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    If AI learns from human behaviour, does it also adopt human bias, or does it simply repackage it in a more polished form?

    Featured faculty: Li Hongfei
    Written by Pan Jingyi

    Childhood friends Queenie Fan and Day Lau started their handbag brand, Cafuné, a decade ago in Hong Kong. The label has grown its retail footprint across Asia, yet success did not shield Fan from the kind of scepticism many women founders know well.

    “When you start your own business at a young age, people are not always willing to take you seriously, especially in the leather industry, which is typically more traditional and male-driven,” Fan said in an interview.

    Her story is far from unique. Katherina‑Olivia Lacey, a co-founder of a Singapore‑based tech startup Quincus, had investors question her role during a seed funding round. A 2025 report by the Organisation for Economic Co-operation and Development also found women are 25 per cent less likely than men to receive bank loans to fund their businesses.

    “Different ways of asking questions change the way AI defines successful entrepreneurs.”

    Professor Li Hongfei

    AI
    Different ways of asking questions change the way AI defines successful entrepreneurs.

    The myth of the hard-charging leaders who win through aggression and swagger, typical masculine traits, is still alive and prevalent in modern culture. An artificial intelligence (AI) model trained on a myriad of stories and human writing to converse and answer questions, called a large language model, may learn and accept that skewed worldview.

    However, Li Hongfei, Assistant Professor in the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School, discovers that AI can be wiser than humans.

    “Our study found that large language models generally exhibited a balanced gender perception of entrepreneurship, with a slight preference for feminine traits. However, algorithms may show a notable bias towards masculinity in specific scenarios, or when you use a different approach to ask the questions.”

    AI advocates gender equity

    In a study titled Detecting gender stereotype biases against women entrepreneurs in large language models, Professor Li, along with Cao Xian of Illinois State University, Xu Qingyu of the City University of Hong Kong, and Zhu Ruoqing of the University of Illinois Urbana-Champaign, asked ChatGPT, a major language learning model, to describe characters of successful entrepreneurs from selected words: dominance, forcefulness, aggressiveness, assertiveness, warmth, sensitiveness, emotiveness, and expressiveness.

    The results are encouraging. Rather than choosing purely masculine traits, such as dominance and aggressiveness, the model consistently selects three words for both successful men and women entrepreneurs, namely assertive, expressive, and warm. While assertiveness is traditionally seen as masculine, the other two are closer to feminine traits.

    “This contrasts with historical and popular literature that overwhelmingly portrays successful entrepreneurs with stereotypically masculine traits,” Professor Li says. “This pattern might reflect programmed efforts by ChatGPT to minimise unethical gender bias in descriptions of successful entrepreneurs.”

    AI companies have used several methods to prevent their systems from repeating sexist ideas, such as filtering out biased content and adding more examples of women in leadership roles. OpenAI, for instance, runs fairness tests to see how ChatGPT responds to a question when the user’s gender or name changes, ensuring its neutrality.

    AI
    The study shows that large language models generally exhibited a balanced gender perception of entrepreneurship, with a slight preference for feminine traits.

    Women entrepreneurs win sometimes

    In another experiment, Professor Li and the team fed ChatGPT with texts highlighting masculine traits, feminine traits, a mix of both, and neutral traits to subtly put the model in different mindsets. They then asked it to evaluate a business proposal from a gender-neutral founder to see whether exposure to certain traits would change how AI judges the proposal.

    As in earlier results, AI shows little evidence of gender stereotyping. More specifically, ChatGPT does not undervalue feminine traits in general business evaluations and explicitly points out that the entrepreneur’s gender doesn’t affect the outcomes.

    To make the test more realistic, the team asked AI to evaluate actual entrepreneurial ideas from Reddit, and it still doesn’t exhibit gender biases. In fact, the algorithms even give higher marks to ideas written in a warmer, more collaborative and people‑focused style, as in a more feminine tone.

    When bias finally appears

    The picture shifts when ChatGPT was asked to behave less like a conversation partner and more like a venture capitalist analysing investment opportunities.

    In the last experiments, ChatGPT was assigned to weigh different personality traits and detailed business ideas, then determine an investment outcome. This test is closer to how AI is used in real life for screening applications, scoring founders, and ranking business opportunities using financial calculations.

    Here, the result changes. ChatGPT favours more assertive, risk-embracing, and affirmative pitches that reflect masculine character. In other words, once the AI is pushed to think more technically, masculine traits carry more weight.

    AI
    When asked to behave like an investor analysing with formulas, AI quietly tilts towards a stereotypical pattern.

    “Different ways of asking questions change the way AI defines successful entrepreneurs,” Professor Li says. “When being asked to behave like a data analyst or investor to calculate an investment score using a formula rather than simply ranking an idea, AI doesn’t ‘realise’ it is dealing with a gender question and treats the task as a mathematical exercise.”

    Human involvement is crucial

    As AI becomes a bigger part of entrepreneurial life — helping with everything from business plans to funding decisions — understanding its strengths and limitations is key. Large language models take the women’s side when describing success or rating ideas in a straightforward way, but when asked to behave like an investor analysing with formulas, AI quietly tilts towards a stereotypical pattern.

    “We still need more research, using different methods, to really understand when large language models copy unfair biases and when they help challenge them,” says Professor Li.

    For women founders like Fan, Lacey, and others building their ventures, AI can be a useful sounding board that does not automatically downgrade them for being women or for using a more collaborative and emotional tone. However, the study also reminds us that AI outputs should not be treated as completely impartial.

