The research exploits a natural experiment embedded in Türkiye’s pandemic response. After the country confirmed its first COVID-19 case on 11 March 2020, the government suspended university and secondary education, closed shopping malls, cafes, and entertainment venues, restricted restaurants to takeaway service, imposed travel limits on air and public road transport, and eventually introduced curfews across all provinces. Crucially, these measures targeted specific sectors—transport and storage, accommodation and food services, real estate, and professional, scientific, and technical activities—while leaving manufacturing, mining, construction, trade, information technology, finance, and other industries formally untouched. That sector-specific pattern allowed the authors to designate four restricted sectors as a treatment group and compare their trajectories against a set of unaffected comparison sectors, before and after the restrictions took effect.

The method at the heart of the study is difference-in-differences, a workhorse of empirical economics. The logic is straightforward: if the treated and control sectors were moving along similar paths before the pandemic, then any divergence afterward can plausibly be attributed to the treatment—in this case, the restrictive measures. The authors estimated models with sector fixed effects, which absorb all time-invariant characteristics of each industry, and month fixed effects, which soak up macroeconomic shocks hitting every sector simultaneously. The coefficient of interest, an interaction between sectoral treatment status and the post-March 2020 period, captures the differential change in outcomes experienced by restricted sectors relative to everyone else. Standard errors were clustered at the sector level, and the parallel-trends assumption was tested formally using pre-treatment data.

The data came from two of Türkiye’s official statistical institutions. Monthly job vacancies and job placements were drawn from administrative records of the Turkish Employment Agency, known as ISKUR, covering seventeen sectors from March 2019 to March 2021. Productivity was harder to pin down at the monthly frequency, so the authors constructed a novel proxy: the consumer-price-index-adjusted turnover index published by TURKSTAT, divided by the number of paid employees in each sector. This revenue-based measure, covering ten sectors over thirty-four months from September 2018 to June 2021, captures short-run changes in real revenue per worker rather than fully adjusted labor productivity—a distinction the authors are careful to emphasize, since turnover and value added can diverge, and the measure ignores capital intensity.

The headline result is striking for its restraint. Across the full sample, the difference-in-differences estimates show no statistically significant association between the restrictive measures and job vacancies, job placements, or the revenue-based productivity proxy. In other words, once common pandemic dynamics were accounted for, sectors that were formally restricted did not fare measurably worse than sectors that were not. The descriptive data do reveal two distinct phases: a temporary dip in logged job vacancies during the initial wave, and a more prolonged but ultimately modest association between restrictions and job placements, with the larger magnitude appearing in the second wave beginning in November 2020. But the aggregate regressions point to a consistent conclusion—the immediate labor market contraction looks more like the footprint of the pandemic itself than of the policy curbs.

The picture becomes more textured when the authors split the economy by formality. Using sectoral informality estimates from earlier research, they classified mining, water supply, construction, wholesale and retail trade, accommodation and food services, and administrative services as high-informality sectors. In these subsamples, the point estimates told a story of vulnerability: job vacancies, placements, and productivity all appeared to decline more sharply in restricted informal sectors, while formal sectors showed relative resilience, with even a marginally positive association between restrictions and job vacancies in the preferred specification. The interpretation is intuitive. Informal firms rely on cash flows, face-to-face interaction, and short-term labor arrangements, leaving little room for remote work or organizational restructuring. Formal firms, by contrast, could pivot to digital tools and telework.

Yet the authors subject their own findings to a demanding robustness check, and the results temper the narrative. With so few sector clusters—as few as four in some specifications, and only a single treated sector in the informal subsamples—conventional cluster-robust standard errors can understate uncertainty. Applying a wild-cluster bootstrap procedure, the study finds that every informal-sector estimate that appeared significant under conventional inference loses statistical significance, with bootstrap p-values ranging from 0.17 to 0.20. The formal-sector job vacancy estimate weakens from conventional significance to a marginal bootstrap p-value of 0.073. Parallel-trends diagnostics also fail for informal-sector job vacancies under both the seasonally adjusted and unadjusted specifications. The authors are transparent about this: the informal-sector heterogeneity is a descriptive pattern warranting further investigation, not definitive statistical evidence.

