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Hiring More Nurses Generates Revenue for Hospitals

Underfunding is driving an acute shortage of trained nurses in hospitals and care facilities in the United States. It is the worst such shortage in more than four decades. One estimate from the American Hospital Association puts the deficit north of one million. Meanwhile, a recent survey by recruitment specialist AMN Healthcare suggests that 900,000 more nurses will drop out of the workforce by 2027. American nurses are quitting in droves, thanks to low pay and burnout as understaffing increases individual workload. This is bad news for patient outcomes. Nurses are estimated to have eight times more routine contact with patients than physicians. They shoulder the bulk of all responsibility in terms of diagnostic data collection, treatment plans, and clinical reporting. As a result, understaffing is linked to a slew of serious problems, among them increased wait times for patients in care, post-operative infections, readmission rates, and patient mortality—all of which are on the rise across the U.S. Tackling this crisis is challenging because of how nursing services are reimbursed. Most hospitals operate a payment system where services are paid for separately. Physician services are billed as separate line items, making them a revenue generator for the hospitals that employ them. But under Medicare, nursing services are charged as part of a fixed room and board fee, meaning that hospitals charge the same fee regardless of how many nurses are employed in the patient’s care. In this model, nurses end up on the other side of hospitals’ balance sheets: a labor expense rather than a source of income. For beleaguered administrators looking to sustain quality of care while minimizing costs (and maximizing profits), hiring and retaining nursing staff has arguably become something of a zero-sum game in the U.S. The Hidden Costs of Nurse Understaffing But might the balance sheet in fact be skewed in some way? Could there be potential financial losses attached to nurse understaffing that administrators should factor into their hiring and remuneration decisions? Research by Goizueta Professors Diwas KC and Donald Lee, as well as recent Goizueta PhD graduates Hao Ding 24PhD (Auburn University) and Sokol Tushe 23PhD (Muma College of Business), would suggest there are. Their new peer-reviewed publication* finds that increasing a single nurse’s workload by just one patient creates a 17% service slowdown for all other patients under that nurse’s care. Looking at the data another way, having one additional nurse on duty during the busiest shift (typically between 7am and 7pm) speeds up emergency department work and frees up capacity to treat more patients such that hospitals could be looking at a major increase in revenue. The researchers calculate that this productivity gain could equate to a net increase of $470,000 per 10,000 patient visits—and savings to the tune of $160,000 in lost earnings for the same number of patients as wait times are reduced. “A lot of the debate around nursing in the U.S. has focused on the loss of quality in care, which is hugely important,” says Diwas KC. But looking at the crisis through a productivity lens means we’re also able to understand the very real economic value that nurses bring too: the revenue increases that come with capacity gains. Diwas KC, Goizueta Foundation Term Professor of Information Systems & Operations Management “Our findings challenge the predominant thinking around nursing as a cost,” adds Lee. “What we see is that investing in nursing staff more than pays for itself in downstream financial benefits for hospitals. It is effectively a win-win-win for patients, nurses, and healthcare providers.” Nurse Load: the Biggest Impact on Productivity To get to these findings, the researchers analyzed a high-resolution dataset on patient flow through a large U.S. teaching hospital. They looked at the real-time workloads of physicians and nurses working in the emergency department between April 2018 and March 2019, factoring in variables such as patient demographics and severity of complaint or illness. Tracking patients from admission to triage and on to treatment, the researchers were able to tease out the impact that the number of nurses and physicians on duty had on patient throughput. Using a novel machine learning technique developed at Goizueta by Lee, they were able to identify the effect of increasing or reducing the workforce. The contrast between physicians and nursing staff is stark, says Tushe. “When you have fewer nurses on duty, capacity and patient throughput drops by an order of magnitude—far, far more than when reducing the number of doctors. Our results show that for every additional patient the nurse is responsible for, service speed falls by 17%. That compares to just 1.4% if you add one patient to the workload of an attending physician. In other words, nurses’ impact on productivity in the emergency department is more than eight times greater.” Boosting Revenue Through Reduced Wait Times Adding an additional nurse to the workforce, on the other hand, increases capacity appreciably. And as more patients are treated faster, hospitals can expect a concomitant uptick in revenue, says KC. “It’s well documented that cutting down wait time equates to more patients treated and more income. Previous research shows that reducing service time by 15 minutes per 30,000 patient visits translates to $1.4 million in extra revenue for a hospital.” In our study, we calculate that staffing one additional nurse in the 7am to 7pm emergency department shift reduces wait time by 23 minutes, so hospitals could be looking at an increase of $2.33 million per year. Diwas KC This far eclipses the costs associated with hiring one additional nurse, says Lee. “According to 2022 U.S. Bureau of Labor Statistics, the average nursing salary in the U.S. is $83,000. Fringe benefits account for an additional 50% of the base salary. The total cost of adding one nurse during the 7am to 7pm shift is $310,000 (for 2.5 full-time employees). When you do the math, it is clear. The net hospital gain is $2 million for the hospital in our study. Or $470,000 per 10,000 patient visits.” Incontrovertible Benefits to Hiring More Nurses These findings should provide compelling food for thought both to healthcare administrators and U.S. policymakers. For too long, the latter have fixated on the upstream costs, without exploring the downstream benefits of nursing services, say the researchers. Their study, the first to quantify the economic value of nurses in the U.S., asks “better questions,” argues Tushe; exploiting newly available data and analytics to reveal incontrovertible financial benefits that attach to hiring—and compensating—more nurses in American hospitals. We know that a lot of nurses are leaving the profession not just because of cuts and burnout, but also because of lower pay. We would say to administrators struggling to hire talented nurses to review current wage offers, because our analysis suggests that the economic surplus from hiring more nurses could be readily applied to retention pay rises also. Sokol Tushe 23PhD, Muma College of Business The Case for Mandated Ratios For state-level decision makers, Lee has additional words of advice. “In 2004, California mandated minimum nurse-to-patient ratios in hospitals. Since then, six more states have added some form of minimum ratio requirement. The evidence is that this has been beneficial to patient outcomes and nurse job satisfaction. Our research now adds an economic dimension to the list of benefits as well. Ipso facto, policymakers ought to consider wider adoption of minimum nurse-to-patient ratios.” However, decision makers go about tackling the shortage of nurses in the U.S., they should go about it fast and soon, says KC. “This is a healthcare crisis that is only set to become more acute in the near future. As our demographics shift and our population starts again out, demand for quality will increase. So too must the supply of care capacity. But what we are seeing is the nursing staffing situation in the U.S. moving in the opposite direction. All of this is manifesting in the emergency department. That’s where wait times are getting longer, mistakes are being made, and overworked nurses are quitting. It is creating a vicious cycle that needs to be broken.” Diwas Diwas KC is a professor of information systems & operations management and Donald Lee is an associate professor of information systems & operations management. Both experts are available to speak about this important topic - simply click on either icon now to arrange an interview today.

