Featured faculty: Robert Li Xiang
Written by Ellis Ng

“Travel changes you. As you move through this life and this world, you change things slightly, you leave marks behind, however small. And in return, life—and travel—leaves marks on you,” said the late American documentarian, Anthony Bourdain. Travelling is supposed to be an exercise for the soul.

However, tourist misbehaviour has constantly dotted headlines. Last year, anti-tourism protests erupted in Spain’s Canary Islands over tourists’ bad behaviour and overtourism, and similar strikes have since spread to Barcelona, Málaga, Athens, and other European cities. In Japan, the same problem has driven the city of Fujiyoshida to cancel its annual cherry blossom festival.

Most misconducts, like being noisy, littering, queue-jumping, and disregarding local customs, might seem minor, but they add up for locals. Traditional countermeasures, such as signage or staff patrolling to issue reminders, often fall short. Visitors easily overlook signs, and confrontations can flare up between tourists and staff.

As tourism boards and site managers search for better ways to manage visitors, Robert Li Xiang, the Fung King Hey Memorial Professor of Tourism Management and Director of the School of Hotel and Tourism Management at the Chinese University of Hong Kong (CUHK) Business School, suggests that robots can be an effective tool for this.

Equipped with artificial intelligence (AI), Professor Li notes that robots can act as persuasion agents to encourage positive behaviour. Far from replacing human interaction, they provide a non-confrontational means to foster responsible conduct and enhance the experience for both tourists and locals.

“Intelligent robots can influence behaviour through a few simple but powerful mechanisms. When a robot approaches a visitor or speaks to them, it creates a sense that ‘someone is watching,’ which can make people more aware of their actions,” he says.

Smart robots to encourage smart behaviour

A study titled Robot guardians: Mitigating tourists’ deviant behavior with intelligent robots documents the findings of Professor Li, as well as Zhang Mengyang, Pang Shuo, and Liu Na at Southwest Jiaotong University, and Shi Si at the Southwestern University of Finance and Economics in Chengdu, that robots outperform signage and humans when it comes to persuading tourists to behave.

In a field experiment at a busy intersection in southwestern China, among 8,148 observed tourists over three consecutive weekends, 17 per cent jaywalked when human staff were on patrol and 25.1 per cent when only signage was placed. This number dropped to 12.5 per cent when a robot was present.

“Robots feel less personal than human staff, so people may be more open to listening without feeling judged or embarrassed.”

Professor Robert Li Xiang

In other scenario-based experiments and AI-generated simulations with participants in China and the US, the results also show that intelligent robots are more influential in affecting tourist behaviour. The reason is that robots created a keen sense of being watched without the psychological tension that human intervention often triggers.

Professor Li grounds the findings in impression management theory, which holds that people control their behaviour when they feel they are being seen. Unlike surveillance cameras, robots can provide on-site intervention and activate self-awareness, but not as personally intimidating as a human figure, reducing the defensiveness that can undermine compliance.

“Robots feel less personal than human staff, so people may be more open to listening without feeling judged or embarrassed. This fusion, being noticeable but not confrontational, helps nudge people towards better behaviour,” Professor Li says.

Different looks for different messages

How a robot looks and speaks also needs to match. When a human-looking robot delivers a stern warning, it can feel socially threatening, and people get defensive. But if that same robot uses a touch of humour, the interaction feels lighter, and people are more willing to conform.

The underlying reason comes down to social threat and embarrassment. A basic-looking robot, on the other hand, doesn’t trigger much social pressure on its own, so a direct message works best. Humour from something that clearly isn’t human can make the message feel unserious.

Therefore, if its primary function is to intervene in deviant behaviour, a less human-looking robot with a more serious tone would be effective. “A simpler-looking robot may be more effective with a direct message, but a human-like robot can get away with using humour. Getting this combination right makes a big difference in how people respond,” Professor Li says.

“The key is finding the right balance. Robots need to be noticeable enough to catch attention and signal that behaviour matters, but not so intimidating that people feel uncomfortable or defensive.”

The future of smart and sustainable tourism

Smart robots offer a consistent, safer way to address daily misconduct, and the study opens new possibilities for smart tourism as authorities grapple with growing challenges in visitor management.

“For policymakers, robots provide a softer approach to public management, encouraging better behaviour through gentle reminders rather than strict enforcement,” Professor Li adds. “For businesses, robots can ease the burden on frontline staff, who often have to deal with difficult or confrontational situations.”

This approach could work in other environments too, including transport hubs, hospitals, shopping malls, campuses, and residential communities. “We’re already seeing early examples, for instance, robots helping with traffic guidance or reminding people of public rules in some Chinese cities.”

Looking ahead, Professor Li sees the most promising approach is likely a combination of robots and humans. Robots can handle routine reminders in a consistent, non-confrontational way, while human staff can step in for more complex or sensitive situations.

Still, organisations will need to address practical challenges before deploying robots in public. “On the practical side, organisations need to think about costs, maintenance, and whether the technology is reliable enough for daily use,” he says. “It’s also important to consider how robots will work alongside human staff.”

Privacy is another concern, especially if robots collect or process data. “Organisations should be transparent about how the robots are used and avoid making public spaces feel overly watched. Most importantly, robots should be used to give gentle reminders, not to shame or punish people.”

The post Could intelligent robots be the cure for bad tourists? first appeared on China Business Knowledge.

Featured faculty: Li Jingyu
Written by Joanne Madrid

The pandemic was a poignant reminder of the importance of information technology, or IT. Almost overnight, businesses scrambled to go digital, with video calls replacing boardroom meetings and cloud platforms keeping teams connected.

The rush to adopt technology has not slowed since. According to McKinsey & Company’s 2025 report, 88 per cent of firms across 105 countries are now using artificial intelligence in at least one area of their business, a spike from 20 per cent in 2017.

For China, technology is the core of its economic powerhouse. Private companies contribute 70 per cent of the country’s technological innovation, and Chinese tech firms, whether in semiconductors, artificial intelligence, or robotics, have been rushing to go global.

Companies now have a wealth of options to choose tech tools, but does piling on more technology automatically make a company better prepared for the next crisis? Not necessarily, according to a study co-written by Li Jingyu, an Assistant Professor of the Department of Management at the Chinese University of Hong Kong (CUHK) Business School.

“Having too much variety of IT tools can actually make it more costly and difficult for companies to come up with new plans, decide on the best ones, and then put them into action,” says Professor Li. “This problem gets much, much worse during unexpected shocks, where companies have to make decisions and act quickly.”

The paper, titled Navigating the storm: Towards a theory of IT portfolio diversity, leadership power, and organisational resilience to major shocks, found that companies with a moderate range of digital tools were generally more resilient during crises than those with either very few or many digital tools.

The safe zone of digital tools

Along with Li Mengxiang of Hong Kong Baptist University, Hsieh Po-An at Georgia State University, Wang Xincheng at Tongji University, and Gu Bin at Boston University, Professor Li examined 2,926 listed Chinese firms, tracking their revenues before, during and after the pandemic. Firms that are better at absorbing a shock would see smaller drops in income, or even manage to grow.

