Each year, consumers create 16.3 zettabytes of information—enough to fill over 127 billion iPhones. Sorting through all this information is like trying to find a needle in a haystack the size of California.
Within these treasure troves of data are valuable insights waiting to be discovered. Data scientists use statistics, math, and information technology to sort through enormous datasets with millions of variables, looking for patterns. Yet combing through this information takes immense power, not to mention computer memory. So do they sort through it all?
That’s where people like Zhigen Zhao, associate professor of Statistical Science at the Fox School, come in.
Zhao and his statistician colleagues invent new ways to use statistics, overcome computation limitations, and see patterns through the noise. Their discoveries range from a newly patented methodology that enables users to analyze millions of data points in seconds to a new threshold for pinpointing statistical significance.
Deciphering Genetic Codes
Humans have 20,000 genes in our DNA. Much like data, decoding how each gene interacts with another can provide valuable insight, in this case into a person’s health. With over 190 million possible pairs, that’s a lot of variables to test.
“Years ago, 10,000 was considered a big data set, but not anymore,” says Zhao. When using standard algorithms like distance correlation, statisticians run into issues with computation speed, and the old algorithms can’t keep up with the large datasets available today.
Zhao and his colleagues devised a methodology that can analyze all of these variables in seconds. “Our method only takes two-tenths of a second to finish this kind of calculation,” says Zhao. His computer would crash when using older algorithm to analyze a dataset of that size.
“People’s health can depend on a specific combination of their genes,” says Zhao. This revolutionary methodology, which was recently approved for a patent, can identify certain combinations of genes that may help doctors understand medical issues ranging from heart disease and Alzheimer’s to obesity and alcoholism.
Discovering Differences in Education
With millions of pieces of information, statisticians and data scientists often grapple with the problem of false discoveries—inferring a pattern that is not truly significant. Statisticians try to account for these false discoveries, but this may lead to a less complete picture of the data.
Zhao and his colleagues created a new algorithm to reduce the number of false discoveries while keeping more pertinent patterns than other methods. Zhao’s team applied this algorithm to school districts in California, analyzing standardized test scores of students from over 4,000 elementary schools.
The researchers compared pass rates from two groups of students, the socioeconomically advantaged and the socioeconomically disadvantaged. Normally, the advantaged students will have higher scores than their disadvantaged counterparts. However, Zhao used his algorithm to identify schools that have unusually small or unusually large differences between the two populations—where the disadvantaged students were either significantly underperforming or overperforming in statewide math tests.
Their new algorithm found more schools whose populations have significant differences in test scores, providing a more complete understanding of the dataset. “The main idea for this method is to incorporate school district information to get a new threshold,” says Zhao. “The standard method, which doesn’t include this information, can be either overly conservative or overly liberal.” This kind of refined analysis can help district and state policymakers to reallocate resources to support underperforming schools or to imitate overperforming schools.
From education to healthcare and everything in between, Zhao and his fellow statisticians sort through enormous datasets, finding new ways to compute that better our everyday lives.
This story was originally published in On the Verge, the Fox School’s flagship research magazine. For more stories, visit www.fox.temple.edu/ontheverge.
As consumers, we have said goodbye to hailing taxi cabs in the pouring rain. We have stopped stressing about public transit schedules and delays. Some of us have even found alternative solutions to a costly ambulance ride.
Instead, we just get an Uber.
Ride-sharing platforms like Uber and Lyft are one of the biggest ways people participate in what is known as the “sharing economy,” through which individuals share goods, like homes and condos on Airbnb and VRBO, or services, like labor and freelance work on TaskRabbit and Upwork.
For many, participating in the sharing economy as a consumer is freeing. But how have the suppliers—those who own cars or homes—been affected in the last decade?
Jing Gong, assistant professor of Management Information Systems at the Fox School, sought out the answer.
Consumer or consumed?
Using Uber as an example, Gong could see two sides of the same coin. On one hand, the demand side, consumers who use Uber might be more willing to give up their cars in favor of the convenience of temporary ownership, what she called the “cannibalization effect.”
On the supply side, however, Gong could also see that providers may have an incentive as well. Drivers—or those desiring to be drivers—may actually invest in their cars in order to capitalize on the income available in the sharing economy.
To discover the answer, Gong and her co-authors—Brad Greenwood, associate professor of Information and Decision Sciences at the University of Minnesota’s Carlson School of Management, and Yiping Song, associate professor of Marketing at Fudan University’s School of Management—investigated Uber’s entry into different cities in China. Using a unique dataset of new personal vehicle registrations between 2010 and 2015, Gong and her colleagues analyzed new car purchases compared to Uber’s introduction to the country starting in 2013.
Because Uber came to different Chinese cities at different times, the research team was able to use a statistical technique called difference in differences, which mimics a lab experiment, to compare groups classified as controlled or treated. As the platform rolled out, the team used variables in both geography and time to understand Uber’s effects compared to the control cities.
In the paper, “Uber Might Buy Me a Mercedes Benz: An Empirical Investigation of the Sharing Economy and Durable Goods Purchase,” the researchers found that both riders and drivers have become consumers.
“The consumption of Uber needs to be satisfied by more cars being available,” says Gong. “As more people are giving up on public transportation or car ownership, others are seeing the opportunity of becoming a driver, which in return calls for an increase in car sales and trade-ins.”
Entrepreneurs without red tape
The sharing economy has made way for entrepreneurs, sans the red tape.
Gong’s study found that Uber’s arrival to a city was correlated with an increase in new vehicle ownership—about eight percent on average. The researchers estimated that roughly 16 percent of new owners were purchasing their cars in order to become Uber drivers.
The effects were varied when the researchers analyzed key conditions. First, Uber had a stronger effect on the sale of smaller cars than larger cars, with owners placing a high premium on features like fuel efficiency. Second, women were less affected by Uber’s entry into a marketplace, but still experienced a significant increase in car ownership. Finally, young people were more significantly affected, given their higher likelihood to drive for ride-sharing platforms, change jobs, and have more volatile income.
Now, having a car or a home has allowed owners to see an opportunity for financial gain. For those who are unemployed or underemployed, ride-sharing has given them the tools and flexibility of a consistent income.
Effects from Detroit to D.C.
In this study, the researchers disprove a popular myth that Uber’s arrival has people fleeing car ownership. Knowing that buyers are now looking to purchase goods specifically for participating in the sharing economy, how should manufacturers react?