Decoding the Future of AI: From Disruption to Democratisation and Beyond

The global AI landscape has become a melting pot for innovation, with diverse thinking pushing the boundaries of what is possible. Its application extends beyond just technology, reshaping traditional business models and redefining how enterprises, governments, and societies operate. Advancements in model architectures, training techniques and the proliferation of open-source tools are lowering barriers to entry, enabling organisations of all sizes to develop competitive AI solutions with significantly fewer resources. As a result, the long-standing notion that AI leadership is reserved for entities with vast computational and financial resources is being challenged. This shift is also redrawing the global AI power balance, with a decentralised approach to AI where competition and collaboration coexist across different regions. As AI development becomes more distributed, investment strategies, enterprise innovation and global technological leadership are being reshaped. However, established AI powerhouses still wield significant leverage, driving an intense competitive cycle of rapid innovation. Amid this acceleration, it is critical to distinguish true technological breakthroughs from over-hyped narratives, adopting a measured, data-driven approach that balances innovation with demonstrable business value and robust ethical AI guardrails. Implications of the Evolving AI Landscape The democratisation of AI advancements, intensifying competitive pressures, the critical need for efficiency and sustainability, evolving geopolitical dynamics and the global race for skilled talent are all fuelling the development of AI worldwide. These dynamics are paving the way for a global balance of technological leadership. Democratisation of AI Potential The ability to develop competitive AI models at lower costs is not only broadening participation but also reshaping how AI is created, deployed and controlled. Open-source AI fosters innovation by enabling startups, researchers, and enterprises to collaborate and iterate rapidly, leading to diverse applications across industries. For example, xAI has made a significant move in the tech world by open sourcing its Grok AI chatbot model, potentially accelerating the democratisation of AI and fostering innovation. However, greater accessibility can also introduce challenges, including risks of misuse, uneven governance, and concerns over intellectual property. Additionally, as companies strategically leverage open-source AI to influence market dynamics, questions arise about the evolving balance between open innovation and proprietary control. Increased Competitive Pressure The AI industry is fuelled by a relentless drive to stay ahead of the competition, a pressure felt equally by Big Tech and startups. This is accelerating the release of new AI services, as companies strive to meet growing consumer demand for intelligent solutions. The risk of market disruption is significant; those who lag, face being eclipsed by more agile players. To survive and thrive, differentiation is paramount. Companies are laser-focused on developing unique AI capabilities and applications, creating a marketplace where constant adaptation and strategic innovation are crucial for success. Resource Optimisation and Sustainability The trend toward accessible AI necessitates resource optimisation, which means developing models with significantly less computational power, energy consumption and training data. This is not just about cost; it is crucial for sustainability. Training large AI models is energy-intensive; for example, training GPT-3, a 175-billion-parameter model, is believed to have consumed 1,287 MWh of electricity, equivalent to an average American household’s use over 120 years1. This drives innovation in model compression, transfer learning, and specialised hardware, like NVIDIA’s TensorRT. Small language models (SLMs) are a key development, offering comparable performance to larger models with drastically reduced resource needs. This makes them ideal for edge devices and resource-constrained environments, furthering both accessibility and sustainability across the AI lifecycle. Multifaceted Global AI Landscape The global AI landscape is increasingly defined by regional strengths and priorities. The US, with its strength in cloud infrastructure and software ecosystem, leads in “short-chain innovation”, rapidly translating AI research into commercial products. Meanwhile, China excels in “long-chain innovation”, deeply integrating AI into its extended manufacturing and industrial processes. Europe prioritises ethical, open and collaborative AI, while the APAC counterparts showcase a diversity of approaches. Underlying these regional variations is