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Personality matters: the tie between language and how well your video content performs

Why does one piece of online video content perform better than another? Does it come down to its relevance, production values, and posting and sharing strategies? Or are other dynamics at play? There are plenty of theories about what, when and how to post if you want to drive the performance of your video. But new research by Goizueta’s Rajiv Garg, associate professor of information systems and operations management, sheds empirical and highly nuanced new light on the type of language to inject in a content if you really want to accelerate consumption. And it turns out that a lot of it depends on personality. Together with Haris Krijestorac of HEC Paris and McCombs’ Maytal Saar-Tsechansky, Garg has run a large-scale study, analyzing the words spoken and used in speech-heavy videos posted to YouTube, and then organizing those words by personality – how they “score” in terms of the so-called Big Five personality traits. “The Big Five is a system or taxonomy that has been used by psychologists and others since the 1980s to organize different types of personality traits. These traits are extroversion, agreeableness, openness, conscientiousness, and neuroticism,” says Garg. “In previous research into video content performance, we’ve looked into mechanisms such as posting and re-posting on different channels and how they impact the virality of one video over another. But we were intrigued by the role of language and how different words map to these personality traits, which in turn might have an impact on user emotion or response.” Emory has this entire comprehensive article that includes more details on the Big Five and it is available for reading here: If you are a journalist looking to cover this topic – then let our experts help with your story. Rajiv Garg from Emory’s Goizueta Business School is available to speak with media – simply click on his icon now to arrange an interview today.

Online ratings systems shouldn’t just be a numbers game

When you’re browsing the internet for something to buy, watch, listen, or rent, chances are that you will scan online recommendations before you make your purchase. It makes sense. With an overabundance of options in front of you, it can be difficult to know exactly which movie or garment or holiday gift is the best fit. Personalized recommendation systems help users navigate the often-confusing labyrinth of online content. They take a lot of the legwork out of decision-making. And they are an increasingly commonplace function of our online behavior. All of which is in your best interest as a consumer, right? Yes and no, says Jesse Bockstedt, associate professor of information systems and operations management at Emory’s Goizueta Business School. Bockstedt has produced a body of research in recent years that reveals a number of issues with recommendation systems that should be on the radar of organizations and users alike. While user ratings, often shown as stars on a five- or ten-point scale, can help you decide whether or not to go ahead and make a selection, online recommendations can also create a bias towards a product or experience that might have little or nothing to do with your actual preferences, Bockstedt says. Simply put, you’re more likely to watch, listen to, or buy something because it’s been recommended. And, when it comes to recommending the thing you’ve just watched, listened to, or bought yourself, your own rating might also be heavily influenced by the way it was recommended to you in the first place. “Our research has shown that when a consumer is presented with a product recommendation that has a predicted preference rating—for example, we think you’ll like this movie or it has four and a half out of five stars—this information creates a bias in their preferences,” Bockstedt says. “The user will report liking the item more after they consume it if the system’s initial recommendation was high, and they say they like it less post-consumption, if the system’s recommendation was low. This holds even if the system recommendations are completely made up and random. So the information presented to the user in the recommendation creates a bias in how they perceive the item even after they’ve actually consumed or used it.” This in turn creates a feedback loop which can reflect authentic preference, but this preference is very likely to be contaminated by bias. And that’s a problem, Bockstedt says. “Once you have error baked into your recommendation system via this biased feedback loop, it’s going to reproduce and reproduce so that as an organization you’re pushing your customers towards certain types of products or content and not others—albeit unintentionally,” Bockstedt explains. “And for users or consumers, it’s also problematic in the sense that you’re taking the recommendations at face value, trusting them to be accurate while in fact they may not be. So there’s a trust issue right there.” Online recommendation systems can also potentially open the door to less than scrupulous behaviors, Bockstedt adds. Because ratings can anchor user preferences and choices to one product over another, who’s to say organizations might not actually leverage the effect to promote more expensive options to their users? In other words, systems have the potential to be manipulated such that customers pay more—and pay more for something that they may not in fact have chosen in the first place. Addressing recommendation system-induced bias is imperative, Bockstedt says, because these systems are essentially here to stay. So how do you go about attenuating the effect? His latest paper sheds new and critical light on this. Together with Gediminas Adomavicius and Shawn P. Curley of the University of Minnesota and Indiana University’s Jingjing Zhang, Bockstedt ran a series of lab experiments to determine whether user bias could be eliminated or mitigated by showing users different types of recommendations or rating systems. Specifically they wanted to see if different formats or interface displays could diminish the bias effect on users. And what they found is highly significant. Emory has published a full article on this topic – and its available for reading here: If you are a journalist looking to cover this topic or if you are simply interested in learning more, then let us help. Jesse Bockstedt, associate professor of information systems and operations management at Emory’s Goizueta Business School. He is available to speak with media, simply click on his icon now – to book an interview today.