At the heart of the study is the concept of IT portfolio diversity, which refers to the variety of digital tools a company can deploy. This includes everything from cloud computing and video-conferencing systems to mobile applications and enterprise management software.

The analyses find that companies with a moderate level of IT portfolio diversity have genuine advantages. They have sufficient technologies to allow them to shift operations online, coordinate staff remotely, and keep information flowing when normal routines are upended.

“Having too much variety of IT tools can actually make it more costly and difficult for companies to come up with new plans, decide on the best ones, and then put them into action.”

Professor Li Jingyu

Yet the benefits did not keep rising in a straight line. Firms that had accumulated a very wide array of technologies often struggled during the crisis. A sprawling and fragmented technology setup can be expensive to maintain and difficult to coordinate.

These problems become acute when speed and clarity are most needed, such as during a crisis. In normal times, firms felt less pressure to reorganise their systems. After the crisis, many had already adapted to new ways of working. “When IT portfolio diversity is too low or too high, it can lead to inferior performance related to organisational resilience,” Professor Li adds.

Think of it as a chef’s kitchen. A good range of knives, pans and appliances makes cooking faster and more versatile. But cram every kitchenware imaginable onto the worktop and the cook room becomes cluttered and confusing, especially when hundreds of unexpected guests arrive.

Giving technology leaders a seat at the table

Having the right tools is only half the equation, because the man behind the gun pulls the trigger. Who is in charge of those tools and how much authority they hold matters significantly.

Companies where senior technology executives sat on the board or held top-level positions were far better at turning a diverse set of digital tools into a real edge. These leaders could coordinate resources across departments, resolve conflicts between teams, and ensure that technology decisions supported the company’s broader strategy under intense pressure.

“Firms that intend to build digitally enabled organisational resilience to withstand unforeseeable shocks should pay special attention to enhancing the power of their IT leaders,” Professor Li says.

Without a high level of authority, even well-stocked technology tools can go to waste. If the head of technology lacks the standing to redirect resources or overrule competing departmental priorities during a crisis, the firm’s digital tools may sit underused or, worse, pull in different directions.

It is worth mentioning that what constitutes too much varies from company to company. Companies with very strong IT leaders might be able to manage a much wider array of digital tools effectively before getting overwhelmed.

Industry context changes the calculus

Not all industries experienced the crises in the same way. Transport and hospitality were devastated during the pandemic, but pharmaceuticals and express delivery boomed. These contrasting fortunes shaped how much the technology-leadership combination mattered.

In hard-hit sectors, the payoff from owning diverse digital tools with strong tech leaders was amplified. Affected firms benefit more from well-coordinated digital responses, but if their digital systems are disjoint, more severe consequences ensue. In this case, technology becomes a high-stakes game.

For businesses that thrive during crises, their digital portfolios and powerful tech leaders aren’t critical to survival since they already meet what the market needs.

In short, digital expansion alone does not make a company crisis-proof. Organisations need to think carefully about how many different technologies they can realistically manage, and ensure that the people responsible for those technologies have decision-making authority.

“Our findings underscore the need for firms to deliberately cultivate organisational resilience, enabling them to strategically align IT portfolio diversity and the authority of tech leaders in responding to different environments,” says Professor Li.

While the study covers only Chinese listed companies, she believes the core insight is likely to resonate well beyond borders. In a crisis, the winners are not necessarily the companies with the most technology, but those with the right amount and the leadership to make it count.

The post Why too much tech hurts resilience first appeared on China Business Knowledge.

Featured faculty: Philip Zhang Renyu and Lin Yunduan
Written by Putro Harnowo

Not everything needs to carry meaning, especially on social media. Take 67, a nonsensical expression Gen Alpha uses to confuse adults, for example. While digital platforms can forecast trends by analysing users’ behaviour, humans are inherently unpredictable and easily swayed by others. Algorithms may struggle to keep pace.

Digital anthropologist Brian Solis said, “Social media is about sociology and psychology, not technology.” This can explain many inconsequential trends exploding online. Within their social network, people randomly influence and are influenced by others, even when they don’t actually know each other.

“You may have heard of the six degrees of separation, where everyone in the world is connected through a chain of no more than six acquaintances. It means that everyone is actually more connected than they realise through social networks,” says Lin Yunduan, Assistant Professor of the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School.

Social networks lie at the intersection of many disciplines, from sociology and marketing to even politics. Understanding how ideas spread within communities or whether a new product thrives in the market amid unpredictable human behaviour becomes critical.

Given that people respond to one another in messy, often unpredictable ways, it can be hard to pin down why an idea catches on, or why a product takes off in one community but not another. To cut through that complexity, Professor Lin introduces the fixed-point approximation, a method that distils the back-and-forth of social influence into a clear picture of how these behaviours ultimately settle across the network.

“Imagine it as if a group of people want to schedule a gathering. It starts as an unspecified plan, as anyone may still change their minds. When someone confirms they can make it, their friends may become more likely to join, but when someone who confirmed later cancelled due to a sudden change, this can also ripple through the group,” she says.

“The fixed point refers to a certain level where, after these influences play out, each person’s likelihood of adopting an idea becomes steady and doesn’t change anymore.”

Predicting the trends with a mathematical formula

In a paper titled Nonprogressive diffusion on social networks: Approximation and applications, Professor Lin and Associate Professor Philip Zhang Renyu from the same department collaborate with Zhang Heng of Arizona State University and Max Shen of the University of Hong Kong to develop a deterministic approach to decode interactions within the unpredictable social network.

The fixed-point approximation starts from a few interpretable ingredients, including network structure to know who is connected to whom, intrinsic value or how much each person likes or dislikes the new idea before influences from others, noise distribution or the unpredictable whims that sway a person’s mind, and network effect intensity or how sensitive a person is to being influenced by their connections.

“Basically, we try to find a middle ground to estimate how people will behave under the influence of a network structure.”

Professor Lin Yunduan

This framework offers a way to capture social influence at scale without tracking every possible chain reaction in the network. Instead, it estimates each person’s likelihood of adoption under peer influence. For example, in a small neighbourhood, A has a 90 per cent chance of buying and B has a 30 per cent chance.

The approach is most reliable for people embedded in large, well-connected communities, since no single contact can easily dominate the outcome, and the influence of many peers creates a more stable signal. By contrast, for individuals with very few connections, the prediction can be harder, since one friend’s decision can meaningfully tilt the result, and random factors play a larger role.

To address those outliers, the paper proposes a small add-on step. After producing the main estimate, it focuses on low-connection individuals and generates many plausible scenarios for what their close contacts might do, then averages the results to refine that person’s adoption likelihood.  Professor Lin provides the formula of the framework in a GitHub repository here.

“Basically, we try to find a middle ground to estimate how people will behave under the influence of a network structure,” she says. “The approach does not require simulating every possible ripple through the network, yet it still captures the influence patterns accurately, turning messy, shifting interactions into a clear picture of each person’s likelihood of adopting a new trend.”

The researchers have examined their framework using five actual Facebook networks available in an open-access digital archive. The results show that the framework can accurately measure the likelihood of a new idea adoption, with an average error of less than 3.5 per cent. The graph below illustrates the framework’s efficiency in a small network compared with real-world results.