“In order for drivers to stay current while being cost-efficient, they are paying attention to the type of cars they are buying,” says Gong. “Whether it is for style or fuel economy, manufacturers are willing to market specific vehicles in order to draw in drivers.”
With Uber and other platforms, workers are bypassing the formalities of employment regulations. While lawmakers have highly regulated incumbents in the industries, like taxi companies and professional car services, startups have not had to contend with such high obstacles.
“Policymakers are having to reconsider whether this business model can sustain itself without intervention,” says Gong. She suggests lawmakers be thoughtful about reducing regulations on these established industry players to provide a level playing field.
A New Frontier
It is evident that platforms like Uber have changed the economic game faster than industries can keep up.
“The sharing economy is changing the landscape because it’s consumer to consumer,” says Gong. “The dynamics are different because the drivers are consumers of cars but the riders are also consumers of cars. With the manufacturers in the mix, there are more players.”
This research, the first of its kind to analyze the impact of the ridesharing economy on car owners, can provide insights to industries across the sharing economy. The introduction of Airbnb, for example, could encourage more homeownership for those looking to make money in new hot rental markets. Manufacturers of these goods will need to understand, build for, and market to these new customers.
Powered by new technologies and an entrepreneurial spirit, the sharing economy will continue to grow in both importance and prevalence. Yet, the question remains:
Is a new car—and gig—in your future?
This story was originally published in On the Verge, the Fox School’s flagship research magazine. For more stories, visit www.fox.temple.edu/ontheverge.
Sometimes ideas for academic research can come from the unlikeliest of places. Like out of your earbuds.
Hilal Atasoy, assistant professor in the Department of Accounting at the Fox School, was hardly expecting to discover a subject that would lead to years of study while listening to a podcast, but that is exactly what happened.
“I was listening to a story about a cancer patient,” says Atasoy. In addition to being physically and emotionally difficult, having cancer can be costly. The patient explained that during her treatment she had moved and had to change hospitals and doctors several times because of her relocation and other reasons.
“She was saying how difficult it was to keep transferring her tests, results, procedures, and other records. She had to go through this ordeal again and again,” recalls Atasoy. Finally, the patient landed at a hospital with a good electronic health records (EHR) system, and she didn’t need to go to any extra trouble or expense anymore.
That got Atasoy thinking. Since the HITECH Act of 2009 made the migration of patient information from paper files to electronic health records mandatory, many studies have investigated whether this shift actually benefits hospitals, as electronic health records systems are costly to implement.
The results of previous research, particularly around healthcare costs, have been inconclusive. Studies point to the likelihood that costs actually go up—not down—as electronic health records systems are put into practice, at least for the individual hospital in question. But Atasoy’s research looks beyond the adopting hospital to the region surrounding it. “The question we’re asking in the study is whether the impacts of the electronic health records go beyond the adopting hospital.”
It’s common for someone to have a dermatologist at one hospital, get a mammogram at a different hospital, and see a primary care doctor affiliated with a yet a third institution, especially if that person lives in a city. When you factor in the costs at not only the individual hospital that adopted EHRs but also the costs at surrounding hospitals where there are shared patients, Atasoy has found that there is a marked cost-saving benefit after all. Estimates suggest that if one hospital in each area adopts an EHR system, it would add up to a net reduction of $18 billion in healthcare costs nationwide.
To conduct her research, Atasoy relied on several data sets. “We tracked information about the adoption of electronic health records systems at almost all the hospitals in the U.S. from 1998 to 2012,” she says. She also used Medicare data, census data, and HIMSS data (a dataset that comprises information about EHR use across the country). Atasoy and her team used statistical analysis software to interpret the numbers and come to their conclusions about the costs and benefits of EHR beyond the walls of any one hospital. Her research was published last year in the journal Management Science.
Atasoy notes that implications for her research extend beyond the healthcare sector. “It shows the importance of connections across different organizations. Businesses might be connected, for example, through shared customers,” she says. “Obviously, the firms are focused on their customers and their purchases and all the information they have on their customers right within their business, but there are many organizations that share customers or share suppliers. They have these connections.”
Her work on hospital-level data led into her current research, which focuses on patient-level data and seeks to identify the cost and quality of care benefits that could come with the widespread sharing of EHR between health institutions. “We’ve learned that only 20 percent of doctors use electronic health records, and what we’ve seen suggests that there are significant benefits to patients when doctors do use them,” says Atasoy. This seems to be especially true for patients living with chronic conditions such as cancer, diabetes, or heart disease.
Atasoy hopes her research will help spark a discussion about the value of hassle-free information reciprocity at hospitals, something that, on a policy level, she believes needs to be incentivized. Just as she began to look at the bigger picture, viewing hospitals regionally as a group and not individually, viewing a patient’s multi-year health journey and not just a single procedure, she hopes hospital administrators will zoom out, too.
“One big problem with healthcare in the United States is that it’s very fragmented,” says Atasoy. Her work reveals that a hospital isn’t an island and that the free flow of information will ultimately benefit everyone’s bottom line.
This story was originally published in On the Verge, the Fox School’s flagship research magazine. For more stories, visit www.fox.temple.edu/ontheverge.
Victor H. Gutierrez-Velez never expected his work to lead him to the topic of public health. His expertise lies in remote sensing science, analyzing data such as satellite images. “Every day, numerous satellite images are taken,” says Gutierrez-Velez. And the information drawn from these images has both academic and commercial applications.
For example, satellite images can help prescribe management, fertilization, irrigation, and other activities in precision agriculture, according to Gutierrez-Velez. They can help the insurance industry assess risks related to flooding or other natural disasters, or to verify crop insurance complains. Satellite imagery can allow energy companies to pinpoint the ideal location for solar panels. And this kind of data, it turns out, can even come in handy when it comes to fighting certain diseases.
To that end, partnering with colleagues with expertise in biology and public health, Gutierrez-Velez, assistant professor in the College of Liberal Arts, has recently been drawn to an unlikely research subject: mosquitoes. Specifically, the tiger mosquito (scientific name: aedes albopictus). What’s so interesting about this tiny, blood-sucking bug?
“It’s worrisome. They can spread the Zika virus and other dangerous diseases,” says Gutierrez-Velez.