a shared trajectory for the evolution of AI, increasingly guided by principles of responsible AI: encompassing ethics, sustainability and open innovation, although the specific implementations and stages of advancement differ across regions. The Critical Talent Factor The evolving AI landscape necessitates a skilled workforce. Demand for professionals with expertise in AI and machine learning, data analysis, and related fields is rapidly increasing. This creates a talent gap that businesses must address through upskilling and reskilling initiatives. For example, Microsoft has launched an AI Skills Initiative, including free coursework and a grant program, to help individuals and organisations globally develop generative AI skills. What does this mean for today’s enterprise? New Business Horizons AI is no longer just an efficiency tool; it is a catalyst for entirely new business models. Enterprises that rethink their value propositions through AI-driven specialisation will unlock niche opportunities and reshape industries. In financial services, for example, AI is fundamentally transforming operations, risk management, customer interactions, and product development, leading to new levels of efficiency, personalisation and innovation. Navigating AI Integration and Adoption Integrating AI is not just about deployment; it is about ensuring enterprises are structurally prepared. Legacy IT architectures, fragmented data ecosystems and rigid workflows can hinder the full potential of AI. Organisations must invest in cloud scalability, intelligent automation and agile operating models to make AI a seamless extension of their business. Equally critical is ensuring workforce readiness, which involves strategically embedding AI literacy across all organisational functions and proactively reskilling talent to collaborate effectively with intelligent systems. Embracing Responsible AI Ethical considerations, data security and privacy are no longer afterthoughts but are becoming key differentiators. Organisations that embed responsible AI principles at the core of their strategy, rather than treating them as compliance check boxes, will build stronger customer trust and long-term resilience. This requires proactive bias mitigation, explainable AI frameworks, robust data governance and continuous monitoring for potential risks. Call to Action: Embracing a Balanced Approach The AI revolution is underway. It demands a balanced and proactive response. Enterprises must invest in their talent and reskilling initiatives to bridge the AI skills gap, modernise their infrastructure to support AI integration and scalability and embed responsible AI principles at the core of their strategy, ensuring fairness, transparency and accountability. Simultaneously, researchers must continue to push the boundaries of AI’s potential while prioritising energy efficiency and minimising environmental impact; policymakers must create frameworks that foster responsible innovation and sustainable growth. This necessitates combining innovative research with practical enterprise applications and a steadfast commitment to ethical and sustainable AI principles. The rapid evolution of AI presents both an imperative and an opportunity. The next chapter of AI will be defined by those who harness its potential responsibly while balancing technological progress with real-world impact. Resources Sudhir Pai: Executive Vice President and Chief Technology & Innovation Officer, Global Financial Services, Capgemini Professor Aleks Subic: Vice-Chancellor and Chief Executive, Aston University, Birmingham, UK Alexeis Garcia Perez: Professor of Digital Business & Society, Aston University, Birmingham, UK Gareth Wilson: Executive Vice President | Global Banking Industry Lead, Capgemini 1 https://www.datacenterdynamics.com/en/news/researchers-claim-they-can-cut-ai-training-energy-demands-by-75/?itm_source=Bibblio&itm_campaign=Bibblio-related&itm_medium=Bibblio-article-related

AI, Data & Digital Regulations: Global Risks & Opportunities in 2025

The adoption of artificial intelligence (AI) technologies and the massive growth of data generation is leading to significant advantages in global business. However, it is also presenting greater challenges with cybersecurity, data governance, regulatory compliance, and ethical conduct. In the video below, hear digital investigations and discovery experts Antonio Rega and Simon Placks discuss risks and opportunities around AI, data, and digital regulations covered in the 2025 J.S. Held Global Risk Report. To view the report and learn more about crypto and digital asset risks and opportunities click on the button below: Looking to know more or connect with Simon Placks or Antonio Rega? Simply click on either expert's icon now to arrange an interview today.

