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.
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.
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.
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.
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.
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.”
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.
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.
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.”
There are two types of neighbors in a social network: the ones you know directly, and the ones your friends know. Research has shown that direct peers have a significant influence on social networks, from joining Facebook to subscribing to Netflix. Yet indirect neighbors—those with whom you have a mutual friend, but do not interact directly—can also affect behaviors.
“People want to know what others think of them,” says Paul A. Pavlou, senior associate dean of research and professor of management information systems at the Fox School, “especially those in similar positions. In order not to lose influence, an individual would eventually make the same judgment and same decision as his peers.”
Pavlou, alongside co-researchers Bin Zhang of the University of Arizona and Ramayya Krishnan of Carnegie Mellon University, studied how direct and indirect peers influence groups by using Caller Ring Back Tones (CRBT) adoption in Asian cellphone markets, in their paper published in Information Systems Research last year. In analyzing 200 million calls from 1.4 million users, the researchers overcame statistical and computational challenges of the immense dataset by using subpopulations of 200 or 500 people, each group its own network of friends.
The researchers found that, in the larger group, indirect peer influence has a significant positive effect. In the case of CRBTs, a caller’s knowledge of her acquaintances’ use of ringback tones encourage her to be “on-trend” and thus adopt the same behavior. Yet in a smaller group, a caller has a greater desire for individuality, resulting in a decision not to adopt.
This study sheds more light on the complicated, large-scale networks that exist today. By understanding how peer influence works with both direct and indirect neighbors, businesses can learn the best strategies for things like product diffusion, content creation, and software adoption within social networks. “If businesses want to trigger higher adoption rates, then for smaller groups, they only need to focus on individuals with many direct connections,” says Pavlou. “While in for larger groups, they should not only focus on popular individuals but also those who have many common friends.”
How much is a hashtag worth to you?
This simple symbol has become ubiquitous across many social media platforms. Started in August 2007, the hashtag, also known as the pound (#) sign, was officially adopted by Twitter in 2009 as a way to group conversations and aggregate similar themes. Now, having spread to sites like Instagram, Facebook, LinkedIn, and Pinterest, the hashtag has become a key element of many companies’ social media strategies. With that pervasiveness comes power—and pitfalls.
“Creating an original hashtag gives a firm control over a specific social media space,” says Subodha Kumar, professor of Marketing and Supply Chain Management at the Fox School. Businesses can use this tool to increase recognition of their brand, generate buzz, and expand their audiences.
Yet creating a hashtag does not automatically mean the company owns it, says Kumar. Hashtags are susceptible to hijacking, in which competitors or consumers use the hashtag for unofficial messaging—like when McDonald’s attempted to generate positive publicity with #McDStories but instead received thousands of complaints about the fast food chain.
So, how can a company protect its social media reputation? For some, the answer lies in trademarking.
“The trademark protection of hashtags can increase consumer confidence,” says Kumar. Since the U.S. Patent and Trademark Office began allowing hashtags to be registered trademarks in 2013, more and more companies are protecting their intellectual social media property. In 2015, nearly 1,400 hashtags were submitted in trademark applications. “It prevents other competitors from using similar hashtags to mislead consumers.”
However, trademarks may come with a price. “Trademarking a hashtag may prevent or restrict its use,” Kumar says. The successful spread of a hashtag lies in its ability to be used by anyone, connecting millions of Twitter threads and Instagram photos into one conversation. By trademarking, companies could be stifling this kind of organic engagement.
Little research has been done to understand whether a trademarked hashtag makes a firm’s social media audience more or less engaging. Kumar, along with Naveen Kumar of the University of Memphis and Liangfei Qiu of the University of Florida, wanted to know: does trademarking a hashtag defeat its original purpose?
Kumar and his co-authors investigated the tension in these two opposing sides—the organic nature of a hashtag and the restrictive nature of a trademark—in their paper, “A Hashtag is Worth a Thousand Words: An Empirical Investigation of Social Media Strategies in Trademarking Hashtags.”