In 2016 when the Zika pandemic caught his interest, mosquitoes dominated the headlines. Once thought to be limited to tropical and subtropical regions, the tiger mosquito had expanded its territory into most continents. Climate change plays a role, but these mosquitoes are also particularly aggressive. They’re among the 100 most invasive species in the world. In the 1980s, they were first spotted in the U.S. in Texas. Today, they reach as far north as Connecticut. Their presence in Pennsylvania remains an ongoing public health concern.
For his project, a recipient of the Office for the Vice President of Research‘s Targeted Grant Program and supported by the Data Science Institute housed at the Fox School, Gutierrez-Velez decided to look at multiple datasets, including climate data, information gathered from sampling for the presence of the tiger mosquito, land cover data, and census information. Gutierrez-Velez believes that with these and other datasets as inputs, machine learning and advanced algorithms can be used to predict the locations of tiger mosquito populations in advance of the season.
One of the most interesting possible findings of this research is that the tiger mosquito is less of a rural dweller than previously thought. “What we’re finding contradicts conventional wisdom about where these mosquitoes live. They are becoming domesticated animals. They prefer to be where lots of humans are living closely together—in cities. Because they love our blood,” says Gutierrez-Velez.
Scientific curiosity led Gutierrez-Velez to census data, which is not necessarily an obvious source of information to predict the presence or absence of a small flying bug. “If they feed on humans, human behavior should have something to do with it,” he says. And it does seem like including this data makes for a more accurate prediction about where the mosquitoes will go next.
Gutierrez-Velez’s ultimate goal for the project is to perfect a reliable working model that can be used to predict the upcoming mosquito season. Knowing that a particularly bad mosquito season is about to start will give officials the opportunity to plan in advance.
For example, the most affected areas can be targeted for treatment before the problem becomes unmanageable. Residents could be strongly cautioned in advance of the season to deal with housing-related conditions, such as places that collect standing water, which act as mosquito breeding areas. In the event that mosquitoes are spreading Zika or another virus, these protections could even save lives.
“There’s a lot we can do if we have a model that can say, ‘Hey, it’s going to be a bad year for mosquitoes, get ready,’” says Gutierrez-Velez.
A personalized touch can make all the difference.
When you log into Amazon, Netflix, or Facebook, one of the first things you see are recommendations for products, shows, or friends you may know—all based on things you have already bought, watched, or liked.
Recommender systems have eliminated the time-consuming effort of understanding and anticipating what exactly users want, sometimes before they know they want it. Using vast collections of detailed data points, data scientists can create a trail of digital breadcrumbs, which follows Internet users as each sale, search, and interaction becomes part of an algorithm for new suggestions. These platforms can predict and encourage your next shopping sprees, binges, and bucket lists.
In the private sector, companies have long been using technology-enhanced learning in order to proactively suggest and anticipate their consumers’ choices. But how can these mechanisms be most effectively applied to academia?
“We have to learn something new every day,” says Dr. Konstantin Bauman, assistant professor in the Management Information Systems (MIS) Department at the Fox School of Business. “With the traditional path, we go to university, take some courses, meet with the instructor once a week, and go to lectures. But today, there are many different types of tools and materials available online that are able to educate large groups in a personalized and direct way.”
Educational companies like Coursera, Lynda.com and the Khan Academy already use recommender systems to suggest courses their users may like, based on their history. Bauman, however, wanted to know whether personalized e-learning can help students struggling to comprehend a particular subject.
“Education is one important application of recommender systems for society to target materials for specific learning paths,” says Bauman.
Bauman, along with co-author Alexander Tuzhilin of New York University’s Stern School of Business, examined the personalized e-learning systems approach with the help of a tuition-free online university. By using curricula from 42 classes and test results from 910 students over three semesters, the researchers created a system to pinpoint—and address—specific areas within a student’s comprehension that needed improvement.
The team reported their findings in the paper, “Recommending Remedial Learning Materials to Students by Filling Their Knowledge Gaps,” which was published in MIS Quarterly in 2018.
In this real-life experiment throughout the 2014-2015 academic year, Bauman’s team identified where students’ knowledge waned and provided materials to supplement these gaps. “Instead of revising the entire lesson, we provided catered lessons to fill those gaps,” says Bauman.
The students had diverse backgrounds, from both the United States and developing countries, and studied in a variety of programs, from business to computer science to art history. The researchers split the students into three groups: a control group that received no recommendations, a group that received non-personalized recommendations, and a group that received recommendations tailored to the individual student.
Bauman and his team created taxonomies that mapped all the topics covered within a specific course, built a library of remedial learning materials, and matched test questions with course topics. After analyzing test scores, the researchers identified the students’ weaknesses. The students in the non-personalized group received generic recommendations for the course, while students in the personalized group received remedial materials for specific topics that were identified via testing.
“First, we showed that most of the students who received our recommendations found them relevant and helpful,” says Bauman. Second, the “average” students, who received a test score between 70 and 90 in previously taken courses, were most affected by personalized recommendations. “These students improved their performance on the final exams significantly more, in comparison to their prior performance before they received personalized recommendations than the students from the control group.” For this subset of students, the personalized group received an average grade of 83.22 in their final exams, while the control group scored an average of 79.39.
The study received limited interactions with students who were classified as “falling behind” (those whose previous grade averages were below 70) as only six students who received personalized recommendations actually clicked on the materials. Similarly, students who were “excellent” (with average grades above 90) were less likely to need remedial lessons.
Bauman found that, by determining specific materials needed to supplement their understanding, students saved time and energy in preparation for their exams.
“Learning systems have the capability of picking up patterns and behaviors that can clearly predict necessary methods that are worthwhile and timely,” says Bauman. For students and professors, time that may be used to teach a specific lesson can be accomplished through recommender systems, saving more time for interactions that encourage new ideas and understandings.
One thing is for sure—when it’s time to come back for more, a new suggestion will be waiting.
The Class of 2019 from the Fox School is full of high achievers. Jonathan Huynh is one of them, but he took a path unique to undergraduate students—a deep dive into research.
“I have always been purpose-driven,” says Huynh. “The education I’ve received at Fox has constantly challenged me to delve deeper into concepts and ideas and look at them from an out-of-the-box perspective.”
Huynh is a part of the first graduating class of undergraduate students with a Statistical Science and Data Analytics (SSDA) major at the Fox School. Looking back at his journey, “I actually started out in actuarial science, but ultimately got drawn to [this program],” says Huynh. “I liked the idea of being able to gain quantitative and analytics skills to translate large data sets into meaningful solutions.”