Survival analysis: Forecasting lifespans of patients and products

How long will you live? Should you spring for that AppleCare+ warranty for your iPhone? When will your buddy pay you back for that lunch? For centuries, soothsayers have striven to understand the lifespan of things – be they patient longevity, product lifecycles, or even time to loan default. Nowadays, scientists have turned away from reading tea leaves and toward survival analysis – a complex data science method for predicting not only whether an event will happen (the death of a patient, the failure of a product or machine, default on a payment, and so on) but when this event is likely to occur. But it’s problematic. Until now, the tools of survival analysis have only been applicable in certain settings. This is due to the inherent heterogeneity of what is being analyzed: differences in patient lifestyles, demographics, product usage patterns, and so on. New research by Goizueta Business School’s Donald Lee, associate professor of information systems and operations management and of biostatistics and bioinformatics, has yielded a new tool that greatly extends survival analysis to broader use cases. “Historically, scientists have used classic survival analysis tools to predict the lifespan of different things in different fields, from products to patients,” Lee said. “Since the 1950s, the Kaplan-Meier estimator has been the benchmark for analyzing lifetime data, particularly in clinical trials. The next breakthrough came in the 1970s when the Cox proportional hazards model was introduced, which allows researchers to incorporate variables that can affect the predictability of things like patient mortality.” The problem with the existing survival analysis tools, Lee said, is that they make certain assumptions that can skew the predictions if the assumptions are not met. “There are very few existing tools that can incorporate variables without imposing assumptions on how they affect survival, let alone when there are a lot of variables that can also change over time. For example, two iPhones will have different lifespans depending on the temperature at which they are stored, amongst many other factors. But it’s unlikely that storing your phone at 30 degrees will halve its lifespan compared to storing it at 60 degrees. This sort of linear relationship is commonly assumed by existing tools.” Lee’s team developed a new survival methodology based on something called gradient boosting: a machine learning technique that combines decision trees to yield predictions. The method, Lee said, is totally assumption-free (or nonparametric in technical parlance) and can deal with a large number of variables that can change continuously over time, making it significantly more general than existing methods. Nothing like it has been seen until now, he noted. “Calculating the survival rate of anything is super complex because of the variables. Say you want to create an app for a smart watch that monitors the wearer’s vitals and use this information to create a real-time warning indicator for stroke. Doing this accurately is difficult for two reasons,” Lee explained. “First, a large number of variables may be relevant to stroke risk, and the variables can interact in ways that break the assumptions central to existing survival analysis methods. And second, variables like blood pressure vary over time, and it is the recent measurements that are most informative. This introduces an additional time dimension that further complicates things.” The software implementation of Lee’s method, BoXHED, overcomes both issues and allows scientists to develop real-time predictive models for conditions like stroke. The trained model can then be ported to a watch app to tell its wearer if and when they’re likely to have a stroke, a process known as inferencing in machine learning lingo. The implications, Lee said, are huge. “BoXHED now opens the door for modern applications of survival analysis. In previous research, I have looked at the design of early warning mortality indicators for patients with advanced cancer and also for patients in the ICU. These use other methods to make predictions at fixed points in time, but now they can be transformed into real-time warning indicators using BoXHED.” He cited the case of end-stage cancer patients who are often better served by hospice care than by aggressive therapy. “Accurate predictions of survival are absolutely critical for care planning. In previous analyses, we have seen that using existing predictive models to inform end-of-life care planning can potentially avert $1.9 million in medical costs and 1,600 days of unnecessary inpatient care per 1,000 patient visits in the United States. BoXHED is likely to lead to even better results.” Lee’s research paper is forthcoming in the Annals of Statistics. He has also created an open-source software implementation of BoXHED, which can radically improve the accuracy of survival analysis across a breadth of applications. The paper describing BoXHED was published in the International Conference on Machine Learning, and the latest version of the BoXHED software can be found online. If you are a journalist or looking to speak with Donald Lee – simply click on his icon now to arrange an interview or appointment today.

