Stoic – Why Statues Matter

Nobody cared more about statues than the Greeks and the Romans. In fact, the only reason we know what many of the Stoics looked like is because they were preserved in marble by sculptors many thousands of years ago.

The Stoics knew that statues were important. Aristocreon, a nephew of Chrysippus, put up a statue of his uncle—to honor his memory and his role in the founding of Stoicism. The grandfather of Cato was once asked why there was no statue of him. His answer: I’d rather people ask why there isn’t a statue of me than why there is. The idea for the Greeks and Romans was to put up these statues so that we might look up and be inspired by the deeds and the principles of the great men (and women) who came before us.

But today, what statues do we put up? Last year, Michigan became the home of a new statue of Robocop. Most people can agree that statues of Confederate generals (see: traitors) are not appropriate to maintain with public funds. That’s as far as we’re able to go though. We’re not building new statues, that’s for sure. We can hardly agree on who we admire enough to capture in stone or bronze.

That’s really sad and really scary. Because each generation needs guidance. We need to be called to honor the greatness of our past (and in the case of some monuments, reminded of the failures and mistakes civilization has made). We need to see—in tangible form—the principles that we as a people hold dear, that we are aspiring to mirror in our own lives.

A nation—an era—is judged by the monuments it erects just as a home is judged by the art that hangs on its walls. So that’s the question for the world and for you as an individual today: What statues are you putting up? And are you living by the example they stand for?

Collection – In Your Relationships With Other People, You’re Either Overfunctioning or Underfunctioning

A psychologist explains why these little known concepts are huge in understanding relationships!

There are two kinds of people in any relationship — an overfunctioner (OF) and an underfunctioner (UF).

A basic understanding of this difference and how it plays in your relationships with other people is the first step in being able to make larger, important changes, according to Dr Will Meek, a counselling psychologist, and the Director of Counseling and Psychological Services (CAPS) at Brown University.

An imbalance in power is common in many relationships in life and at work.

Murray Bowen(1931–1990) was the first psychologist to study the family in a live-in setting and described specific details about how families function as systems. Michael E. Kerr wrote about Bowen’s systems in his book, Bowen Theory’s Secrets: Revealing the Hidden Life of Families.

According to Bowen, OFs and UFs get stuck in a mutually reinforcing trap. In any situation, you either quickly switch into fixing mode or pull back and hope others will take responsibility.

Awareness is the key to changing this pattern in your home and work life.

Overfunctioners are quick to act. They enjoy taking control. Sometimes unconscious without realising it. They want to attack the to-do list at home and at work.

“The OF takes on more than his or her fair share of responsibility for (say) housework, parenting, or finances because otherwise they don’t get done,” Oliver Burkeman explains.

They easily burnout, because they want to fix everything and everybody, and they have too much to do every day. They don’t know how to take a break. OF’s are frequently overwhelmed, and neglect self-care.

As “effective” as they may be, overfunctioners can be overpowering, especially if you want to take control of your life at your own pace. An OF believes he/she knows a better way for an UF.

In a relationship or family system, they can easily create tension and conflict, even though they think they are handling the issues and solving problems everyone is ignoring.

Underfunctioners on the other hand, tend to hold back or zone out. They wait for others to manage things for them. Sometimes they have problems meeting deadlines and making real progress. They frequently rely on others to make decisions for them. Underfunctioners are laid back and make improvement at a slower pace. They tend to zone out to TV quickly and can easily appear to others as unmotivated.

“UFs are often seen as “having so much potential but wasting it” in the eyes of others, and can be thought of as taking less than 100% responsibility for life (someone else takes the rest, which we will see in a moment),” writes Meek.

Are you over-functioning for your partner, grown children, co-workers or friends? If you do 90% of the work at home or at work, you are an overfunctioner.

It’s important to note that, people become OF’s and UF’s because of their past experiences. Sometimes patterns of overfunctioning and underfunctioning are often learned and passed on through generations. The earlier part of your life can better explain how you behave today.

Over-functioners were are often expose to practical life responsibilities early in life. They assumed the role as part of a family system.

Under-functioners are often over-protected in early life. “…they often get a disproportionate amount of attention and resources directed their way (even if a good amount of it is negative),” says Meek.

Aim for an optimal functioning life

When we are functioning optimally, we are often not taking more than our share of responsibility, or leaving our duties for others to do.

Think of an optimally functioning person as having 100% responsibility for his/her life. This is the goal for most people in any relationship. Everyone should be playing their part in a successful relationship.

Breaking the pattern can be tough, but not impossible.

It starts with noticing this imbalance in power in your relationships with family members and others at work.

OF’s need to step back and engage UF’s when things are not getting done or when bad things happen in a relationship. This can create anxiety and stress for OF’s because they can’t stand the mess, and the long to-do list.

It will take time for both of you to get used to the new balance.

You can begin the process of creating more balance in your relationships, leaving you happier and healthier.

You can notice and make a list of where you can stop over-functioning, and start a conversation with your partner or colleague to resolve the emotional balance.

Changing the power dynamics of any relationship can be complicated.

Intimate relationships can be the hardest one to balance because we are most invested in our relationships at home, but you can redistribute responsibility for completing tasks if you first become aware of the power struggle.

Once you are aware of them, start a conversation with your partner, colleague or friend talk about your discovery. Together, sit down and set priorities.

If you consistently overstepped your boundaries or pull back from your responsibilities, you can still pursue a healthy, balanced relationship with your partner, colleagues or friends.

By Thomas Oppong

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Collection – Flushing out the money launderers with better customer risk-rating models

Advanced risk-rating models dramatically improve detection by applying machine learning and statistical analysis to better-quality data and dynamic customer profiles.

Money laundering is a serious problem for the global economy, with the sums involved variously estimated at between 2 and 5 percent of global GDP.1 Financial institutions are required by regulators to help combat money laundering and have invested billions of dollars to comply. Nevertheless, the penalties these institutions incur for compliance failure continue to rise: in 2017, fines were widely reported as having totaled $321 billion since 2008 and $42 billion in 2016 alone.2 This suggests that regulators are determined to crack down but also that criminals are becoming increasingly sophisticated.

Customer risk-rating models are one of three primary tools used by financial institutions to detect money laundering. The models deployed by most institutions today are based on an assessment of risk factors such as the customer’s occupation, salary, and the banking products used. The information is collected when an account is opened, but it is infrequently updated. These inputs, along with the weighting each is given, are used to calculate a risk-rating score. But the scores are notoriously inaccurate, not only failing to detect some high-risk customers, but often misclassifying thousands of low-risk customers as high risk. This forces institutions to review vast numbers of cases unnecessarily, which in turn drives up their costs, annoys many low-risk customers because of the extra scrutiny, and dilutes the effectiveness of anti–money laundering (AML) efforts as resources are concentrated in the wrong place.