J.S. Held Global Risk Report Unpacks AI Challenges and Digital Regulations Reshaping Business

Artificial intelligence (AI) is transforming industries, yet its rapid adoption brings new risks and regulatory scrutiny. The J.S. Held 2025 Global Risk Report provides expert perspective on AI-driven cyber threats, data governance challenges, and compliance requirements shaping the future of business. As companies integrate AI to enhance efficiency, they must also navigate risks such as data poisoning, biased AI outputs, and legal exposure under the EU AI Act. The report highlights how businesses can safeguard their operations while leveraging AI’s potential for cybersecurity, fraud detection, and operational efficiency. Key insights from the report include: The growing use of AI by cybercriminals to launch sophisticated attacks The environmental impact of AI’s energy-intensive data centers How AI-specific insurance products are evolving to cover new risks Compliance challenges posed by the EU AI Act for high-risk systems The rise of AI governance roles to ensure ethical implementation “With regulatory landscapes shifting and cyber risks escalating, the 2025 Global Risk Report helps equip businesses with the knowledge needed to stay ahead of evolving threats,” noted digital forensics, data governance, privacy, security, emerging technology, and discovery expert Antonio Rega. London-based digital investigations and discovery expert Simon Placks joins Antonio Rega to discuss risks and opportunities around AI, data, and digital regulations explored in the J.S. Held 2025 Global Risk Report in this video: Beyond AI, the J.S. Held 2025 Global Risk Report examines four additional critical risk areas: sustainability, supply chain disruptions, cryptocurrency trends, and cyber risk management. Each section offers actionable strategies to mitigate threats and capitalize on emerging opportunities. For media inquiries, requests for interviews, or to further discuss the risks and opportunities outlined in the report, email GlobalRiskReport@jsheld.com. To connect with Simon Placks or Antonio Rega simply click on either expert's icon now. For any other media inquiries - contact : Kristi L. Stathis, J.S. Held +1 786 833 4864 Kristi.Stathis@JSHeld.com

Crypto & Digital Assets: Global Risks & Opportunities in 2025

The adoption of cryptocurrency and digital assets is expected to increase in all forms this year given the pro-crypto stance of the new Trump administration. Traditional financial institutions and fintech companies are bringing cryptocurrencies to their customers and searching for regulatory and legal clarity. In the video below, J.P. Brennan, Global Head of Fintech, Payments, Crypto Compliance and Investigations, discusses crypto and digital asset risks and opportunities covered in the 2025 J.S. Held Global Risk Report. To view the report and learn more about crypto and digital asset risks and opportunities click on the button below: Looking to know more or connect with J.P. Brennan about the adoption of cryptocurrency and digital assets? Simply click on his icon to arrange an interview today.

J.S. Held Experts Examine Crypto’s Pitfalls and Potential

The global cryptocurrency market has surged to a staggering USD 3.4 trillion. However, alongside this rapid expansion, significant challenges and risks continue to emerge. The J.S. Held 2025 Global Risk Report examines the evolving landscape of crypto and digital assets, highlighting both the potential and the pitfalls of this dynamic sector. The explosion of cryptocurrency adoption across industries—from gaming to decentralized finance (DeFi)—has led to increased regulatory scrutiny and security concerns. With the expected growth in the number of users to exceed 107.3 million in the market by 2025, every sector is looking at what crypto and this blockchain technology can do to transform their business. Even the gaming industry has entered the crypto space with bridging services offering “Play-to-Earn” (P2E) games. While anonymity remains a key feature in both the risk and success of cryptocurrency, the concept of “Know Your Customer” on centralized platforms is still required but continues to evolve because not all anonymity is evil. Despite regulatory, environmental, geopolitical, and other business risks, the J.S. Held 2025 Global Risk Report reveals how the crypto industry continues to evolve, offering new opportunities for businesses and investors around: Enhanced Transparency & Security Regulatory Clarity Education & Compliance Digital Identity Solutions “With regulatory frameworks tightening globally—from the European Union’s Markets in Crypto-Assets (MiCA) law to China’s outright ban—the future of crypto remains at a critical inflection point,” observes J.P. Brennan, Global Head of Fintech, Payments, Crypto Compliance and Investigations at J.S. Held. “As the industry matures, the balance between risk mitigation and innovation will shape the next phase of digital asset adoption,” J.P. Brennan adds. J.P. Brennan examines the crypto risks and opportunities outlined in the 2025 J.S. Held Global Risk Report in this video: Cryptocurrency and digital asset risk is just one of the five key areas analyzed in the J.S. Held 2025 Global Risk Report. Other topics include sustainability, supply chain, Artificial Intelligence (AI) and data regulations, and managing cyber risk. If you have any questions or would like to further discuss the risks and opportunities outlined in the report, please email GlobalRiskReport@jsheld.com. To connect with J.P. Brennan, simply click on his icon now. For any other media inquiries - contact : Kristi L. Stathis, J.S. Held +1 786 833 4864 Kristi.Stathis@JSHeld.com