Study of auto recalls shows carmakers delay announcements until they can 'hide in the herd'

BLOOMINGTON, Ind. - Automotive recalls are occurring at record levels, but seem to be announced after inexplicable delays. A research study of 48 years of auto recalls announced in the United States finds carmakers frequently wait to make their announcements until after a competitor issues a recall - even if it is unrelated to similar defects. This suggests that recall announcements may not be triggered solely by individual firms' product quality defect awareness or concern for the public interest, but may also be influenced by competitor recalls, a phenomenon that no prior research had investigated. Researchers analyzed 3,117 auto recalls over a 48-year period -- from 1966 to 2013 -- using a model to investigate recall clustering and categorized recalls as leading or following within a cluster. They found that 73 percent of recalls occurred in clusters that lasted 34 days and had 7.6 following recalls on average. On average, a cluster formed after a 16-day gap in which no recalls were announced. They found 266 such clusters over the period studied. "The implication is that auto firms are either consciously or unconsciously delaying recall announcements until they are able to hide in the herd," said George Ball, assistant professor of operations and decision technologies and Weimer Faculty Fellow at the Indiana University Kelley School of Business. "By doing this, they experience a significantly reduced stock penalty from their recall." Ball is co-author of the study, "Hiding in the Herd: The Product Recall Clustering Phenomenon," recently published online in Manufacturing and Service Operations Management, along with faculty at the University of Illinois, the University of Notre Dame, the University of Minnesota and Michigan State University. Researchers found as much as a 67 percent stock market penalty difference between leading recalls, which initiate the cluster, and following recalls, who follow recalls and hide in the herd to experience a lower stock penalty. This indicates a "meaningful financial incentive for auto firms to cluster following recalls behind a leading recall announcement," researchers said. "This stock market penalty difference dissipates over time within a cluster. Additionally, across clusters, the stock market penalty faced by the leading recall amplifies as the time since the last cluster increases." The authors also found that firms with the highest quality reputation, in particular Toyota, triggered the most recall followers. "Even though Toyota announces some of the fewest recalls, when they do announce a recall, 31 percent of their recalls trigger a cluster and leads to many other following recalls," Ball said. "This number is between 5 and 9 percent for all other firms. This means that firms are likely to hide in the herd when the leading recall is announced by a firm with a stellar quality reputation such as Toyota. "A key recommendation of the study is for the National Highway Traffic Safety Administration (NHTSA) to require auto firms to report the specific defect awareness date for each recall, and to make this defect awareness date a searchable and publicly available data field in the auto recall dataset NHTSA provides online," Ball added. "This defect awareness date is required and made available by other federal regulators that oversee recalls in the U.S., such as the Food and Drug Administration. Making this defect awareness date a transparent, searchable and publicly available data field may discourage firms from hiding in the herd and prompt them to make more timely and transparent recall decisions." Co-authors of the study were Ujjal Mukherjee, assistant professor of business administration at the Gies College of Business at the University of Illinois who was the lead author; Kaitlin Wowak, assistant professor of IT, analytics, and operations at the Mendoza College of Business at the University of Notre Dame; Karthik Natarajan, assistant professor of supply chain and operations at the Carlson School of Management at the University of Minnesota; and Jason Miller, associate professor of supply chain management at the Broad College of Business at Michigan State University.