Dr. Pallavi Chitturi, deputy chair of the Statistical Science Department, says that the new undergraduate major in Statistical Science and Data Analytics is highly rigorous. “Students get a solid foundation in statistical methods, programming languages and statistical computing, which is why the major is gaining popularity among students and employers alike,” says Chitturi.
It is rare to see an undergraduate student so deeply involved in high-quality research. “My first exposure to research was through Dr. Robert Pred, the academic director of the Fox Business Honors program,” says Huynh. ”My friend and I did an independent research project over the summer of 2017 and Dr. Pred helped set us up with an advisor to oversee our research.”
Since then, Huynh became involved with data science research projects at Temple’s College of Public Health. One of the ongoing projects that Huynh is working on compares the difference between the cost to patients and their outcomes at the Temple University Hospital versus other hospitals in the area. “Dr. Michael Halpern, an associate professor in the College of Public Health, reached out to us as they were looking for a research assistant with strong statistical skills and Jonathan was a perfect fit,” says Chitturi, who presented Huynh with this opportunity. “Dr. Halpern was so impressed by the quality of his work that he later hired another student from the SSDA major.”
Huynh largely attributes his early success to the well-designed and differentiated curriculum at the Fox School. “I’ve seen how beneficial it is to have technical skills backed by an understanding of business for courses in data science,” Huynh says. “It allows you to be at the intersection of knowing how to comfortably work with data to drive business decisions–a skill that recruiters highly value.”
Huynh plans on pursuing a master’s degree in the near future and is looking at specialized fields of data science such as Artificial Intelligence and Machine Learning. When asked if a doctorate in data science is in the cards, Huynh says he believes education is a matter of continuous learning. “Even if I don’t pursue formal education [like a PhD], I will always be self-learning… and keeping up-to-date with the latest technologies,” says Huynh.
Huynh‘s ultimate goal is to run a startup that uses data science to solve important problems that have the potential to improve the world. “I have always had entrepreneurial aspirations,” says Huynh. “The connections that I have made at Fox and the experiential learning opportunities I’ve had here have really shaped my perspectives and prepared me to achieve these goals.” He has already started on this journey, having participated in 2019 Be Your Own Boss Bowl ® pitch competition and winning the “Crowd Favorite” award.
As of now, Huynh is all set to begin his foray into the corporate world as a Business Technology Analyst at Deloitte in the Government and Public Sector practice. Huynh says, “The thing I am most excited about is to be able to make a real impact in the everyday lives of people, as I will be working on projects with government agencies to make the lives of people easier.”
Learn more about programs in the Department of Statistical Science.
Change doesn’t happen overnight, especially in education.
For years, academics and business executives alike have questioned whether the insights from business school research conducted are getting into the hands of those who need it. The debate about “rigor versus relevance” is age-old. While the answer may seem simple, the process of getting there is complex.
The Fox School of Business is committed to pushing this conversation forward. On Friday, March 29, the Fox School’s Translational Research Center (TRC) hosted the 2019 Impact Summit, bringing together deans, faculty and students from across disciplines and parts of the world to determine how schools can move the needle of impact in tangible ways.
The attendees sought to answer the question: How can business school leadership change the way research is conceived, produced and implemented to prioritize impact?
These are five lessons business school leaders can apply:
1. Start at the top. “It takes time to re-engineer a school at a systems level,” said Tarun Khanna, a professor at the Harvard Business School. However, a top-down perspective is key to encouraging institutional change.
Jerry Davis, associate dean at the Ross School of Business, highlighted the University of Michigan’s experiments with the promotion process. By making research impact a more significant part of an associate professor’s evaluation, he advised, deans can use promotion structures to affect change in the way their faculty conduct research. Getting top business schools across the country to agree on a new evaluation structure would be even more influential.
2. Instill impact’s importance early. The attendees also discussed tackling the issue of impact from the opposite side—starting with junior faculty and doctoral students. Elizabeth Cowley, deputy dean of the University of Syndey, said that in Australia, “faculty are encouraged to build a narrative of the long-term impact [they] have had on some sector of society.” Attendees agreed, remarking on the importance of letting junior faculty members define for themselves how they would want to make an impact and develop a strategy based on that objective. With doctoral students, the starting point should be their research questions—advisors should ask if it is grounded in a real-life phenomenon and has relevance in the business world.
3. Systematically engage with business. “Business leaders tend to look at our schools primarily as labor markets for sourcing the MBAs and business graduates,” said Joanne Li, dean of the business school at Florida International University. “We need to help them recognize us as knowledge markets as well. We are able to produce expert knowledge vital for their business growth and survival.”
Brent Beardsley, the chief strategy officer at Vanguard, talked about the value of an advisory board made up of executives, entrepreneurs and academics. “That mix is really rich,” he said. “This is a lab outside of the walls of Vanguard’s large institution that can get out in front of market trends and themes.”
Participants championed the creation of a brokerage platform between companies and universities that could connect those who have real problems to those working on practical solutions. Simple activities like business sabbaticals for faculty, corporate engagement in research projects and programs like Fox Management Consulting can help faculty to better define their research questions.
4. Use teaching as a tool. One speaker suggests a change in vocabulary to underscore the importance of teaching. “We shouldn’t be referring to a ‘teaching load,’ said Gautam Ahuja of SC Johnson Graduate School of Management at Cornell University. “It’s not a load, it’s a tool.” Academic leadership can encourage faculty to step into the shoes of learners, focus on practical insights in the classrooms and foster intellectual questions with relevance. Stronger connections to industry, through practitioner conferences, relationships with practice faculty and co-teaching with executives can also benefit classroom outcomes.
5. Be a community hub. Business schools will also benefit from a stronger community connection. “We should be known by the community where they can come to get ideas,” said Will Mitchell, a professor at the University of Toronto’s Rotman School of Management. Attendees brainstormed ways to make research more accessible but noted that faculty will need different reward structures and training to bring that to fruition. Ideas like three-minute presentations or one-page summaries of academic papers can help get ideas out of academia and into the real world.
Ronald Anderson, interim dean of the Fox School, remarked at the end of the day that a lot was learned. “Disruption is going to have to be part of the process,” he said. “Technology and innovation are changing higher education, and research is going to have to address that.”
The event, a follow-up to the 2018 Editors’ Summit, is part of a series of initiatives by the TRC to change how both academics and practitioners view business research. Other activities have included the TRC’s Seminar Series, which invites executives to share their viewpoints on faculty research presentations, and case writing workshops, which encourage faculty members to learn and perfect their skills in writing and submitting teaching cases for publication.
