Expert Insight: NFL Fandom: The Last Cultural Unifier?

Aug 7, 2024

8 min

Michael Lewis



In 2024, few cultural touchstones unify America. One of the remaining cultural unifiers is the NFL. It is almost guaranteed that the Super Bowl will be the most watched television program each year. Add Taylor Swift (another rare cultural unifier) attending to watch her boyfriend and an appealing halftime musical guest, and you can have over 120 million people watching the same program at the same time. Nothing else comes close.


There is little doubt that the NFL is the undisputed champion of American sports. But how do the various NFL fandoms compare? Which team has the top fandom, and which struggles (struggle is relative here, as the lowest-ranked NFL fandom is still impressive)? This is an interesting question in a couple of ways. First, it reveals something important about the level of connection in different cities. Cities with stronger fan bases tend to have more of a shared identity. Boston residents share more love across their teams (Celtics, Red Sox, Bruins, Patriots) than folks from Tampa Bay. “Sports” cities are fundamentally different. It's also an interesting marketing analysis. Fandoms are people who share passion and love for what are essentially brands. Examining fandom can reveal something critical about how brands that inspire fandom are built.


Comparing fan bases can also inflame passions. Sports fans are (often) the ultimate fans as they closely identify with their teams and feel each victory as a personal triumph and each loss as a defeat. Because fans’ identities are tied to their teams, ranking fan bases can feel like an attack. Saying Browns fans aren’t as good of fans as Ravens fans feels like an attack on Cleveland.


The deeper perspective motivating this analysis is that fandom is about cultural passion, so what people are fans of largely dictates the tone and content of our societies. A society that loves baseball, country music, and trucks feels very different from one that favors soccer, opera, and Vespas. The fandom rankings are a snapshot in time of how fandom works in the NFL. And remember, the NFL is not just the top sports league in America but also the closest thing we have in 2024 to a shared societal passion.


Analyzing Fandoms


I have been ranking NFL and other fan bases for more than a decade. These fandom analyses are an example of brand equity analytics, and they use two types of data. The goal is to understand the relationship between market characteristics and fandom outcomes at the league level. We can then evaluate each team based on how it performs relative to league norms.


The fandom or market outcome measures include things like data on prices, attendance, and social media following. These are measures of fan engagement. Prices provide a signal of how much market power a team has created. Attendance shows the enthusiasm of fans in the market to pay for tickets and take the time to travel and attend. Social media following reveals how many fans the team has in and out of their home market. Each metric has advantages and limitations. Social media following provides an indication of national fandom, but it also captures casual fans who would never pay for a ticket.


The second aspect of the analysis focuses on market potential. NFL markets vary from New York, with a population of 20 million, to Green Bay, with a few hundred thousand. Income levels in San Francisco are far higher than in Jacksonville or Cleveland. I use a range of demographics, but income and population are the major factors. Again, the metrics are good but not perfect. For example, using MSA populations isn’t perfect because teams have different footprints. The Packers are more of a Wisconsin team than a Green Bay team. The teams in New York and LA share a market. Should they each get half of the metro area population? One factor that I do not control for is competition. In the southeast, NFL teams may compete with SEC teams. I have debated this issue (with myself) and have decided to neglect it.


This year's analysis includes a significant change from last year. The significant change is that I am not controlling for team performance. Controlling for team performance is helpful because it isolates core or unchanging fandom. This approach has appeal, as we can argue that teams with more passionate fandoms will be more resilient against losing seasons. The downside of controlling for performance is that we get less of a measurement of the fandom's overall value. If a team like Kansas City is on an extended winning streak, then the Chiefs brand is very valuable at the moment. Controlling for winning makes the analysis more about the core, near-permanent passion of a fandom, while not controlling makes the results more relevant to current brand power.


The analysis involves three steps. The first step creates measures of each team’s relative fandom outcomes and market potential. The second step develops a statistical model of the relationship between market potential and fandom outcomes. The third step compares each team's fandom outcomes with the statistical model's predictions. The third step is a comparison of actual results versus predicted – the key point is that the prediction is based on leaguewide data. As these analyses are always imperfect, the best way to consider the fandom rankings is as tiers. I like the idea of quadrants.