The researchers compared firm-level tweet data from 102 companies, split between a “treated” group of companies who had trademarked a hashtag between 2014 and 2017 and a “control” group of similar firms. The study compared tweets from before and after the hashtag’s trademark approval, analyzing the level of engagement through likes, comments, and tweets, as well as the linguistic content of the tweet, including its emotions, tone, and style.
Based on this study, Kumar and his colleagues discovered some key factors of making a trademarked hashtag work for a company:
1. Companies that trademark hashtags have higher social media engagement.
This study is the first to identify that trademarking hashtags can improve firms’ engagement with its audiences on social media—though the effects have varying levels of intensity for different types of firms and social strategies. “Trademarking a hashtag can increase the number of retweets by 27 percent,” says Kumar, “which is a considerable amount.”
Yet firms can not trademark hashtags arbitrarily. The U.S. Patent and Trademark Office treats hashtags like any other trademark: in order to be approved, the company needs to prove that the hashtag is a key part of the firm’s identity and that trademarking works in the consumers’ favor by preventing or reducing confusion.
2. Trademarking hashtags works better for smaller, less popular companies with fewer Twitter followers.
While the study demonstrates that trademarking increases social media engagement, Kumar and his colleagues investigated how this effect varies among different types of firms. After comparing the companies in the top and bottom percentiles in terms of Twitter followers, the researchers found that firms with fewer Twitter followers had more significant increases in their engagement after trademarking hashtags than companies with larger followings.
Kumar hypothesizes that small companies see larger positive effects because fewer consumers are aware of their brands and products. “Without trademark protection, other competitors can easily use similar hashtags to mislead consumers,” he says. “In contrast, for popular firms with more Twitter followers, it is more difficult to mislead consumers, even in the absence of trademark protections.”
3. Writing styles are more important to firms that use trademarked hashtags.
The researchers also studied how companies used language in their social media strategies to understand the key drivers that cause trademarking hashtags to increase engagement. “This is based on the assumption that the way that people use words reflect how they think,” says Kumar. For example, using pronouns can reflect a self-centered focus, or using prepositions and conjunctions can indicate more nuanced thinking.
The study found that when hashtags are trademarked, a firm’s writing style becomes more important to its social media engagement. “People tend to like a more narrative and informal writing style in tweets,” Kumar says. The researchers saw that more positive, colloquial, and confident writing increase retweeting by up to 10 percent.
4. Effects of increased social media engagement last longer when hashtags are trademarked.
Recognizing that trademarking is a lengthy and expensive process, the researchers sought to discover whether the increased engagement lasted in the long term.
“Before trademarking hashtags, writing more tweets with desirable linguistic styles has only a contemporaneous effect,” says Kumar, meaning that the tweets’ increase in engagement was immediate, but dropped off quickly. After one month, it was no longer significant. “Trademarking hashtags makes things different,” Kumar says. After trademarking, the researchers found that the effects of increased engagement were still happening a month later.
Based on their research, Kumar and his colleagues believe that, especially for smaller companies with fewer followers, trademarking their intellectual social property, like hashtags, is a worthwhile investment. However, to get the maximum bang for your buck, Kumar suggests that companies consider the longevity of their chosen hashtag.
Social media can be fleeting, so invest wisely.
Home-sharing has revolutionized the lodging market. Today, digital platforms such as Airbnb and HomeAway are popular choices over conventional hotel stays. With the industry expanding exponentially over the past decade, home-sharing lodging is expected to reach $107 billion—or 10% of total accommodation bookings in the country—by 2025.
So what makes Airbnbs so popular? Three researchers from the Department of Tourism & Hospitality Management at Temple University’s School of Sport, Tourism and Hospitality Management sought to answer that question.
In a study recently published in Tourism Management, Assistant Professor Yang Yang, PhD student Karen Tan and Professor Xiang (Robert) Li used a dataset from a nationwide household tourism survey to better understand this growing segment of American travelers.