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    “When using AI to screen applications or analyse pitches, adding human oversight is still important to avoid unintentional prejudice,” Professor Li adds. “When you ask AI to help you make a decision, you need to understand what the rationale behind its decision is.”

    Ultimately, given that gender bias is historically prejudiced human-generated data on which AI is trained, the discerning judgment of humans remains paramount. This vital insight reinforces the indispensable role of humans in ensuring that technology elevates fairness rather than perpetuates inequities.

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      foreign investment

      A new study shows foreign firms help foster local businesses, until they start crowding them out

      Featured faculty: Ma Xufei
      Written by Pan Jingyi

      Cross-border capital flows are no longer just about money. When multinational companies build factories or expand operations overseas, they bring along technology, management know-how, supply-chain connections, and access to international markets. In this case, inward foreign direct investment is often viewed as an engine for local growth and competitiveness.

      However, many also view foreign investment cautiously, citing concerns about potential harm to domestic industries. Policymakers around the world have issued regulations to limit foreign investment, such as national security screenings, sector-specific prohibitions, capital requirements, and the like, to safeguard local interests.

      For China, foreign investment is paramount. The Ministry of Commerce reported that 70,392 new foreign-invested firms were established last year, a 19 per cent year-on-year increase, while pledging more policy support. Meanwhile, Chinese companies are actively expanding abroad and venturing into advanced technologies. There is clear evidence that foreign capital can boost local businesses, but to what extent?

      “Over the past two decades, provinces in China that attracted significant foreign direct investments have experienced a rapid increase in the establishment of local firms, while less foreign-invested regions continue to struggle,” says Ma Xufei, Professor of the Department of Management at the Chinese University of Hong Kong (CUHK) Business School. “Hence, we take a detailed approach to explore how foreign firms influence local entrepreneurs.”

      foreign investment
      When foreign firms’ domination exceeds 48 thresholds, competition intensifies, and the space for local startups narrows.

      Professor Ma’s new study, Beyond direct impact: Exploring inward FDI’s multifaceted effects on new venture creation, takes a close look at the conundrum. In collaboration with Luo Lingli and Lei Linan of Zhejiang University, as well as Yamanoi Junichi of Waseda University, Professor Ma finds that foreign investment brings opportunities for local startups, within certain limits.

      The 48 per cent threshold

      The team analyses data covering all Chinese-registered firms from 2013 to 2023, and discovers that more foreign investment isn’t always better. The effect depends on whether foreign firms and new local enterprises or startups operate in the same industry and region.

      When foreign companies operate in the same industry and province as local firms, the benefits to local counterparts increase up to a point, and become detrimental as they move further, forming an inverted U-shaped trajectory. Such benefits peak when foreign firms account for 48 per cent of all the sales in a specific industry and province.

      Below this threshold, local firms can learn technologies, managerial expertise and marketing insights from their foreign counterparts through knowledge transfer, or Professor Ma calls it spillover. “At this level, foreign firms still struggle to adapt to local markets, providing local entrepreneurs with novel opportunities to capitalise on,” he says.

      “Supportive environments often have clearer rules, which make it easier and cheaper to do business, helping local entrepreneurs create and scale up their new ventures.”

      Professor Ma Xufei

      The pattern changes once foreign presence becomes too strong. As foreign investment rises, competition intensifies, and the space for new entrants narrows. At this stage, foreign firms’ domination drives up costs and attracts local talent with higher pay and benefits. “As a result, the influx of foreign competitors can discourage local startups and make it harder for them to survive,” he adds.

      The gravity of local ecosystems

      Entrepreneurial environments also shape the extent to which foreign investment helps or harms local businesses. Specifically, the study indicates that the more developed a region’s non-state economy, or how much a region is driven by private businesses and market forces rather than government control, the more it enhances the positive spillover effects.

      A stronger non-state economy encourages cooperation between local and foreign firms and facilitates positive spillover. “Such supportive environments often have clearer rules, which make it easier and cheaper to do business, helping local entrepreneurs create and scale up their new ventures,” Professor Ma says.

      However, there’s a caveat. Supportive non-state economy also allows foreign firms to expand more effectively and compete more aggressively, even dominating key resources such as top suppliers and skilled talent, thereby helping them surpass the 48 per cent threshold. If this happens, local startups may find it harder to survive.

      foreign investment

      Looking for a safe haven for local growth

      So, how can local entrepreneurs make the best of inward foreign direct investment? The study finds that instead of competing head-to-head, local entrepreneurs can learn from foreign friends and apply the know-how to related industries or other regions with similar customers, products, or operational requirements.

      For instance, if foreign automakers invest heavily in a region, local startups in related industries, such as auto parts manufacturing or electric vehicle batteries, can benefit by supplying these firms or adopting their production techniques. In regions with significant foreign investment in the technology sector, startups in software development or IT services may leverage the knowledge and customer base built by foreign firms.

      foreign investment
      “Local entrepreneurs can identify the related industries by analysing value chains and looking for suppliers, distributors and customers of foreign-invested industries. After that, they shall identify industries that share labour pools, technologies, or customer bases,” Professor Ma adds.

      “By redirecting their target markets to related industries or neighbouring regions, local entrepreneurs can use what they learned with less direct competition from foreign firms.”

      What can policymakers do?