The researchers also compare it with other models that examine interactions within a network and find that their framework is 70 to 230 times faster than the basic simulations and 23 to 30 times faster than the advanced simulations.

Wider adoption in businesses and communities

A strong suit of fixed-point approximation is its ability to quickly pinpoint the key actors to maximise the adoption of a trend or idea, while accounting for unpredictable factors within a social network. This framework can be used in any practical setting where one’s behaviour impacts others.

“For instance, in a product launch, someone will purchase the new product, and these first purchasers may influence others to follow,” Professor Lin says. “Our framework can help to identify which first purchasers have a high downstream impact more quickly. These purchasers don’t necessarily have large numbers of followers, but are those positioned to spread adoption efficiently through their networks.”

While the framework can operate offline, digital platforms have advantages due to their infrastructure, connectivity and ability to utilise data in real time. Therefore, the framework would enable platforms to respond more quickly to market changes and stay ahead of competitors, while also adjusting their strategies over time to sustain momentum.

Another strong point of fixed-point approximation is its ability to help firms set pricing strategies by accounting for network influence. For retailers, this means the framework can help measure how many customers are likely to purchase a new product at different prices and set realistic sales goals.

Beyond profits, government or community leaders trying to spread an important message or encourage a new behaviour can use this framework to identify key community members whose participation will most effectively encourage others. The framework can also help understand how to seed these messages within the community to achieve widespread adoption.

The post How to forecast trends amid uncertainty first appeared on China Business Knowledge.

Featured faculty: Tony Ke
Written by Sally Ho

Amid the dominance of streaming platforms, digital piracy, or the unauthorised and illegal downloading or streaming of movies, music, and other copyrighted content, has been a persistent headache for the entire creative industry. A data company, MUSO, reported that visits to digital piracy websites have surged from 130 billion in 2020 to 216 billion in 2024.

Piracy websites offer free illegal content to watch and download, while monetising the visitor traffic through sponsored ads to generate revenue. Most jurisdictions treat such commercial piracy as a criminal offence and punishable by fines, imprisonment, or both. However, shutting down piracy websites has been an uphill battle for law enforcement.

Authorities have been blocking many piracy websites to protect copyrighted content, but piracy firms frequently change their web domain since they can host their servers anywhere to evade detection. Therefore, regulators are now trying to curb piracy from the demand side by introducing penalties aimed at users.

“To understand anti-piracy policy, you have to model a strategic ‘cat-and-mouse’ game, where penalties change piracy firms’ technological advancements and consumer behaviour.”

Professor Tony Ke

A notable example is the US Prioritising Resources and Organisation for Intellectual Property (PRO-IP) Act, which imposes US$1,000 to US$200,000 civil penalties, and France’s Regulatory Authority for Audiovisual and Digital Communication (ARCOM) Law, with a €1,500 or around US$1,750 fine for downloading, copying and streaming illegal content.

“These demand-side regulations are unique to digital content, as digital consumption can be traced by regulators more easily than physical transactions, making it feasible for law enforcement to identify users who download or stream pirated content,” says Tony Ke, Professor of Marketing at the Chinese University of Hong Kong (CUHK) Business School.

However, piracy firms constantly assist their users in hiding their digital footprint through encryption, automated random IP addresses, virtual private network providers, and many more. Most users are aware of this support, as the piracy firms make anti-tracking methods apparent on their websites, providing a sense of security from law enforcement.

This dynamic can explain why, despite high penalties, users continue to flock to piracy websites in large numbers, as measured by Google Trends below. An important question then emerges: Do penalties for digital piracy consumption actually work?

In his new study, Regulating digital piracy consumption, Professor Ke, in collaboration with his PhD student Chen Jieteng and Gao Yuetao of Xiamen University, suggests that penalties may, in fact, increase piracy rather than curb it. In some cases, heavier penalties can even encourage more piracy.

A cat-and-mouse game in anti-piracy policy

“To understand anti-piracy policy, you have to model a strategic ‘cat-and-mouse’ game, where penalties change piracy firms’ technological advancements and consumer behaviour,” Professor Ke says. “In this model, consumers understand the penalties, but pirate platforms also respond by investing in anti-tracking tools that make enforcement less effective.”

Specifically, the researchers design a model consisting of copyright holders that offer high-quality content and set a price, piracy firms that host a free and low-quality pirated version, the regulator that sets a penalty on consumers who get caught accessing pirated content, and consumers whose preferences depend on product quality, price, and the expected penalty.

“Demand for piracy often arises when copyrighted content is unavailable elsewhere,” Professor Ke adds. “Consumers with medium incomes are prone to piracy and willing to risk penalties due to budget constraints, while still seeking access to diverse content. The piracy firm’s anti-tracking technologies significantly influence their behaviour.”

Through various analyses, the study suggests that regulators should carefully balance the level of penalties with the cost and availability of anti-tracking technology. “When investing in anti-tracking technology is relatively cheap and easy for piracy firms, the regulator should avoid harsh penalties since doing so can trigger even stronger anti-tracking investment,” says Professor Ke.

The model shows that when the anti-tracking technologies are affordable, piracy initially declines as penalties increase. However, sufficiently high penalties can induce piracy firms to invest in anti-tracking technologies that help users evade detection, ultimately leading to higher levels of piracy consumption. In this context, regulators should target a moderate penalty that is just good enough to deter piracy, and tolerating a small amount of piracy can actually lead to better overall outcomes.

“However, in a scenario where investing in anti-tracking technologies is costly for piracy firms, higher penalties can be effective and may even deter demand and supply altogether,” says Professor Ke. In this case, the risk of being caught is higher and steep penalties can reduce piracy significantly.

Implications for content platforms and regulators

For content platforms and the creative industry, counterproductive regulation can be discouraging, as they might face uncertain returns on investment that affect their decisions in producing new content. Therefore, policymakers need to design not just the level of penalties, but also the strategic responses of piracy firms carefully.

“A more effective approach is to balance demand and supply-side actions,” Professor Ke adds. “On the demand side, piracy can be reduced by making legitimate options more attractive, affordable, convenient, and widely accessible, rather than relying on penalising users. On the supply side, enforcement should focus on deterring piracy firms and the infrastructure that enables large-scale piracy.”

Technology plays a pivotal role in enabling piracy firms and consumers alike. In a digital world where anti-tracking tools are increasingly sophisticated, effective regulation may require moderation, creativity, and a deep understanding of the ecosystem, rather than pushing for heavy fines.

“Additionally, digital tracking is constrained by data privacy regulations, and tech companies offer opt-out choices for such tracking features, so policymakers also need to take into account these limitations when designing effective enforcement,” Professor Ke adds.

He also notes that some platforms may have realised the complexity of the cat-and-mouse game in digital piracy and now offer “freemium” structures that combine free access with advertising. This new strategy opens an avenue for further research to understand how these models affect consumers’ willingness to pirate.

The post How to keep digital pirates at bay? first appeared on China Business Knowledge.