Some brief comments on the members of each quadrant (Elite, Solid, Role Players, Benchwarmers). I will be discussing each fandom on social media.


TikTok: @fanalyticspodcast


Instagram: @fanalyticsmikelewis


YouTube: @fanalyticsmike


A bonus figure follow the Quad overviews.


The Results



Quadrant 1: The Elite

The Dallas Cowboys lead the top group of teams, followed by the Packers, Eagles, Chiefs, 49ers, Raiders, Patriots, and Steelers. Sounds a lot like what the man on the street would list as the top NFL brands. The Cowboys and Packers leading the way is no surprise. The Cowboys are second in social following and the leaders in attendance. The Packers are an astonishing fandom story as the team is located in the definitive small market. The Eagles leading the Steelers is going to be troubling in Western Pennsylvania, but the Eagles have more pricing power and more social following. The 49ers are a solid NFL fandom with few weaknesses. The Patriots are in a new era, and it will be fascinating to see if they maintain their top-tier position as Brady and Belichick become memories.


The Chiefs' presence in the top group is a change from past years and is due to the shift away from controlling for performance. The Chiefs have a great fandom, but the team’s success currently pumps them up. The Chiefs are in a brand-building phase as the team continues building its dynasty. The question for the Chiefs is where they end up long-term.


I don't fully understand the Raiders' ranking. The Raiders are midrange in attendance and social following but do well because are reported to have the highest prices in the league. I suspect this is more an idiosyncrasy of the Las Vegas market than a reflection of significant passionate fandom.


Quadrant 2: Solid Performers

The Quadrant 2 teams are the Broncos, Giants, Panthers, Seahawks, Saints, Ravens, Texans, and Browns. These are the solid performers of NFL fandoms (brands). These are teams with above expected fandom outcomes for their relative market potentials.


The Quadrant 2 clubs are all passionate fanbases (maybe one exception) despite very different histories. For example, the AFC North rival Ravens and Browns differ in both relative history and frequency of winning. Cleveland fandom involves significant character, while the Ravens are a “blue-collar” brand that has been a consistent winner. There are a lot of great stories in Quad 2. The Saints were once the Aints but are now a core part of New Orleans. The Broncos and Giants are great fandoms who are probably angry to be left out of Quad 1.


The Panthers' position is unexpected and may be due to some inflated social media numbers. This is the challenge when an analysis is based only on data. When data gets a little weird, like an inflated social media follower count dating back to Cam Newton's days, the results can also get a little weird. This is a teachable moment—do not analyze and interpret data without knowing the context (the data-generating processes).


Quadrant 3: Role Players

Quadrant 3 fandoms are teams whose fandom outcomes are slightly below average league performance (for similar markets). The Quadrant 3 teams include (in order) the Bills, Falcons, Buccaneers, Jets, Vikings, Bears, Dolphins, and Bengals. There are some interesting teams in Quad 3. The Bills have a great and notorious fandom. Jumping through flaming tables in subzero weather should get you into the top half of the rankings? The big-market Jets and the small-market Bengals have two of the most fascinating QBs in the league. Both clubs could be poised to get to Quad 2 with a Super Bowl or two. Da’Bears may be one of the most disappointing results. A team with an SNL skit devoted to their fandom in a market like Chicago shouldn’t be in Quad 3. Other quick comments: The Falcons need to win a title. Florida is tough for professional teams. The Vikings should play outside.


Quadrant 4: Hopium

These are the NFL's weakest fandoms, with the key phrase being “the NFL’s.” The Quad 4 teams, in order, are the Lions, Rams, Jaguars, Colts, Titans, Commanders, Chargers, and Cardinals. It’s a lot of teams who have not won regularly and have many moves and name changes. The Lions are poised for a move upward and maybe a sleeping giant of a fandom. They have the most watchable coach in the league and the most surprising celebrity fan. An interesting side story in Quad 4 is the battle for Los Angeles between the Rams (formerly of Saint Louis) and the Chargers (previously San Diego). They play in the same market, but the Rams have won more. But will Herbert lead the Chargers past the Rams?