      While foreign investment can be a powerful engine for learning and growth, its benefits to local communities are not guaranteed. Therefore, Professor Ma suggests that local regulators implement targeted investment promotion, balanced competition policies, cluster development, and regular monitoring.

      Attracting foreign firms in industries with high growth potential can be achieved by offering tax incentives, subsidies, or streamlined regulations. Regulators should also support local firms through subsidies, training, or access to financing to ensure they can coexist with foreign firms.

      foreign investment
      Regulators can support local firms through subsidies, training, or access to financing to ensure they can coexist with foreign firms.

      To facilitate spillover further, industrial clusters where foreign and local firms can collaborate would provide infrastructure and networking platforms. “The regulator should also continuously monitor foreign direct investment levels to ensure they do not exceed the threshold where competitive pressures outweigh learning opportunities, and adjust the policies accordingly,” he adds.

      The findings can also be partially generalised to other countries, especially emerging markets, but with caution. Countries with diverse regions and significant economic disparities may experience dynamics similar to those of China, but countries with a weak non-state economy may observe different effects.

      “The type of industries also matters,” says Professor Ma. “The presence of multinationals in industries like technology or manufacturing may generate effects comparable to those observed in China, but other sectors like agriculture or resource extraction might behave differently.”

      Finally, heightened geopolitical tensions and restrictions imposed by certain countries on investment in China have hindered spillovers from foreign firms. In this regard, Professor Ma suggests that the government take proactive steps, such as encouraging local enterprises to fill the knowledge-transfer gap by providing research and development grants and innovation subsidies.

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      More investment in infrastructure, workforce skills, and industrial clusters would also help spread advanced technology more widely within the country.

      “Local firms must also invest in building their own capabilities, for example, through training programmes or partnerships with domestic universities, and develop alliances with other domestic firms to compensate for the loss of foreign expertise and networks,” he adds. “They could also look for investment opportunities in neighbouring countries.”

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        While algorithms promise faster and smarter human resource management, employees may see the process as colder and less human

        Featured faculty: Choi Sungwoo
        Written by Pan Jingyi

        Derek Mobley had applied to more than 100 jobs over several years and had admittedly received rejection notices within minutes or hours. Confused and furious, the US citizen sued Workday, a human resources software firm that handled most of his applications, alleging that its artificial intelligence (AI) screened out his applications based on his age, race, and disabilities.

        While Workday has argued that it’s not liable for hiring decisions, a court conditionally certified the age discrimination claims last year. This highly anticipated lawsuit will set a new precedent for AI-driven hiring practices and serves as a reminder that handing over employment decisions to algorithms can lead to backlash.

        AI
        AI is reshaping human resource management.

        AI has inevitably reshaped human resource management, as also seen across industries today. A 2025 survey from Resume Builder shows that a majority of US managers have relied on AI for high-stakes decisions, such as promotions, rises and even layoffs. Akin to a dystopian Black Mirror episode, bosses are turning to machines to decide who’s in and who’s out.

        Although more and more companies embed automation into their human resource operations, little is known about the impact on employee morale when their career is in the hands of a non-human actor. This is the puzzle that Choi Sungwoo, Assistant Professor of the School of Hotel and Tourism Management at the Chinese University of Hong Kong (CUHK) Business School, seeks to answer.

        Professor Choi uncovers a latent repercussion of advanced technology in human resource management: organisational dehumanisation. “Organisational dehumanisation is the feeling of being reduced to a mere functional component of an organisation, much like a single bolt in a large machine, where your unique qualities, emotions and individuality are largely disregarded.”

        Why AI can feel dehumanising

        In a study titled AI in human resource management: A driver of organisational dehumanisation and negative employee reactions, Professor Choi works with Shin Hyejo of the Hong Kong Polytechnic University and Kim Hyunsu of the University of Macau on three scenario-based online experiments. They recruited nearly 700 participants through Prolific, an online platform widely used in academic research.

        “When AI performs human resources operations, employee characteristics are seen as numbers. Therefore, employees would feel like they are not treated as humans.”

        Professor Choi Sungwoo

        AI
        People reacted more negatively when the decision-maker was AI.

        Across all three experiments, participants were asked to imagine that decisions about their promotion or performance review were being made either by an AI system or by a human manager. The results were consistent: people reacted more negatively when the decision-maker was AI.

        Those reactions were not trivial. Participants reported lower commitment, stronger turnover intentions, and even greater retaliatory feelings when seeing AI deciding their livelihood. In practice, they are more likely to search for another job and warn others to avoid working for the company.

        A couple of factors drive such dehumanising feelings, Professor Choi notes. AI lacks the ability to understand social norms, personal issues and ethical concerns as a human manager can. AI also works in incomprehensible ways to laypeople, and employees may fail to understand how AI reaches its conclusions. As a result, they feel powerless and excluded from the decision-making process.

        “Putting it all together, loss of empathy, transparency, and control can leave people feeling objectified,” Professor Choi says. “When AI performs human resources operations, employee characteristics are seen as numbers. Therefore, employees would feel like they are not treated as humans.”

        Can human resources automation thrive?

        Different companies have different sentiments towards AI. Professor Choi and his collaborators identify what they describe as a cultural paradox: companies with more collaborative and family-like cultures may experience greater resistance to AI in human resources management.

        In these collaborative environments, employees believe that the management values cooperation, support and interpersonal relationships. If AI is then used to make major decisions, the technology can clash with such a principle.

        AI
        Rather than allowing AI to make decisions on its own, designing systems that enable humans and technology to coexist is important.