Featured faculty: Ko Chiu-yu
Written by Putro Harnowo

The fuss and feathers around bitcoin and cryptocurrency sometimes obscure the basic technology behind them. Indeed, blockchain, as the fundamental technology, has the potential to revolutionise industries beyond finance.

Blockchain is a distributed, encrypted digital ledger or record that everyone can see and agree on through computers. Its unique feature has opened a new mechanism called a smart contract, a self-executing agreement implemented as code on a blockchain that automatically performs actions without a middleman. Once deployed, this contract has a unique and immutable address that prevents unauthorised changes.

Leveraging this technology, a new study by Ko Chiu-yu, Associate Professor at the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School, examines how smart contracts can be utilised to solve disputes in the supply chain.

“Supply chains involve multi-tiered arrangements with numerous bilateral contracts. When disruption arises, figuring out who should bear the loss can be complicated,” says Professor Ko. “Smart contracts can automatically manage, track, and settle these losses fairly, especially when an action of a party initiates sequences of unanticipated damages that affect others.”

For instance, when a supplier fails to ship a component on schedule to an electronic assembler, the assembler would face compensation demands from the distributors for delayed delivery. A question then emerges: When actions of a party affect another party’s agreements with a third party, how should the liability be shared between the initiator and other parties for the damage?

In a study titled Sharing sequentially triggered losses: Automated conflict resolution through smart contracts, Professor Ko and his collaborators propose “the fixed-fraction rules” to fairly share responsibilities among parties in a supply chain. Each liability is split between the party that initiated the problem and the other parties that caused further damages later in the sequence.

Professor Ko compares it to a choose-your-own-adventure game with a dial. One end shows 0, which means the first party is responsible for all the costs, and the other end shows 1, which means everyone only pays for their own mistakes. The easy middle ground is to split the costs fairly between the initiator and the next party affected, using simple fairness principles like “let’s all chip in equally so nobody gets the short end” to keep the peace.

“Smart contracts can automatically manage, track, and settle losses fairly, especially when an action of a party initiates sequences of unanticipated damages that affect others.”

Professor Ko Chiu-yu

How can blockchain help?

Along with Jens Gudmundsson and Jens Leth Hougaard of the University of Copenhagen, Professor Ko takes a step-by-step approach in creating the fixed-fraction rules. They began by defining core allocation principles to balance fairness and incentives, making liabilities shared among each party based on a fixed fraction of the total loss.

A party is only aware of the agreements it participates in, so each party is only responsible for the loss associated with its own purview. Therefore, the initiator shall cover the rest of the loss since they could have done something to avoid the damage. For the loss incurred by several connected parties, the liabilities are shared equally among the initiator and the other parties. With these rules, the initiator is incentivised to avoid starting the chain of loss while also acknowledged for their limited control over further damage.

“The fixed-fraction rules operate on a similar principle to a common term in the supply chain called fixed share rate contracts, where the costs, risks, or liabilities arising from issues like delays, defects, or product recalls are shared among the involved parties based on predetermined fixed fractions,” says Professor Ko. “These terms have been shown to incentivise improved product quality.”

In ensuring fairness, the researchers further set out four principles. First, if losses occur in two different cases, the system can simply add up each party’s responsibility from both cases to get the total loss. Second, if the system combines two separate losses into one, the way of sharing the liabilities should stay fair and consistent. Third, if the number of parties involved changes, the responsibility shares also adjust accordingly. Lastly, parties not involved in causing any loss shouldn’t be responsible for anything.

To illustrate, the researchers extend the model to a scenario represented by a loss tree below, where any party can initiate the chain of loss. When B fails to meet its agreement with E, a total loss of US$19 occurs, which is calculated from a direct link with E and indirect links with F and G. According to the fixed-fraction rules using a benchmark middle-ground split, B pays US$14 to cover the full loss with E plus half of the losses with F and G (each taking an equal half as the balanced default for shared accountability). Accordingly, E cover the remaining US$5.

This approach ensures the initiator bears primary responsibility without overburdening downstream parties, maintaining incentives for prevention across the chain. Meanwhile, A, C, and D aren’t affected.

The fixed-fraction rules can be implemented in smart contracts by storing the agreements in a loss tree. Involved parties shall make deposits to cover potential losses, and with a set of functions, the blockchain can automatically compute and distribute liabilities in case of damage. If everything goes well, the deposits will be returned to conclude the deal.

The future of smart contracts

Supply chain is not the only one with an interwoven network. Given its ability to address the chain of loss, Professor Ko believes that fixed-fraction rules can be applied in other industries, such as automating cost-sharing in loan defaults, handling group claims after disasters in insurance, sharing penalties for construction delays in real estate, and many more.

However, there is a limit on how the rules can work, since their success depends on reliable data sources and integration with their supporting ecosystem. In many countries, the legal framework for smart contracts is also still evolving, and there is no uniformity in regulation about blockchain worldwide.

“Complex and high-value disputes will likely be settled through courts, as it takes time and effort to verify evidence and examine the terms stated in the contracts,” says Professor Ko. “Therefore, automatic conflict resolution works best for clear-cut, data-driven disputes with less room to argue, and facts can be verified automatically.”

With that being said, smart contracts will work best to settle smaller disputes, such as in delivery delays verified by sensors or tracking systems, e-commerce issues confirmed by delivery logs, and licensing or intellectual property breaches tracked through secure digital records.

In the era of AI, Professor Ko anticipates technologies to enhance smart contracts to be more adaptive by using predictive analytics to detect patterns and prevent disputes. Natural language processing would also be able to interpret ambiguous terms, and automated verification may validate data and trigger more accurate settlements.

“By combining AI-driven analysis with smart contracts for complex cases, and monitoring regulatory compliance in real time, technologies can improve efficiency, especially in sectors such as public services, e-commerce, and insurance,” he adds.

The post Can blockchain solve supply chain disputes? first appeared on China Business Knowledge.

Featured faculty: Choi Sungwoo, Kim Keongtae, Francisco Cisternas, Philip Zhang, Michael Zhang
Written by Pan Jingyi

Technology has been playing a pivotal role in shaping the business landscape in 2025. The world’s first law to regulate artificial intelligence (AI) by the EU is expected to be fully in force this year, while AI companies like Google, DeepSeek, and OpenAI have rolled out their latest models in rapid succession. Down under, Australia has also made history as the first country to ban social media for kids.

Meanwhile, US and Chinese companies have ramped up AI integration in their e-commerce to make “apps for everything,” and Nvidia’s CEO says quantum computing, which can solve problems too complex for classical computers, is approaching a critical turning point from early research to practical, scalable application. In hardware side, robotic companies around the world are vying for dominance.

Building on this surge, we bring together insights from the Chinese University of Hong Kong (CUHK) Business School faculty on how technology will redefine the future of business in China and beyond. In the second part, we will also share perspectives on other hot topics relevant to economics and consumer behaviour.

1. Future service robots: Humanlike interactions vs. humanlike bodies

Robots are no longer merely helpful assistants in factories. They have also become tireless servers at restaurants and dazzling performers on stage. A Morgan Stanley report estimates that the number of humanoid robots, or robots that mimic the human body, will likely reach nearly 1 billion by 2050, with China expected to have the highest number by then.