The methodological care extends to the vacancy data themselves. The authors discovered that seasonal adjustment of short administrative series during an unprecedented structural break can distort inference, potentially misinterpreting shock-driven variation as seasonal movement. They therefore report two specifications for job vacancies—one seasonally adjusted, one raw—and place greater weight on the unadjusted model, which lets the sector and time fixed effects absorb temporal variation without the risk of adjustment artifacts. This kind of methodological self-scrutiny is rare and valuable, particularly in a literature where pandemic-era data are short, noisy, and prone to structural breaks that standard statistical machinery was never designed to handle.

The findings align with a growing international consensus. Research on South Korea, where lockdowns were minimal, documented job destruction comparable to that in the United States and the United Kingdom, suggesting that fear of contagion and voluntary distancing drive much of the economic damage. Real-time tracking studies in the United States similarly found that spending and employment collapsed before or regardless of formal orders. Türkiye’s sector-level evidence adds an emerging-market dimension to this picture, indicating that even in an economy with substantial informality, the aggregate labor market response was shaped more by the pandemic shock than by the regulatory response to it.

The policy implications are sobering. If restrictions themselves were not the primary driver of labor market damage, then lifting them quickly is not a reliable route to economic recovery—and imposing them need not be economically catastrophic if paired with the right support. But the suggestive evidence of informal-sector fragility points to where policy should focus: targeted income support for informal workers and micro-enterprises during closures, and investments in digital and operational resilience that would help the most exposed firms weather future shocks. As the authors conclude, uniform containment measures can generate uneven consequences across sectors with different levels of formality, and economies like Türkiye—where informality and structural dualism remain prevalent—need crisis-response tools calibrated to that heterogeneity. In a world preparing for the next pandemic, that may be the study’s most enduring lesson.

Subject of Research: The impact of COVID-19 restrictive measures on the labor market and productivity in Türkiye

Article Title: Impact of COVID-19 restrictive measures on labor market and productivity in Türkiye

Article References: Dolu, A., & İkizler, H. (2026). Impact of COVID-19 restrictive measures on labor market and productivity in Türkiye. Heliyon, 12(15), Article e45535. https://doi.org/10.1016/j.heliyon.2026.e45535

Image Credits: AI Generated

DOI: 10.1016/j.heliyon.2026.e45535

Keywords: COVID-19, labor market, Türkiye, difference-in-differences, job vacancies, job placements, labor productivity, informal economy, lockdowns, emerging markets, econometrics, public policy

The study, conducted by Mohammed Ahmed Yousef Al-Qadhi and Syed Zamin Shah of Xidian University in China, tackles a question that has long divided corporate finance scholars. Does pursuing sustainability drain a company’s cash, or does it build financial resilience? The theoretical case cuts both ways. On one side, green investments—developing eco-friendly products, overhauling production processes, filing environmental patents—demand upfront spending that firms often finance from internal funds, directly depleting cash buffers. On the other side, stricter environmental regulation can raise compliance costs and uncertainty, pushing firms to hoard more cash as a precaution. The new evidence comes down firmly on the first side: across all three measures of environmental improvement the researchers examined, greener firms held systematically lower liquidity.

The researchers measured corporate liquidity using the financial liquidity ratio—the proportion of cash and cash equivalents relative to current liabilities—a standard gauge of a firm’s ability to meet short-term obligations with immediately available resources. Environmental improvement was captured through three related but distinct indicators. Environmental product innovation, or EPI, tracks product-level efforts to develop goods and services with reduced ecological impact. Sustainable environmental progress, or SEP, reflects broader operational improvements in environmental practices. Environmental improvement patent filings, or EPR, count formally protected innovation outputs. Separating these dimensions matters, the authors argue, because they represent different stages of the sustainability journey: product redesign, process-level progress, and codified technological achievement.