Quad 4 illustrates an important lesson: consistency. The Rams moved from St. Louis and then back to LA. The Chargers went from San Diego to LA. The Colts left Baltimore in the middle of the night. The Titans were the Oilers and moved from Houston to Nashville. The Cardinals were the other NFL team Saint Louis lost. The Commanders should have stopped with their previous name.



The Fandom Outcomes / Market Potential Matrix


The following figure is a bit of bonus material that may provide some insight into the inner workings of the analysis.


The figure below shows the performance of each team on the Fandom Outcome and the Market Potential Indexes. The upper left region features teams with less lucrative markets but above-average fandoms, like the Packers, Steelers, and Chiefs. The lower right region is the teams with below-average fandom outcomes despite high potential markets, like the Commanders, Chargers, and Rams. This pictorial representation is also interesting as it shows teams with similar positions. These similarities can be somewhat surprising. For example, the Lions and Dolphins have very similar profiles despite the differences between Detroit and Miami.




Mike Lewis is an expert in the areas of analytics and marketing. This approach makes Professor Lewis a unique expert on fandom as his work addresses the complete process from success on the field to success at the box office and the campaign trail.


Michael is available to speak with media - simply click on his icon now to arrange an interview today.



Interested in following Future Fandom! Subscribe for free to receive new posts.



Connect with:
Michael Lewis

Michael Lewis

Professor of Marketing

www.fandomanalytics.com All Things Fandom and Sports Analytics

Revenue Management & Dynamic PricingCustomer Relationship ManagementSports AnalyticsSports MarketingFandom

You might also like...