Hitting all the right notes - Georgia Southern music industry degree ready to launch

Georgia Southern University’s Department of Music earned national accreditation for a new music industry degree, the final step for an innovative program that combines music, technology and entrepreneurship. Launching in the fall of 2021, the new music industry program will prepare musicians for evolving careers in music. The program curriculum combines a traditional degree with 21st-century technology and performance opportunities. Accreditation from the National Association of Schools of Music (NASM) allows the new program, Bachelor of Arts in Music with a concentration in music industry, to be offered at the Armstrong Campus in Savannah. Students will have the option of declaring an emphasis area in music technology or music business. “We could not be more excited about this program,” said Steven A. Harper, Ph.D., chair of the Department of Music. “For many years, the music program has been itching to expand its reach and regional impact. Savannah is perfectly suited for a degree of this type and we couldn’t be more pleased to have this degree come to fruition.” The music industry program includes courses in music management, live sound, recording studio techniques, digital audio workstations and music entrepreneurship. “The numerous music industries in Savannah include music manufacturers, performing organizations/venues and major music festivals. These industries can provide ample internship possibilities for hands-on experience in a chosen area,” Harper said. “We are able to reach a student body we’ve never been able to serve before. We can prepare students for a whole different set of in-demand careers and we can create ties with the music industry in Savannah in a way that’s never been possible for us until now. It’s going to be a huge boon for the department, the college, the university and the Armstrong Campus.” One professor key to the program will be Stephen Primatic, DMA, who teaches percussion, theory, jazz and music technology. His versatility is evidenced by the books he has written: two on percussion pedagogy and another on instrument maintenance and repair. “This program will be beneficial to our students, the University and the community of Savannah, offering education and training for music careers in the 21st century,” said Primatic. If you are a journalist looking to know more about the Bachelor of Arts in Music with a concentration in music industry or would like to interview Steven A. Harper, Ph.D., chair of the Department of Music or Professor Stephen Primatic -- simply reach out to Georgia Southern Director of Communications Jennifer Wise at jwise@georgiasouthern.edu to set and time and date.

Alternative Data Can Offer Insight into GameStop Action on Wall Street

Thomas Shohfi, an assistant professor in the Lally School of Management at Rensselaer, says that looking at alternative data can offer important insights into the turbocharged trading of GameStop. “Volatility in options on GameStop, Nokia, and AMC is exploding,” says Shohfi. “Short sellers are taking massive losses, covering their positions and pushing the stocks even higher. WallStreetBetters keep looking for soft spots in the hedge fund short portfolios to ‘blow up’ their value again and again. It’s a mob-fund mentality.” Working with a former student, Shohfi has analyzed trends from the WallStreetBets subreddit and other social media platforms. He can provide an astute understanding as to how investors have reached this moment, why this has happened, and what the impact that this event will have in the future. “Practitioners, investors, and analysts are always looking for an advantage,” according to Shohfi. “The biggest advantage that we see today is through alternative data. It’s just a rich environment to observe human behavior, incentives, and gender  and disclosure effects that affect capital markets like we have seen with GameStop.”