The econometric machinery behind the findings is deliberately robust. Because cash-holding decisions tend to persist over time—firms that hold cash this year usually hold cash next year—the researchers employed a two-step system Generalized Method of Moments estimator, a technique designed for dynamic panels where the number of firms is large relative to the number of years. This approach uses lagged values of the variables as internal instruments to mitigate endogeneity problems arising from reverse causality, omitted variables, and the persistence of liquidity policy. The initial sample comprised 1,953 non-financial BRICS firms; after removing observations with missing values and applying a 1 percent winsorization to tame extreme outliers, the final estimation sample included 1,053 firms. Firm-level data came from Thomson Reuters DataStream, while macroeconomic variables were drawn from the World Development Indicators.

The results were statistically significant across all three environmental indicators: each was negatively associated with financial liquidity, supporting the study’s three hypotheses. The pattern held in complementary fixed-effects estimates and in sub-period tests splitting the sample before and after the COVID-19 pandemic, although the strength of the relationship varied by indicator and period. Environmental product innovation and patent filings remained negative in both pre- and post-pandemic windows, while broader sustainable environmental progress weakened somewhat after the pandemic struck—a hint that the liquidity consequences of sustainability may depend on the type of environmental activity and prevailing economic conditions.

What does a negative association between greenness and cash actually mean? The authors are careful to stress that it does not automatically signal financial weakness. Under the trade-off theory of cash holdings, which anchors the study’s theoretical framework, firms balance the benefits of liquidity—precautionary protection, transaction convenience, financing flexibility—against the costs of letting capital sit idle. Firms engaged in environmental improvement may simply be deploying internal funds that would otherwise remain as reserves, financing cleaner technologies and greener products from their own pockets. Alternatively, successful sustainability efforts may reduce the need for large precautionary balances altogether: greener operations can lower costs, cut environmental risk, strengthen reputation, and ease access to external finance, all of which diminish the insurance value of holding cash.

The control variables in the analysis reinforce this interpretation. Firms with more tangible assets, larger scale, greater loan financing, and access to developed banking sectors all held less liquidity—consistent with the idea that collateral and external financing options reduce the pressure to stockpile cash. Intriguingly, inflation showed the opposite sign: firms in countries with higher price instability held more cash, suggesting that macroeconomic uncertainty amplifies precautionary liquidity demand. This contrast is telling. When firms voluntarily reduce cash in response to sustainability commitments, the behavior looks like strategic allocation rather than distress; when they increase cash in response to inflation, the behavior looks like classic precautionary saving.

The BRICS setting is central to the study’s significance. These economies combine rapid growth, expanding capital markets, and severe environmental challenges, yet they differ substantially in institutional quality, financial development, environmental regulation, and sustainability reporting practices. Firms there often face stronger financial constraints than their developed-market counterparts, making internal funds disproportionately important—a logic that echoes the pecking-order theory of corporate finance, in which firms prefer internal financing over debt and equity when information asymmetries are high. In such environments, the decision to spend cash on green innovation is a genuine trade-off, not a routine line item. The authors caution, however, that the findings should be generalized carefully, both across the heterogeneous BRICS bloc and to other emerging or developed economies.

The study is candid about its limitations. The available data restricted the set of control variables—profitability, growth opportunities, dividend policy, ownership structure, and governance characteristics, all staples of the cash-holdings literature, could not be included consistently. Cross-sectional dependence tests rejected the assumption of independence across firms, meaning the fixed-effects estimates serve only as complementary checks. The authors note that future validation using Driscoll-Kraay standard errors, feasible generalized least squares, and method-of-moments quantile regression, along with alternative liquidity measures and standardized sustainability variables, would strengthen the evidence base. Internal GMM instruments reduce but cannot fully eliminate endogeneity concerns, so the results are best read as dynamic panel associations rather than definitive proof of causality.