In the past, financial institutions have hesitated to do things differently, uncertain how regulators might respond. Yet regulators around the world are now encouraging innovative approaches to combat money laundering and leading banks are responding by testing prototype versions of new processes and practices.3 Some of those leaders have adopted the approach to customer risk rating described in this article, which integrates aspects of two other important AML tools: transaction monitoring and customer screening. The approach identifies high-risk customers far more effectively than the method used by most financial institutions today, in some cases reducing the number of incorrectly labeled high-risk customers by between 25 and 50 percent. It also uses AML resources far more efficiently.

Best practice in customer risk rating

To adopt the new generation of customer risk-rating models, financial institutions are applying five best practices: they simplify the architecture of their models, improve the quality of their data, introduce statistical analysis to complement expert judgment, continuously update customer profiles while also considering customer behavior, and deploy machine learning and network science tools.

1. Simplify the model architecture

Most AML models are overly complex. The factors used to measure customer risk have evolved and multiplied in response to regulatory requirements and perceptions of customer risk but still are not comprehensive. Models often contain risk factors that fail to distinguish between high- and low-risk countries, for example. In addition, methodologies for assessing risk vary by line of business and model. Different risk factors might be used for different customer segments, and even when the same factor is used it is often in name only. Different lines of business might use different occupational risk-rating scales, for instance. All this impairs the accuracy of risk scores and raises the cost of maintaining the models. Furthermore, a web of legacy and overlapping factors can make it difficult to ensure that important rules are effectively implemented. A person exposed to political risk might slip through screening processes if different business units use different checklists, for example.

Under the new approach, leading institutions examine their AML programs holistically, first aligning all models to a consistent set of risk factors, then determining the specific inputs that are relevant for each line of business (Exhibit 1). The approach not only identifies risk more effectively but does so more efficiently, as different businesses can share the investments needed to develop tools, approaches, standards, and data pipelines.

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2. Improve data quality

Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models. Incorrect know-your-customer (KYC) information, missing information on company suppliers, and erroneous business descriptions impair the effectiveness of screening tools and needlessly raise the workload of investigation teams. In many institutions, over half the cases reviewed have been labeled high risk simply due to poor data quality.

The problem can be a hard one to solve as the source of poor data is often unclear. Any one of the systems that data passes through, including the process for collecting data, could account for identifying occupations incorrectly, for example. However, machine-learning algorithms can search exhaustively through subsegments of the data to identify where quality issues are concentrated, helping investigators identify and resolve them. Sometimes, natural-language processing (NLP) can help. One bank discovered that a great many cases were flagged as high risk and had to be reviewed because customers described themselves as a doctor or MD, when the system only recognized “physician” as an occupation. NLP algorithms were used to conduct semantic analysis and quickly fix the problem, helping to reduce the enhanced due-diligence backlog by more than 10 percent. In the longer term, however, better-quality data is the solution.

3. Complement expert judgment with statistical analysis

Financial institutions have traditionally relied on experts, as well as regulatory guidance, to identify the inputs used in risk-rating-score models and decide how to weight them. But different inputs from different experts contribute to unnecessary complexity and many bespoke rules. Moreover, because risk scores depend in large measure on the experts’ professional experience, checking their relevance or accuracy can be difficult. Statistically calibrated models tend to be simpler. And, importantly, they are more accurate, generating significantly fewer false-positive high-risk cases.

Building a statistically calibrated model might seem a difficult task given the limited amount of data available concerning actual money-laundering cases. In the United States, suspicious cases are passed to government authorities that will not confirm whether the customer has laundered money. But high-risk cases can be used to train a model instead. A file review by investigators can help label an appropriate number of cases—perhaps 1,000—as high or low risk based on their own risk assessment. This data set can then be used to calibrate the parameters in a model by using statistical techniques such as regression. It is critical that the sample reviewed by investigators contains enough high-risk cases and that the rating is peer-reviewed to mitigate any bias.

Experts still play an important role in model development, therefore. They are best qualified to identify the risk factors that a model requires as a starting point. And they can spot spurious inputs that might result from statistical analysis alone. However, statistical algorithms specify optimal weightings for each risk factor, provide a fact base for removing inputs that are not informative, and simplify the model by, for example, removing correlated model inputs.

4. Continuously update customer profiles while also considering behavior

Most customer risk-rating models today take a static view of a customer’s profile—his or her current residence or occupation, for example. However, the information in a profile can become quickly outdated: most banks rely on customers to update their own information, which they do infrequently at best. A more effective risk-rating model updates customer information continuously, flagging a change of address to a high-risk country, for example. A further issue with profiles in general is that they are of limited value unless institutions are considering a person’s behavior as well. We have found that simply knowing a customer’s occupation or the banking products they use, for example, does not necessarily add predictive value to a model. More telling is whether the customer’s transaction behavior is in line with what would be expected given a stated occupation, or how the customer uses a product.

Take checking accounts. These are regarded as a risk factor, as they are used for cash deposits. But most banking customers have a checking account. So, while product risk is an important factor to consider, so too are behavioral variables. Evidence shows that customers with deeper banking relationships tend to be lower risk, which means customers with a checking account as well as other products are less likely to be high risk. The number of in-person visits to a bank might also help determine more accurately whether a customer with a checking account posed a high risk, as would his or her transaction behavior—the number and value of cash transactions and any cross-border activity. Connecting the insights from transaction-monitoring models with customer risk-rating models can significantly improve the effectiveness of the latter.

While statistically calibrated risk-rating models perform better than manually calibrated ones, machine learning and network science can further improve performance.

5. Deploy machine learning and network science tools

While statistically calibrated risk-rating models perform better than manually calibrated ones, machine learning and network science can further improve performance.

The list of possible model inputs is long, and many on the list are highly correlated and correspond to risk in varying degrees. Machine-learning tools can analyze all this. Feature-selection algorithms that are assumption-free can review thousands of potential model inputs to help identify the most relevant features, while variable clustering can remove redundant model inputs. Predictive algorithms (decision trees and adaptive boosting, for example) can help reveal the most predictive risk factors and combined indicators of high-risk customers—perhaps those with just one product, who do not pay bills but who transfer round-figure dollar sums internationally. In addition, machine-learning approaches can build competitive benchmark models to test model accuracy, and, as mentioned above, they can help fix data-quality issues.