        “When a collegial workplace adopts AI for major human resource decisions, it can feel like a betrayal,” Professor Choi explains. “Employees experience a dissonance between the human-centred values the culture espouses and the perceived quantification of their worth that AI involvement implies.”

        By contrast, the negative effects of AI appear to be less intense in companies with a more outcome-oriented system, where performance and results are already prioritised over interpersonal connections. But that does not mean AI is entirely harmless in such settings.

        Even in outcome-focused organisations, AI-driven decisions on the workforce can still backfire and brew dehumanisation. Companies that deploy an AI system to select the most suitable candidates for promotion still see employees feel their aspirations or contributions are overlooked.

        In short, whether focusing on outcomes or collaborations, the company needs to take the human aspect into account when adopting AI in human resources operations.

        Keep “human” in human resources

        Reputation is a valuable asset for a company. When job marketplaces like Glassdoor, Indeed, Seek, and even Google nowadays provide user-generated company reviews, the efficiency gains from AI might be quickly diminished by a wave of criticism from current and former employees.

        For companies and business leaders, the message is not to abandon AI, but to use it wisely. One priority, Professor Choi says, is transparent communication. “Companies should clearly explain why AI adoption in human resources is necessary and reassure employees that it does not compromise the organisation’s core commitment to supportive and human-oriented growth.”

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        Rather than allowing AI to make decisions on its own, Professor Choi suggests designing systems that enable humans and technology to coexist. “This hybrid approach helps preserve the sense that consequential decisions about people are ultimately made by people. If AI serves only in an assistive capacity with limited input into the final decision, the dehumanisation effect should be substantially mitigated.”

        “Human resource practices are highly sensitive, and AI could be most valuable in managing less critical yet voluminous tasks, such as initial application screening, freeing human managers to focus on more complex and high-stakes decisions,” Professor Choi adds. “Despite that, companies should always be mindful of the risks of dehumanising feelings and act accordingly.”

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          Social network

          Who needs a crystal ball when you can use mathematics to calculate whether a product or idea will catch on with the masses?

          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.

          blockchain
          Ideas spread within unpredictable social networks through friends and strangers.

          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.

          social network
          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.

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          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.

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            ESG

            Saving the earth might grab eyeballs online, but it doesn’t always win retail investors’ hearts

            Featured faculty: Michael Zhang
            Written by Sally Ho

            Social media has levelled the playing field of access to financial knowledge, granting institutional and retail investors alike equal access to timely news and sentiment that shape their decisions. Take the collapse of Silicon Valley Bank in 2023, for example. A panic spiralled on social media turned a bank with US$212 billion in assets into bankruptcy in just two days.

            Meanwhile, environmental, social and governance (ESG) performance has become one of the most talked-about corporate lingos, not just among consumers but also as a signal in modern investing. Companies are held accountable for their sustainability claims and practices, and failure to do so may put them in the spotlight or, even worse, lawsuits.

            ESG
            Strong ESG scores attract more attention but do not necessarily receive positive sentiment.

            Retail investors nowadays increasingly express their views online, influencing other investors’ behaviour and market movements. On social media, a company’s stance on climate change, labour practices, or corporate governance can spark heated discussions. However, little is known about how much retail investors actually value ESG practices among corporates.

            “Sustainable investing has accelerated in the past few years, but most discourses focus on how ESG affects firm value or analyst recommendations,” says Michael Zhang, Wei Lun Professor of Business AI at the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School.

            “There is a significant gap between the rising importance of ESG in the corporate world and the lack of understanding regarding how retail investors actually process ESG-related information.”

            Professor Zhang’s latest study, Attention or sentiment: How social media react to ESG?, aims to address this gap and finds that, when it comes to sustainability, retail investors’ talk and walk don’t always go hand in hand. While retail investors do care about ESG, they may not be able to determine if such practices are financially material in the short term.

            Classic dilemma of profit vs. planet

            To explore how retail investors react on social media about companies’ ESG performance, Professor Zhang, along with Kalok Chan at City University of Hong Kong, Xu Dapeng of South China University of Technology, and Hong Hong of Tongji University, examines tens of thousands of posts on Seeking Alpha, a popular online community platform for retail stock investors.

            With more than 17 million monthly visitors, Seeking Alpha publishes content written by diverse contributors and features comment sections, forums, and groups where users discuss investment strategies. Given these characteristics, this platform has been dubbed social media for retail investors.

            The researchers focus on firms in the S&P 500 index, or the top US-listed companies. After including only firms discussed on Seeking Alpha and having ESG scores, the final sample consists of 429 firms.

            “Managers should realise that in the short term, ESG gets you noticed, but financial metrics likely still drive the sentiments.”

            Professor Michael Zhang

            Given that online attention and sentiment are often drivers of stock market volatility and trading volume, the team categorised the posts into two key responses: social media attention and social media sentiment. Attention refers to how many posts are about a certain company, and sentiment refers to the emotional tone, including optimistic or pessimistic attitudes, towards the company.

            After matching and analysing the social media posts with ESG performance scores from Sustainalytics, a global provider of ESG ratings and data, the researchers found that firms with strong ESG scores attract more social media attention. ESG score upgrades are associated with increased social media attention, while downgrades result in decreases in the following months.

            However, retail investors on the platform do not necessarily express more positive feelings toward firms with high ESG scores. Investors also do not show more positive sentiment after ESG upgrades or more negative sentiment after downgrades. This suggests a disconnect where sustainability sentiment does not always align with visibility.