However, for human-centric service industries, such as hospitality and tourism, Choi Sungwoo, Assistant Professor of the School of Hotel and Tourism Management, offers another perspective: “I don’t necessarily think humanoid robots represent the primary direction for the future of service robotics.”

His recent research examined how assistive robots can empower employees with disabilities, but also highlights the importance of personal interaction. Robots can help with daily tasks, but customers still crave genuine human interactions and emotional connection, something that robots can’t truly replicate. Therefore, hiring humans in the hospitality industry remains crucial, even with the rise of robotic technology.

“Although a large body of research has demonstrated the benefits of humanoid robots, the goal of most companies is not to make robots physically resemble humans. Rather, it is to enable machines to interact with customers in more natural and humanlike ways, through tone, language, and behaviour.”

Therefore, Professor Choi expects AI-powered chatbots to lead the way in hospitality and tourism by increasingly interacting with customers, moving beyond simple tasks to take on more engaging roles. “By handling routine call centre-type tasks like answering frequently asked questions, handling bookings and check-ins, and scheduling appointments, chatbots can help free human staff to focus on more value-added and personalised services to create memorable experiences.”

2. Blockchain-verified AI agents bolster stablecoin safety

Blockchain is a decentralised digital ledger that records transactions across many computers, making it secure and transparent. As AI spreads across industries, its combination with blockchain could reshape finance by making systems more autonomous and interoperable, according to Kim Keongtae, Professor of the Department of Decisions, Operations and Technology.

His previous study shed light on the rising cryptocurrency and its influences on other technologies, underscoring the impact and functionality of blockchain on a wide range of applications. As AI takes on human tasks like trading and customer service, its ability to operate across platforms securely becomes critical, but without a universally accepted and verifiable digital identity, the AI programme cannot easily interact with other platforms.

“Blockchain provides the missing infrastructure, a neutral and verifiable identity layer for AI agents,” Professor Kim says. “The synergy extends to fraud detection and trust assurance. As AI models detect anomalies and suspicious behaviour, blockchain provides a tamper-proof source of truth to verify and cross-reference identities, transactions, and behavioural patterns.”

This secure, interoperable foundation also matters for a type of cryptocurrency called stablecoins, which are pegged to a stable asset like a fiat currency or commodities. As Hong Kong implemented a new regulatory framework for stablecoin issuers in August 2025, Professor Kim notes that its smooth launch is crucial for accelerating broader blockchain adoption and establishing the city as a regional leader in digital finance.

A cautious start by limiting issuance to a few trusted and well-funded companies can help establish standards for governance. “Over time, a broader range of HK$‑ or Chinese yuan‑pegged stablecoins could unlock local use cases and reduce reliance on US$‑backed stablecoins,” he adds. “In the near to medium term, investment and trading purposes are likely to remain the dominant use of stablecoins.”

3. More personalised e-commerce experience and smarter algorithms

E-commerce platforms nowadays deliver not just personalised product suggestions, but entire experiences tailored to consumers’ interests, making shopping feel personal, fast, and seamlessly woven into everyday life. Looking ahead, the momentum will only build.

Francisco Cisternas, Senior Lecturer of the Department of Marketing, anticipates that smarter models fuelled by richer data will allow more accurate predictions and better-timed offers. His recent study proposed a new budget-conscious model that can make the online retail recommendations more accurate. “Most routine tasks, such as recommending products, setting prices and designing creatives, are now already handled by algorithms,” he adds.

While AI is moving from a helpful assistant to the main decision-maker in e-commerce, Dr Cisternas points out that this doesn’t mean humans are out of the loop. AI often outperforms humans on repetitive and data-rich tasks, but it can falter when preferences are diverse or the data is scarce. “AI will be the central engine for many day-to-day decisions, while human and AI hybrids are the optimal mode,” he says.

In China, e-commerce giants have built a thorough ecosystem that integrates shopping, payments, logistics and social media under one roof. In the future, the country’s retail sector will continue to push the boundaries of seamless multi-channel integration, Dr Cisternas notes.

However, e-commerce must pivot from the old “right product, right moment” mantra to “right relationship, right lifetime” as shoppers look for more than just a quick purchase. “Personalisation that focuses on building long-term relationships with customers will outperform aggressive one-time price promotions,” Dr Cisternas adds.

4. Low-effort entertainment content dominates on social media

For most of us, social media isn’t just for connecting with friends, but also to see the world. Yet, it also often harbours a darker side that harms mental health and well-being. The Australian ban on social media has highlighted how “predatory algorithms” encourage youth to spend excessive time on screens.

This ban sheds light on the crucial role of humans as social media continues to evolve. “In the age of AI-driven tools flooding social media, humans will not compete with technology, but rather to distinguish themselves through superior judgment by knowing which content truly matters and defining the values and priorities that guide meaningful discourse,” says Philip Zhang, Associate Professor of the Department of Decisions, Operations and Technology.

Professor Zhang’s recent study shows that although AI can generate content and enhance social media consumption by filling missing metadata, it still falls short of matching the boundless creativity of humans. Human role would be even more crucial in the future, as Professor Zhang anticipates that social media will increasingly prioritise effortless consumption.

“If I were to imagine boldly, social media might instead evolve into a brain-computer interface one day,” he says. A brain-computer interface creates a direct communication channel between the brain and an external device, allowing users to control machines with their thoughts.

To complement the preference for low mental effort, simpler and more entertaining content would flourish greatly. This will make it harder for serious material to compete for attention—but not impossible.

He cites a podcast as an example and highlights the needs of seeking uninterrupted and insightful experiences. “While different platforms converge on similar features, the key is to identify niche audiences with specific and underserved needs.”

5. AI won’t fundamentally transform most industries yet

As elaborated above, AI has been used across industries. Our other recent articles have also explored how AI has and will continue to change our lives, from doing our jobs, data analysis, to supply chain management, with the vast majority of AI adoption remaining in early stages, rather than enterprise-wide scaling that reshapes core operations.

While there is lingering concern over the so-called “AI-winter”, where funding, interest, and excitement in AI dwindle, Michael Zhang, Wei Lun Professor of Business AI of the Department of Decisions, Operations and Technology, remains optimistic about its near-term impact. “Over the next few years, AI will undoubtedly boost productivity, especially in language and data-related tasks, but it is unlikely to fundamentally transform most industries, as current large language models still lack robust logical reasoning capabilities,” he says.

“Sectors closely tied to text and language processing, such as content creation, translation, legal documentation, and customer service, will experience the most transformative impact from AI in China,” Professor Zhang adds.

The post China Business Knowledge’s 5 tech waves to watch in 2026 first appeared on China Business Knowledge.

Featured faculty: Zhu Kaijie
Written by Joanne Madrid

While innovation, craftsmanship and creativity have been praised as the force of modern industry, an intangible enemy is quietly lurking in the shadows. Counterfeits have aggressively spread across almost all industries, from luxury products, cosmetics, and drugs to electronics and even food and beverages, persistently traversing beyond borders.