Even with those caveats, the implications are striking. For corporate managers, the message is that sustainability planning and liquidity management cannot live in separate silos: green investments should be timed and financed so they do not create avoidable short-term financial pressure. For investors, lower cash reserves at environmentally active firms may reflect strategic deployment of capital rather than lax financial discipline—a distinction that could change how sustainability-oriented portfolios are screened. For policymakers in emerging economies, the findings argue for expanding access to green finance, offering incentives for environmental innovation, and strengthening disclosure standards, so that firms are not forced to choose between ecological responsibility and financial flexibility. As climate pressures intensify and capital markets increasingly price environmental performance, the study suggests that the green transition is already rewriting the quiet arithmetic of corporate cash—one patent, one cleaner product, one efficiency gain at a time.

Subject of Research: The relationship between environmentally sustainable improvements and corporate liquidity in BRICS emerging-market firms

Article Title: Economic Consequences of Environmentally Sustainable Improvements for Corporate Liquidity in Emerging Markets

Article References: Al-Qadhi, M. A. Y., Al-Qadhi, M. A. Y., & Shah, S. Z. (2026). Economic Consequences of Environmentally Sustainable Improvements for Corporate Liquidity in Emerging Markets. Discover Global Society, 4(1), Article 219. https://doi.org/10.1007/s44282-026-00590-5

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00590-5

Keywords: corporate liquidity, cash holdings, green innovation, BRICS, sustainability, environmental patents, system GMM, emerging markets, trade-off theory, corporate finance, COVID-19, green finance

The research, led by Tuyen Kim Thi Dinh and Minh Pham of Ho Chi Minh City Open University together with colleagues from the university’s School of Advanced Study, set out to fill a persistent gap in the literature. Previous studies of livestream commerce had examined individual factors that drive purchase intention, but they paid limited attention to the integrated psychological process by which cognitive evaluations transform into emotional responses and, ultimately, behavioral intentions. To capture that process, the team turned to a classic theoretical structure from environmental and consumer psychology: the Cognition-Affect-Behavior framework, often abbreviated as CAB.

The CAB framework rests on a deceptively simple idea. When people encounter an environment, whether a physical store or a digital space, they first form cognitive appraisals of it, then generate affective or emotional reactions, and finally produce behavioral responses such as approaching, staying, or buying. Applied to livestream commerce, the cognitive layer includes how useful viewers perceive the platform to be, how easy they find it to use, and how strongly they feel transported into the scene, a sensation researchers call perceived telepresence. The affective layer is captured by perceived enjoyment, the pleasure viewers derive simply from watching. The behavioral layer is purchase intention, the self-reported likelihood of buying through the livestream.

To test this model, the researchers surveyed 489 Vietnamese consumers who had watched livestreams and intended to purchase through them. The sample skewed female, was concentrated in Southern Vietnam, and was highly educated, a demographic profile that mirrors the core audience of livestream selling platforms in the region. The team then applied structural equation modeling, a statistical technique that allows researchers to test networks of hypothesized relationships simultaneously, estimating both direct paths between variables and indirect pathways that run through mediating constructs. This approach is particularly well suited to frameworks like CAB, where the theoretical interest lies not just in whether individual factors matter but in how they chain together.

The results were striking in their clarity. Three factors emerged as direct, statistically significant drivers of purchase intention: perceived telepresence, perceived enjoyment, and perceived ease of use. In other words, viewers who felt present in the livestream environment, who found the experience fun, and who found the technology effortless were all more likely to say they would buy. Telepresence deserves particular emphasis. In a livestream, the sensation of being there, watching a host demonstrate a product, answer questions, and respond to comments in real time, appears to do psychological work that static product pages cannot replicate. The study’s authors argue that their findings clarify the role of perceived telepresence in this context, positioning it as a central cognitive ingredient of the livestream experience rather than a peripheral novelty.