Network science is also emerging as a powerful tool. Here, internal and external data are combined to reveal networks that, when aligned to known high-risk typologies, can be used as model inputs. For example, a bank’s usual AML-monitoring process would not pick up connections between four or five accounts steadily accruing small, irregular deposits that are then wired to a merchant account for the purchase of an asset—a boat perhaps. The individual activity does not raise alarm bells. Different customers could simply be purchasing boats from the same merchant. Add in more data however—GPS coordinates of commonly used ATMs for instance—and the transactions start to look suspicious because of the connections between the accounts (Exhibit 2). This type of analysis could discover new, important inputs for risk-rating models. In this instance, it might be a network risk score that measures the risk of transaction structuring—that is, the regular transfer of small amounts intended to avoid transaction-monitoring thresholds.

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Although such approaches can be powerful, it is important that models remain transparent. Investigators need to understand the reasoning behind a model’s decisions and ensure it is not biased against certain groups of customers. Many institutions are experimenting with machine-based approaches combined with transparency techniques such as LIME or Shapley values that explain why the model classifies customers as high risk.

Moving ahead

Some banks have already introduced many of the five best practices. Others have further to go. We see three horizons in the maturity of customer risk-rating models and, hence, their effectiveness and efficiency (Exhibit 3).

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Most banks are currently on horizon one, using models that are manually calibrated and give a periodic snapshot of the customer’s profile. On horizon two, statistical models use customer information that is regularly updated to rate customer risk more accurately. Horizon three is more sophisticated still. To complement information from customers’ profiles, institutions use network analytics to construct a behavioral view of how money moves around their customers’ accounts. Customer risk scores are computed via machine-learning approaches utilizing transparency techniques to explain the scores and accelerate investigations. And customer data are updated continuously while external data, such as property records, are used to flag potential data-quality issues and prioritize remediation.

Financial institutions can take practical steps to start their journey toward horizon three, a process that may take anywhere from 12 to 36 months to complete (see sidebar, “The journey toward sophisticated risk-rating models”).

As the modus operandi for money launderers becomes more sophisticated and their crimes more costly, financial institutions must fight back with innovative countermeasures. Among the most effective weapons available are advanced risk-rating models. These more accurately flag suspicious actors and activities, applying machine learning and statistical analysis to better-quality data and dynamic profiles of customers and their behavior. Such models can dramatically reduce false positives and enable the concentration of resources where they will have the greatest AML effect. Financial institutions undertaking to develop these models to maturity will need to devote the time and resources needed for an effort of one to three years, depending on each institution’s starting point. However, this is a journey that most institutions and their employees will be keen to embark upon, given that it will make it harder for criminals to launder money.

By Daniel Mikkelsen, Azra Pravdic, and Bryan Richardson

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Collection – Purpose over profit: How Generation Z is redefining business

Asia’s young consumers are demanding that companies reflect their values on equality and the environment

TOKYO/KYOTO — Riho Matsumaru’s revelation came in March. While studying in London, the 21-year-old joined a student protest against the climate crisis, one of hundreds of events held simultaneously across the globe. The message of the protests resonated with her, and spurred her to try to drive action back home.

“There is a growing sense of crisis in me,” she said. “I feel anxious and frustrated about our current society. … I want Japan to be as active as the rest of the world.”

On Sept. 20, Matsumaru will join hundreds of thousands of young people in more than 100 countries in a mass “strike” for the climate, timed to coincide with a major United Nations summit in New York. The “Fridays for Future” movement is inspired by the 16-year-old Swedish student Greta Thunberg, whose weekly walkouts from school have transformed her into a global icon. The movement has spread rapidly this year, and has made its way to Asia; young people in Malaysia, India, the Philippines, Bangladesh and Japan are all set to strike this September.

Last month, a small group of young people gathered in Kyoto to prepare for a walkout in the city. Among them were Matsumaru and Yuhei Tsukamoto, a first-year master’s student at Kyoto University and coordinator for Fridays for Future Kyoto.

“Our society won’t change unless we take action,” Tsukamoto said. “There are a growing number of young people in Japan with the same spirit. We need to come together in order to organize bigger protests. Catching the public’s attention will lead to change.”

School students in New Delhi take part in a “Fridays for Future” climate protest in April.   © Reuters

Matsumaru, Tsukamoto and Thunberg herself are representative of a generation that is set to reshape the political and economic landscape worldwide. Globally connected and highly conscious of social and environmental issues, Generation Z — individuals born in the mid-1990s and the first decade of the 2000s — are coming of age into an era of rapid social, technological and environmental change.

Even more so than the millennial generation that preceded them, they are demanding greater things from their leaders and the companies that they interact with; to attract them, businesses now have to adapt and to improve, to focus on and to demonstrate that they are ethical and sustainable.

“More than any other generation that came before, Generation Z is more prepared to open their wallets for a brand that promotes causes about social impacts, such as climate, LGBTQ, racial or social justice,” said Sertac Yeltekin, chief operating officer at Singapore-based, socially focused venture capital fund Insitor Partners. “This gives them unprecedented power to shape the success or downfall of companies. They are intrinsically aware that they can drive this corporate change.”

Shaped by uncertainty

The millennial generation, born from the early 1980s to the mid-to-late 1990s, were often characterized as individualistic to the point of narcissism — children of relative plenty who came of age in an era of global economic growth. Generation Z, by contrast, have been shaped by uncertainty — political, economic and environmental. Twentieth-century models of employment have been eroded by technological change. Governments no longer seem to have the answers to economic stagnation and social tension. An impending climate catastrophe is casting a pall over their futures, and previous generations are failing to take action.

Born in 1997, Rina Usui, a fourth-year student at International Christian University in Tokyo, plans to march against climate change for the first time on Sept. 20. “It’s natural for me and my friends to think about the environment because it’s our future,” she said. “Trying to make a change and finding a solution to lessen our worries or concerns for tomorrow is common sense. … When I talk to my parents about the climate crisis, they say that experts will deal with it. That really surprises me, and makes me realize the gap between my generation and those that are older.”

This has profound implications for businesses. Through to 2030, Gen Z will make up the largest consumer segment worldwide, according to market research provider Euromonitor International. Nine hundred and sixty million of those individuals will be in Asia, and the companies that want them as employees and as customers will have to get better at being better — proving their environmental, social and governance credentials to a demographic cohort that cares, and that does its research.

“In reality, many of the companies still see ESG as a sort of fad,” said Masaya Yomaru, who studies Gen Z at Japan’s largest advertising agency, Dentsu. “The way things are going, they will need to start thinking of sustainability more as a crucial part of business. … Gen Z has an abundant amount of information, and thus have the power to choose and demand. If this group of tech-savvy young people who have a high level of literacy on social issues turn against a company, it will be very damaging.”