Check out some other posts from Emory University, Goizueta Business School

8 min

#Expert Research: Incentives Speed Up Operating Room Turnover Procedures

The operating room (OR) is the economic hub of most healthcare systems in the United States today, generating up to 70% of hospital revenue. Ensuring these financial powerhouses run efficiently is a major priority for healthcare providers. But there’s a challenge. Turnovers—cleaning, preparing, and setting up the OR between surgeries—are necessary and unavoidable processes. OR turnovers can incur significant costs in staff time and resources, but at the same time, do not generate revenue. For surgeons, the lag between wheels out and wheels in is idle time. For incoming patients, who may have spent hours fasting in preparation for a procedure, it is also a potential source of frustration and anxiety. Reducing OR turnover time is a priority for many US healthcare providers, but it’s far from simple. For one thing, cutting corners in pursuit of efficiency risks patient safety. Then there’s the makeup of OR teams themselves. As a rule, well-established or stable teams work fastest and best, their efficiency fueled by familiarity and well-oiled interpersonal dynamics. But in hospital settings, staff work in shifts and according to different schedules, which creates a certain fluidity in the way turnover teams amalgamate. These team members may not know each other or have any prior experience working together. For hospital administrators this represents a quandary. How do you cut OR turnover time without compromising patient care or hiring in more staff to build more stable teams? To put that another way: how do you motivate OR workers to maintain standards and drive efficiency—irrespective of the team they work with at any given time? One novel approach instituted by Georgia’s Phoebe Putney Health System is the focus of new research by Asa Griggs Candler Professor of Accounting, Karen Sedatole PhD. Under the stewardship of perioperative medical director and anesthesiologist, Jason Williams MD 02MR 20MBA, and with support from Sedatole and co-authors, Ewelina Forker 23PhD of the University of Wisconsin and Harvard Business School’s Susanna Gallini PhD, staff at Phoebe ran a field experiment incentivizing individual OR workers to ramp up their own performance in turnover processes. What they have found is a simple and cost-effective intervention that reduces the lag between procedures by an average of 6.4 percent. Homing in on the Individual Williams and his team at Phoebe kicked off efforts to reduce OR turnover times by first establishing a benchmark to calculate how long it should take to prepare for different types of procedure or surgery. This can vary significantly, says Williams: while a gallbladder removal should take less than 30 minutes, open-heart surgery might take an hour or longer to prepare. “There’s a lot of variation in predicting how long it should take to get things set up for different procedures. We got there by analyzing three years of data to create a baseline, and from there, having really homed in on that data, we were able to create a set of predictions and then compare those with what we were seeing in our operating rooms—and track discrepancies, over-, and underachievement.” Williams, a Goizueta MBA graduate who also completed his anesthesiology residency at Emory University’s School of Medicine, then enlisted the support of Sedatole and her colleagues to put together a data analysis system that would capture the impact of two distinct mechanisms, both designed to incentivize individual staff members to work faster during turnovers. The first was a set of electronic dashboards programmed to record and display the average OR turnover performance for teams on a weekly basis, and segment these into averages unique to individuals working in each of the core roles within any given OR turnover team. The dashboard displayed weekly scores and ranked them from best to worst on large TV monitors with interactive capabilities—users could filter the data for types of surgery and other dimensions. Broadcasting metrics this way afforded Williams and his team a means of identifying and then publicly recognizing top-performing staff, but that’s not all. The dashboards also provided a mechanism with which to filter out team dynamics, and home in on individual efforts. “If you are put in a room with one team, and they are slower than others, then you are going to be penalized. Your efforts will not shine. Now, say you are put in with a bigger or faster team, your day’s numbers are going to be much higher. So, we had to find a way to accommodate and allow for the team effect, to observe individual effort. The dashboards meant we could do this. Over the period of a week or a month, the effect of other people in the team is washed out. You begin to see the key individuals pop up again and again over time, and you can see those who are far above their peers versus those who, for whatever reason, are not so efficient.” Sharing “relative performance” information has been shown to be highly motivating in many settings. The hope was that it would here, too. Three core roles: Who’s who in the Operating Room turnover team? OR turnover teams consist of three roles: circulating nurse, scrub tech, and anesthetist. While other surgery staff might be present during a turnover, depending on the needs of consecutive procedures, these are the three core roles in the team, and they are not interchangeable in any way: each individual