Perceived usefulness told a subtler story. It did not exert a direct, statistically meaningful effect on purchase intention on its own. Instead, its influence ran through enjoyment: viewers who found the livestream useful became more engaged and entertained, and that heightened enjoyment in turn lifted their intention to buy. This mediated pathway is a technically important finding because it suggests that usefulness in livestream commerce is not consumed coldly, as a rational calculation of value, but is converted into emotional currency before it shapes behavior. A host who provides genuinely informative product demonstrations does not merely inform the audience; the information makes the show more enjoyable, and the enjoyment sells the product.

Perhaps the most intriguing result concerned expectation confirmation, the degree to which the experience matches what viewers anticipated. Rather than acting as a direct driver, expectation confirmation operated as a moderator, specifically of the relationship between perceived ease of use and purchase intention. In practical terms, this means that the payoff of a smooth, frictionless viewing experience depends on whether the livestream lives up to expectations. When expectations are confirmed, ease of use translates more powerfully into purchase intention; when they are not, even a technically seamless experience may fail to convert viewers into buyers. This moderating role had not been clearly established in prior livestream research, and the authors highlight it as a key contribution of the study.

Methodologically, the research was conducted with careful attention to ethical standards. The study was approved by the Institutional Review Board of Ho Chi Minh City Open University, with approval number 1644/QD-DHM issued on August 4, 2025, and all participants were informed about the purpose and procedures of the study and provided informed consent before taking part. The authors declare no competing interests, and the article is published open access under a Creative Commons license, making the full technical detail of the model available to researchers and practitioners worldwide.

The theoretical significance of the work lies in its extension of the CAB framework into livestream commerce, a domain the framework had rarely been applied to in integrated form. By demonstrating that cognitive appraisals feed emotional responses which then drive behavioral intentions, and by specifying where moderators like expectation confirmation intervene, the study offers a coherent psychological architecture for understanding digital consumer decision-making. It also situates that architecture in an emerging market context, where livestream commerce is growing rapidly and where most existing theory, built largely on Western e-commerce data, has been untested. The Vietnamese sample, dominated by young, educated, female consumers in the country’s south, provides a valuable data point for a global literature that has often overlooked such markets.

The practical implications are equally concrete. For platform designers, the primacy of telepresence and enjoyment suggests that investment should flow toward features that deepen immersion and delight, such as high-quality video, interactive overlays, responsive comment systems, and charismatic host training, rather than toward interface complexity. For sellers and hosts, the mediated role of usefulness implies that informative content is not optional; it is the raw material from which enjoyment is built. And for marketers, the moderating effect of expectation confirmation delivers a cautionary lesson: overpromising in promotional material can backfire, because unmet expectations blunt the conversion power of an otherwise effortless experience. As livestream commerce expands across emerging online markets, the study suggests that the platforms that thrive will be those that understand a simple psychological truth, that people do not buy from streams they merely watch, but from streams that make them feel present, capable, and genuinely entertained.

Subject of Research: Consumer psychology of purchase intention in livestream commerce using the Cognition-Affect-Behavior framework

Article Title: Understanding purchase intention in livestream commerce through the Cognition-Affect-Behavior framework

Article References: Dinh, T. K. T., Doan, B. T. T., Tran, T. B. N., Vo, L. T. N., Pham, D. N., Dinh, T. M. N., & Pham, M. (2026). Understanding purchase intention in livestream commerce through the Cognition-Affect-Behavior framework. Discover Psychology. https://doi.org/10.1007/s44202-026-00911-4

Image Credits: AI Generated

DOI: 10.1007/s44202-026-00911-4

Keywords: livestream commerce, purchase intention, Cognition-Affect-Behavior framework, perceived telepresence, perceived enjoyment, perceived ease of use, expectation confirmation, structural equation modeling, consumer behavior, Vietnam, emerging markets, cyberpsychology