“If this group of tech-savvy young people who have a high level of literacy on social issues turn against a company, it will be very damaging” – Masaya Yomaru, specialist in Generation Z at Dentsu

A growing number of global companies have bowed to the needs of young consumers. Facing pressure from customers over low wages in their supply chain, this year Swedish fast-fashion house H&M Hennes & Mauritz made moves to improve transparency by launching a new website tool that lists details of their products’ suppliers and their factories. In the U.S., McDonald’s has said it will shift to using 100% cage-free eggs by 2025, and is increasing the number of vegan items on its global menus.

Those that fail to adapt can find themselves on the wrong side of fast-moving campaigns, as a “hyperconnected” generation of consumers can be quick to organize against them.

“Since they are engaged in rapid-fire banter and commentary, there is a lot of room for interpretation,” said Patrick Reichert, research fellow in social innovation at IMD Business School. “As a result, companies face huge challenges to align their brand with the attitudes and expectations of Gen Z.”

Consumer activism

The need for companies to focus on ESG goes beyond risk management, however, because younger consumers are increasingly integrating their social and environmental concerns into their buying decisions.

Ginjiro Nakayama, a fourth-year university student in Osaka, works part-time at Patagonia. The U.S. outdoor clothing company has undergone a resurgence in recent years, in no small part because of its long history of ethical and sustainable production. “I tend to think more about how my purchases affect the environment,” he said. “I don’t consume things just because it’s cheap. I only buy things that are really necessary.”

Gen Z already has substantial spending power. Research by the consultancy OC&C estimates that, in 2018, total direct spending by Gen-Z consumers was $2.4 trillion. This cohort also has a considerable ability to shape household spending. IBM research showed that 70% of Gen Zs have influence over how their family spends money.

A survey by Euromonitor found that 52% of Gen-Z consumers in Asia “try to have a positive impact on the environment through their everyday actions.” That has helped to boost the profile of companies that embody the concerns of ethical consumers.

“This is an incredibly important time for leaders to adapt their practices, strategies, and innovation to fit Gen Z as this huge new generation will soon be the fastest-growing generation in the workforce and the most important group of consumer trendsetters,” said Jason Dorsey, president of the Center for Generational Kinetics, a generational research and consulting firm.

“There is a growing sense of crisis in me,” says 21-year-old student Riho Matsumaru, center. “I feel anxious and frustrated about our current society. … I want Japan to be as active as the rest of the world.” (Photo by Ken Kobayashi)

Lush, a U.K.-based cosmetics company, has defined itself by its ethical stances on its sourcing of ingredients, on labor conditions, on animal testing and on its use of packaging. The company set up its first Asia store in Tokyo in 1999, and today operates in nearly 50 countries with around 930 stores worldwide, 180 of which are in Asia.

Famous for its colorful, heavily scented products, the company has worked to reduce the amount of packaging it uses. Around 60% of the company’s total products are now “naked,” or free of packaging and preservatives, while it also offers products, such as shampoo, in solid form and free from plastic.

Lush has also ridden a wave of opposition to the use of palm oil in consumer products, which began in Europe but has spread around the world. Large-scale cultivation of palm oil is linked to the destruction of tropical rainforests, with implications for biodiversity and the climate crisis. Last year, Lush launched an Asiawide #SOSsumatra campaign to promote its new 100% palm-oil-free shampoo bar, which aimed to spread awareness of deforestation on the Indonesian island, and to raise funds for rehabilitation of land.

At cosmetics company Lush, around 60% of products are now “naked,” or free of packaging and preservatives. (Photo by Ken Kobayashi)

The company’s stands have occasionally attracted controversy. In 2012, Lush’s support for the West Papuan independence movement put it in opposition to the government of Indonesia, which governs the region. However, its uncompromising activism has given it a loyal following among ethically-minded consumers.

“All of our initiatives and campaigns give us the opportunity to hit ground-level issues and impact real change, which is an important goal for us,” said Annabelle Baker, director of Lush Asia Limited. “We will never think we have done enough.”

Asian brands are notorious for being late to the show when it comes to sustainability, lagging behind their U.S. and European counterparts in embracing environmental, social and governance initiatives. Research by Nikkei found that among 263 global companies studied, there were only eight companies in the Asia-Pacific region that reached the top 50 of a ranking on “ROESG” scores — derived by multiplying the company’s return on equity percentage number with an ESG score; 80% of the top 100 were Western corporations.

This may be changing, particularly among those that are exposed to global markets.

Following rising criticism over the conditions of workers within the global apparel supply chain, Uniqlo parent Fast Retailing published a list of the core factories that sew its garments in 2017; this year, it revealed all of its major suppliers.

“Customers everywhere else, including Asia, are increasingly aware and knowledgeable, and interested in a sustainable future,” Yukihiro Nitta, group senior vice president and head of sustainability at Fast Retailing, said. “We are working to understand and reply to these needs.”

Traditional companies that are less visible to consumers are also making changes, aware that down the line their corporate customers will have to demand traceability and sustainability.

Fuji Oil Holdings, Japan’s largest palm oil processor, has recently begun to improve the transparency of its supply chain. Since 2016, it has laid out annual targets on improving its palm-oil sourcing, and in October last year it began operating a 60 million ringgit ($14.4 million) processing plant in Malaysia, in partnership with United Plantations, a local company, aiming to achieve full traceability of the palm oil that it buys by 2020.

Fuji Oil has also been making inroads into the emerging, but potentially enormous, market for meat alternatives. Growing awareness of the environmental cost of meat production, notably among younger consumers, is driving an increase in vegetarianism and so-called flexitarianism, where people consciously cut down on the amount of meat they consume.

In the U.S., meatless burger pioneer Beyond Meat listed on Nasdaq in May. Its stock has since surged more than 500%, giving it a market capitalization of more than $9 billion.

Fuji has invested in developing soy-based alternatives to meat and dairy products, including an imitation uni — sea urchin gonads, which are a delicacy in Japan — made from vegetable oils and soy.

“The emergence of flexitarian consumers around 2015 was a turning point and pushed us to accelerate our business on vegan products,” said Kiyohito Suzuki, executive officer at Fuji Oil. “We understand that young consumers are finding value in eco- and people-friendly products,” he added.

Japan’s Fuji Oil Holdings has begun developing imitation sea urchin, prompted by the rise of “flexitarianism” in recent years. (Photo courtesy of Fuji Oil Holdings)

Authenticity first

Gen-Z consumers are already entering the workforce; as they and the rest of their cohort start to earn, they will have a greater capacity to shape consumer markets, meaning that the trend toward ethical consumption is likely to accelerate.

To adapt, companies need to do more than simply put an ethical gloss on their existing businesses — instead, they need to fully embrace and adopt the values of the new generation.