Learn more about the Fox School’s Translational Research Center.
More than 15 million adults struggle with alcohol addiction. In fact, according to the CDC, one in ten deaths of working-age adults in America is linked to alcohol. That’s one reason data on alcohol use has been chosen by researchers for study from the enormous data set from the U.S. Department of Veterans Affairs’ ambitious Million Veteran Program (MVP). The VA intends as the project’s name states, to gather data on an astonishing one million service members.
Kuang-Yao Lee, assistant professor of statistical science at the Fox School, sees a world of potential new knowledge in this vast cache of data. This is particularly true of alcohol use because the data from the MVP is longitudinal, which means the same measurements are tracked over time. Alongside the support from the VA, Lee’s project received funding through from Office for the Vice President of Research at Temple University.
Volunteers in the MVP each submit blood samples as well as health surveys, amassing a dataset that comprises both genetic data and behavioral patterns. Beginning in 2016 when he was a researcher at Yale University, Lee and his colleagues have been using this information-rich resource to search for the specific combination of genes that correspond to alcohol and other substance use.
“Previous studies have suggested [these genes exist], but mostly were only limited to small scales or restricted conditions,” says Lee. “We want to use statistical models to find out if this is really a valid assumption. Our results so far suggest a very strong association.”
While ample electronic health records and genetic data have long been available to researchers, only recently has the efficient computing power become available to slice and dice the information into accurate, usable new insights and discoveries. More sophisticated algorithms combined with larger-than-ever computer storage capacity, as well as parallel computation techniques, allow today’s researchers to make meaning from a huge amount of complex data.
How huge? “Depending on the facility, the whole genome sequencing [for one person] can produce hundreds of millions of variants,” says Lee. Questionnaires allow researchers to gather large amounts of information about each subject every time they are administered. Multiply that by one million veterans. “We’re talking about not just billions, but millions of millions of points of data,” he says.
Data with this level of complexity can lead to findings that are more nuanced and reliable than in the past. Previously statistics sometimes led to oversimplified and other not-quite-right conclusions. We’ve all heard the old axiom, “There are three kinds of lies: lies, damned lies, and statistics.” But as so-called big data increases in scope and complexity and the tools used to analyze this data become more sophisticated, statistics are becoming more honest than ever before. From projects such as the Million Veteran Program and other similarly vast datasets, new genetic truths may ultimately emerge.
There are many possible real-world applications for this research. For one thing, determining which specific genes are linked with alcohol and other substance abuse could lead to new and better medicines and treatments for the very veterans who have volunteered their most sensitive personal information for this work. A dialed-in genetic profile that indicates a vulnerability for substance abuse could be used to screen kids and even adults while there is still time for effective early interventions that can keep them on a healthy path. Given the current public health crisis around opioids, alcohol, and other substance use, a breakthrough of this kind could have far-reaching benefits.
Lee says that the knowledge gleaned from the Million Veteran Program about substance abuse may lead to similar projects that could help solve other vexing behavioral, health, and genetic puzzles. He also notes that the innovative statistical models and tools he’s used in this research could be applied in myriad ways to other complex datasets.
For example, online shopping platforms can easily observe huge amounts of individual consumers and, at the same time, collect data across large numbers of variables. “One of the core problems in business analytics is to use statistical models to study the inter-dependency between observed variables, for example, the dependency between decision making and consumer behavior,” Lee says.
“There are a surprising number of similarities between genomics and online shopping.”
Everything around us seems to be getting smarter by the day—like smart refrigerators, driverless cars and robotic assistants. The “Internet of Things” (IoT), which is the internet-enabled network of everyday devices, has become prevalent in our lives, both inside and outside of the workplace. But with the rapid developments in recent technologies like Artificial Intelligence (AI), will these intelligent systems make human workforce redundant?
In other words: do we run the risk of being replaced by machines?
Paul Pavlou, Milton F. Stauffer Professor at the Fox School, argues that instead of replacing us, AI and humans will work side-by-side to address some of the bigger problems that neither can solve alone. Popularly referred to as “Augmented Intelligence,” this concept focuses on the assistive role of AI to improve human intelligence, rather than computers fully taking over our jobs.
Man vs. Machine
While computers have the ability to collect, aggregate and analyze an enormous amount of data, humans surpass machines when dealing with ambiguity, vagueness and incomplete information. Augmented Intelligence recognizes these complementary strengths and problem-solving capabilities of man and machine. “This collaborative interaction between human beings and computers arises when IoT collects the data and AI tools perform calculations based on criteria determined by humans,” says Pavlou, who is also the co-director of Temple’s university-wide Data Science Institute.
For example, GIANT Food Stores has introduced “Marty,” a robotic assistant, to the 172 stores in Philadelphia and the surrounding region. The robot roams the store, seeking to identify and eliminate spills from foods, products or liquids. Other examples can be found in the retail industry, where location-based technology devices and eye-tracking devices can help optimize the placement of merchandise. Meanwhile, salespeople equipped with mobile devices can leverage personalized information in real-time to sell products customized to individual shoppers.
A More Human IoT
In the future of work, managers can embrace both the fully-automated and Augmented Intelligence solutions. This choice depends on factors such as the nature of the task, expected performance and the costs and risks of autonomous IoT solutions that would operate without any human interventions. For example, automated manufacturing, predictive maintenance and security IoT solutions may—cautiously—be fully automated. But in industries like healthcare, cybersecurity and financial technology, human oversight will still be crucial.
For the time being, appropriate IoT designs should maintain a reasonable level of human control and oversight, says Pavlou. “This will give us adequate time to get comfortable with delegating control to machines.” In the distant future, machines alone might dominate decision-making in most applications. However, Pavlou says, “It will be a fairly long time until this happens. Until then, major intellectual advances will be made by humans and computers working together.”
NAO came to Temple University about three years ago, when Li Bai and Carole Tucker, researchers from the Colleges of Engineering and Public Health, and, joined Heidi Grunwald, director of Temple’s Institute for Survey Research, to study robotics and surveys.
The team wanted to explore a big idea: What if NAO, this cute, two-foot tall, human-ish robot, could be programmed to give health surveys to children on the autism spectrum? Could they create a system to collect patient-reported outcomes in this tough-to-survey population?