The research, conducted by Bui Huy Khoi of the Industrial University of Ho Chi Minh City in Vietnam, set out to disentangle the psychological machinery that connects sustainability perceptions to buying decisions in the cosmetics sector. Rather than asking consumers directly whether they intend to buy green products, the study built a structural model in which four sustainability-related factors, green attitude, green subjective norms, perceived behavioural control and green advertising, were tested for their influence on brand trust, which in turn was tested as a driver of purchase intention. The design reflects a growing recognition in consumer psychology that intentions are rarely shaped by attitudes alone; they are mediated by layers of belief, social context and confidence in the seller.

Methodologically, the study took a mixed-methods approach. In the first, qualitative phase, the researcher refined and contextualised the measurement scales, ensuring that the survey instruments captured what green attitude, social pressure, control and advertising genuinely mean to cosmetics consumers in an emerging market rather than importing constructs wholesale from Western literature. In the second, quantitative phase, survey data were analysed using partial least squares structural equation modelling, or PLS-SEM, a statistical technique well suited to testing networks of hypothesised relationships between latent psychological variables. PLS-SEM estimates how strongly each construct predicts the next, allowing the researcher to quantify both direct effects and the indirect, mediated pathways that run through brand trust.

The results are striking in their asymmetry. Three of the four sustainability factors, green attitude, perceived behavioural control and green advertising, exerted a significant positive impact on brand trust. In plain terms, consumers who hold favourable dispositions toward environmentally friendly products, who feel capable of actually choosing and using green cosmetics, and who are exposed to credible green advertising, come to trust the brands behind those products. That trust then carries the weight: brand trust mediated the relationship between all three of these factors and purchase intention, acting as the bridge between what consumers believe about sustainability and what they decide to buy.

The fourth factor, however, refused to cooperate. Green subjective norms, the perceived social pressure from family, friends and reference groups to buy sustainable products, showed no statistically significant influence within the model. This null result is arguably the most provocative finding in the paper. Much of the classical literature on pro-environmental behaviour, rooted in the theory of planned behaviour, treats subjective norms as a core pillar of intention formation. The study’s finding suggests that, at least among the young, digitally engaged consumers surveyed in this emerging-market setting, the decision to buy green cosmetics is not primarily a social conformity play. People are not buying sustainable lipstick because their friends approve; they are buying it because they trust the brand and feel personally able to make the choice.

Why would social norms fail while personal attitudes and perceived control succeed? One plausible reading, consistent with the study’s framing, is that cosmetics are a highly personal, identity-laden product category. Choices about skin, scent and appearance are made at the level of the individual mirror, not the dinner table. In a digital-first consumer environment, information about a brand’s environmental credentials arrives through advertising and online content rather than through face-to-face social endorsement, which may weaken the channel through which subjective norms traditionally operate. The author is careful to caution, however, that this pattern should not be interpreted as broadly generalizable across consumer segments or markets; norms may matter far more in other cultures, age groups or product categories.

The mediation finding deserves particular attention because it reframes how sustainability marketing works. If green attitudes and green advertising influenced purchase intention directly, the managerial prescription would be simple: make consumers feel positive and keep advertising. But the model shows that these factors work on intention largely through trust. Sustainability perceptions are, in effect, an input into a trust-building process, and trust is the currency that gets spent at the checkout. This has a sobering implication for an industry plagued by greenwashing accusations. When a brand’s environmental claims are perceived as exaggerated or false, the damage is not confined to the credibility of the claim itself; it corrodes the very mechanism through which all sustainability messaging converts into sales.

For managers, the study’s practical message is pointed. In this specific context, building trust through credible green communication and enhancing consumers’ perceived behavioural control may be more effective than relying on social influence mechanisms. Credible communication means verifiable claims, transparency about ingredients and sourcing, and advertising that can withstand scrutiny rather than vague eco-imagery. Enhancing perceived control means lowering the practical barriers to green choices: clear labelling, accessible price points, easy availability and product performance that matches conventional alternatives. A consumer who believes a green cosmetic will work, can find it easily and can afford it is a consumer positioned to trust the brand behind it, and trust is what converts belief into a purchase.