Usui, the climate activist, said she “seeks authenticity from companies but [doesn’t] know what to believe,” especially with all kinds of information floating online. “I wish I could talk to people who are actually making the product, or something. I want a connection.”

Cleared land at an oil palm plantation in Johor, Malaysia.   © Reuters

Truly aligning with Gen Z’s values will require far deeper transformation for most companies.

Articulating and achieving a purpose, though, is difficult to do — and harder to fake. “Vision” and “mission” have become common terms at many companies, IMD’s Reichert said. “However, why a business exists is a bigger and more complex question. Purpose is not only about economic exchanges — it reflects something more aspirational. … [However], if consumers deem the purpose to be too generic, unauthentic or if a company violates its self-imposed ethical standards, the consequences come fast and hard.”

Authenticity means doing more than just throwing money at corporate social responsibility, or marketing initiatives, experts said. It means bringing social metrics into the core of the business, and cleaving strategy to values.

“The only way for companies to be in unison [with Gen-Z consumers] at this game is to become a true corporate activist — with the caveat, ‘be genuine.’ This generation’s decisions about anything is driven by values and can only be adopted by a brand that is as sincere as Gen Z is about these issues,” Insitor’s Yeltekin said. “If they detect any inauthenticity in your branding, they switch allegiance from being your company’s promoter to your company’s detractors.”

By JADA NAGUMO, Nikkei staff writer

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Landscape – Chinese science and the US–China tech war

The sharp deterioration of US–China relations raises a series of challenges for Chinese scientific development. US concerns over China’s technological progress are leading to a notable tightening of export controls and foreign investment regulations, stricter controls over visas for Chinese scientists and engineers and active investigations into the behaviour of ethnically Chinese scientists working in US universities and companies. The once flourishing bilateral relationship in science and technology — in universities, industry and government — is now clouded by growing concerns over national security and the protection of intellectual property.A robot arm is displayed at a research centre of Siasun Robot & Automation Co in Tianjin, China, 6 August 2019 (Photo: Reuters/Imagine China/File Photo).

But while pressures from the United States could inhibit progress in the short run, they could also further stimulate techno-nationalist efforts — reminiscent of the withdrawal of Soviet assistance in the early 1960s — to build more independent Chinese systems for research and innovation. Four characteristics of Chinese scientific development will condition its response to a technology war.

First, the complex interactions between China’s exposure to international science and technology and its indigenous development experiences present cultural conflicts as well as policy challenges. The international environment — especially interactions with the United States — strongly influenced the speed and direction of Chinese science and technology. While tapping into the resources of the international environment, China also put in place a series of domestic research, education and industrial policies to enhance indigenous capabilities and to facilitate the assimilation of knowledge from abroad. Although this dual-track strategy has been largely successful, underlying tensions between the ‘foreign’ and the ‘domestic’ persist and shape political and cultural orientations towards science, technology and innovation.

Second, there has long been a divide between Chinese industrial enterprises and a research system centred in universities and in the Chinese Academy of Sciences. Until recently, the enterprise sector lacked a strong research orientation and sought proven technologies from abroad instead of longer-term developmental cooperation with the domestic research system.

Despite pressure from the state to ‘serve national needs’, the research system at its best has evolved into a cosmopolitan community producing internationally recognised publications and novel technologies, but lacking a strong commitment to cooperation with domestic enterprises. The technology war is likely to reinforce recent trends towards more effective ‘research to production’ relations and, as in the 1960s, the aligning of the technical community with national strategic objectives.

Third, features of the Chinese political system strongly influence the nature of Chinese science and technology. The Chinese Communist Party (CCP) imposes the terms of state–society relationships, long favouring the use of policy preferences to support the state’s agenda. Science is seen as serving the interests of the state, with little room for more autonomous realms supporting the activities of a professional community or the growth of a private economy.

The strengthened role of the CCP in research, educational and industrial organisations under President Xi Jinping is intended to boost scientific and technological development and has been characterised by generous infusions of funds, ongoing reforms to correct systemic weaknesses and careful analyses of international trends. However, it also introduces elements of political rigidity which seem antithetical to the genuine creativity which the state now seeks to foster.

Fourth, China faces a challenge in building a world-class talent pool. China’s improved higher education system is churning out large numbers of science and engineering graduates. But many of China’s brightest seek graduate training abroad and subsequently often build distinguished careers outside of China. In order to encourage these graduates to return — especially those in fields important for national research policy — China has initiated talent programs, now targeted by the United States in the technology war. These programs have had mixed success, with many of China’s leading researchers preferring to maintain their primary professional bases in the United States while attempting to balance cosmopolitan impulses against residual patriotism. Whether US policies will drive leading talents back to China remains to be seen, as does the larger question of the future of the extensive trans-pacific ‘brain circulation’.

Chinese policymaking reflects an awareness of the problems emanating from these characteristics of the country’s development and of being a ‘latecomer’ to scientific and technological prominence. China has become a successful ‘fast follower’ in established industries and technologies, but the churn of its policy thinking has always included strategies of ‘leapfrogging’ to new technologies underlying new industries in which China could have a leadership position.

While China may suffer setbacks in some areas of the high-technology industry that rely on countries such as the United States, there will likely be a renewed policy effort to push research and technological frontiers into new areas of high value-added production. This is already evident in areas such as quantum communications and AI. These policies, combined with an ethos of science serving the interests of the state and appeals to nationalism, will consolidate trends towards the development of an identifiable ‘Chinese model’ of research and innovation.

A critical question about the future of the Chinese model is the extent to which the technology war will lead to a ‘decoupling’ from the broader international system, as some policymakers in Washington are attempting to promote.

Decoupling impulses may lead to a spilt in the way science is done in the 21st century — like driving on the right and driving on the left, as some in China now muse. Such a split challenges norms of universalism in science and does not bode well for international consensus on such critical questions as scientific integrity and ethical responses to new technologies.

Some observers argue that despite concerns about a split, this is an era characterised by the globalisation of research and innovation which makes this scenario unlikely. China is still highly dependent on access to Western technology and research environments. There is much to be said for these arguments. But they may underestimate the extent to which decoupling initiatives are already eroding trusted norms of international cooperation — norms which will not be easy to re-establish. The metaphor of driving on either the right or the left and the realities of an evolving ‘Chinese model’ need to be taken seriously for both its creative possibilities and internal contradictions.