A Free App Can Help School and College Administrators Contain COVID-19

With COVID-19 infection rates rising across the country as students return to school for the spring semester, how will schools and colleges control the spread? COVID Back-to-School can help. It’s a free online tool that predicts the outcome of taking specific measures to curtail the spread of the virus. The algorithm powering the app was developed by Rensselaer Polytechnic Institute computer science professor Malik Magdon-Ismail and builds upon the success of COVID War Room, an algorithm that can predict the spread of COVID-19 in smaller cities and counties across the United States and select international locations. Administrators at Rensselaer consulted COVID Back-to-School when devising a COVID-19 management plan that successfully kept the infection rate on campus well below 0.5% during the fall 2020 semester, even with most students attending in-person classes. Magdon-Ismail, an expert in machine learning, designed the algorithm to allow administrators at schools of all levels, as well as ordinary citizens, to quantitatively analyze various strategies for containing the virus. Users can enter details about their institution — like the zip codes students come from, the size of the school, how often students are tested, the number of expected interactions during a class or meal — and COVID Back-to-School will project outcomes like the proportion of students likely to arrive infected, the proportion of students likely to be infected over time, and the number of likely new infections every 14 days. “This is a publicly available tool that we’re hoping schools can use to quantitatively analyze re-opening strategies,” Magdon-Ismail said. “Schools can use it, at least, to evaluate how their current strategy will play out assuming an infection on campus. Better still, COVID Back-to-School allows schools to try out various strategies before actually implementing them, to see what works and what doesn’t.” Magdon-Ismail is available to discuss how the algorithm works and the utility it may provide to colleges and universities across the country in the spring semester.

Trump’s reaction to defeat further confirms urgency for school focus on social-emotional skills

Sandra Chafouleas, psychologist and behavioral health expert from the University of Connecticut, weighs in: Imagine what would happen if a preschooler didn’t “use their words” when they got upset about sharing, instead stomping around yelling while adults simply observed in silence. Think about what the school climate would feel like if a student punched another during recess while others watched without seeking help. Now consider the actions – and inactions – by Donald Trump on January 6 as the electoral vote counts occurred at the U.S. Capitol. Those behaviors show a desperate need for social emotional learning. According to the Collaborative for Academic, Social, and Emotional Learning (CASEL), social emotional learning involves five core competencies: self-awareness, self-management, social awareness, relationship skills, and responsible decision-making. Trump did not demonstrate these competencies when the election didn’t go the way he wanted. Connecting these school scenarios and Trump’s behaviors is not intended to contribute to the ever-mounting list of recommended consequences that could result from his fueling the insurrection that our nation has just experienced. It does bear noting, however, that if Trump were a Black teenager, he most certainly would have received exclusionary disciplinary action such as suspension and perhaps even expulsion from school. The purpose in connecting the two scenarios is to draw energies toward actions that propel us forward in bridging a divided nation. The responsibility for forward movement falls to future generations, which means it is critical that we pay attention to what happens in schools right now. We need to demand that policies and practice — and necessary resources — are put in place to strengthen school capacity to support students on their path to holding responsibility for democracy. Many excellent resources have quickly appeared to assist educators in teaching about the insurrection. Discussion guides are available to facilitate defining key terms, contrasting events through a social justice lens, and comparing justifications for action using fact checking. Other resources have been released that help adults talk about violence and support emotional safety of kids. What seems to be less prominent, however, is a direct connection to the social, emotional, and behavioral skills that we have just witnessed are missing. Education systems have begun the work of acknowledging their historic roles in contributing to exclusion, inequity, and intolerance of differences. Educators are working hard to turn the tide toward promising alternative approaches. Prominent among those approaches is a focus on social emotional skills. In either classroom scenario above, educators would be jumping into discussion about what supports are needed to address student needs. Social and emotional well-being fulfills us throughout every stage of life – integrating those skills should be in all that we do as adults to model, teach, and give feedback to our children. Of course schools must teach academic content areas and have high expectations, but there is tremendous potential to increase capacity to embed exploration, active practice, and positive feedback about social and emotional skills within each corner of the day. As one example, history professor Kellie Carter Jackson writes about challenges in teaching violence in political history. The author describes the need to question how political violence should be labeled, which could reveal an expression of unmet need by marginalized people. Learning through this analysis offers social and emotional parallels, such as examining biases, recognizing emotions, and examining integrity. As another, Facing History and Ourselves offers a classroom resource specific to the insurrection. Activities reference principles of social and emotional learning, such as steps for educators to practice self-awareness and relationship skills by examining their own emotions and perspectives. Student self-management and social awareness builds through reflection activity that builds civic agency. All of these examples offer incredible opportunity in social and emotional learning that could be advanced with more explicit connection. Entrenching social and emotional learning within the school day beyond this immediate teachable moment also is needed to enable sustained effort. CASEL identifies adults as key to social emotional strategies that will maintain safe, supportive, and equitable learning environments for this moment in history. To do so requires a strong collection of social, emotional, and behavioral education policies and practices. Responsibility for urgently resourcing this collection rests within each of us, right now, to ensure future generations who can and do take part in a resilient democratic nation. Dr. Chafouleas is licensed psychologist and Distinguished Professor, with expertise in school psychology and school mental health at the University of Connecticut’s Neag School of Education. If you’re a reporter looking to speak with Dr. Chafouleas about this topic – let us help. Simply click on her icon to arrange an interview today.