The study also contributes to a broader scholarly conversation about emerging markets. Much of the sustainability marketing literature has been built on data from Europe, North America and developed East Asia, where environmental awareness has had decades to mature. Emerging markets present a different landscape: rapidly growing middle classes, younger demographics, high digital engagement and environmental concerns that often arrive alongside, rather than after, mass consumption. Understanding how green perceptions function in such settings matters not only for the cosmetics industry but for any sector betting that the next generation of consumers will pay for sustainability. The finding that trust, not social pressure, is the pivotal variable offers a testable hypothesis for researchers working in other emerging-market contexts.

There are, of course, limits to what any single survey-based model can establish. Structural equation modelling identifies associations consistent with a theoretical pathway; it cannot prove causation in the experimental sense, and the study’s own author flags that the limited role of subjective norms in this sample should not be over-read. The sample’s composition, young and digitally engaged consumers, means the findings may not extend to older shoppers or to markets where green consumption follows different social dynamics. Still, the study’s contribution is clear and well-earned: it clarifies the relative importance of selected green factors in shaping brand trust and, indirectly, purchase intention, and it elevates trust from a vague buzzword to a measurable, mediating mechanism. In an industry where green claims multiply faster than the evidence behind them, that is a finding worth trusting.

Subject of Research: The effect of sustainability perceptions and brand trust on purchase intention for green cosmetics

Article Title: Sustainability, brand trust, and purchase intent in the cosmetics industry

Article References: Khoi, B. H. (2026). Sustainability, brand trust, and purchase intent in the cosmetics industry. Discover Sustainability. https://doi.org/10.1007/s43621-026-04845-8

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04845-8

Keywords: sustainability marketing, brand trust, purchase intention, green advertising, green attitude, perceived behavioural control, subjective norms, cosmetics industry, PLS-SEM, consumer behaviour, greenwashing, emerging markets

Tunneling occurs when controlling shareholders exploit their positional advantage to divert assets, profits or business opportunities away from minority investors. Common manifestations include related-party transactions priced to favor the controlling owner, loans and advances extended to affiliates that are never repaid on commercial terms, guarantees issued for the private benefit of connected parties, and outright misappropriation of funds. Because controlling shareholders typically hold voting power disproportionate to their cash-flow rights, the private gains from tunneling can exceed their share of the losses inflicted on the firm, making the practice rational for the dominant owner even as it destroys value for everyone else.

The study measures tunneling primarily through the net level of other receivables that controlling shareholders and their related parties owe to the listed firm, a widely used proxy in Chinese empirical research because misappropriated funds often sit on the balance sheet in this form. The authors construct this measure from firms’ annual reports and combine it with ESG performance scores, allowing them to test statistically whether companies that score higher on environmental, social and governance dimensions exhibit less evidence of resource diversion by their dominant owners.

The empirical findings are consistent: higher ESG performance is associated with significantly lower tunneling by controlling shareholders. The relationship survives a battery of robustness checks, including alternative measures of both ESG performance and tunneling, adjustments for the potential endogeneity of ESG choices, and the use of instrumental-variable and lagged-value strategies to address the concern that causality might run the other way. Firms with stronger ESG profiles, the results suggest, are systematically less likely to see their resources siphoned off by insiders with control.

Why would environmental and social responsibility discipline a controlling shareholder who wants to raid the till? The study identifies several interlocking mechanisms. First, ESG performance functions as a reputational asset. A controlling shareholder contemplating tunneling must weigh the private benefit of diversion against the cost of damaging a hard-won public image of responsible stewardship. Because ESG ratings are increasingly visible to investors, regulators, business partners and international capital, the reputational penalty of exposure rises with the firm’s ESG standing, tipping the cost-benefit calculation away from expropriation.