            Talk is cheap, but vibe speaks volumes

            ESG
            Firms shouldn’t assume that high visibility from ESG activities automatically translates into a positive image.

            The study further examines the three major components of ESG separately and their individual impact on social media attention and sentiment. The environmental and social components represent the main drivers of increased attention online, while the governance aspect did not have any significant impact.

            For online sentiment, social and governance aspects have no significant impact, but surprisingly, the environmental score alone is associated with less favourable sentiment. This finding might seem counterintuitive, but it aligns with a specific stream of financial theory: many retail investors treat environmental efforts as a cost, rather than a clear financial benefit.

            “It is likely that retail investors in these online communities often view high environmental commitment as a financial burden,” Professor Zhang says. “From a utilitarian investment perspective, extensive spending on environmental initiatives, like emission cuts or resource reduction, can be seen as an expense that might hurt financial performance.”

            Despite being beneficial to wider society, investing in sustainability initiatives can raise questions about short-term profitability and provoke scepticism due to a perceived threat to a company’s bottom line. It appears that retail investors on online forums tend to be driven primarily by financial concerns, rather than environmental causes.

            Research implications and future directions

            ESG activities may increase visibility among retail investors, but firms shouldn’t assume that higher visibility automatically translates into a positive image, since investor sentiment is driven by profit. “Companies need to manage their expectations regarding the return on their ESG investments when it comes to public perception,” Professor Zhang adds.

            “Maintaining ESG standards is crucial for relevance and visibility, even if it doesn’t immediately result in a warmer reception from retail investors. Managers should realise that in the short term, ESG gets you noticed, but financial metrics likely still drive the sentiment.”

            For market analysts and regulators, the disconnect between attention and sentiment raises questions about how ESG information is communicated and interpreted. Social media may amplify awareness, but it doesn’t guarantee confidence in sustainability practices or in their financial implications.

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            Looking ahead, Professor Zhang expects to examine whether the findings hold true for smaller-cap companies, not just S&P 500 firms. “We also plan to explore other digital channels such as X [formerly Twitter], Yahoo! Finance, or Google search to see if the attention and sentiment dynamics might differ on general social media platforms,” he adds.

            For now, the key takeaway is clear. In the digital age, seeing isn’t always believing. ESG draws attention, but steering investor sentiment requires more than just doing good.

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              New study reveals how GenAI is reshaping the way we search for travel information, and when we still prefer to “just Google it”

              Featured faculty: Lisa Wan
              Written by Pan Jingyi

              It was supposed to be a fun summer trip to Puerto Rico last year, as a Spanish couple had done everything ChatGPT planned, until they were refused to board the plane for not obtaining proper paperwork. In another case, two tourists were lost in a rural Peruvian town trying to find an imaginary destination suggested by AI.

              AI has been hailed as the new technological evolution, but these stories remind us not to take technology at face value. On the other hand, these cases also highlight how trip planning has moved from a search bar of internet browsers to ChatGPT, DeepSeek, Grok, and the like. Scrolling through a sea of blue links is gradually replaced with a single prompt.

              “Opting for an unfamiliar and novel search method like GenAI can be seen as a risky choice for making concrete plans.”

              Professor Lisa Wan

              “When ChatGPT was first introduced, we immediately sensed its strong potential for tourism information search, which largely depends on context and user preferences,” says Lisa Wan, Associate Professor of the School of Hotel and Tourism Management and the Department of Marketing at the Chinese University of Hong Kong (CUHK) Business School.

              travel-AI
              Trip planning often starts from curiosity and then turns into concrete actions.

              “Unlike traditional search engines that primarily provide fragmented information through hyperlinks, generative AI, or GenAI, can synthesise information, generate narratives, and adapt responses to users’ preferences.”

              With much positive and negative news surrounding GenAI, Professor Wan seeks to understand what travellers actually perceive of the new technology. Working with Li Yuan of Zhejiang University, along with Luo Xiaoyan and Ding Xu of Sun Yat-Sen University, she conducted the research Advancing information search through GenAI: the roles of search type, travel motive and GenAI customisation level.

              Across a series of studies involving more than 800 participants from different countries, the team examined when people lean towards GenAI or retreat to traditional search engines. They find that travellers’ willingness to use GenAI depends on their search purpose, travel motives, and whether the AI agent is tailored for trip planning.

              When GenAI is less trustworthy

              Trip planning often starts from curiosity and then turns into concrete actions. Individuals who come across a destination on social media or over casual conversation may want to find more about the must-sees, the overall vibe, and, as their interest deepens, may seek further information on specific prices and booking options.

              Based on the above process, the researchers grouped these behaviours into two search types: non-decision-based, where individuals browse for general information about a destination, and decision-based, when more detailed information is sought for final decision-making.

              “These differences can influence which search tools people choose,” Professor Wan says. “In the decision-based search, a small bad decision based on inaccurate information can turn into bigger problems, causing consumers to be more cautious.”

              When participants are in decision-making mode, they prefer to gather information using traditional search engines. “Opting for an unfamiliar and novel search method like GenAI can be seen as a risky choice for making concrete plans,” she adds.

              Professor Wan notes that new technologies often face a natural trust gap, especially when mistakes have significant consequences. Moreover, scepticism towards GenAI also reflects a rational assessment of its limitations in providing real-time and verified data, as reported in recent news.

              travel-AI
              Travel motives can affect travellers’ willingness to use GenAI.