“First, we looked into what segment of consumers choose Airbnbs over conventional hotel stays,” Yang says. The researchers studied five broad categories of user-motivations: tripographics (including the purpose of the trip, nights of stay, expenditure, children companions, and group size), past travel experiences, tech savviness, socio-demographics (such as age and education) and destination characteristics (like home-sharing supply and crime rate).
“Airbnbs are selected by travelers with particular needs,” Yang notes. “Tourists who are younger, more tech-savvy and traveling with a large group size were the leading users.” Some of the other characteristics common across most users included travel for leisure purposes, itineraries planned in advance, interest in local cultural activities and the presence of personal vehicles during the trip.
The rate of crime in the destination was an important determinant in the choice of stay as well. “Travelers are less likely to stay in Airbnbs when there are crime-related security concerns,” Yang says. “Hosts and platforms should consider ways to mitigate tourists’ fear of crime, such as the introduction of home safety features, methods of crime prevention or even by offering insurance coverage.”
Yang highlights that their study challenges the popular stereotype that travelers choose Airbnbs mainly because they are cost-effective. “We did not find any significant effects of household income and price differences between hotels and Airbnbs on tourists’ choices,” Yang says. Based on this insight, he thinks that any price wars between hotels and Airbnbs would not be beneficial for either group.
The researchers also investigated the effect on the guests’ experiences when staying in Airbnbs versus a hotel. “Trip satisfaction did not differ between the two groups,” says Yang, “but the perceived value of the trip was significantly higher in the home-sharing group.”
That additional sense of value experienced by the users reflected the extra benefits that they received in Airbnbs that were not met in a traditional hotel setting. Yang says, “Facilities such as household amenities, extra space, experience authenticity and host-guest interactions were some of the key reasons.”
Karen Tan, a PhD student in the department and a co-author of the paper, believes that Airbnbs do not necessarily jeopardize the business of hotels. “Home-sharing may very well appeal to a segment of the population that previously didn’t travel as much,” she says. “Peer-to-peer accommodation could just be making the lodging pie larger.”
Much of the optimism underlying the projected growth of home-sharing lodging arguably lies in its untapped potential. “As the market for Airbnb grows,” says Yang, “hotels should not compete on lower prices, but rather focus on aspects that deliver greater value to guests.”
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Most public officials want to stay in office—and insurance regulators are no different. In the days, weeks, and months leading up to the elections, many assume that public officials would be proactive, striving to implement policies that improve their credibility and increase their chances of reelection. However, recent studies by Martin Grace, Harry Cochran Professor of Risk, Insurance, and Healthcare Management at the Fox School and Tyler Leverty of the University of Wisconsin-Madison, say that this is not the case for insurance regulators.
The financial health of the insurance companies is closely monitored by the state insurance departments to provide protection to the policyholders. When a company faces a financial crisis, the regulators intervene and help them regain their footing. In situations where the company is irreversibly dying, they are declared insolvent, or bankrupt.
To keep these stages in check, insurance regulators conduct regular financial examinations, especially for companies facing financial crisis. In their paper, ”Do Elections Delay Regulatory Action?” which was accepted by the Journal of Financial Economics, Grace found that these interventions on failing companies fall by up to 78% in the year leading up to an election. These delays result in an increased cost of failure for both policyholders and taxpayers.
The reason for this seems to be rooted in the political incentives for the insurance regulators. Insurance commissioners are elected by popular vote in some states or appointed by the governor in the others. To have a positive opinion around their candidateship, insurance commissioners avoid making formal regulatory orders or making declarations of insolvency for insurance companies up to a year before the elections. “As this could raise questions on their competency and could be seen as a black mark when they run for higher office,” says Grace, “it is easier for insurance regulators to delay companies’ bankruptcies. So they strategically postpone any official resolution until after election day.”