Potentially, this research could solve a number of difficult problems. Currently, its parents fill out surveys on behalf of their kids. Researchers would prefer patient-reported outcomes. It’s much more accurate than information filtered through a third party, such as a parent. “Kids with autism may be willing to say they are depressed, but not in front of their mother,” says Tucker. When a one-foot-tall robot with a cute robotic voice such as NAO is asking questions instead of a human clinician, researchers might get reliable patient-reported outcomes in a way they have not been able to in the past.
The team’s research would also include another stream of valuable information: para-data. The camera inside the robot would “watch” the subject as NAO asked the survey questions. Additionally, via the sensor the subject wears (a Microsoft wristband), researchers can monitor things like facial expression, heart rate, and body motion. This para-data is a rich vein of knowledge, particularly when combined with the survey questions, response time, and answers.
If the subject pauses an extra long time when a certain question is asked, the NAO can play a game (like rock, paper, scissors), take a break, or give a high five to reduce anxiety. This is one way that the robot uses para-data to adapt to a child’s answers. The para-data also helps the researchers better understand survey responses. “For example, we can tell if a particular question made a subject nervous and then down-weight the answer, or not count it,” explains Grunwald.
“The robot’s face is much less complex than a human face and human facial expressions,” says Tucker. That makes it much less overwhelming for a young person on the autism spectrum who may find it challenging to read people’s faces and maintain eye contact.
Their project received funding through the Office for the Vice President of Research’s Targeted Grant Program at Temple University, with matching funds from all three represented schools.
Planning the research has been an iterative process. On the computer science side, Bai and his engineering students have been exploring the feasibility of using NAO this way. Bai and the students have been answering questions like, “What features would be nice? How can we use sensors to pull in data and incorporate the Microsoft band?” They have iterated and refined the data architecture, a database where the data are meshed together so that the robot can read all of the survey response data–coupled with the para-data (sensor data).
Meanwhile, the questionnaire and para-data collection process have been tested on different groups, starting with older kids not on the autism spectrum. As trial subjects, children aged 10 and up can provide specific, meaningful feedback on interacting with NAO. More recently, a community event brought a group of children on the autism spectrum to campus, and the team had an opportunity to see NAO interact with the intended study subjects. Going forward, they have the kind of pilot data that can win the funding to drive this effort forward.
This work can benefit groups beyond younger people on the autism spectrum. Any time data reported directly from a patient may be skewed or inaccurate—such as dementia patients, for example—the survey methods used in this work could prove enormously helpful to clinicians.
“With future improvement in this type of research, I think we will see more robotic diagnostic platforms that will be developed. One of the functionalities will be surveys of the patients about their health conditions. It could be particularly important for people who can not find a good hospital in their neighborhood,” says Bai.
Practical applications of this work in the future aren’t limited to the realms of research and medicine by any means. “Artificial intelligence and robotics will be the next technology push to drive the economy of our country, There will be countless business world applications—such as personal robotic assistants (such as the iPhone’s Siri) or self-driving cars,” says Bai. He believes that the technology in this project will fuel innovations across all sectors of the economy in the years to come.
Etsy—the online treasure chest for all things handmade—cultivates a community for those who have a knack for crafts like candle-making, knitwear, jewelry, or pottery. With over 1.7 million active vendors and close to 28.6 million active consumers, Etsy has established a peer-to-peer business platform that eliminates the middleman of corporate production. Yet this marketplace is more than just an e-commerce site; it is a community of like-minded individuals who appreciate handicrafts.
Within the site, buyers and sellers interact through a variety of IT-enabled features, like following and messaging shops, reviewing and favoriting products, and curating lists of products. Yet as sellers socialize by favoriting and promoting others’ products, are they redirecting potential customers away from their shops?
Professor Sunil Wattal and doctoral student Ermira Zifla of the Management Information Systems Department at the Fox School of Business investigate how social mingling affects e-commerce marketplaces in their paper, “Understanding IT-enabled Social Features in Online Peer-to-Peer Business for Cultural Goods.”
“What really fascinated us about this platform is that you have this community aspect, but you are also introducing this e-commerce agenda,” says Wattal.
“We thought that sellers may have mixed incentives to participate in the online community,” adds Zifla. “On the one hand, participating by following others and posting in forums may increase the visibility of sellers and subsequently increase their sales. On the other hand,” she continues, “following other sellers and sharing their products could negatively impact sales by diverting traffic away from their own page.”
While online communities have often been the subject of research, this is one of the first studies to link social indicators with economic performance. Using a dataset of nearly 2,000 sellers on Etsy, Wattal and Zifla examined their interactions in the online community and found how socializing with others can inherently affect a shop’s sales.
The researchers identified two categories of social e-features that promote new products and validate users:
1. Community participation features—such as following other sellers and joining teams—which facilitates socializing with other members, and
2. Content curation features—such as curating favorite lists, sharing products, and favoriting shops—which serve as tools for validation and tastemaking.
“When you are following other people on Etsy, those people are listed on your page as a form of validation, for what you like to buy as a consumer or what you can provide as a producer,” said Wattal.
The researchers hypothesized that community participation and content curation would increase a seller’s online status by increasing their number of followers, but would decrease a seller’s sales by diverting attention away from their own products.
Using a web crawler to collect public information, the pair obtained a dataset of 1,728 unique glass sculpture sellers—a randomly chosen subcategory of marketplace shops on Etsy—to compile a year’s worth of data, including sellers’ followers, lists, favorited products, and sales.
Analyzing the data proved the researchers’ hypotheses correct: a 10 percent increase in community participation, like following other sellers, and content curation, like favoriting products, resulted in a 3.89 percent decrease in sales. Yet this reduction was outweighed by the effects of cultivating a stronger social following. In other words, the same activities that led to a direct decrease in sales helped sellers attract more followers, and were associated with an indirect increase in sales by 4.64 percent—an overall net gain.
“IT-enabled features have benefits that supersede the negative,” says Wattal, “since exposure is what can ultimately lead you to be on an influential list or you can simply commercialize yourself to the point of high-status.”
Trends can come and go as quickly as a trendsetting blogger changes her mind. Yet in the realm of vintage trinkets and artisanal finds, relationships stay relevant.
This story was originally published in On the Verge, the Fox School’s flagship research magazine. For more, visit www.fox.temple.edu/ontheverge.
What was it like to be a woman earning a doctorate degree forty years ago? Dr. Gloria Thomas, PhD ’80, has firsthand experience.