              In non-decision-based situations, however, the pattern shifts. When people are causally exploring or thinking about a destination, GenAI’s conversational style and ability to synthesise broad information become more appealing.

              Traveller’s mindset and customisation make a difference

              Looking further into what factors might encourage people to use AI in decision-making scenarios, Professor Wan and her collaborators found that the travel motive is the crucial piece. Specifically, participants motivated by a utilitarian goal that focuses on efficiency and convenience reported a higher preference for GenAI, whereas those with a hedonic motive of prioritising fun and pleasure are more likely to stick with traditional search engines like Google.

              For utilitarian travellers, GenAI is preferred for its ability to filter information and organise search results, reducing the effort to compare options manually. Meanwhile, hedonic travellers enjoy the traditional browsing experience, mostly because search engines feature a richer mix of photos, videos, maps, reviews, and unexpected discoveries.

              “Those prioritising fun and pleasure may find the variety and richness of multimedia content more appealing, providing a more immersive and enjoyable searching experience compared to the textual responses generated by GenAI,” says Professor Wan.

              Customisation levels also affect user preference for AI. As booking platforms increasingly embed AI plugins for specific tasks, such as suggesting available hotels based on user preferences and providing customer service via AI chatbots, the study finds that such customisations can boost trust in GenAI.

              How the tourism industry should adopt and develop GenAI

              travel-AI
              When people are causally exploring a destination, GenAI’s conversational style is more appealing.

              Given that GenAI is often more preferred in the non-decision stage, Professor Wan suggests platforms make an AI assistant visible in the main search bar to inform travellers general information about destinations, such as major attractions and cultural highlights. Another application is to display GenAI responses alongside traditional search results, allowing travellers to cross-check information easily.

              While AI transformation continues to gain momentum, Professor Wan observes that fundamental challenges remain. “Many firms invest heavily in AI solutions but see limited results in daily operations. Two common obstacles are the lack of in-house talent to integrate AI into workflows and the tendency to adopt generic tools that don’t match real user demand.”

              Furthermore, she observes that rapid AI advancements and shifting customer demand require firms to continually adapt this technology. “Rather than treating GenAI adoption as a one-off technological upgrade, firms need to view it as an organisation transformation process that involves gradual development, cross-functional collaboration and iterative experimentation.”

              The future of travel planning

              Professor Wan believes that AI will not completely replace search engines just yet, at least in the near future. Instead, travel information would be more distributed, with different tools serving different purposes. “GenAI is more likely to complement travel planning rather than substitute the traditional way,” she adds.

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              Will lack of internet skills prevent seniors from travelling?

              Interestingly, she suggests that social media will be the close contender for search engines. In Chinese Mainland, for example, RedNote has already become a starting point for many travellers for its first-hand reviews. “The real shift is towards interactive, experience-rich and peer-validated information, something that social media and GenAI offer in different ways.”

              Another takeaway is a concern about how GenAI can subtly change how travellers engage with places and experiences. Therefore, she encourages travellers to keep interacting with locals and communities. “The goal is not to reject intelligent tools, but to remain attentive to how they reshape human capabilities and experience.”

              On this page...
                blockchain

                A small glitch can create ripples like a domino effect in the supply chain, but smart contracts offer a quick and fair way to share responsibilities

                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.”

                blockchain
                Supply chain disruptions often trigger multiple disputes over loss allocation due to layered structures and numerous bilateral contracts.

                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.

                blockchain
                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.

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                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.

                blockchain
                Complex disputes require courts for thorough evidence, so automatic conflict resolution suits clear-cut, data-verifiable cases with less room for argument.

                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.

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                  As economic headwinds and shifting consumer behaviour influence the market, how should businesses anticipate and adapt?

                  Featured faculty: Wu Jing, George Yang, Johnny Li, and Lisa Wan
                  Written by Putro Harnowo

                  The world started 2026 with a complex mix of opportunities and risks. Global productivity and economy have slowed down, but the Organisation for Economic Co-operation and Development expects emerging Asian markets to be resilient.

                  Following the recent US-China tariff truce, China achieved a record trade surplus exceeding US$1 trillion last year, setting the stage for intriguing developments in 2026. Meanwhile, sustainability backlash dominated 2025, with significant environmental, social, and governance (ESG) investment outflows in the US, leaving the sector trajectory uncertain.

                  Rapid demographic ageing in Asia and Europe will transform the insurance industry, with developed markets projected to see 35 per cent more individuals aged 65 and older by 2050 compared to 2025. Amid declining birth rates, younger consumers shift their priorities to products and services that provide emotional satisfaction, fueling the “emotional consumption” trend that continues to shape business.

                  Against these backdrops, we present our 2026 outlook by gathering insights from the Chinese University of Hong Kong (CUHK) Business School faculty. The first outlook highlights the hottest topics in technology, and the second part looks into economic and consumer behaviour that will redefine businesses.

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                  1. New global order with a fragmented yet innovative world

                  Trade frictions between the US and China have already driven global firms toward diversification, prompting a shift away from reliance on Chinese manufacturing. However, Wu Jing, Professor at the Department of Decisions, Operations, and Technology, explored in his study that complete decoupling remains challenging due to entrenched dependencies.

                  international trade
                  Conflicting global supply chains may create bifurcation but also accelerate innovation through competition.

