Port-au-Prince was hit hard by an earthquake in 2010.
“The software used to route deliveries is focused on maximizing profits and minimizing costs, but that didn’t seem the most appropriate software to use when it came to getting people food and water,” she says.
Cambell’s current research is helping drivers learn what roads are still useable and which have become impassable as a result of the disaster, so that emergency workers will know before leaving the path least likely to be damaged.
“We want to give drivers a recommended path and some back-up options in case they encounter road failures,” says Campbell, who is working on the project with Tippie doctoral student Preethi Isaac. “In a disaster, it is important to recognize that information on road conditions is slow to come in. Also, cell phones usually don’t work so it is important to give drivers as much information as possible before they leave the depot with supplies.”
She said that Haiyan creates a whole new set of circumstances, not the least of which is that much of the damage was caused in remote areas that were difficult to access even before the storm.
One element of disaster logistics that Campbell and others are studying is where to locate pre-positioned supply depots in advance of a storm.
“If you put them too close to the coast, for instance, they might be destroyed by the storm, so you have to put them someplace that’s far enough away to be safe but no so far that it takes too long to get the supplies to the people who need them,” she says.
Thomas Elected to INFORMS Transportation Science and Logistics Society (10/29/13)
Tippie College of Business Associate Professor Barrett Thomas has been elected vice president/president-elect of the INFORMS Transportation Science and Logistics Society. His three-year term will include a year in the roles of vice president, president, and pastpPresident.
The TSL Society provides INFORMS members with a sustained, specialized focus on the topics of transportation science and logistics. Their efforts are devoted to current and potential problems of the industry, contributions to their solution, and the integration of related branches of knowledge and practice. The INFORMS Transportation Science and Logistics (TSL) Society was formed in 2004 with the merger of the Transportation Science and Logistics Sections and has more than 1,000 members.
Barrett Thomas is as associate professor of management sciences in the Tippie College and also serves as the faculty director of the MBA Strategic Innovation Career Academy. He holds a Leonard A. Hadley Research Fellowship. He is an associate editor of IIE Transactions, Focused Issue on Operations Engineering and Analytics, Transportation Systems Analysis Department; an editorial board member for Surveys in Operations Research and Management Science; and an associate editor of INFOR: Canadian Journal of Operational Research. He recently was awarded an NSF grant (along with Tippie professor Ken Brown) to develop new models to help businesses improve workforce development and employee training. Thomas has a Ph.D. and an M.S. in industrial and operations engineering from the University of Michigan and a B.A. in mathematics and economics from Grinnell College.
Pant Named Associate Editor of the Year (10/11/13)
Gautam Pant, associate professor of management sciences at the University of Iowa's Tippie College of Business, has been named Associate Editor of the Year for his work with the Information Systems Research (ISR) Journal.
Information Systems Research (ISR) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society. More information on the journal can be found here: http://isr.journal.informs.org/
Pant has been with the Department of Management Sciences in the Tippie College of Business since 2011. His expertise is in the areas of analytics, business intelligence, online visibility, and web mining. He received the David Eccles Emerging Scholar Award from the University of Utah in 2009-2011. He received his Ph.D. from the University of Iowa in 2004, his M.S. in computer science from Baylor University in 1999 and a B.E. in computer engineering, VJTI, from the University of Mumbai in 1996.
Discover 11 Hot College Majors That Lead to Jobs (U.S. News & World Report, 9/10/13)
Looking for an academic direction with terrific growth potential? Some traditional fields are newly hot at the bachelor's level; in other cases, enterprising colleges are creating new majors in emerging fields. Here are some hot majors you might want to consider.
1. Biomedical engineering
3. Forensic science
4. Computer game design
6. Data science
7. Business analytics: While closely related to data science, business analytics is primarily a business major, says Kenneth Gilbert, head of the department of statistics, operations, and management science at the University of Tennessee, which launched a degree program in 2010. Courses include computer software, math, statistics, and communication skills.
Rutgers Business School introduced a business analytics and information technology major for undergrads in 2011. The University of Iowa offers a BBA in business analytics and information systems, while Old Dominion University features a major in business administration/business analytics.