As Flexible Voting Options Scrutinized, Expert Says Online Voting Not a Safe Alternative

The popularity of — and controversies surrounding — early voting and mail-in ballots demonstrates a demand for more flexible voting options. But online voting shouldn’t be up for consideration, according to James Hendler, the head of the Institute for Data Exploration and Applications at Rensselaer Polytechnic Institute.  Hendler also chairs the U.S. Technology Policy Committee of the Association for Computing Machinery, the world’s largest and oldest society of individuals involved in all aspects of computing. In public statements expressing his own opinion and on behalf of the ACM, Hendler has discussed the vulnerabilities of online voting and the organization’s effort to press against its adoption. Hendler argues that online voting is not, and cannot be made to be, secure against malware and denial of service attacks — and that no app or underlying technology, including blockchain, holds potential to overcome those challenges. "The current state of mobile voting is that we are not ready to deploy it at scale, that it has significant technical and socio-technical aspects, particularly cybersecurity, that we need to worry about, and that there are alternatives,” Hendler said. “The ACM has worked hard as an organization to explain our evidence-based reasoning, and to express the hope that online-voting won’t be used now and in the foreseeable future.” In explaining why online voting is more complicated than online banking, shopping and other common internet activities, Hendler said, “The main reason that online voting is more complex is that it must maintain anonymity, no one is allowed to know how you voted. Securing online voting without providing access to identity is extremely difficult. There are other reasons as well including the staggering cost and the lack of a centralized US authority, but identity management remains the number one.” Under his leadership, the ACM’s U.S. Technology Policy Committee, along with leading organizations and experts in cybersecurity and computing, sent a letter to all governors, secretaries of state and other state election directors urging them not to allow the use of internet or voting app systems. Hendler has extensive experience in policy and advisory positions that consider aspects of artificial intelligence, cybersecurity and internet and web technologies as they impact issues such as online voting and the regulation of social media and powerful technologies including facial recognition and artificial intelligence. In light of ongoing political unrest, Hendler is available to speak to diverse aspects of information technology as related to the election, AI in applications like policing, and the politics related to social media.