                  “Currently, the most prominent strategy is ‘China plus one’ where companies maintain a baseline of production in Chinese Mainland but diversify into other emerging markets,” he says. “Relocating operations to allied or nearby countries appears to mitigate geopolitical risks, but their long-term sustainability is uncertain.”

                  A notable example of such dependencies is the controls over high-end computing chips by the US, which may not survive without the supply of rare earths from China. This tug-of-war was resolved at a summit of the two world leaders last year, but the truce is seen as a temporary fix, as Singapore’s Prime Minister echoed that the intense competition will continue.

                  “Companies are increasingly forced to navigate multiple, often conflicting regional supply chains, each governed by its own set of rules. In practice, this often means maintaining dual systems, one aligned with Western standards and another with China, which significantly drives up operational costs as they must build production lines and logistics networks to comply with different regulatory regimes,” Professor Wu adds. “If relations deteriorate further, a bifurcated supply chain system is probable.”

                  Not only posing a risk to global economies, Professor Wu sees geopolitical fragmentation likely to hamper sustainable supply chains by disrupting the flow of critical materials, driving up costs and creating inefficiencies. However, he believes there would be a silver lining. “Fragmentations may accelerate innovation through competitive investments, as companies facing disruptions would be incentivised to develop innovative solutions and technologies.”

                  2. Green finance is recalibrating

                  The US political polarisation, coupled with EU regulatory adjustments amid corporate and governmental pressure, drove much of the ESG backlash last year. Elsewhere, ESG investments face stricter rules: China’s new framework requires listed companies to disclose their decarbonisation plans this year, while firms listed on Hong Kong’s Hang Seng Composite LargeCap Index are mandated to disclose carbon emissions from their suppliers.

                  green finance
                  Sensible ESG initiatives should align with corporate strategy and profit goals but require a longer-term view than traditional approaches.

                  These developments underscore resilience, refining the field by weeding out superficial approaches. “Maximising ESG value is not only about disclosing and reporting, but also about what the companies are actually doing,” says George Yang, Professor at the School of Accountancy. “Firms need to be transparent and provide credible and verifiable evidence to stakeholders, especially investors.”

                  One of the main criticisms is that green investments may obscure the potential earnings. Professor Yang’s recent study finds that prioritising ESG information can make a company’s stock price less accurately reflect future returns, since investors may overlook traditional financial metrics. This finding reveals implications that extend beyond the surface.

                  “Sensible ESG initiatives are intended to be aligned with corporate strategies and shareholder values, including profit maximisation. However, in the value maximisation of ESG investments, we need to pay attention to a longer time frame than in the traditional approaches,” he adds.

                  Value maximisation of ESG investments involves incorporating ESG factors to achieve optimal financial performance. As opposed to traditional approaches that typically focus on maximising profits in the short term, ESG investments often take a longer time, even years, to deliver full benefits for shareholders.

                  Such a gap calls for the need to manage and balance shareholders’ expectations. In this regard, Professor Yang emphasises financial analysts’ crucial role in linking sustainability goals to investor decisions. “Financial analysts should pass investors’ concerns and expectations to the firm and help the firm to improve its actual ESG initiatives.”

                  3. Insurers’ battle for the ageing population

                  As the proportion of elderly citizens rises in some parts of the world, the insurers face mounting pressure to manage spiralling claim costs and a wave of soon-to-retire customer base. Johnny Li, Professor at the Department of Finance, observes that only those who master the art of extracting valuable insights from large and intricate big data can survive.

                  insurance
                  Insurers need to use data analytics to accurately categorise health risks and set premiums, or be crowded out of the market.

                  “Insurers aim to accurately categorise individuals with different health profiles into appropriate risk categories and corresponding premiums effectively. Those that fail to leverage data analytics for this purpose will be crowded out of the market,” he says.

                  To illustrate, Insurer A charges US$100 for all customers, and Insurer B uses predictive analytics, leveraging health history, lifestyle, and medical records, to assess the risk of each policyholder and charges US$50 to healthy customers and US$150 to less healthy ones. Healthy individuals would choose Insurer B, leaving Insurer A with high-risk clients, rising costs, and eventual failure.

                  “In practice, there are no insurance products that can be called unique,” Professor Li says. “Many insurers are already using predictive analytics, but those that are willing to invest more to have more refined models can put customers into finer categories, and they tend to have a better competitive advantage.”

                  Professor Li has developed a new method to forecast longevity risk, a financial risk of a person living longer than their savings, for China’s population. The country only saw the insurance industry emerge after 1979, making its population data inconsistent. As a comparison, insurers in Western markets have collected risk data since the 18th century.

                  He notes that China’s vast territory leads to regional differences in longevity risk, and these trends are likely to diverge further as socioeconomic disparities persist. Therefore, predictive analytics is essential for insurers to thrive. “With limited data available in the Chinese market, factors such as gender, city of residence, and income may be incorporated into a machine-learning-supported model.”

                  4. Emotional connection is the prime consumer driver

                  2025 has seen collectable plush monster toys called Labubu taking the world by storm, with teenagers and adults lining up at stores. In Hong Kong, a Japanese character series, Chiikawa, has captured fans’ hearts through themed cafés and pop-up events celebrating its cute and comforting charm.

                  tourism
                  Hong Kong’s East-West culture, Cantonese heritage and festivals can drive experience-focused consumption amid economic pressures.