And, Grace says, “The more competitive the race is, the more bad news might matter.” While appointed commissioners tend to delay interventions only before tightly contested elections where the appointing governor is running for office, elected regulators delay interventions before all elections.
To conduct this study, the researchers collected data from approximately 3,200 firms and 300 separate elections in 50 states over 21 years (1989-2011). With varying election dates and state-regulated insurance policies, Grace says, “these heterogeneities gave us a very rich data to study a given insurer at different intervals of time, across different states, and at various stages of the electoral cycle.”
With so much data and possible causations, it took the researchers about eight years to publish the paper. During various presentations of the research, Grace recollects offering a dollar to anyone who could come up with a plausible explanation to the observation that they hadn’t heard of before. ”We covered it all,” Grace says. “But if someone came up with a new idea, I would give them a dollar.” However, given their extensive data set and time, Grace and his co-author were confident in their findings that elections were the main cause of these delays.
Grace emphasizes that these delays are important because they cost taxpayers more money. When an insurance company goes bankrupt and they run out of cash to pay off their debts, the balance is covered by the government from the pool of state taxes collected from policyholders of the healthy insurers. For example, he reasons, “Let’s say we have a $100 left in the failed insurer. If we closed the insurer immediately, the value would remain $100.” However, if the insurer is closed in 6 months, there would be more costs associated, like paying employees and managers of the failed insurer. “That means all taxpayers will have to pick up the balance.” Grace’s research found that delays increased the cost to taxpayers by up to $0.48 dollars for every dollar of failed insurers assets at the time of insolvency.
Research shows that prompt governance reduces the delays caused due to elections. “This was seen to be especially true in the case of appointed regulators,” says Grace. Current laws mandate regulators to report and take timely corrective actions at prescribed levels of declining capital of the insurers, limiting the regulators’ ability to delay.
The effect of delays in regulating insurance companies has a discreet yet profound effect on the cost of insurance to society. Timely settlement of claims, especially when the insurance company is in a financial crisis, helps decrease the cost of failure to both the policyholders and taxpayers.
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The “agency theory of the firm,” a way of looking at social interactions in business, says that managers are agents of shareholders. As such, managers must generally make decisions that maximize shareholder profits. Since the Citizens United case in 2010, those decisions have included the right to make unlimited independent political expenditures, under the right to freedom of expression.
So what are the ethical implications of companies making contributions for or against a political candidate? Daniel Isaacs, assistant professor of Legal Studies and academic director in the Fox School, weighs on this question in his article, “When Government Contractors May or May Not Spend Money on Political Speech,” which has been accepted for publication in the Journal of Business Ethics.
“There are some situations where it will be in the economic interests of businesses to forgo making independent political expenditures,” says Isaacs. By aligning profit motives with ethical conduct, Isaacs aims to remove barriers to ethical behavior.
Sometimes, however, profits and ethics do not align. In these cases, Isaacs argues that managers may not use the agency theory of the firm as a means to escape their ethical obligations.
For example, says Isaacs, imagine a private prison that is experiencing a reduced number of prisoners due to declining crime rate in the state. The prison has the right to make independent political expenditures on behalf of a candidate that favors laws that would require courts to impose longer prison sentences for all crimes. The outcome of these expenditures and the succeeding election would increase profits for the private prison by ensuring a steady stream of prisoners who will spend more time in jail.
But what happens if maximizing profits for shareholders by making these independent political expenditures leads to profit and unethical outcomes, like longer prison sentences? Does the agency theory allow managers to ignore the ethical situation and simply make money? No, says Isaacs, “because the agency theory relies on the concept that principals must do that which agents dictate.” If that is the case, though, managers cannot act beyond the authority of their principals.
“This relationship between the managers and the shareholders does not dilute the managers’ moral obligation,” Isaacs says. “The agency theory does not grant them an ethical free pass.”
Isaacs says that the shareholders lack the power to authorize managers to make profits in a way that they wouldn’t do themselves. “And managers cannot escape their ethical obligations by claiming that they were just following orders,” he says.