assumes the same responsibilities in every team they join. Typically, turnover tasks will include removing instruments and equipment from the previous surgery and setting up for the next: restocking supplies and restoring the sterile environment. Turnover tasks and activities will vary according to the type of procedure coming next, but these tasks are always performed by the same three roles: nurse, scrub tech, and anesthetist, working within their own area of expertise and specialty. OR turnover teams are assembled based on staff schedules and availability, making them highly fluid. Different nurses will work with different scrub techs and different anesthetists depending on who is free and available at any given time. With dashboards on display across the hospital’s surgery department, Williams decided to trial a second motivational mechanism; this time something more tangible. “We decided to offer a simple $40 Dollar Store gift card to each week’s top performing anesthetist, nurse, or scrub technician to see if it would incentivize people even more. And to keep things interesting, and sustain motivation, we made sure that anyone who’d won the contest two weeks in a row would be ineligible to win the gift card the following week,” says Williams. “It was a bit of a shot in the dark, and we didn’t know if it would work.” Altogether, the dashboards remained in situ over a period of about 33 months while the gift card promotion ran for 73 weeks. It was important to stress the foundational importance of safety and then allow individuals to come up with their own ways to tighten procedures. This was a bottom-up, grassroots experience where the people doing the work came up with their own ways to make their times better, without cutting corners, without cutting quality, and without cutting any safety measures. Jason Williams MD 02MR 20MBA Incentives: Make it Something Special and Unique Crunching all of this data, Sedatole and her colleagues could isolate the effect of each mechanism on performance and turnover times at Phoebe. While the dashboards had “negligible” effect on productivity, the addition of the store gift cards had immediate, significant, and sustained impact on individuals’ efforts. Differences in the effectiveness of the two incentives—the relative performance dashboard and the gift cards—are attributable to team fluidity, says Sedatole. “It’s all down to familiarity. Dashboards are effective if you care about your reputation and your standing with peers. And in fluid team settings, where people don’t really know each other, reputation seems to matter less because these individuals may never work together again. They simply care less about rankings because they are effectively strangers.” Tangible rewards, on the other hand, have what Sedatole calls a “hedonic” value: they can feel more special and unique to the recipient, even if they carry relatively little monetary value. Something like a $40 gift card to Target can be more motivating to individuals even than the same amount in cash. There’s something hedonic about a prize that differentiates it from cash—after all, you will just end up spending that $40 on the electricity bill. Asa Griggs Candler Professor of Accounting, Karen Sedatole “A tangible reward is something special because of its hedonic nature and the way that human beings do mental accounting,” says Sedatole. “It occupies a different place in the brain, so we treat it differently.” In fact, analyzing the results, Sedatole and her colleagues find that the introduction of gift cards at Phoebe equates to an average incremental improvement of 6.4% in OR turnover performance; a finding that does not vary over the 73-week timeframe, she adds. To get the same result by employing more staff to build more stable teams, Sedatole calculates that the hospital would have to increase peer familiarity to the 98th percentile: a very significant financial outlay and a lot of excess capacity if those additional team members are not working 100% of the time. These are key findings for healthcare systems and for administrators and decision-makers in any setting or sector where fluid teams are the norm, says Sedatole: from consultancy to software development to airline ground crews. Wherever diverse professionals come together briefly or sporadically to perform tasks and then disperse, individual motivation can be optimized by simple mechanisms—cost-effective tangible rewards—that give team members a fresh opportunity to earn the incentive in different settings on different occasions—a recurring chance to succeed that keeps the incentive systems engaging and effective over time. For healthcare in particular, this is a win-win-win, says Williams. “In the United States we are faced with lower reimbursements and higher costs, so we have to look for areas where we can gain efficiencies and minimize costs. In the healthcare value model, time and costs are denominators, and quality and service are numerators. Any way we can save on costs and improve efficiencies allows us to take care of more patients, and to be able to do that effectively. “We made some incredible improvements here. We went from just average to best in class, right to the frontier of operative efficiency. And there is so much more opportunity out there to pull more levers and reach new levels, which is truly encouraging.” Looking to know more or connect with Asa Griggs Candler Professor of Accounting, Karen Sedatole?  Simply click on her icon now to arrange an interview or time to talk today.