Today, Dr. Thomas is an accomplished researcher, a dedicated professor, and an esteemed administrator at Baruch College.
But in 1980, she was a trendsetter for women at the Fox School of Business.
As the first woman to obtain a doctorate from the Fox School, Thomas received her PhD in marketing, a field that is now predominantly women, but was all men during her tenure at Temple. “Women were very uncommon in business PhDs, even marketing, when I was in school,” she recalled. “And I rarely saw women at conferences.”
Dr. Thomas is currently a professor of marketing and the Director of the Zicklin Undergraduate Honors Program at the Zicklin School of Business at Baruch College, City University of New York. Thomas praises her experience at Temple University for the appreciation she has developed towards public institutions.
“Temple has taught me to believe in public education,” Thomas professed. “I went to Baruch right from Temple and we have really smart students from all over the world with parents who don’t speak English or have any money.” After years of private schools, Thomas’ experience at the Fox School helped her appreciate the value of diversity in education. “Cultural exposure makes public institutions more valuable and it gives students opportunities they normally wouldn’t have,” she said.
With undergraduate degrees in math and art history, Thomas pursued a doctorate in marketing. Following graduation, she went straight to Baruch, where her roles included professor, associate dean, and director of the doctoral program. She currently serves as director of the business honors program.
“My current role is my most favorite,” Thomas said. “Many students at large public schools don’t get the attention they would at a private school, but I make sure to give that attention in my honors program.”
Thomas credits her mother, a graduate of the University of Pennsylvania’s law school in the 1940s, for her then unconventional educational choices. “I grew up thinking everyone was equal. I never thought that [by going to business school] I was going into a man’s profession,” Thomas said.
That ‘man’s profession’ has changed. Today, 50-percent of PhD students are women at the Fox School, compared to 45-percent for all business-focused doctoral programs in the United States, according to the Council of Graduates Schools’ 2017 report.
Thomas did not let any obstacles get in her way of her goals. “It never occurred to me that women couldn’t do whatever they wanted to,” she recounted. “In reality, many women [at that time] didn’t even know they had options.”
“It never occurred to me that I didn’t.”
Learn more about Fox School Research.
Data-driven decision-making is now the norm in many workplaces. Executives collect and analyze information to inform hiring practices, promotions, and insurance premiums. However, Leora Eisenstadt, assistant professor of Legal Studies at the Fox School, warns that the kinds of data that employers can track should be safeguarded by law, to both protect employees’ privacy and limit employers’ liability.
For many, work and personal time have begun to blur together as smartphones and emails have invaded the home. As this line erodes between the home and office, employees are often left unaware that their employers can glean so much information from their personal lives. “Most of us have left enormous data trails,” says Eisenstadt, “that employers are now beginning to access in order to create the most efficient workplaces possible.”
With social media, FitBits, and online healthcare platforms, Eisenstadt says, employers are gathering data from more than just workplace activities. Healthcare service platforms, for example, can tell by looking at internet searches, prescriptions changes, or specialist appointments that employees are planning to start a family or have major surgery.
The platforms indicate that only top-level numbers are shared with employers, not individual names of employees. However, she argues, “that knowledge could lead to companies making decisions about promotions, hiring, and terminations based on this information.” Narrowing down gender and age, for example, could give employers enough clues to know which of their employees were likely to be trying to have a baby soon.
In her paper, “Data Analytics and the Erosion of the Work/Non-Work Divide,” which was accepted for publication by the American Business Law Journal, Eisenstadt asserts that the current legal statutes do not provide enough protection to both employers and employees. “Laws like HIPAA and the Pregnancy Discrimination Act likely do not apply to data gleaned from search queries,” she says. And there are virtually no laws or regulations prohibiting employers from collecting and relying on data gleaned from employees’ social media profiles, from facial recognition software, or from Fitbits.
So why should employers care about overreaches into employee privacy?
“The erosion of the work/non-work divide will impact the concept of a ‘scope of employment’ and employer attempts to avoid liability for their workers’ actions,” says Eisenstadt. Over the years, courts have seen the line blur between personal and work-related activities—like a case in 1928 in which an auto sales manager crashed a car, killing an employee on the way home from a staff appreciation dinner. The courts found the company liable for the death, and considered the events to be “within the scope of employment.” This move toward an expanding “scope of employment” has only grown with the advent of laptop computers, smartphones, and the myriad other devices and technologies that make it easier and sometimes even essential to bring work outside of the traditional physical boundaries of the workplace.
By gathering data from nonwork activities, Eisenstadt cautions that employers may be pushing this trend to new, more troubling places. By eroding the work/non-work divide so dramatically, companies may be opening themselves up to new liabilities for employee health issues, violent outbursts, or other employee behavior that would previously have been considered to be outside the “scope of employment.”
Data analytics can be an extremely powerful tool. “It allows humans to capture, analyze, and use massive quantities of data,” says Eisenstadt, “that the human brain can not make sense of on its own.” Yet, in today’s environment of data concerns and privacy breaches, Eisenstadt warns, companies should be cautious of data mining that goes too far.
In today’s fast-paced society, if there is one word that doesn’t escape us, it is “busy.” How does this ongoing obsession with the idea of being busy affect the choices we make?
As a behavioral scientist, Monica Wadhwa, associate professor in Marketing and Supply Chain Management at the Fox School, studies the impact of having a busy mindset on decision making. In a paper that was recently published in the Journal of Consumer Research, Wadhwa discovered that people who see themselves as busy are more likely to make decisions that are beneficial in the long run, such as making healthier choices.
Prior research has established that high-stress situations—especially when work has to be completed within set deadlines—impair consumers’ ability to exercise self-control. As a result, people tend to give in to impulses that have negative long-term health consequences.
But turns out that that is not the end of the story. While being overworked can be problematic, there are benefits to feeling busy.
Wadhwa highlights that there lies a difference between being busy under time pressure and having a busy mindset. “A busy mindset is merely a perception that one is busy,” says Wadhwa. “Two people could have the same amount of work to do, but the perceptions of busyness could differ.”
Wadhwa notes, “Feeling busy gives people a sense of pride.” This behavior stems from the fact that busy people are perceived to be more important and have a higher social status. “It makes us feel valued and makes us believe that every moment of our lives matters,” says Wadhwa. “When you feel you are important, you make decisions that are better for you from a long-term beneficial perspective.”