Companies should consider whether it is in their best interests to make independent political expenditures, as forgoing in some cases might make them more appealing. For example, if a company voluntarily waives its right to make independent political expenditures, Isaacs argues that it can use that to its competitive advantage. “One of the risks that at least one private prison identified in its disclosure statement was that the public may change its perception of private prisons,” says Isaacs. “If the public becomes hostile to the concept of private prisons, governments may stop entering into contracts with the corporations—something that a reasonable investor would want to know.”
With the boundaries of profitability, law and ethical obligations blurring in the real world of business, Isaacs’ research works to identify ways in which the market can support ethical decision making. He finds an unexpected friend in agency theory, arguing that the way people justify profit maximization, also serves to demonstrate the limits of shareholder power to engage in or authorize others to undertake such behavior.
“Shareholders and managers, as human beings, have a moral obligation, and desiring profits does not justify all actions of achieving them,” he concludes.
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Peace has finally been brokered in a long-standing argument between two schools of thought in statistical science.
Research from Deep Mukhopadhyay, professor of statistical science, and Douglas Fletcher, a PhD student, was accepted for publication in Scientific Reports, a journal by Nature Research. Their research marks a significant step towards bridging the “gap” between two different schools of thought in statistical data modeling that has plagued statisticians for over 250 years.
“There are two branches of statistics: Bayesian and Frequentist,” says Mukhopadhyay. “There is a deep-seeded division, conceptually and operationally, between them.” The fundamental difference is the way they process and analyze the data. Bayesian statistics incorporates external domain-knowledge into data analysis via so-called “prior” distribution.
“Frequentists view ‘prior’ as a weakness that can hamper scientific objectivity and can corrupt the final statistical inference,” says Mukhopadhyay. “I could come up with ten different kinds of ‘prior’ if I asked ten different experts. Bayesians, however, view it as a strength to include relevant domain-knowledge into the data analysis.” This has been a disagreement in statistics over the last 250 years.
So, which camp is right? “In fact, both are absolutely right,” says Mukhopadhyay. In their paper, they argued that a better question to ask is, how can we develop a mechanism that incorporates relevant expert-knowledge without sacrificing the scientific objectivity?
The answer, Mukhopadhyay says, can ultimately help design artificial intelligence capable of simultaneously learning from both data and expert knowledge—a holy grail problem of 21st Century statistics and AI.
“The science of data analysis must include domain experts’ prior scientific knowledge in a systematic and principled manner,” Mukhopadhyay says. Their paper presents Statistical rules to judiciously blend data with domain-knowledge, developing a dependable and defensible workflow.
“That is where our breakthrough lies,” says Mukhopadhyay. “It creates a much more refined ‘prior,’ which incorporates the scientist’s knowledge and respects the data, so it’s a compromise between your domain expertise and what the data is telling me.”
Answering that question—when and how much to believe prior knowledge—offers dozens of real-world applications for Mukhopadhyay’s work. For example, healthcare companies can use apply this to new drugs by leveraging doctors’ expertise without being accused of cherry picking data for the sake of a speedy or unusually successful clinical trial.
Mukhopadhyay thanks Brad Efron of Stanford University, for inspiring him to investigate this problem. “It took me one and a half years to come up with the right question,” says Mukhopadhyay. “I believe Bayes and Frequentist could be a winning combination that is more effective than either of the two separately in this data science era.”
*This article corrects an earlier version by specifying that the research was published in Scientific Reports, a journal by Nature Research.
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The Fox School of Business is making history—and driving real impact.
On Monday, March 12, the Fox School hosted a first-of-its-kind forum that brought together editors-in-chief of leading academic business journals across multiple disciplines. The 2018 Editors’ Summit united academia and industry, researchers and executives, students and educators, for a day of dialogue on a way forward to generate transformative impact of business school research.
With leadership from Charles Dhanaraj, director of the Fox School’s new Translational Research Center, over 150 people discussed the opportunities for creating impactful research and barriers standing in the way.