Author: Richard P Suttmeier, University of Oregon

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Thịt heo và thương chiến

Khi những cơn gió nhè nhẹ buông kèm theo một chút se lạnh vào đầu tháng 9, ấy cũng là lúc báo hiệu mùa cốm mới đã về. Hương cốm thoang thoảng ngay đầu mùa như gợi nhớ gợi thương bao hoài niệm về những thứ truyền thống xa xưa. Cốm không chỉ là món quà truyền thống mà còn là món quà của kỷ niệm, của yêu thương gói ghém, hơn hết là để thưởng thức lại kỷ niệm ấu thơ từ “thức quả của lúa non” mang lại…

Trong [Hà Nội] “12 thương nhớ” của Vũ Bằng, vào cái độ này là “gạo mới chim ngói” với cốm là nốt cao trào của “bản nhạc tháng”, mà đi tròn cả một năm cũng chẳng có “con heo”, phải chăng hình tượng đó đã quá quen thuộc trong từng nếp sinh hoạt của người Việt nói riêng và người châu Á nói chung…?

“…Ăn một miếng cơm như thế, nó cứ lừ đi trong cuống họng, vừa thơm vừa mát mùi nhựa gạo. Nhưng chỉ ăn chơi bời một hai bữa là cùng, chớ ăn hàng ngày thì phải thổi cho ráo nước, cơm cứ tơi lên, không khô, không nát thì mới gọi là thổi khéo…” – Vũ Bằng đã nói vậy; thật nên thơ, giàu cảm xúc… Một miếng cơm như thế mà được ghém kèm với một miếng ba chỉ rim ngọt lừ của thịt tươi, thái độ dầy vừa khéo, nêm nếm vừa đủ của “bà nội trợ có tâm” kiêm bếp trưởng quyền lực trong nhà thì “ông thần khẩu” nào cũng phải chịu… nhưng qua cuộc chiến thương mại, hình ảnh đã này như nhạt nhòa qua khung cảnh tranh cướp từng miếng thịt heo ngày khai trương siêu thị Mỹ Costco ở Thượng Hải…


Với cách nhìn từ góc độ của South China Morning Post, chiến tranh thương mại Mỹ – Trung giống như một bài thử sức bền của hai nền kinh tế. Người Trung Quốc tiêu thụ 700 triệu con heo mỗi năm, chiếm 50% nhu cầu toàn cầu. Thịt heo là loại thịt rất được yêu thích và đóng một vai trò rất quan trọng tại Trung Quốc, chiếm 60% tổng lượng thịt được tiêu thụ. Chiếm một nửa tổng đàn heo trên toàn cầu và là một thực phẩm chính của người Trung Quốc, đồng nghĩa với việc khan hiếm thịt heo có thể gây bất ổn xã hội ở Trung Quốc. Theo Tổng cục Thống kê Quốc gia Trung Quốc, giá thịt tăng 18,2% so với cùng kỳ tháng 7 năm ngoái. Trong đó, giá thịt heo tăng 27%, đẩy chỉ số giá tiêu dùng nhích lên thêm 0,59%.

Tháng 8/2018, ca cúm heo châu Phi đầu tiên được xác nhận ở Trung Quốc, trùng khớp với thời điểm chính quyền Bắc Kinh dỡ bỏ lệnh cấm nhập khẩu thịt heo từ Nga. Trên mạng xã hội, nhiều người Trung Quốc suy đoán dịch bệnh bắt nguồn từ Nga và bùng lên vì Trung Quốc tăng cường nhập thịt heo Nga thay cho thịt heo Mỹ. Nhưng, Daniel Chen, một YouTuber người Trung Quốc có tiếng, cho rằng Trung Quốc có lợi thế hơn Mỹ khi cho rằng: “người Mỹ sẵn sàng bỏ phiếu loại bỏ một tổng thống khi họ phải chuyển từ ăn thịt bò sang ăn thịt heo, còn người Trung Quốc có thể chịu đựng được việc chuyển từ ăn thịt heo sang ăn rau”, ông Chen quả quyết.

Trước khi dịch cúm heo châu Phi lan rộng, Trung Quốc đã áp thuế 62% lên thịt heo nhập khẩu từ Mỹ. Tháng trước, Bắc Kinh tuyên bố ngừng mua nông sản Mỹ để trả đũa chính quyền Tổng thống Donald Trump. Nhưng trên thực tế, trước khi thuế bổ sung của ông Trump có hiệu lực ngày 1/9, Trung Quốc đẩy mạnh mua thịt heo Mỹ. Nước này nhập khẩu tới 1.861 tấn thịt heo từ ngày 16/8 đến 23/8. Tết Trung thu đến gần, giá thịt heo tại Trung Quốc tiếp tục tăng vọt. Giới chuyên gia kinh tế dự đoán giá thịt heo tại Trung Quốc sẽ còn tiếp tục tăng cho tới năm 2020.

Cũng như Việt Nam, thịt heo là thực phẩm quan trọng tại thị trường Trung Quốc, có ảnh hưởng lớn tới chỉ số lạm phát. Theo South China Morning Post, điều đáng lo ngại với nền kinh tế Trung Quốc là giá thịt heo tăng vọt lên mức kỷ lục trong vài tuần qua. Ngày 20/8, chính quyền thị trấn Phủ Điền thuộc tỉnh Phúc Kiến (Trung Quốc) thông báo trợ giá 0,56 USD cho mỗi kg thịt heo. Theo đó, người dân địa phương có căn cước hợp lệ sẽ được mua tối đa 2 cân (tương đương 1kg) thịt heo. Tuy nhiên, thay vì có tác dụng trấn an công chúng, thông báo của thị trấn Phủ Điền khiến nhiều người Trung Quốc lo ngại tình trạng giá cả leo thang và gợi nhớ lại thời kỳ tem phiếu – “phiếu bình ổn giá thịt heo” của hàng chục năm trước đây – được Đài Á Châu Tự Do (RFA) mô tả và chia sẻ ý kiến của một thị dân nơi có thực hiện chính sách này, trong đó, loại phiếu này cũng chỉ dành cho người của một số tổ chức, dân thường khó lòng có được. Với giá thịt heo trên khắp Trung Quốc Đại Lục không ngừng tăng mạnh, đã lên mức cao kỷ lục chưa từng có trong lịch sử. Kiểm soát giá thịt heo đã trở thành “nhiệm vụ chính trị quan trọng”. Gần đây Phó thủ tướng Trung Quốc Hồ Xuân Hoa cảnh báo giá thịt heo tăng chóng mặt thời gian qua có thể ảnh hưởng đến hình ảnh của đảng Cộng sản Trung Quốc và phá vỡ ổn định kinh tế nước này, do đó, việc bảo đảm nguồn cung thịt heo là “quân lệnh” của Trung ương ĐCSTQ, đồng thời nhấn mạnh rằng nếu giá thịt heo bất ổn có thể khiến bất ổn lây lan đến cả ngày kỷ niệm 70 năm ĐCSTQ xây dựng chính quyền (quốc khánh). Bên cạnh đó, Chính phủ của ĐCSTQ cũng triển khai hội nghị nhằm xây dựng chính sách liên quan, bao gồm cả việc phục hồi hoạt động nuôi heo; hủy bỏ lệnh cấm và hạn chế chăn nuôi heo; chính sách khích lệ nông dân mở rộng quy mô chăn nuôi.