5 min

Why Simultaneous Voting Makes for Good Decisions

How can organizations make robust decisions when time is short, and the stakes are high? It’s a conundrum not unfamiliar to the U.S. Food and Drug Administration. Back in 2021, the FDA found itself under tremendous pressure to decide on the approval of the experimental drug aducanumab, designed to slow the progress of Alzheimer’s disease—a debilitating and incurable condition that ranks among the top 10 causes of death in the United States. Welcomed by the market as a game-changer on its release, aducanumab quickly ran into serious problems. A lack of data on clinical efficacy along with a slew of dangerous side effects meant physicians in their droves were unwilling to prescribe it. Within months of its approval, three FDA advisors resigned in protest, one calling aducanumab, “the worst approval decision that the FDA has made that I can remember.” By the start of 2024, the drug had been pulled by its manufacturers. Of course, with the benefit of hindsight and data from the public’s use of aducanumab, it is easy for us to tell that FDA made the wrong decision then. But is there a better process that would have given FDA the foresight to make the right decision, under limited information? The FDA routinely has to evaluate novel drugs and treatments; medical and pharmaceutical products that can impact the wellbeing of millions of Americans. With stakes this high, the FDA is known to tread carefully: assembling different advisory, review, and funding committees providing diverse knowledge and expertise to assess the evidence and decide whether to approve a new drug, or not. As a federal agency, the FDA is also required to maintain scrupulous records that cover its decisions, and how those decisions are made. The Impact of Voting Mechanisms on Decision Quality Some of this data has been analyzed by Goizueta’s Tian Heong Chan, associate professor of information systems and operation management. Together with Panos Markou of the University of Virginia’s Darden School of Business, Chan scrutinized 17 years’ worth of information, including detailed transcripts from more than 500 FDA advisory committee meetings, to understand the mechanisms and protocols used in FDA decision-making: whether committee members vote to approve products sequentially, with everyone in the room having a say one after another; or if voting happens simultaneously via the push of a button, say, or a show of hands. Chan and Markou also looked at the impact of sequential versus simultaneous voting to see if there were differences in the quality of the decisions each mechanism produced. Their findings are singular. It turns out that when stakeholders vote simultaneously, they make better decisions. Drugs or products approved this way are far less likely to be issued post-market boxed warnings (warnings issued by FDA that call attention to potentially serious health risks associated with the product, that must be displayed on the prescription box itself), and more than two times less likely to be recalled. The FDA changed its voting protocols in 2007, when they switched from sequentially voting around the room, one person after another, to simultaneous voting procedures. And the results are stunning. Tian Heong Chan, Associate Professor of Information Systems & Operation Management “Decisions made by simultaneous voting are more than twice as effective,” says Chan. “After 2007, you see that just 3.4% of all drugs and products approved this way end up being discontinued or recalled. This compares with an 8.6% failure rate for drugs approved by the FDA using more sequential processes—the round robin where individuals had been voting one by one around the room.” Imagine you are told beforehand that you are going to vote on something important by simply raising your hand or pressing a button. In this scenario, you are probably going to want to expend more time and effort in debating all the issues and informing yourself before you decide. Tian Heong Chan “On the other hand, if you know the vote will go around the room, and you will have a chance to hear how others’ speak and explain their decisions, you’re going to be less motivated to exchange and defend your point of view beforehand,” says Chan. In other words, simultaneous decision-making is two times less likely to generate a wrong decision as the sequential approach. Why is this? Chan and Markou believe that these voting mechanisms impact the quality of discussion and debate that undergird decision-making; that the quality of decisions is significantly impacted by how those decisions are made. Quality Discussion Leads to Quality Decisions Parsing the FDA transcripts for content, language, and tonality in both settings, Chan and Markou find evidence to support this. Simultaneous voting or decision-making drives discussions that are characterized by language that is more positive, more authentic, and more even in terms of expressions of authority and hierarchy, says Chan. What’s more, these deliberations and exchanges are deeper and more far-ranging in quality. We find marked differences in the tone of speech and the topics discussed when stakeholders know they will be voting simultaneously. There is less hierarchy in these exchanges, and individuals exhibit greater confidence in sharing their points of view more freely. Tian Heong Chan “We also see more questions being asked, and a broader range of topics and ideas discussed,” says Chan. In this context, decision-makers are also less likely to reach unanimous agreement. Instead, debate is more vigorous and differences of opinion remain more robust. Conversely, sequential voting around the room is typically preceded by shorter discussion in which stakeholders share fewer opinions and ask fewer questions. And this demonstrably impacts the quality of the decisions made, says Chan. Sharing a different perspective to a group requires effort and courage. With sequential voting or decision-making, there seems to be less interest in surfacing diverse perspectives or hidden aspects to complex problems. Tian Heong Chan “So it’s not that individuals are being influenced by what other people say when it comes to voting on the issue—which would be tempting to infer—rather, it’s that sequential voting mechanisms seem to take a bit more effort out of the process.” When decision-makers are told that they will have a chance to vote and to explain their vote, one after another, their incentives to make a prior effort to interrogate each other vigorously, and to work that little bit harder to surface any shortcomings in their own understanding or point of view, or in the data, are relatively weaker, say Chan and Markou. The Takeaway for Organizations Making High-Stakes Decisions Decision-making in different contexts has long been the subject of scholarly scrutiny. Chan and Markou’s research sheds new light on the important role that different mechanisms have in shaping the outcomes of decision-making—and the quality of the decisions that are jointly taken. And this should be on the radar of organizations and institutions charged with making choices that impact swathes of the community, they say. “The FDA has a solid tradition of inviting diversity into its decision-making. But the data shows that harnessing the benefits of diversity is contingent on using the right mechanisms to surface the different expertise you need to be able to see all the dimensions of the issue, and make better informed decisions about it,” says Chan. A good place to start? By a concurrent show of hands. Tian Heong Chan is an associate professor of information systems and operation management. he is available to speak about this topic - click on his con now to arrange an interview today.