The Organisation for Economic Co-operation and Development calculated that the value of counterfeit goods in 2021 was around US$467 billion, or 2.3 per cent of total global imports. The fake products increasingly mirror the look, feel and packaging of genuine brands, making them far more difficult for consumers to identify.

Companies have invested heavily in technologies such as microchips, machine-learning image checks, laser-etched micro-patterns, and many more to protect their brands. Governments have also ramped up their regulations and enforcement to protect consumers. Oddly, despite these efforts, fighting counterfeits has grown increasingly difficult.

“Advanced technologies empower companies, but also arm counterfeiters with the tools to create highly convincing fakes to mislead consumers,” says Zhu Kaijie, Professor in the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School. “Illicit manufacturers exploit technology through reverse-engineering techniques to mimic security features and undermine brand integrity.”

This battle of wits raises burning questions: How can brands optimise their anti-counterfeiting technologies, and how should authorities adjust their strategies? Professor Zhu’s latest study, Combating counterfeit products: Anti-counterfeiting technology and law enforcement, answers the above questions and explains why anti-counterfeiting defences often fail to stop the flood of fakes.

Understanding the rules of the game

In collaboration with Yao Shiqing of Monash University and Yang Ruina of Xi’an Jiaotong University, Professor Zhu developed a game-theoretic model that mirrors real-world dynamics among brands, counterfeiters, regulators, and customers. Game theory has been widely used in economics, business, and policymaking to analyse strategic choices, making it highly practical to address counterfeit issues.

In this model, counterfeiters always look for opportunities to make profits, real brands try to outsmart the counterfeiters, customers cannot tell real from fake, and authorities deploy measures to crack down on counterfeit products. The researchers then developed scenarios based on the existing literature on anti-counterfeit measures.

“Advanced technologies empower companies, but also arm counterfeiters with the tools to create highly convincing fakes to mislead consumers.”

Professor Zhu Kaijie

Brands usually fight counterfeits by leveraging technology, which counterfeiters can often replicate later, especially in places with active black markets where criminals sell not only fake goods but also counterfeit security labels. Authorities use law enforcement, but sometimes lack the resources and consistency to monitor the growing scale of fake markets.

Brands with no anti-counterfeiting technology will see their products easily imitated. When brands modestly increase anti-counterfeiting technology, counterfeiters will put more effort into getting around it and may even increase production to cover extra costs, as long as the profits outweigh the risks. In this case, brands can only win by making a significant technological leap that counterfeiters cannot catch up with.

Authorities can employ corrective and preventive approaches. Corrective enforcement is applied after counterfeit products have been sold, involving penalties and compensation to brand owners. Preventive enforcement involves factory inspections, warehouse checks, and pre-sale interventions to stop fake products before reaching the market. The researchers illustrate the model’s underlying assumptions and sequence below.

Why do anti-counterfeiting measures weaken over time?

Increasing penalties, such as legal actions and financial sanctions, can have two effects. First, higher penalties increase the risk associated with producing and selling fake products, making counterfeiting less attractive. Second, increased penalties signal a highly regulated market and motivate customers to purchase authentic products.

However, higher demand from customers will attract counterfeiters, who try harder to enter the market, increasing the likelihood of fakes despite high penalties. Although steep penalties theoretically can deter counterfeiters, in practice, law enforcement often lacks the resources needed to enforce them effectively. The brand eventually cannot rely solely on penalties and invests more in technology to tackle fake products.

In some markets, more substantial penalties may even diminish a company’s anti-counterfeiting efforts. Upon receiving financial compensation from the prosecuted counterfeiters, brands tend to rely on law enforcement to recover losses and cut back on anti-counterfeit measures, paradoxically weakening their counterfeit protection.

Lessons for consumers, companies, and investors

As there is no one-size-fits-all solution, Professor Zhu suggests that companies align with authorities closely. Such collaborations are essential, particularly because combatting counterfeiting is inherently complex and requires tailored strategies.

“The value of collaboration heavily depends on the coupling between the company’s anti-counterfeiting technology and law enforcement type,” he says. “As the companies and the government share the common goal of combating counterfeits, one might expect their actions substitute for each other. However, we find that the two function as complements, meaning that strengthening one measure can stimulate the other.”

For instance, Professor Zhu explains, companies with mid-range products like household appliances, toys, and consumer goods would benefit from reactive collaboration, where the authorities focus on corrective actions. This approach is more efficient and cost-effective, given that anti-counterfeiting technologies are less feasible for these products.

Firms offering high-end products, such as smartphones and computers, would gain more benefits from preventive enforcement, including authentication technologies, supply chain tracing, early detection systems, and close collaboration with regulators to block fakes before entering the market, rather than reacting after the fakes are sold. This approach will boost confidence in the market and enhance customer trust.

Brands should also keep investing in anti-counterfeiting technologies to help customers distinguish genuine products. This investment needs careful evaluation and regular updates, as these technologies often become accessible to counterfeiters within months.

The advancement of counterfeiting technology has led to the adoption of blockchain verification systems to ensure product authenticity. The Aura Blockchain Consortium, for instance, issues digital certificates for luxury goods, making it harder for counterfeiters to tamper with ownership records or forge product histories.

“The recent advancement in applying artificial intelligence or AI to intellectual property rights protection further strengthens the potential of preventive enforcement,” says Professor Zhu. “AI-based intellectual property analytics can uncover relationships, trends and patterns of intellectual property infringement, enhancing early detection and targeted intervention.”

The post As counterfeits persist, can brands win the game? first appeared on China Business Knowledge.

Featured faculty: Zhang Yinglei
Written by Ellis Ng

Earnings reports are the scoreboard of a company’s financial health. However, behind those soaring revenue numbers, the truth can sometimes be buried. Some firms inflate their revenues to dazzle investors. It’s a deceptive game that brought giants like the payment company Wirecard and the property developer Evergrande to the ground.

Revenue misstatement can be difficult to spot. Firms often have complex operations and various ways of recording revenue, which can obscure the true financial picture. Traditional audit procedures may not always detect subtle manipulations, particularly when management crafts the presentation of revenues to fit with strategic narratives.

This challenge has led auditors to seek independent and external sources to help spot potential revenue misstatements. A new study suggests that Google can provide answers, given the search engine’s unique feature of collecting user queries.

“Customers nowadays seek product information, such as quality reviews, outlets, and pricing, before making a purchase. As the largest search engine globally, Google serves as a valuable resource to aggregate demand information,” says Zhang Yinglei, Associate Professor at the School of Accountancy at the Chinese University of Hong Kong (CUHK) Business School.

In a study titled Using Google searches of firm products to detect revenue management, Professor Zhang and her collaborators introduce the manipulation up (MUP) model by harnessing big data. The model leverages the search volume index provided by Google Trends that quantifies the relative frequency of searches for a particular term and compares it with the company’s reported sales figures.

“If reported sales growth significantly rises while Google search volume for the firm’s products significantly declines, this discrepancy should raise a red flag for auditors, analysts, and fraud investigators,” she says.

With this model, auditors and fraud investigators can verify whether the reported revenue aligns with actual consumer interests. It also presents a low-cost and timely tool for auditors that leverages publicly accessible data to independently validate reported revenues and identify fraud.