Trong ngắn hạn nhằm đảm bảo hỗ trợ nhu cầu của xã hội, Bộ thương mại Trung Quốc thông báo sẽ cân nhắc bổ sung nguồn cung từ “kho lưu trữ thịt heo đông lạnh trung ương” vào thời điểm thích hợp nhằm bình ổn giá cả. Chế độ lưu trữ thịt heo được Trung Quốc khởi động vào năm 2007, song quy mô của nó là bí mật quốc gia. Trung Quốc bắt đầu dự trữ thịt heo đông lạnh từ những năm 1970. Số thịt heo “chiến lược” được coi là phương án đối phó với các trường hợp khẩn cấp và ổn định giá khi cần thiết. Ngoài thịt được giữ trong kho lạnh, chính phủ Trung Quốc cũng đang dự trữ một kho thịt sống. Trong khi chính quyền các địa phương bắt đầu phải động tới kho dự trữ của họ, kho thịt heo ở trung ương vẫn chưa có dấu hiệu suy suyển. Các chuyên gia cho rằng, kho dữ trự này sẽ chỉ được mở nếu cuộc khủng hoảng thịt heo đi tới mức đặc biệt nghiêm trọng – chúng sẽ đến tay nông dân nếu tình hình thiếu hụt trở nên trầm trọng. Lần cuối cùng Bắc Kinh khai thác nguồn cung thịt heo trong kho dự trữ trung ương là vào tháng 1 năm nay, 10.000 tấn thịt heo được bung ra thị trường ngay trước Tết.

Bộ giao thông vận tải Trung Quốc ra quyết định các xe vận tải heo và thịt heo sẽ được hưởng chính sách “làn xanh” – cho phép miễn cước lưu thông đường bộ. Tuy nhiên, không phải chỉ là vấn đề đơn giản và có thể khắc phục vừa bằng cách nhập khẩu để bù đắp trong khi nỗ lực khôi phục đàn heo, Bắc Kinh cũng đang phải đau đầu giải quyết vấn nạn “heo dịch” từ các quốc gia khác. 11/9 vừa qua, Bắc Kinh cấm nhập khẩu thịt heo từ Philippines, quốc gia đang đối đầu với dịch tả heo châu Phi. Trung Quốc cũng cấm nhập khẩu thịt heo từ Slovakia vào tháng trước vì lý do tương tự.

Do đó, với phân tích dự đoán giá thịt heo có thể tiếp tục tăng cao trong những tháng tới, đạt đỉnh 30 NDT (khoảng hơn 97 nghìn VNĐ) cho 1kg, tăng hơn 40% so với hiện tại, giá cao sẽ khiến Trung Quốc gặp nhiều áp lực hơn khi phải nhập khẩu thêm thịt heo từ thế giới. Rabobank ước tính sản lượng thịt heo ở Trung Quốc có thể sụt giảm tới 25%, và điều này đồng nghĩa Bắc Kinh sẽ phải nhập khẩu khoảng 1,5 triệu tấn thịt heo để đáp ứng nhu cầu người dân. Các nhà xuất khẩu heo trên thế giới sẽ hưởng lợi từ tình hình này. Trong tình hình căng thẳng cùng một lúc với nhiều nước như Mỹ, Canada, Úc… châu Âu sẽ là khu vực nhận được nhiều lợi ích về thương mại nhất; khối lượng thịt heo nhập khẩu châu Âu tại Trung Quốc đã tăng 54% trong nửa đầu năm 2019. Hầu hết số thịt này tới từ Tây Ban Nha, Đức, Đan Mạch, Hà Lan và Pháp.

Nói như thế không có nghĩa Trung Quốc hoàn toàn dựa vào các nước Châu Âu, trước hết phải nói tới những nước hàng xóm có nét văn hóa nói chung và ẩm thực nói riêng như Việt Nam sẽ là những nơi được nghĩ tới đầu tiên và bởi vậy sẽ phần nào chịu ảnh hưởng đầu tiên.

Thực tế cho thấy, nhiều thương lái đang tiếp tục thu mua heo hơi xuất đi Trung Quốc với mức lãi cả triệu đồng mỗi con dù nguồn cung trong nước dự báo thiếu hụt. Việt nam đã tiêu hủy khoảng 4,4 triệu con heo, thiệt hại hàng nghìn tỷ đồng sau vỏn vẹn 7 tháng kể từ khi phát hiện trường hợp nhiễm dịch đầu tiên cho tới nay vùng dịch đã lan ra 63 tỉnh thành trên cả nước. Thậm chí, nhiều hộ vẫn chưa dám tái đàn vì lo tiềm ẩn rủi ro bệnh dịch tả heo châu phi có khả năng bùng phát trở lại; do đó, Cục chế biến và Phát triển thị trường nông sản đã nhận định giá heo hơi tăng mạnh tại các địa phương do nguồn cung khan hiếm cục bộ trong tháng 8/2019, đồng thời dự báo giá thịt heo có xu hướng tăng trong những tháng cuối năm, đặc biệt là vào dịp Tết Nguyên đán do nguồn cung giảm, thị trường Trung Quốc tiếp tục khan hàng.

Giá heo Trung Quốc cao so với Việt Nam, trong khi cầu lại tăng do nước này hủy mua hàng từ Mỹ nên hàng Việt nếu đạt chất lượng vẫn qua được đường tiểu ngạch“, theo một thương lái miền Nam, và cũng là thể hiện xu hướng chung khi ngày một nhiều hơn các đầu mối hỏi nguồn heo cung ứng để xuất đi Trung Quốc, tuy nhiên, các thương lái [tại Long An] cho biết không có hàng để bán vì nguồn cung tại một số tỉnh ở miền Nam đang giảm mạnh; đặc biệt tại Đồng Nai – thủ phủ ngành chăn nuôi heo, Hiệp hội chăn nuôi Đồng nai xác nhận, dù nguồn cung giảm do dịch tả heo châu Phi, vẫn có hiện tượng thương lái Việt gom hàng miền Nam ra Bắc và đi Trung Quốc vì chênh lệnh giá quá cao.

Trong bối cảnh căng thẳng như vậy, để ổn định an sinh xã hội, Bộ Thương mại Trung Quốc xác nhận đã cho phép các doanh nghiệp nước này xúc tiến việc mua trở lại nông sản Mỹ, đồng thời kêu gọi Washington có các động thái thiện chí tương tự trước giờ đàm phán và bắt đầu yêu cầu phía Mỹ báo giá một số mặt hàng nông sản, nhờ vậy, các dấu hiệu hạ nhiệt căng thẳng thương chiến giữa Mỹ và Trung Quốc đã bắt đầu thể hiện rõ hơn.