Lockdown teleworking impacts productivity of women more than men

When the COVID-19 pandemic led countries all over the world to lock down their economies in early 2020, there was an unprecedented global shift to teleworking in white collar sectors. A trend that had been gathering traction was suddenly and exponentially accelerated and many of the world’s largest corporations, Google and Facebook among them, have announced plans allowing employees to work from home well into 2021 or indefinitely. Remote working not only appears to work, but it appears to have a number of advantages—savings in office maintenance costs and time spent commuting, not to mention enabling organizations to safeguard productivity when there’s a major shock or crisis. But is it all good news? Or good news for all? A new paper by Ruomeng Cui, assistant professor of information systems and operations management at Emory’s Goizueta Business School, reveals an important drop in the productivity of female academics around the world in the wake of the COVID-19 lockdowns. In fact, in the ten weeks following the initial lockdown in the United States, their productivity fell by a stunning 13.9 percent relative to that of male colleagues. And it’s likely to do with the disproportionate burden of responsibility for household needs and childcare that persistently falls on women, Cui said. “We know that gender inequality persists both in the workplace and at home, and we were curious to see how the lockdown scenario would attenuate or exacerbate the situation for women,” Cui said. Anecdotal evidence from her own field—academia—showed that in the weeks following the stay at home mandate in March, there was an upswing of around 20 to 30 percent of papers submitted to journals. However, the overwhelming majority of these were being authored by men. Intrigued, Cui teamed up with Goizueta doctoral student Hao Ding and Feng Zhu from Harvard Business School to conduct a systematic study of female academics’ productivity and output during this period. “We knew that the lockdown had disrupted life for everyone, including academics. With schools and kindergartens closed and people taking care of work and household obligations at home, we intuited that women would be affected more than men as they are disproportionately burdened with domestic and childcare duties,” Cui said. For female academics this would theoretically be particularly acute, as the critical thinking that goes into research calls for quiet, interruption-free environments. To put this to the test, Cui and her co-authors created a large data set covering all the new social science research papers produced by men and women, across 18 disciplines and submitted to SSRN, a research repository, between December 2018 to May 2019 and then from December 2019 to May 2020. From this set, they were able to extract information on titles, authors’ names, affiliations, and addresses to identify their countries and institutions, as well as faculty pages to distinguish between men and women. In total they collected just under 43,000 papers written by more than 76,000 authors in 25 countries. Looking at the data, Cui and her colleagues were able to compute the total number of papers produced by male and female academics each week and then compare the productivity of both before and after the start of the lockdown. Prior to the pandemic, the 2019 period showed no significant changes in productivity in either gender. But in the 10 weeks following the shock of lockdown, a clear gap emerges between men and women, with female academics’ productivity falling by just under 14 percent in comparison to their male colleagues. Interestingly the effect was more pronounced in top-ranked research universities. This is likely because top schools require faculty to publish research as the primary requisite for promotion, so men would be motivated to continue authoring papers before and after the lockdown. These findings lend solid, empirical clout to the notion that women do take a hit to productivity when care and work time are reorganized, Cui noted. “We see clearly that women are producing less work as a consequence of working from home. In the field of academia, that has huge implications as achieving a permanent position, or tenure, is generally linked to your research output,” she said. “So, there is a serious fairness issue there. If women are producing less because the burden of household responsibility is greater for them than for men, then you’re likely to see fewer female academics get tenure through no fault of their own.” Indeed, one of the other findings of the study shows that while productivity fell, the quality of female-authored research measured by downloads and citations did not. Then there’s the issue of teleworking and gender. With a significant proportion of the world’s white-collar organizations still working from home and unlikely to head back to the office any time soon—and as many schools and childcare facilities remain closed due to the pandemic—Cui is concerned that productivity as a measure of value and a marker of success might mean the odds are further stacked against women. And not just in academia. “We looked at universities in particular, but our findings can really be externalized to any other industry because the underlying issues here are universal. So, with remote working becoming normalized, I think there’s a real onus on organizations of every type to think about how to mitigate these unintended consequences,” she said. “There needs to be more thought about how we measure value or potential of employees.” Cui calls for organizations and institutions to consider these factors when they evaluate male and female workers in the present context and looking to the future. Among the kinds of proactive moves they might consider are to make training programs for male and female employees that explore fairness and encourage a more even distribution of responsibility in the home and for children. “There’s nothing to be gained in prioritizing productivity as a tool for evaluation and just giving women more time, say, to produce as much,” Cui warned. “You’re just left with the same scenario of women doing more than their fair share. Solving this issue is really much more about being aware of it, getting educated about it, and changing your mindset.” If you are a journalist looking to cover this research or speak with Professor Ciu about the subjects of telework and productivity, simply click on her icon now to arrange an interview today.