Kert Anzilotti, M.D., Appointed President of the Medical Group of ChristianaCare

Kert Anzilotti, M.D., MBA, FACR has been appointed president of the Medical Group of ChristianaCare. Anzilotti has served as interim president since June 2024. He will also continue in his role as system chief medical officer of ChristianaCare. As president of the ChristianaCare Medical Group, Anzilotti will seek to improve every aspect of care for every person the Medical Group touches. He will focus on the optimization of care delivery, strategic visioning, network development, clinical technology implementation and leveraging medical informatics. Anzilotti will continue to develop new care models that transcend settings, promote value-based care and improve the patient experience across the clinical enterprise. Among his priorities are the adoption of population health measures, the embedding of health equity into care delivery and workforce development, further expansion of access points for patients and the continuous enhancement of patient and caregiver experience. “Dr. Anzilotti is exceptionally qualified to lead the Medical Group of ChristianaCare,” said Janice E. Nevin, M.D., MPH, president and CEO of ChristianaCare. “His passion for our mission and vision for the future strength of our Medical Group is unwavering. Since joining ChristianaCare in 2011, Dr. Anzilotti has earned a well-deserved reputation as a thoughtful and collaborative leader.” Anzilotti has served in numerous leadership roles at ChristianaCare, including as chief medical officer, acute care; chair of the Department of Radiology; medical director of Imaging Services; and physician leader of the Neurosciences Service Line. He also previously served as Interim President and CEO for the eBrightHealth ACO with responsibility for physician leadership and network operations. He is board certified in Neuroradiology. “Over the many years I have been at ChristianaCare, I have had the privilege of witnessing the dedication and compassion of my Medical Group colleagues as we served together with love and excellence,” Anzilotti said. “I am honored to lead this incredible, dynamic group that is reshaping the future of care, ensuring everyone we serve can achieve their best health.” Anzilotti earned his medical degree from Jefferson Medical College of Thomas Jefferson University in Philadelphia. He earned his MBA at the University of Delaware, completed the Managing Health Care Delivery Course at Harvard Business School and graduated as Physician Executive Fellow in the Health Management Academy, GE Fellows Program. The Medical Group of ChristianaCare consists of over 2,200 dedicated doctors, nurse practitioners, physician assistants and other caregivers. This highly skilled team delivers exceptional care through ChristianaCare’s community-based primary care and specialty care practices serving Delaware and surrounding states. Additionally, the Medical Group collaborates with ChristianaCare hospitalists to ensure seamless continuity of care for our patients, from primary care to hospital care and back again.

ExpertSpotlight: Today is Women’s Equality Day

Women’s Equality Day on August 26 marks a pivotal moment in history, celebrating the anniversary of the 19th Amendment’s adoption, which granted women the right to vote in the United States. This day is not just a commemoration of past achievements but a call to address the ongoing challenges women face in achieving full equality. From wage gaps and representation in leadership to reproductive rights and gender-based violence, the fight for women’s equality continues to be a crucial issue in today’s society. This topic is significant as it highlights both the progress made and the work still needed to ensure true equality for all women. Key story angles that journalists might explore include: The evolution of women’s rights since the 19th Amendment and the ongoing struggle for gender equality. Current challenges women face in the workforce, including wage disparity and underrepresentation in leadership roles. The role of women in politics and the importance of female representation in government. Intersectionality in the women’s rights movement: how race, class, and other identities intersect with gender. The impact of recent legal decisions and legislation on women’s reproductive rights. Celebrations and events surrounding Women’s Equality Day across the country. This alert emphasizes the importance of reflecting on both historical achievements and current challenges, making it a compelling topic for coverage. Connect with an expert about Women’s Equality Day: To search our full list of experts visit www.expertfile.com

A future with one plug: how universal EV outlets simplify charging for electric vehicle owners

Have you ever found yourself frustrated with the numerous types of charging plugs for electric vehicles when going to charge your car? Picture this: a future where every charging station supports a universal outlet. No more worrying about whether your plug will fit or if you need an adapter. Sounds like a dream, right? Well that dream is now real.  University of Delaware professor Willett Kempton and his coauthors have recently released a new paper outlining a new universal EV outlet standard in World Electric Vehicle Journal. His coauthors include University of Delaware PhD graduates Rodney McGee and Garrett Ejzak.  There are three standard EV charging connectors – the part you hold in your hand that plugs into EVs with matching inlets – in North America. Rather than requiring three charging stations at each location, Willett and his team proposed to have a universal EV outlet on the charging station, and cars would come with a cable with a universal plug to plug into the station.  The solution for EV charging is similar to what has already evolved for charging cell phones and other portable electronics. Cell phones and laptops have many different types of power inlet connections on the device, incompatible with each other. This solution was deliberately designed so that todays’ EVs and charging stations do not need to be replaced. Because these new standards have resulted from a consensus of more than 150 participants from the automotive, charger, and power industries, new innovations will also be coming with the adoption of the new standards. These include lower-cost and lower-maintenance charging stations, higher energy efficiency.  Kempton, McGee and Ejzak can be reached by clicking Kempton's contact button. 