8. Petroleum engineering
9. Public health
Excerpted from the U.S. News "Best Colleges 2014" guidebook, which features in-depth articles, rankings, and data.
More Shipments a Good Sign for the Economy (The Gazette, 8/24/13)
More than 1.4 million carloads of goods and commodities were shipped across the country in rail cars during the month of July, according to an August report by the Association of American Railroads.
This is a slight decline from July 2012, as the amount of carloads of coal and grain fell—both commodities shipped out of the Corridor—but is still a steady increase since 2009. In July of this year, the weekly average of goods shipped was around 277,000 carloads compared with 262,000 carloads in July 2009.
“More moving is a reflection of more consumption,” said Ann Campbell, an associate professor of management sciences at the University of Iowa who studies intermodal movement—goods shipped by more than one means of transportation.
Demand for rail service is a result of the demand for the goods that railroads haul elsewhere and can be a gauge for broader economic activity.
Carloads of petroleum were up 24.9 percent in July 2013 over July 2012. Crushed stone, sand, iron and steel scrap, cement, and primary metal products also all saw increases in the number of carloads year-over-year.
Additionally, the number of consumer goods being shipped have led analysts to believe holiday sales will rise from last year, according to Bloomberg News. Total U.S. intermodal volume was up 4 percent for the four weeks ending Aug. 10 compared with a year ago.
However, Campbell was quick to note that just because more trains may be moving across the country, it doesn’t mean all the goods they’re shipping are American made.
“It could have arrived at a port and was then put on a train,” she said. “So it’s not clear who makes it.”
Another factor possibly contributing to a rise in rail shipments, Campbell said, is that rail is more cost effective. Trains can move more goods at a time and are cheaper when rising gas prices and new rules regulating truck drivers hours are factored in, she said.
University of Iowa Offers New Business Analytics Major for Undergrads (Data Informed, 8/8/13)
Starting this fall, undergraduate students at the University of Iowa will for the first time be offered an opportunity to major in business analytics.
The university’s Tippie College of Business approved a new track to its management information systems major, essentially allowing students to choose one of two IS majors.
That new track and major—Business Analytics and Information Systems (BAIS)—is designed to teach students how to manage and analyze vast amounts of data in order to improve an organization’s productivity and profitability.
“When you’re collecting data and trying to turn it into insight, you’re trying to improve your process and improve what you’re doing, whether that’s selling retail or managing supply chains or working in health care,” says Jeffrey Ohlmann, associate professor of management sciences at Tippie. “The BAIS major combines topics from computer science, industrial engineering, mathematics, and statistics and teaches them through the prism of business problem solving.”
Ohlmann says the idea for a business analytics major had been brewing for a few years as it became clear to Tippie faculty that big data was becoming a critical resource to enterprises, which must cope with an ongoing shortage of trained employees able to analyze data to improve their businesses.
In addition to creating an entire BAIS major, the business school also added some classes to the information systems major to teach undergrads how to “develop systems to handle large amounts of data,” Ohlmann says.
A growing number of colleges and universities offer advanced degrees for data analytics but institutions offering undergraduate degrees for data analytics are rare. Among the few are Northwestern College in Iowa, the College of Charleston, and Oxford University in England.
The Tippie College of Business has an MBA program in lean process improvement, and Ohlmann says the school has been able to “leverage the expertise of the faculty there” in designing the BAIS curriculum for undergrads.
“The ideals are the same, but we’re adapting them to a big data environment,” he says.
Ohlmann, who will teach a class in business process analysis for the BAIS major, says the new track will also offer classes in business process improvement, business intelligence and data mining, supply chain management, and optimization and simulation modeling.
Students in the BAIS track will learn about three kinds of analytics: descriptive, predictive, and prescriptive, with a heavy emphasis on the latter two. While descriptive analytics has been around for a long time, the most value for enterprises comes from using analytics to predict behavior and outcomes as well as to prescribe courses of action.
“Prescriptive analytics probably is the most sophisticated one,” Ohlmann says. “A lot of companies aren’t quite there yet.”
The goal of the BAIS track is to give undergrads marketable skills in these more advanced and valuable branches of data analytics.