4 min

Expert Perspective: The Hidden Costs of Cultural Appropriation

In our interconnected world, cultural borrowing is everywhere. But why do some instances earn applause while others provoke outrage? This question is becoming increasingly crucial for business leaders who must carefully navigate cultural boundaries. Take the backlash the Kardashian-Jenner family faced for adopting styles from minority cultures or the controversy over non-Indigenous designers using Native American patterns in fashion. These examples highlight the issue of cultural appropriation, where borrowing elements from another culture without genuine understanding or respect can lead to accusations of exploitation. Abraham Oshotse, an assistant professor of organization and management at Goizueta Business School, along with Assistant Professor of Sociology and Anthropology at Hebrew University Yael Berda and Associate Professor of Organizational Behavior at the Stanford Graduate School of Business Amir Goldberg, explores this in their research on “cultural tariffing.” They shed light on why high-status individuals, such as celebrities or industry leaders, often come under fire when crossing cultural boundaries. The Concept of Cultural Tariffing Oshotse and coauthors define cultural tariffing as “the act of imposing a social cost on cultural boundary crossing. It is levied on high-status actors crossing into low-status culture, in order to mitigate the reproduction of the status inequality.” This notion suggests that the acceptance or rejection of cultural boundary-crossing is influenced by the perceived costs and benefits. Cultural appropriation involves taking elements from a culture that one does not belong to, without permission or authority. For example, when Elvis Presley brought African-American music into the mainstream, it was initially seen as elevating the genre. However, in today’s context, such acts might be criticized as appropriation rather than celebration. This research seeks to analyze people’s modern reactions to different examples of cultural boundary-crossing and which conditions induce cultural tariffing. The Hypotheses The researchers make four hypotheses about participants’ reactions to cultural appropriation: People will disapprove of cultural borrowing if there’s a clear power imbalance, with the borrowing group having more status or privilege than the group they are borrowing from. Cultural borrowing is more likely to be criticized if the person doing it has a higher socioeconomic status within their social group. Cultural borrowing is more likely to be criticized if the person doing it has only a shallow connection to the culture they’re borrowing from. Cultural borrowing is more likely to be criticized if the person doing it benefits more from it than the people from the culture they are borrowing from. Put to the Test Oshotse et al exposed respondents to four scenarios per hypothesis (16 total) with a permissible and a transgressive condition. In the permissible condition, subjects exhibit lower status or socioeconomic standing or a stronger connection to the target culture. Subjects in the transgressive condition exhibit a higher status or socioeconomic standing and less of an authentic connection to the target culture. Insights from the Study Oshotse’s study offers four key insights: Status Matters: Cultural boundary-crossing is more likely to generate disapproval if there’s a clear status difference favoring the adopter. Superficial Connections: The less authentic the adopter’s connection to the target culture, the more likely they are to face backlash. Socioeconomic Influence: Higher socioeconomic status within the adopter’s social group increases the likelihood of disapproval. Value Extraction: The more value the adopter gains relative to the culture they’re borrowing from, the higher the disapproval. These insights are crucial for leaders who want to navigate cultural boundaries successfully, ensuring their actions are seen as respectful and inclusive rather than exploitative. Real-World Implications for Business Leaders Why does this matter for business leaders? Understanding cultural tariffing is crucial when expanding into new markets, launching multicultural campaigns, or even managing diverse teams. The research suggests that crossing cultural boundaries without deep understanding or respect can backfire. That’s especially true when the adopter holds a higher socioeconomic status. Consider the example of a luxury brand adopting traditional African patterns without engaging with the communities behind them. In this case, it risks being seen as exploitative rather than innovative. The consequences aren’t just reputational; they can also impact the brand’s bottom line. This research isn’t just about isolated incidents; it mirrors sweeping societal shifts. Over the past 50 years, Western views have evolved to embrace ethnic diversity and multicultural exchange. But with this newfound appreciation comes a fresh set of challenges. Today’s leaders must navigate cultural interactions with greater care, fully aware of the historical and social contexts that shape perceptions of appropriation. In today’s global and interconnected business landscape, mastering the subtleties of cultural appropriation and tariffing is crucial. Leaders who tread thoughtfully can boost their reputation and success, while those who falter may face serious backlash. By understanding the hidden costs of crossing cultural boundaries, business leaders can cultivate authentic exchanges and steer clear of the pitfalls of appropriation. Abraham Oshotse is an assistant professor of organization & management. He is available speak to media regarding  this important topic - simply click on his icon now to arrange an interview today.

View all posts