#Expert Insight: Political Fandom

The 2024 Presidential campaign has been a roller coaster ride this summer. The upheavals are so fast and unprecedented that the reaction to each event often seems too muted. An assassination attempt and sudden pre-convention withdrawal? In a past generation, these events would be decisive, but in 2024, they seem like just the latest blip in the news cycle. The polls never seem to move more than a couple of points. In such an oddly volatile but also stable environment, our best bet to understanding what is going to transpire during the last 100 days of the election cycle is to look at data that gets to the heart of how voters view the candidates. My choice of fundamental data or essential metric is candidate fandom. Fandom is an unusual metric in politics, but it should be more common. Fandom is about passion for and loyalty to a cultural entity, be it a team, singer, university, or even politician. In fact, MAGA Trump supporters and Bernie Bros share many characteristics with Swifties and Lakers fans. Fans of all these things show up, spend, wear branded apparel, and fiercely defend the object of their fandom. The politicians who inspire fandom, such as AOC, Donald Trump, Barack Obama, and Marjorie Taylor Green, enjoy many advantages and are the celebrities of the political world. Fandom is critical in politics because fans are loyal, engaged, and resilient. Fans are not casual potential voters who may change preferences and are unlikely to make an effort to stand in line to vote. Fans are the voters who will show up rain or shine and who can’t be swayed. In 2024, a fan will interpret a conviction of their candidate as political “lawfare” rather than evidence of criminality. Also, in 2024, a fan will make excuses for signs of aging that would result in children taking a senior’s car keys. The flip side of fandom, anti-fandom, is also a powerful political force. Indeed, politics may be the cultural context in which anti-fandom has the most impact. Taylor Swift may have haters, but these anti-Swifties are not buying tickets to see Katy Perry in protest. But in politics, hatred of a candidate might be as powerful a tool for generating a vote as fandom. Joe Biden’s 2020 campaign was notoriously bad at drawing crowds, suggesting he inspired little passion. In contrast, Trump’s rallies looked like rabid sports crowds complete with matching hats. However, the hatred and fear of Donald Trump inspired sufficient anti-fandom to make Biden competitive. Of course, fandom doesn’t entirely decide elections. In most elections, there isn’t all that much fandom or passion. Beyond the presidency and senatorial contests, most candidates are barely known, and identity factors (race, gender, party affiliation) and candidate awareness are the determining factors. Even in presidential elections, get-out-the-vote efforts (ballot harvesting) and election regulations (voter suppression) combined with effective marketing to the few percent of swing (low information) voters are often the determining factors. Looking toward the future, fandom may be an increasingly salient political metric for multiple reasons. First, the last two decades have witnessed many candidates raised quickly from obscurity with somehow Hollywood-worthy origin stories (Barack Obama, AOC, JD Vance, etc.). In the modern media environment, candidates’ reputations (brands) are increasingly the product of marketing narratives rather than a lifetime of real-world accomplishments. In this new world of politics, fandom will be a critical metric. Second, with the increasing diversity of the American electorate, voting will be increasingly based on identity rather than ideology. Identity-based voting segments are likely to be driven by fandom (and anti-fandom) rather than policy. We see a form of this in 2024, as high inflation has barely made a dent in voters’ preferences for the two parties. A fragmented electorate comprised of racial and gender segments whose preferences are driven by fandom and anti-fandom will lead to increasingly negative campaigns featuring ads highlighting the threat of the non-preferred party’s candidates. When voters are focused on identity, negative advertising becomes the ideal method to use fear to create anti-fandom (hate) to motivate turnout. Kamala Harris versus Donald Trump Barring further disruptions, the matchup is set for the 2024 presidential contest (as of this writing, we do not know the Democratic VP). We do know the matchup between Donald Trump and Kamala Harris is a contest between polarizing figures. Donald Trump is a movement candidate who has redefined the Republican party. He inspires passionate fandom from his followers and amazing antipathy from major media and cultural outlets. Harris is also polarizing. In the immediate aftermath of Biden’s withdrawal, Harris received massive media and donor support. However, Harris has not demonstrated any significant national voter appeal, and her time as VP has generated ample blooper real material. My approach to assessing the race is to examine each candidate's fandom and anti-fandom. Fandom is the candidate’s core, resilient support, while anti-fandom is about antipathy. Fandom and anti-fandom are especially powerful metrics for a candidate because they are relatively fixed after a candidate gains high awareness. Once an individual identifies with the candidate (e.g., they are on the same team), an attack on the candidate is an attack on the individual. This means attack ads do not work because fans feel they are being attacked. Anti-fans are also important because they constrain a candidate’s support. A Trump anti-fan is unpersuadable by efforts from the Trump campaign because their identity is steeped in opposition to him. Fans and anti-fans are trapped in a cycle of confirmation bias where all information is processed to fit their fandom. I use data from the Next Generation Fandom Survey to assess candidate fandom and anti-fandom. The Next Generation Fandom Survey involves a nationwide sample of the U.S. population regarding fandom for sports and other cultural entities. In the 2024 edition, political figures such as Donald Trump, Joe Biden, Kamala Harris, and RFK Jr were included. The survey captured responses from 2053 subjects split evenly across the four primary generations (Gen Z, Millennials, Gen X, and Baby Boomers), and the sample is representative in