Fox School faculty and doctoral students were joined by editors from prestigious business journals from many disciplines, including management, marketing, accounting, finance, operations, management information systems, and international business; colleagues from Villanova University, the Wharton School, and Northwestern University, among others; and executives from the U.S. Securities and Exchange Commission, LyondellBasell, and the Association to Advance Collegiate Schools of Business (AACSB).
Here are five key takeaways from the event:
1. Define impact
What do we mean by “impact” and how do we measure it? “It has to meet the qualifications of rigor, relevance, insights, and action,” said V. Kumar, editor-in-chief of the Journal of Marketing and Regents Professor at J. Mack Robinson College of Business at Georgia State University.
While a definition of impact may remain elusive, participants identified its signs: from small shifts in how companies work and academia teaches, to societal, economic, and public policy changes.
Anne Tsui, president of the Responsible Research Leadership Forum, noted that this discussion about impact was a large step. “In the last 20 or 30 years, rigor began to dominate research and relevance began to decline,” she said. “Today, we’re here to discuss this gap.”
2. Ask the right questions
“Just because something hasn’t been studied doesn’t mean that it should,” said Tyson Browning, co-editor-in-chief of the Journal of Operations Management and professor at Texas Christian University. In order to study issues that affect business, researchers need to know the right questions to ask.
Researchers can develop relationships with businesses, through programs like Fox Management Consulting, or invest in listening platforms to identify what problems businesses face.
Bhavesh Patel, CEO of LyondellBasell, put it another way: “Think about what value your work will create from the beginning. If you do it early, it will guide the work you do.”
3. Know your audience
“In reflecting about practical impact,” said Arun Rai, editor of MIS Quarterly and professor at the J. Mack Robinson College of Business at Georgia State University, “we need to think about partnerships with complementary channels to reach audiences that we do not have core competencies to reach.”
Executives are not reading academic journals, nor should we ever expect them to. If academics want their research to have impact on the real world, they should think beyond publications and about distribution.
“In the Twitter and soundbite era, no one wants to read a 40-page paper,” said Dr. Scott Bauguess of the U.S. Securities and Exchange Commission. “They want the major takeaway.” His suggestion? Write white papers and stylized facts.
Practitioner journals, trade magazines, and popular media like newspapers and TV can also be relevant channels to getting research insights into industry. Mary Barth, senior editor of The Accounting Review and professor at Stanford University, also recommended translating research into thought pieces that are understandable to non-academics. To do that, however, researchers need a new set of skills—like marketing or social media strategies—that require training or support from the school.
4. Adjust the infrastructure
A recurring theme throughout the day was incentives. How can business schools incentivize faculty to produce research that has impact, not just publications? How can editors affect trends in what is published to promote relevance?
Participants brainstormed solutions for both. While structural changes take time, discussions centered on adjusting tenure requirements and timelines, defining impact, creating industry partnerships, hosting workshops with executives, providing funding incentives for research with practitioners and non-tenure-track faculty, and publishing special issues in journals that focus on bundled topics.
Alain Verbeke, editor-in-chief of the Journal of International Business Studies and professor at University of Calgary’s Haskayne School of Business, put it bluntly: “If you really want change, you can’t do it with the existing structure and processes.”
5. Teach the future
Students cannot be neglected in the conversation about impact. “One way we take our research articles and ideas and make them relevant to practice is by teaching them in our classes,” said Jay Barney, editor-in-chief of the Academy of Management Review and professor at the Eccles School of Business at the University of Utah.
Constance Helfat, co-editor of the Strategic Management Journal and professor at the Tuck School of Business at Dartmouth, agreed. “Every single thing I teach is based in academic research. And it works.”
The Fox School is already addressing the way forward. M. Moshe Porat, dean of the Fox School, affirmed his commitment to research and doctoral education throughout the day.