Turning a search engine into a fraud finder

In developing the model, Professor Zhang, along with Chiu Peng Chia of CUHK Shenzhen, Teoh Siew Hong of the University of California, Los Angeles, and Huang Xuan of California State University, first gathered quarterly firm-level sales data and other financial variables from S&P Compustat, which hosts a comprehensive market and corporate financial database.

They also collect Google Trends data to obtain the search volume index for each firm’s products from 2004 to 2020. The researchers then picked each firm’s biggest advertised brand, collected monthly search data for those products, and then compared changes in search interest to the companies’ reported sales to see if significant differences could signal possible revenue manipulation.

“If reported sales growth significantly rises while Google search volume for the firm’s products significantly declines, this discrepancy should raise a red flag for auditors, analysts, and fraud investigators.”

Professor Zhang Yinglei

The analyses confirm that changes in search volume index are positively correlated with actual changes in sales, validating the use of the MUP model as an external measurement correlating with firm revenue. What makes the tool particularly valuable is that Google Trends data can’t be manipulated by company management, making it an impartial source for genuine consumer interest.

“Google search data offers an independent way to verify company claims, rather than relying solely on information that companies can control,” says Professor Zhang.

The missing piece of the puzzle

To gauge the MUP model’s reliability, the researchers further compare its incremental predictability through rigorous testing against four established fraud detection methods in financial audit, such as the F_Score that spots financial anomalies, Stubben’s discretionary revenues model that tracks unusual revenue patterns, analyst sales forecasts, and media and analyst coverage.

The study shows that the MUP model adds unique insights on top of these traditional tools. It also matches with other common warnings of questionable revenue reporting, such as unusual increases in unpaid customer bills (accounts receivable) and suspiciously low funds to cover losses from unpaid bills (bad debt provisions).

Nevertheless, the MUP model is designed as a prototype diagnostic tool that integrates external big data with traditional fraud risk indicators, but it is not intended to be used independently or as a substitute for other fraud detection methods. Thus, this tool is best used as part of multiple approaches rather than relying on it exclusively.

“The MUP model enhances cross-checking methods by adding a source that is hard for companies to manipulate and helping auditors spot problems during quarterly reviews and in industries where customer search behaviour reflects demand strongly,” Professor Zhang adds.

Simply put, this model is most effective for cross-checking revenue reports in the retail and business-to-customer industries, where customers are more likely to search for product information before purchase. By combining data from search engines with traditional financial analysis, auditors can build a more complete picture of a company’s true performance.

The future of fraud detection

Auditors aren’t the only ones to benefit from the MUP model. Investors can also use it to evaluate company risks before making investment decisions, while regulators and policymakers can incorporate it into their fraud prevention strategies.

By analysing Google search data not just for a single product but also for companies within the same industry, analysts and auditors can gauge the relationship between the company’s revenue changes and its competitors. This could help make more accurate and improve the ability to spot fraud.

Comparing competitors’ Google Trends data will also enable analysts to distinguish between company-specific issues and industry-wide trends, helping determine whether declining consumer interest is unique to one company or reflects broader market changes.

What about markets where Google is less commonly used? Professor Zhang believes that the approach works with other search engines. “For example, fraud investigators can utilise the Baidu search index in Chinese Mainland and the Naver search index in South Korea to assess genuine consumer interest in a firm’s products.”

The study further advocates for regulators to adopt a more proactive stance in combating fraud by collecting transaction data from independent external sources and making this information publicly available. Such collaborative efforts would make fraud detection methods more accessible and affordable for auditors and stakeholders.

Easing the identification of potential financial misstatements would diminish the incentives for revenue manipulation, thereby discouraging such unethical behaviour. Ultimately, transparency stands as a powerful deterrent, perhaps the most effective safeguard, against fraudulent behaviours.

The post How to use Google searches to spot corporate fraud first appeared on China Business Knowledge.

Featured faculty: Michael Zhang
Written by Putro Harnowo

Hungry while travelling, but couldn’t decide which restaurant to go to? No worries. Just grab your phone and check the ratings for nearby restaurants. These user-generated reviews appear to be more trustworthy than traditional advertising due to their open submissions, making them handy not only for tourists, but also for locals craving something special.

No wonder platforms like Google Reviews and Yelp are cherished. Local apps like Japan’s Tabelog, South Korea’s Naver and Kakao, Chinese Mainland’s Meituan, and Hong Kong’s OpenRice also thrive on their community-based and more curated ratings. However, these reviews should be taken with a grain of salt. Ratings often vary across different platforms, and a high rating doesn’t always guarantee quality.

“Online ratings can be biased, leading to misleading information for readers,” says Michael Zhang, the Wei Lun Professor of Business AI at the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School.

In his latest study, Why is the grass always greener on the other side? Tourist bias in online restaurant ratings, Professor Zhang finds that one key source is tourist bias in their reviews. “Tourists are about 13.4 per cent more likely to give restaurants a higher rating than locals. If most reviews come from tourists who rate places more positively, locals might feel the restaurant is overrated.”

This tendency is evidently found across all kinds of restaurants, whether chains or independent, cheap or high-end, and among tourists from both large and small cities, across all genders. The study also looks into the very different experiences and expectations about restaurants from local customers and tourists.

Understanding this bias would help businesses better manage customer satisfaction levels and tailor their offerings to meet their customers’ expectations. Meanwhile, customers can leverage the findings to assist their judgment when looking for restaurants.

“Tourists are about 13.4 per cent more likely to give restaurants a higher rating than locals. If most reviews come from tourists who rate places more positively, locals might feel the restaurant is overrated.”

Professor Michael Zhang

Why do tourists tend to give higher ratings?

Along with Xu Da Peng at South China University of Technology, Hong Hong at Tongji University, and Ye Qiang at the University of Science and Technology of China, Professor Zhang collected data from Chinese Mainland’s most popular restaurant review platform, focusing on 10 cities famous for their local cuisines, namely Changchun, Changsha, Guangzhou, Guiyang, Haikou, Suzhou, Tianjin, Xi’an, Xiamen, and Zhengzhou.

The sample consists of 70,950 reviews written by 747 users for nearly 40,000 restaurants with a wide range of prices and popularities. The researchers identify whether a reviewer is a local or traveller by analysing their location information relative to the location of the reviewed restaurants.

Professor Zhang and his team discovered that the positive emotional state while travelling is the reason for tourist bias. Travelling boosts their mood and makes tourists more willing to express their feelings instead of pondering on analytical or detailed reasoning. Reviews from tourists are also shorter but accompanied by more photos, suggesting they care more about sharing their experiences rather than commenting on taste and price. They are also more forgiving of restaurant flaws.

Tourists on the lookout for more than just functional dining are more sensitive to the emotional aspects, such as the restaurant’s vibe and the hospitality they experience, as they mention in their reviews. Meanwhile, locals write more about locations, cooking methods, and prices. The researchers further identify the distinctive words used by each group

Focusing on experience may give the impression that tourists seek more expensive or higher-quality restaurants, but a deeper analysis finds that both locals and tourists who write reviews often avoid fancy establishments. It’s just that reviews from tourists tend to be more positive.