terms of racial background. The survey does not focus on likely or registered voters, so the results reflect overall societal sentiments rather than the electorate's opinions. The critical survey question asks subjects to rate how much of a fan they are of a celebrity on a 1 to 7 scale. In the following discussion, individuals who rated their fandom a 6 or 7 on the 7-point scale are categorized as Fans, while those who rate their fandom a 1 or 2 are classified as Anti-Fans. Table 1 shows the Fandom and Anti-Fandom rates for the entire sample. Donald Trump has a 27% fandom rate compared to Harris's 21%. The fandom rate is crucial because it identifies the candidate's core support. It also indicates something important about the candidate’s potential likability. In terms of anti-fandom, Harris has a slightly higher Anti-Fandom rate. Anti-Fandom is also critical as it shows the percentage of people who hate a candidate. The data suggests that Americans find Harris to be more dislikable than Trump. Notably, the anti-fandom rates are significantly higher than the fandom rates. The American public has significant disdain for politicians. The high anti-fandom rates are both the product of past negative advertising and the cause of future negative campaign strategies. Table 1: Candidate Fandom and Anti-Fandom Table 2 reports fandom rates based of the two gender segments. Trump has a 7%-point advantage with men and a surprising 4% advantage with women. This is a stunning result as Trump is generally regarded as having weakness with female voters. However, this weakness shows up in the anti-fandom rates. In the male segment, Trump has a 5%-point advantage in anti-fandom (fewer anti-fans), but a 3% disadvantage in the female segment. This reveals that Trump is polarizing to women, and almost half of women find Trump to be highly dislikable. This finding is why the Harris campaign is likely to use advertising that casts Trump as misogynistic or a threat to women to motivate turnout by female voters. Table 2: Candidate Fandom by Gender Table 3 shows the fandom rates for the two younger demographic segments: Gen Z and Millennials. This Table also shows Trump’s relative performance versus Biden (in parentheses in the last column). Trump enjoys higher fandom and lower anti-fandom than Harris in both the Gen Z and Millennial segments. In terms of fandom, Trump is plus 6% in Gen Z and plus 11% with Millennials. Critically, Harris outperforms Biden. The Gen Z anti-fandom gap between Trump and Biden favored Trump by 6% points. However, this gap shrinks to just 1% point when Harris is the comparison. The data suggests that Harris is stronger with Gen Z than Biden. Table 3: Candidate Fandom in Younger Generations Table 4 reports the fandom rates based on a racial segmentation scheme. Specifically, the sample is divided into White and Non-White categories. This is a crude segmentation, but it illustrates some essential points. Trump enjoys a significant 14% positive fandom advantage in the White demographic. He also enjoys a 10-point edge in (lower) anti-fandom. The pattern essentially reverses in the Non-White segment, as Harris has a 10-point advantage in fandom and a 17-point edge in anti-fandom. Trump’s anti-fandom in the Non-White segment is critical to the campaign. Nearly half of this segment has antipathy or hate for Trump. This high anti-fandom suggests an opportunity for the Harris campaign to emphasize racial angles in their attacks on Trump. Table 4: Candidate Fandom by Race In addition to fandom and anti-fandom rates across demographic categories, insights can be gleaned by looking at segmentation variables that reflect cultural values or personality. Table 5 shows fandom and anti-fandom rates for Trump and Harris for segments defined by fandom for Taylor Swift (Swifties) and Baseball. The Swifties skew towards Harris. The implication is that young women engaged in popular culture have more positive fandom for Harris and more negativity toward Trump. This is unsurprising given the content of the popular culture and Swift’s personal liberalism. The Swiftie segment shows a much stronger skew for Harris than all but the Non-White segment. Examining the data at a cultural level is vital as it indicates that it isn’t necessarily youth or gender where Harris has an advantage but a combination of youth, gender, and a specific type of cultural engagement. The table also includes fandom rates for baseball fans. In the Baseball Fan segment, Trump enjoys an 8% point fandom advantage and a 7% anti-fandom advantage (lower anti-fandom). Like the case of the Swifties, the fandom rates of Baseball Fans reveal something about Trump’s core support. Baseball is a very traditional game with an older fan base, and traditionalism is probably the core value of Trump fans. Trump’s negative advertising is likely to focus on the threats to traditional values (i.e., Harris is a San Francisco liberal). Table 5: Candidate Fandom and Cultural Segments Commentary and Prediction Fandom is a powerful metric for predicting political success, but like most data points, it doesn’t tell the whole story. Fandom is a measure of unwavering core support while anti-fandom measures the group that will never support and is likely to show up to vote against a candidate. Examining fandom rates across multiple segments reveals that Harris’ core support is concentrated in specific cultural and racial segments. The analysis also suggests that Trump's core support is broader than is usually acknowledged and that his main problem is significant anti-fandom with women and minorities. Harris’ problem is a lack of love, while Trump’s is too much hate. Notably, I am not paying too much attention to the current wave of excitement and enthusiasm surrounding Harris. The recent enthusiasm is likely more a manifestation of the Democratic base’s hopes and a relentless media onslaught than an actual increase in passion for Harris. Maybe there will be a permanent shift upward in Harris’s fandom, but I don’t see any logic for why this would occur. Harris isn’t suddenly more likable or aspirational than she was last month. The argument that the American people are becoming more acquainted with her is dubious, given that she has been the Vice President or a major presidential candidate for almost five years. What are the implications for the upcoming election? Voting is not only about fandom or hate, so