Trước đó, Trung Quốc cũng thông báo sẽ dỡ bỏ thuế 1 năm với 16 mặt hàng nhập khẩu từ Mỹ, bao gồm 4 loại nông sản cần thiết cho nhu cầu hằng ngày của người dân và ngành chăn nuôi cùng một số loại thuốc chữa ung thư. Động thái này của Trung Quốc đã nhận được sự hoan nghênh của Tổng thống Mỹ Donald Trump: “…thể theo đề nghị của Phó thủ tướng Trung Quốc Lưu Hạc và thực tế là họ sắp sửa tổ chức kỷ niệm 70 năm quốc khánh vào ngày 1-10, tôi đã quyết định sẽ dời việc tăng thuế quan lên 250 tỉ USD hàng Trung Quốc (từ 25% lên 30%) từ mốc ban đầu là ngày 1-10 sang mốc mới là 15-10“, Tổng thống Donald Trump đã viết trên Twitter cá nhân vào sáng 12-9 theo giờ VN.

Tuy nhiên, trong một cuộc thăm dò của Harvard CAPS/Harris cho thấy 63% cử tri cho rằng thuế đánh vào hàng Trung Quốc sẽ gây thiệt hại cho Mỹ nhiều hơn Trung Quốc. 74% cử tri nói người tiêu dùng Mỹ đang chịu hầu hết gánh nặng thuế quan, nhưng hơn cả là 2/3 cử tri –  cụ thể 67%, muốn nước Mỹ cứng rắn với Bắc Kinh trong chính sách thương mại, dù cho rằng họ đang bị thiệt nhiều hơn Trung Quốc. Do đó, “Tổng thống Trump có sự ủng hộ mạnh mẽ của công chúng Mỹ khi theo đuổi chính sách cứng rắn với Trung Quốc”, Mark Penn, Giám đốc của công ty Harvard CAPS/Harris Poll, trả lời phỏng vấn với tờ The Hill. “Cử tri Mỹ biết rằng thuế quan tác động tiêu cực đến việc làm và giá cả, nhưng vẫn tin đây là cuộc chiến đúng đắn”.

Tổng thống Trump đã từng nói đàm phán sẽ “KHÓ KHĂN HƠN NHIỀU” đối với Trung Quốc nếu ông tái đắc cử vào năm 2020, cho thấy căng thẳng thương mại sẽ không dịu đi trong tương lai gần; đa số cử tri cho rằng đàm phán sẽ còn kéo dài tới sau cuộc bầu cử tháng 11/2020. 53% không cho rằng ông Trump có thể ký một thỏa thuận trước ngày bầu cử.

Như vậy, với những khó khăn trong nước, việc phá giá đồng Nhân dân tệ của Trung Quốc cũng dường như không thay đổi gì nhiều khi kinh tế đang bị đánh giá là đã đi qua chu kỳ tăng trưởng, các tác động từ chiến tranh thương mại với việc ra đi của nhiều nhà đầu tư trong làn sóng di dời để tranh thuế quan dường như làm trầm trọng hơn các vấn đề. Chương trình “một vành đai một con đường” không còn tạo ra nhiều ảnh hưởng địa chính trị như khi mới được khởi động – khi Trung Quốc còn đang dồi dào tiềm lực tài chính và dự trữ.

Nói như vậy, không có nghĩa là Trung Quốc hoàn toàn là yếu thế hay đã đầu hàng để tiến tới một cuộc dàn xếp thương mại. Báo South China Morning Post bình luận vụ người tiêu dùng Trung Quốc chen chúc mua thịt giảm giá trong ngày khai trương siêu thị Mỹ Costco ở Thượng Hải dẫn tới nhiều câu hỏi lớn khi phải đóng cửa sớm vì “lý do an ninh”, sau khi hàng nghìn khách mua hàng chen lấn, tranh giành các món hàng giảm giá như rượu Mao Đài, bánh sừng bò và thịt heo – thực phẩm có ảnh hưởng lớn tới chỉ số lạm phát. Cũng theo South China Morning Post, điều đáng lo ngại với nền kinh tế Trung Quốc là giá thịt heo tăng vọt lên mức kỷ lục, trong khi đó, Tết Nguyên Đán đến gần, giá thịt heo tại Trung Quốc vẫn tiếp tục tăng vọt. Giới chuyên gia kinh tế dự đoán giá thịt heo tại Trung Quốc sẽ còn tiếp tục tăng cho tới năm 2020, đồng nghĩa với việc lạm phát sẽ tăng lên, gánh nặng đè lên vai người tiêu dùng sẽ lớn hơn.


các quan chức Bộ Thương mại Trung Quốc vẫn khẳng định nền kinh tế nước này sẽ càng mạnh mẽ hơn sau khi vượt qua chiến tranh thương mại. Tuy nhiên,

chỉ có thời gian mới có thể kiểm chứng điều đó…

Xxx – npl

Deals – Vietnam’s social media crowd swells with new firms to take on Facebook, Google

A new social network has entered the already crowded field in Vietnam as the communist party squeezes U.S. tech giants Facebook and Google with a new cybersecurity law.

Lotus, a social network that allows users to create content and share posts to a home page, had received 700 billion dong ($30.14 million) in funding from tech corporation VCCorp and hoped to raise another 500 billion dong, company General Director Nguyen The Tan said at the launch ceremony.

“Lotus was born not to compete with Facebook or any other social networks,” Tan said late on Monday. “We will focus on content and content creation.”

Information Minister Nguyen Manh Hung, who was at the launch, has urged Vietnamese companies to create viable domestic alternatives to foreign social media platforms which are more difficult for the government to control.

Last month, a Facebook-style app, Gapo, also made its debut. Older domestic social platforms such as VietnamTa and Hahalolo have struggled to build large user bases.

Hung said he hoped that eventually the number of Vietnamese people using domestic social networks would be as high as the number using foreign platforms.

There were 58 million Facebook users and 62 million Google accounts in Vietnam as of August, government data showed.

There are no comparable figures for domestic networks. Despite economic liberalisation and increasing openness to social change since the 1990s, the ruling Communist Party retains tight media censorship and does not tolerate dissent.

Several activists and dissidents have been arrested or jailed for posting online content considered to be “anti-state”.

Vietnam has tightened internet rules over the past few years, culminating in a cybersecurity law which came into effect in January requiring foreign companies like Facebook to set up local offices and store data in the country.

By Reuters

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