                  While AI has integrated itself deeper into our daily lives, human emotions remain utterly irreplaceable and may become more profound in consumer behaviour. For example, a recent report by the AI Security Institute shows that a third of UK adults have turned to AI chatbots for emotional support.

                  Lisa Wan, Associate Professor in the School of Hotel and Tourism Management, observes modern customers increasingly seeking deep emotional connections and value beyond the product’s functional benefits. “In the case of Labubu or Chiikawa, the appeal lies beyond the toy, but the surprise in the blind box, scarcity from limited editions, and social buzz increase the emotional drive to buy,” she says.

                  Emotional connection also matters in the tourism industry. Professor Wan’s study highlights how emotional factors, such as thematic storytelling and colour cues, drive customers’ impulsive buying behaviour. Travellers also often form emotional bonds with a destination even before they arrive, sparked by captivating articles, social media, or heartfelt stories shared by friends and loved ones.

                  Applying an emotional touch may also be useful for Hong Kong, which has seen hotel occupancy rebound, but retail spending and hotel stays are lower than pre-pandemic levels. The city could consider shifting away from mass shopping toward cultural and authentic experiences to foster emotional connection.

                  “Hong Kong has unique cultural assets, including the mix of East and West, Cantonese heritage, street markets, and festivals,” says Professor Wan. “More attention should be given to how visitors feel connected to the region and the Greater Bay Area. With economic headwinds and more cost-aware consumers, emotional consumption means shifting from luxury for luxury to emotion-driven value, where deep and meaningful experiences matter, even in moderately priced stays.”

                  Professor Wan elaborates that when customers feel emotionally attached, they become advocates, community members, repeat visitors, and co-creators of value. “Their loyalty goes beyond ‘I like the hotel’ to ‘I feel connected to the brand and destination.’ Loyalty isn’t just about returning customers, but also making them willing to recommend to others.”

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                    Technology continues to reshape modern businesses, a trend set to accelerate as companies embrace AI

                    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.

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

                    robots
                    Robots can help with daily tasks, but customers still crave genuine human interactions.

                    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
                    Blockchain helps make transactions more secure and transparent.

                    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

                    robots
                    E-commerce platforms nowadays deliver entire experiences tailored to consumers’ interests.

                    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

                    blockchain
                    Social media will increasingly prioritise effortless consumption.

                    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

                    robots
                    AI has been used across industries.

                    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.

                    On this page...

                      2025 marked a year of transformative changes and resilience across industries. The advancement of humanoid robots, intelligent tools, and ever-evolving financial complexities is redefining the workforce and reshaping the business landscape. Sustainability also took centre stage, with leaders focusing on responsible growth and human-centric strategies.

                      What topics have been of concern in the past year? How can business leaders and entrepreneurs thrive during this period? Our top 10 most-read articles of the year offer fresh ideas and valuable insights—from smarter ways to leverage technology to simple habits that make a difference.

                      By China Business Knowledge @ CUHK

                      #1 How assistive robots can boost an inclusive workforce

                      Professor Choi Sungwoo, School of Hotel and Tourism Management

                      Technology can empower individuals with disabilities to thrive in the workplace. While its impact on consumer perception varies, a new study suggests that personal interaction is key to success.

                      #2 The science of creativity, genetics and careers

                      Professor Li Wendong, Department of Management

                      Is creativity a blessing for individual well-being and career success? Researchers find that creativity can yield diverse and sometimes conflicting effects on one’s career paths and overall life satisfaction.

                      #3 The green illusion: why eco-conscious people still waste food?

                      Professor Elisa Chan, School of Hotel and Tourism Management

                      Food waste is a major contributor to global warming, yet many people—including those who consider themselves environmentally conscious—remain unaware of its serious impact.

                      #4 Enhancing consumer trust in sponsored ads

                      Professor Wang Weiquan, Department of Decisions, Operations and Technology

                      Misleading ads are fuelling scepticism toward sponsored products and sellers, prompting researchers to examine factors that shape user trust and identify effective strategies to strengthen user confidence.

                      #5 Two cents mean a milestone for startups

                      Professor Willow Wu, Department of Management

                      While it is commonly believed that entrepreneurs should follow the advice of investors, the reality is far more nuanced. New research suggests seizing all possible opportunities to learn.

                      #6 Stay niche for better branding

                      Professor Tony Ke, Department of Marketing

                      How a brand positions itself can make all the difference. While chasing market trends seems tempting, niche brand positioning can be more profitable in the long run by building consumer trust.

                      #7 The matchmaking secrets for high-performing teams

                      Professor Mandy Hu, Department of Marketing

                      Teamwork plays an important role in a fast-paced work environment. Researchers discover a method to enhance firms’ productivity by redesigning teams without incurring additional hiring costs.

                      #8 How mental shortcuts guide loan success and repayment

                      Professor Michael Zhang, Department of Decisions, Operations and Technology

                      People sometimes rely on quick thinking when making decisions, but this comfort can be a disaster when it comes to personal finance. Recent research offers insights into choosing the right shortcut.

                      #9 Do stock buybacks stifle innovation?

                      Professor Kevin Tseng, School of Accountancy

                      Companies are buying back more of their own shares, often to meet earnings targets. While some fear this hurts innovation, a new study finds the pressure can make firms put their priorities straight.

                      #10 The risks and rewards of Chinese shadow banking

                      Professor Su Yang, Department of Finance

                      Chinese banks operate shadow banking as a high-yield wealth management product. Researchers investigate how the competition fuels these products and highlight the need for clearer disclosure.

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