With support from the dean, the Translational Research Center has big plans for the future of research at the Fox School. The center plans to develop a white paper of the findings from the event and is hosting a case-writing consortium for faculty interested in writing and submitting a teaching case through the summer.
“The shift toward impact is a significant one, but it will take time,” said Dhanaraj,. “We will need everyone to make this big move.”
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This was a busy—and for some, award-winning—fall semester for the Fox School research community!
On October 18, the Office of Research, Doctoral Programs, and Strategic Initiatives hosted its 7th Annual PhD Paper Competition in the MBA Commons of Alter Hall. This year, 31 doctoral students and alumni submitted papers and created visual posters of their research to compete for more than $3,000 in cash and prizes.
Papers were evaluated by Fox School faculty, who chose winners in categories including first year, second year, and third-to-fourth year doctoral students. Students also competed for best dissertation proposals and completed dissertations. The 15-member evaluation committee judged the rigor, novelty, and presentation of the research, as well as its contribution to theory, practice, or policy.
Winners included Lauren Spirko of the Statistical Science Department, who won first place in the completed dissertation category for her paper proposing a statistical method for analyzing enormous data sets of genes and their various types of expressions. See a full list of participants and winners here.
On November 1, the Office hosted its 15th Young Scholars Interdisciplinary Forum, which aims to facilitate interdisciplinary collaborative research projects that span disciplines within and outside of the Fox School. Together, twenty Fox doctoral students and faculty members received nearly $35,000 in grant funding for their research.
Han Chen, a Marketing and Management Information Systems PhD student, received a grant for her research aiming to understand the neurophysiological responses to branding and marketing with respect to age. The funding will go toward the purchase of eye-tracking glasses to monitor subjects’ eye movements when reviewing physical and digital advertising materials.
The Executive Doctorate in Business Administration (DBA) program also had students succeed this semester. Terry T. Namkung, a first-year DBA student and CEO of DC Energy Systems, was chosen as one of seven finalists in the 2017 Global Business Challenge. He presented his research—an energy panel that aims to reduce energy waste by 30% by decreasing the inefficiencies of Alternating Current to Direct Current adapters, converters, and inverters—in Brisbane, Australia, in early November.
Carla Cabarle, a second-year DBA student, showcased her work at the Fall 2017 Meeting of the Institute for Fraud Prevention. As one of five finalists, Carla presented on using analytics to predict the risk of financial statement fraud in crowdfunding to academics and industry experts in financial risk and fraud management.
On behalf of Paul Pavlou, senior associate dean of research and Milton F. Stauffer Professor in the Fox School, the Office congratulates the doctoral students and faculty on a very successful fall semester.
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Vikas Mittal, Ph. D. alum of Temple University’s Fox School of Business has been recently appointed as Co-editor of the Journal of Marketing. Along with Neil Morgan of Indiana University, Mittal will be furthering the exceptional flow of submissions coming from the A-level journal. Mittal who brings a dynamic combination of expertise in Consumer Behavior as well Strategy Focus helps to expand the range of expertise that the journal reflects. Mittal who is looking forward to the appointment sees his new post as a tremendous responsibility, and hopes to maintain and serve the mission of the Journal of Marketing.
“In my early years, my research benefitted greatly from the high quality feedback I received from the editorial teams of many journals,” said Mittal. The Journal of Marketing, which has an impact factor measure of 3.8, is seen as a great influencer for notable research and encourages hard work from its reviewers and authors. Mittal whose goal is to continue the tradition of valuable feedback has witnessed the great impact of journals. “At many times, the feedback was tough, but always helpful in improving my research,” he said.
The Fox School of Business, which prides itself of producing efficient and influential academics, recognizes Mittal’s appointment as just that. “My time at the Fox School inculcated the value of serving our discipline in many ways—by publishing high quality research, by mentoring doctoral students, and by serving through the review and editorial process,” said Mittal. As we continue to see present and past students flourish, we are reminded of the dedication and perseverance that our PhD program embodies.