How can restaurants and customers leverage tourist bias?

Given the different interests between locals and tourists, Professor Zhang suggests restaurants apply a dual-focus promotional strategy that addresses the distinct needs of both groups. Restaurants can emphasise service quality to attract tourists, create photo-worthy environments and highlight experiential aspects that tourists can share with others, while also training staff to provide attentive service that generates positive emotional experiences.

To retain local customers, restaurants should focus on fundamentals, such as competitive prices and consistent quality and taste, while offering value propositions that appeal to the rational mind and build a reputation through authentic cooking techniques that locals prefer to mention in reviews.

“To integrate both target markets, restaurants may separate seating areas or dining times to cater to different atmospheres, or differentiate menus by highlighting signature experiences for tourists and the most favourite dishes for local patrons,” he says. “Both groups value quality, so maintaining high standards across all dimensions benefits all target markets.”

For the customers, Professor Zhang suggests taking extra steps to find reviews that better match their preferences and weigh the ratings differently. “Tourists wanting to eat like a local should prioritise longer reviews that highlight the restaurant’s location, cooking methods, value for money, with more analytical wordings. Meanwhile, those seeking a memorable experience should consider reviews highlighting service and ambience, with more photos and emotional expressions.”

As restaurants located in touristy areas may have their overall ratings inflated by travellers, the actual local feedback might be closer to lower-rated reviews.

Taking bias into account for better reviews

To ensure the users receive more accurate reviews, Professor Zhang suggests platforms identify which reviews are submitted by tourists and locals, then calculate separate average ratings for each group and provide functionality that allows users to view ratings from either locals or tourists.

With ever-evolving technologies, machine learning can be deployed to train algorithms to scan and detect reviewer types. Algorithmic adjustments can also be carried out to moderate ratings from identified tourists, considering their tendency to inflate their rating submissions.

For transparency, platforms can add labels mentioning locals or tourists to their reviews or display notes or disclaimers about potential bias in highly rated restaurants with predominantly tourist reviews. Platforms can also show trend lines of ratings separated by reviewer type over time.

Furthermore, platforms can suggest personalised recommendations. For example, platforms can recommend restaurants emphasising service and environment for travellers, while suggesting restaurants highlighting location, cooking quality, and value for local users.

“Overall, we find that the tourist bias is consistent across restaurant types, whether chains or independent, as well as across price levels and cities, making the findings broadly applicable,” Professor Zhang adds.

The post The hidden bias of restaurant reviews first appeared on China Business Knowledge.

Featured faculty: Jesse Yao
Written by Sally Ho

It’s fair to say that no one has been spared from the universal nuisance of scam calls and messages. Bad actors often find the targets from data brokers that collect personal data illicitly or purchase it from platforms to which users have entrusted their information.

Companies collect vast information about their customers to personalise advertisements and product offerings, yet many users are unaware of how valuable their personal data is. While the exact market value of personal data remains obscure, the global data broker industry is estimated to be worth US$277 billion in 2024.

Although countries around the world have issued stringent data protection laws, data misuse and breaches are increasingly common. Many companies mention their commitment to keep users’ data private in their privacy policies, but end up sharing or selling it to third parties without consent.

“Companies have a strong motivation to sell users’ data for immediate profits, and may not realise that they can actually gain consumer trust and loyalty by honouring their commitments to user privacy,” says Jesse Yao, Assistant Professor at the Chinese University of Hong Kong (CUHK) Business School. “Data sales are often not transparent or directly observable. Consumers can’t easily verify if a company is truly keeping its privacy promises.”

Ultimately, the nature of data collection creates a conundrum, where consumers are unsure about sharing their information as companies juggle between keeping and selling data. In his latest paper, Reputation for privacy, Professor Yao explains that such a dilemma is called the “holdup problem,” where two parties hesitate to cooperate due to concern about the opportunistic behaviour of the other party.

Can reputation protect data privacy?

Consumers who believe that a firm values its reputation over immediate profits are more confident in entrusting their personal data with the said firm. Building on this idea, Professor Yao models various scenarios of firm and consumer data interactions and then compares the outcomes in different market structures.

“Companies have a strong motivation to sell users’ data for immediate profits, and may not realise that they can actually gain consumer trust and loyalty by honouring their commitments to user privacy.”

Professor Jesse Yao

The analyses find that privacy protection thrives in a monopoly setting, where one firm dominates. In this setting, customers quickly find out which firm to blame for any data sales. Considering the risks of permanent reputational damage by selling or recklessly handling user data, the firm has a strong incentive to protect data to keep consumer trust and loyalty.

In a competitive market with multiple firms relentlessly trying to outmanoeuvre each other, reputation fails to serve as a privacy gatekeeper. Since consumers cannot easily identify which company leaks or sells their data, and individual firms do not bear the full consequences of harming consumer trust, the repercussions for the offenders are weak and temporary.

Take Apple’s operating system iOS, for instance. The company has quasi-monopoly power over its closed ecosystem and tight controls on both hardware and software. Consumers cannot install software from other manufacturers and will easily point fingers for any data breaches. Since Apple cares so much about reputation, it has strong incentives not to misuse users’ data.

On the other hand, the open Android ecosystem has numerous hardware manufacturers and software developers sharing the market. Consumers often cannot tell which apps were responsible for privacy violations due to noisy data flows and shared infrastructure, making the environment more prone to privacy risks, as evident in many news reports.

“We even find situations where two competing companies at first wanted to stick to their privacy commitment and were very willing to keep their reputations, but the temptation was so strong that they eventually failed to do so,” says Professor Yao.

Why privacy policy and regulation matter

Unfortunately, there is no purely monopolistic market in the real world, and people nowadays use multiple apps on various devices. Companies can easily gain short-term profits by selling data, and customers will find it hard to track down the responsible party. This lack of accountability reduces firms’ incentives to protect privacy. In this case, regulation plays a vital role in ensuring consumers’ rights.

Sound regulation can extend benefits for both consumers and companies. Protecting data privacy will make consumers more confident to share their information and to get better product offerings. At the same time, companies benefit from enhanced reputations and sustainable profits from loyal customers.

“Consumers and companies actually share the same interest, but the companies might be tempted to act against consumers’ interest by selling their data for short-term gains,” says Professor Yao. “Therefore, well-designed regulations are important to encourage businesses to behave responsibly, which benefits both consumers and companies in the long run.”

On top of that, regulators shall impose fines to deter firms from violating privacy commitments. “Liability fines by themselves are not enough, but liability fines with regulatory monitoring could do the trick,” he says.

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How privacy rights affect personal data markets and firm profit

The study offers a general framework for future exploration on the effectiveness of different policy tools and business practices, especially on how emerging technologies like AI will shape privacy dynamics.

As technology advancements tend to increase the benefits and complexity of data use, enforcing privacy in ever competitive markets becomes challenging. Regulators may use AI-based monitoring and enforcement, alongside liability fines, to encourage firms to maintain privacy commitments. Without strong and enhanced regulatory interventions, enforcing data privacy may become more and more difficult as technology progresses.

The post Tech rivalry erodes your privacy first appeared on China Business Knowledge.