we must consider some additional factors. For instance, many potential voters lack passion and knowledge and are more prone to vote based on identity rather than ideology. If a region or demographic segment consistently votes for a party 75% of the time, that’s voting more based on fixed identities than current societal conditions. The American electorate has many of these types of fixed-preference voter segments. Furthermore, as the American electorate becomes more diverse, identity-based voting seems to be making presidential contests more predictable. The baseline seems to be that the Democratic candidate will win the popular vote by a few percentage points, and the Electoral College will come down to a few states, such as Michigan, Pennsylvania, and Wisconsin. Examining past electoral maps shows far more shifting of states across elections. Now, all but a handful of states are regarded as non-competitive. The Figure below shows the presidential popular vote margins for the last 50 years. It shows a trend towards smaller margins for the winning candidate, which is at least partly due to growing ethnic diversity and more fixed (at least in the near and medium terms) identity-based voting. Over the last 13 cycles, the margin of victory has dropped by about 1% every four years. Demographic change has also locked in a high baseline level of support for Democratic candidates. The last time a Republican won the popular vote was in 2004, with George Bush as the incumbent. Figure 1: Presidential Vote Margin 1972 to 2020 In addition to shrinking election margins, demographic change promises to change future campaign tones. The increasing relevance of fandom and anti-fandom, combined with the growing diversity of the electorate, will make 2024 an extremely negative campaign. The 2024 election will be determined by identity-based demographic trends and negative (anti-fandom) marketing campaigns. Demographics are destiny, and America is changing rapidly in ways that make it increasingly difficult for the Republicans to win the popular vote. It doesn’t matter if the Democrat is Harris, Newsom, Clinton, or Whitmer while the Republican is Rubio, Haley, Cruz, or Burgum. The baseline is probably 52% to 48%, D to R. Candidate fandom and anti-fandom probably shift the vote 2 or 3 percent in either direction. The correlation of demographic traits with voting behaviors creates incentives for campaign strategies that focus on identity. Republicans are eager to shift some percentage of Black or Hispanic voters to their cause because it simultaneously reduces the Democrats' base and grows Republican totals. In contrast, Democrats need to motivate marginal voters in the female, Black, and Hispanic segments to turn out. Fear-based appeals are the most effective tool for both parties' goals. Negative messaging is also prevalent because of the general view of politicians. Politicians tend to inspire more antipathy (anti-fandom) than admiration (fandom). The fandom data shows this, as both candidates have far more anti-fans than fans (this holds with other politicians) . The modern election calculus is, therefore, focused on aggressive negative ads that inspire marginal voters to take the initiative to vote against a hated candidate. Passion drives behavior, and it's far easier to drive fear and hatred of a candidate than to inspire passion and admiration. Considering the fandom data and the current electorate, I have two predictions. First, we will witness an incredibly nasty race. Harris’s best bet is to demonize Trump to motivate the anti-Trump voters to turn out. The American culture of 2024 includes constant repetition that many Democratic voting constituencies are marginalized and threatened. These segments are best motivated by using messages that cast the Republicans as the danger or oppressor. Women will fear losing reproductive rights, and African Americans will be primed with threats to voting rights. Trump will also employ negative messaging, but Trump’s adoption of a negative campaign comes from a slightly different motivation. Trump’s core support consists of conservatives who are frustrated by a lack of cultural power and representation. This group is looking for someone who will fight for their values. This desire for a “fighting advocate” explains much of Trump’s appeal, as his supporters are enthusiastic about his “mean tweets and nicknames.” There will also be fear-based advertising as Harris will be positioned as wanting to defund police and open the border. Second, Trump wins in a close contest. Comparing Trump’s and Harris’ fandom and anti-fandom suggests the Harris campaign faces an uphill challenge. Despite the current blitz of enthusiasm for Harris as a replacement for a failing Joe Biden, her “brand” has not shown an ability to stimulate passion, and her dislike levels exceed Trump's. It seems unlikely that she will be able to inspire fans. While Trump has a significant fanbase and weaknesses in terms of strong anti-fandom levels in minority and cultural segments, he probably beat Clinton in 2016 because her anti-fandom was equivalent to his. In contrast, he lost to Biden because Biden had less anti-fandom (in 2020). Kamala Harris seems more like Clinton than Biden, so look for a similar outcome as in 2016. The bottom-line prediction: An exceptionally negative campaign, with Trump’s greater baseline fandom and Harris’s charisma deficit leading to a narrow Trump victory. As in 2016,Trump wins the Electoral College while losing the popular vote. Addendum: Future Fandom Lesson The structure of the American electorate and the propensity of people to vote based on identity rather than ideology mean that negative campaigns are the standard in the near future. The essential observation is that demographic trends create an electorate that is more a collection of identity segments than a homogeneous population that varies in ideology. An increasingly diverse electorate likely means increasingly negative presidential campaigns as negative or fear-based appeals are especially effective when elections focus on threats to identity groups. The tragedy of this situation is that the negative messages of campaigns amplify racial division and acrimony. When the next election occurs, the electorate is even more polarized, and negative or fear-based appeals are again the most effective. 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.