Ohlmann says that rather than teach students using a specific vendor’s software—“a lot of universities end up being SAS shops,” he explains—Tippie College of business “will not be married to a particular technology or software package.”
“We’re still vetting software, trying to find tools with a low learning curve,” he says. “Our goal is to teach skills, rather than train students in a specific software platform.”
Mining Big Data (The Press-Citizen, 8/3/13)
Did you hear the one about the teenager in Minneapolis whose parents freaked out about the baby-related coupons Target was sending her?
Turns out, she really was pregnant; she just hadn’t gotten around to telling them yet. Target sent the coupons based on the fact that she was buying things such as unscented lotions and vitamins, things the company’s data indicated pregnant women tend to buy.
It sounds like science fiction, but it’s the reality of so-called “big data” and the level to which it allows companies to market to specific customers. In recent years, the size of datasets available have multiplied exponentially, and they’re still very cheap to store.
In conversations with professors in the University of Iowa’s Tippie College of Business, executives from companies such as Target, John Deere and State Farm Insurance said they want students trained to organize and analyze their companies’ data and use it make predictions and suggest strategies. In response, the college has created a new undergraduate degree program intended to do just that. Enter, business analytics and information systems.
Businesses long have used data to make decisions. The difference now is the explosion of data that’s available — one theory suggests the amount doubles every couple of years — and the ability of even small companies to process large amounts of data at a relatively low cost, said Gautam Pant, a Tippie associate professor of management sciences.
“It requires a small computer, not much hard-drive space — so it doesn’t cost much,” he said. “Now the question a small business may think about is, ‘What kind of questions should we ask from the data?’”
From there, it takes a more creative mind to devise a mathematical or quantitative approach to use that data to make predictions, said Jeffrey Ohlmann, Tippie associate professor of management sciences. While there certainly is a scientific method to working through the numbers, it takes a human to apply that to problems they see in the real world, he said.
“Often people view this as you dump in the software, you turn a crank, turn it a few times, out comes the answer and then you just have to be able to understand it,” Ohlmann said. “Really, there’s kind of an art form to it.”
Data also can be humbling because it can trump intuition, Pant said. It can draw from millions of observations and prove a person wrong millions of times, he said.
“Big data can prove you wrong big time,” he said. “That’s a humbling experience. It’s true failure you can learn from. That’s a very good learning experience.”
Humans tend to favor simple answers to questions, which often drives them to fall upon conventional wisdom, Ohlmann said. He called upon the example of an entrepreneur who struck it rich drilling oil wells using a different set of metrics to select drill sites than a massive oil company, which had been rejecting potential sites based on decades-old theory.
Companies will now be expected to use solid data to back up their positions, said Michael Hasler, who directs a new M.S. program in business analytics at the University of Texas at Austin.
“I think business and decision-making in general is trending away from going with your gut and more toward looking at the data,” he said.
UT’s one-year program, based in the business school, starts this fall. Hasler said it’s received significant programming support from enthusiastic companies such as Walmart, Dell and IBM. University officials projected 150 applicants and about 400 applied for the program, he said. Of those, 53 were admitted.
UI’s BAIS program, which also starts this fall, is one of the first undergraduate programs of its kind in the country. Experts say most big data-centered programs in higher education are offered at the master’s level.
A master’s-level program made the most sense for UT because Hasler said he wanted to attract students from a variety of undergraduate backgrounds such as physics, engineering and math in addition to business, which comprises about 20 percent of the students.
Ohlmann said companies have expressed interest in both students with undergraduate and graduate-level training. The BAIS program is designed to provide students with essential data analysis skills. A company could then hire them and train them on the nuances of their specific software, he said.
Other companies will look for graduates with specific master’s-level training, Ohlmann said. The Tippie College of Business is currently considering a master’s level program in big data, but it’s yet to be seen whether that will materialize, he said.
New Safety Regulations Limit Hours for Truck Drivers (KWWL, 7/2/13)
Balancing productivity with safety is always a challenge for trucking companies.
"We always want to make sure our drivers are safe and make sure that they take proper breaks," said Greg Payne, support center manager with Transport America Trucking Company.