For example, if one had to choose between an apple and a chocolate brownie, someone who is under significant time pressure would give in to their momentary impulses and pick the brownie. However, a person with a busy mindset would more likely focus on the long-term implications of the choice. Wadhwa says, “They’re more likely to choose the apple, favoring health consequences over taste, which provides only immediate gratification.”
To capture the busy mindset behavior over a wide range of scenarios, Wadhwa and her fellow researchers, Jeehye Christine Kim and Amitava Chattopadhyay, conducted seven experiments, including a field study. In one of the experiments, the researchers analyzed the buying pattern of students at a college dining hall. “We created two types of visual signs to be posted on different days,” explains Wadhwa. One read “Good to go, for busy college students!” whereas the other read “Good to go, for summer college students!” Wadhwa notes that the days when ‘busyness’ was made salient through visual signs, students chose to consume less unhealthy food and fewer fat calories.
To analyze how busyness affects branding, the researchers compared the buying behavior of consumers for brands perceived to be indulgent, such as Carl’s Jr. For the study, consumers were shown an advertisement that featured a tagline that either made busyness salient (It’s good to go for busy college students) or not (It’s good to go for college students). Those participants who saw the ad with busy tagline were less likely to consume the indulgent food from Carl’s Jr. than those who saw the ad with a non-busy tagline. It turns out that for brands that are not perceived as indulgent, such as Subway, busy taglines did not negatively impact consumption behaviors.
The researchers also studied the impact of this mindset on other self-control situations, like saving for retirement among adults and making good grades among students. “We asked adults the percentage of income they are willing to save,” says Wadhwa. “Busy people were willing to save more.” Similar behavior was seen in students—busier students said they’d rather take extra credit even if it means more work.
The findings of this study, besides adding a new dimension to the otherwise popular perspective of being busy, also have important real-world implications, especially to marketers. A growing number of commercials are using the busy appeal to make the product more relevant and favorable to new-age consumers. But the study shows that this strategy could backfire for brands that are perceived as indulgent. “For instance, Dunkin Donuts’ advertisements using a busy appeal may actually reduce consumers’ desire for donuts,” adds Wadhwa.
To consumers and policymakers who are concerned with people’s self-discipline, especially in societal problems such as overeating and food waste, Wadhwa offers: “Perhaps activating a busy mindset may be an effective nudge to facilitate self-control behavior.”
It’s the moment every woman dreads: A routine breast self-examination during an otherwise relaxing shower ends in the panic-inducing discovery of a lump.
Often, what happens next is a long, harrowing journey through a combination of biopsies, surgery, chemotherapy, and radiation. While it’s true that, thanks to advancements in screening and treatment, more and more women survive breast cancer, it’s also true that 80 percent of breast cancer cases have already advanced to an invasive stage at the time of diagnosis.
Today, just 20 percent of breast cancers are identified at the earliest stage, when treatment is most effective and the five-year survivorship rate hovers near 100 percent.
Carlos Barrero, MD, and Oscar Perez-Leal, MD, assistant professors in the Pharmaceutical Sciences Department at Temple University’s School of Pharmacy, wants to change all that. “I believe we can invert those numbers so we’re discovering 80 percent of breast cancers at the very earliest stage,” he says.
The research Barrero and Perez-Leal are conducting may represent a major breakthrough in breast cancer screening. Their work could lead to a simple routine blood test that detects breast cancer sooner than ever before for more women. To do this, Barrero and Perez-Leal are working on identifying a set of biomarkers for breast cancer, a specific signature of early-stage breast cancer detectable in a blood sample.
Their work on this project received funding through the Office for the Vice President of Research’s Targeted Grant Program, and the team is currently in the process of securing additional funding from the National Institutes for Health, and the National Cancer Institute. Perez-Leal is also using the knowledge gleaned from his master’s degree from the Fox School’s Innovation Management & Entrepreneurship program to turn the idea into a feasible product.
Though mammograms are a recommended cancer screening for women age 40 and older, only 65 percent of women over 40 have had one in the past two years, according to the Centers for Disease Control.
“Many women avoid mammograms because they can be uncomfortable, and because of the hassle of needing to make a separate appointment. If screening for early-stage breast cancer became a part of routine blood work, more women would be screened regularly,” says Barrero. That would likely result in more early diagnoses, more effective treatment, and ultimately more long-term cancer survivors.
Through systems biology, advances in mass spectrometry technology that allow the detection of very low concentration of proteins and metabolites, and the availability of large public datasets from thousands of breast cancer tumors, Barrero and Perez-Leal can move this cutting-edge work forward. “Most research of this kind starts with analyzing the blood sample. We start by analyzing the data,” says Perez-Leal. It’s a fresh approach to a longstanding problem.
The researchers start by looking for specific proteins secreted by breast cancer tumor cells across many thousands of samples drawn from breast cancer tumors. The team is searching for a signature set of proteins that can be detected in very low amounts. A vast data set and formidable computing power are essential for finding the precise biomarkers that could, in five to 10 years, lead to the blood test. Recently upgraded mass spectrometry equipment at Temple’s School of Pharmacy allows him to carry out this innovative research.
The promise of this research extends even beyond the hopes of early detection into the possibility of new, more effective medicines to battle breast cancer. Going forward, biomarkers are likely to be an increasingly hot topic for those in the pharmaceutical industry, which represents a significant part of the U.S. economy. Biomarkers such as these are often used as a reference point in drug development; when the biomarkers diminish or disappear in blood tests, it’s evidence that the new drug is working.
Current treatments for breast cancer are effective, but they come with their own health risks and side effects, some of which lead to different health challenges years after patients have recovered from cancer. The identification of these biomarkers would also mean that, in addition to early intervention, a breast cancer patient could get a form of personalized medicine, which is another area of potential business growth for the pharmaceutical industry. For patients, that might mean fewer side effects and complications down the line.
“It’s rare to find a scientist with a business background,” says Perez-Leal. He praises the Innovation Management and Entrepreneurship program with helping him take an idea, establish a business plan, and pitch to investors. “The research community should continue to focus on finding solutions and products to real problems.”
Clearly, breast cancer is a real problem, as the most common cancer among women: one in eight will face a diagnosis in her lifetime. But if Barrero and Perez-Leal succeed, it will be a game-changing advance. Many more women will be diagnosed in cancer’s earliest stages, receive more personalized treatment, overcome the disease, and lead long and healthy lives.