Now, that balancing act may have gotten a little more difficult after the federal government implemented new rules that limit the number of hours truck drivers can be on the road.
The new regulations going into effect this week.
The rules require all truck drivers to take a 30-minute break every eight-hour stretch. Drivers are also limited to the amount of time they can drive between 1 and 5 a.m.
While Payne doesn't anticipate significant changes for his company, he says his drivers will lose time on the roads, hurting productivity.
"It adds cost because drivers won't be able to do all of their 11 to 14 because they need to be taking the break," Payne said.
Researchers say those lost hours add up for companies.
"They may add up to a 2 percent, 4 percent, some sort of cost increase to a company," said Ann Campbell, associate professor of management sciences at the University of Iowa. "They have to make that money back somewhere, so they're going to probably charge a little bit more for their services."
Those added costs will likely be passed on to consumers, although many believe it won't be much.
"This change impacts the things that are traveling a long way across the country," Campbell said. "A big example of that would be groceries. Groceries could maybe go up by a few cents."
While some trucking companies we spoke with off camera are unhappy with the changes, the goal is to keep tired drivers off the road.
As research has shown, a drowsy driver is a dangerous one.
"Whether it's a truck driver or a passenger vehicle driver, if you're drowsy, your performance on the road degrades," said Tim Brown, a researcher with the University of Iowa's National Advanced Driving Simulator.
Tippie Faculty Member Publishes New Text (5/20/13)
Johannes Ledolter, Management Sciences professor at the University of Iowa's Tippie College of Business, has released a new text titled Data Mining and Business Analytics with R. The text, according to publisher John Wiley & Sons, focuses on giving students the processes and tools for collecting and analyzing large quantities of data in order to derive useful insights.
Highlighting underlying concepts and practical computational skills, the book begins with coverage of standard linear regression and the importance of parsimony in
statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; nearest neighbor analysis; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In his text, Ledolter uses R, an open-source software, to guide students through the analysis of "high-dimensional" sets of data.
Ledolter has been with the Tippie faculty since 1978 and holds the C. Maxwell Stanley Professor of International Operations Management. He holds a joint appointment with the Tippie College of Business’ Department of Management Sciences and the University of Iowa's Department of Statistics and Actuarial Science. He is a fellow of the American Statistical Association and the American Society for Quality and an elected member of the International Statistical Institute. He is the coauthor of Statistical Methods for Forecasting, Achieving Quality through Continual Improvement and Statistical Quality Control: Strategies and Tools for Continual Improvement, all published by Wiley.
Information on the book is available at www.wiley.com/WileyCDA/WileyTitle/productCd-111844714X,subjectCd-STB0,descCd-authorInfo.html.
BTA Students Attend AITP-NCC (4/8/13)
Twelve Tippie undergraduate students—Cody Kehl, Megan Moran, Caitlin Bruggeman, Renxuan Xiao, Karly Holland, Mallory Brandt, Ben Ransdell, Scot Alzheimer, Dalton Friedhoff, Alex Staroselsky, J.T. Sandbulte, Dan Senter—participated in this year's Association of Information Technology's annual National Collegiate Conference (AITP-NCC), April 4-6, 2013, in St. Louis, Mo. More than 500 students competed in 12 technical competitions at the conference.
Six of the 12 Tippie students received recognition. Dan Senter and J.T. Sandbulte's team received Honorable Mention in the Network Design Competition; and two teams in the Business Analytics Competition also received Honorable Mention—Karly Holland and Renxuan Xiao, and Caitlin Bruggeman and Dalton Friedhoff. All four students are currently enrolled in the new Business Intelligence course, which is part of the new Business Analytics and Information Systems major to start this fall.
In addition, Yvonne Galusha, lecturer in management sciences and faculty advisor for the Business Technology Association student organization, received a trophy and Samsung Galaxy tablet for receiving the highest faculty score on the Institute for the Certification of Computing Professionals (ICCP) certification exams, which she took "cold" at the conference. Galusha took the exams, so she could better advise students about the tests.
All attendees accomplished a good showing for Tippie.
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