Second, the information channel matters. High-ESG firms tend to attract greater scrutiny from analysts, institutional investors, media and rating agencies, all of which increase the transparency of corporate transactions and raise the probability that related-party dealings will be detected and challenged. ESG-oriented firms also tend to have stronger internal governance structures, including more independent boards and better internal controls, which directly obstruct the approval and concealment of tunneling transactions. Third, external financing pressure reinforces the effect. Firms that want to tap capital markets on favorable terms, particularly foreign institutional investors who increasingly apply ESG screens, have a concrete financial incentive to protect minority shareholders, and refraining from tunneling is a prerequisite for that credibility.

The research also explores heterogeneity, revealing that the disciplining effect of ESG is not uniform across corporate China. The restraining influence of ESG performance on tunneling is stronger in firms with lower external audit quality, weaker investor protection environments and higher financing constraints, conditions under which the reputational and informational safeguards associated with ESG substitute for other governance mechanisms. State-owned enterprises show different patterns from private firms, reflecting the distinct incentives and political constraints that shape managerial and shareholder behavior in each ownership category. These findings suggest that ESG performance operates as a governance substitute precisely where traditional mechanisms are weakest, a result with clear policy relevance for emerging markets.

The Chinese setting makes the study particularly consequential. China’s capital markets host thousands of listed firms in which a single family, founder or state entity typically retains effective control, while minority shareholders provide much of the capital. The separation between control and cash-flow rights, often amplified through pyramidal structures and cross-holdings, creates fertile ground for expropriation, and Chinese regulators have repeatedly tightened rules on related-party transactions and fund misappropriation. Yet enforcement remains uneven, and the study’s results point to a market-based complement to regulation: if firms can be induced to genuinely improve ESG performance, minority investors gain a partially self-enforcing shield against insider expropriation.

The study carries implications well beyond China. Global investors have poured trillions of dollars into ESG-labelled assets, and critics have questioned whether ESG scores capture anything economically meaningful. This research contributes a concrete answer in one important domain: ESG performance is associated with tangible reductions in a specific, measurable form of corporate misgovernance. For asset managers, the results imply that ESG ratings may convey information about the risk of expropriation in emerging-market holdings that conventional financial analysis can miss. For standard-setters and exchanges, the evidence supports policies that integrate ESG disclosure requirements with related-party transaction oversight, since the two mechanisms appear to operate synergistically.

The authors are careful to frame the findings within their limitations. ESG ratings themselves vary across providers, tunneling can take forms not captured by the receivables proxy, and the Chinese institutional context, with its distinctive ownership structures and regulatory environment, may limit generalization to markets where ownership is dispersed. Still, the central message stands: corporate responsibility performance is not decoration. In the battle between controlling shareholders and the minority investors who fund them, credible environmental, social and governance conduct shifts real resources, reducing the leakage of corporate wealth and strengthening the integrity of emerging capital markets from the inside out.

Subject of Research: The relationship between corporate ESG performance and controlling shareholder tunneling in Chinese listed companies

Article Title: Could corporate ESG performance impacts controlling shareholders tunneling: evidence from China

Article References: Could corporate ESG performance impacts controlling shareholders tunneling: evidence from China. (n.d.). https://doi.org/10.1038/s41599-026-08977-0

Image Credits: AI Generated

DOI: 10.1038/s41599-026-08977-0

Keywords: ESG performance, tunneling, controlling shareholders, corporate governance, China, listed companies, related-party transactions, minority shareholders, emerging markets, agency problems, misappropriation, state-owned enterprises

The study arrives at a moment when the hospitality sector, which contributes roughly 10 percent of global GDP, is under intense pressure to reinvent itself. India’s travel and tourism market is expected to grow from an estimated US$75 billion in FY20 to US$125 billion by FY27, with international tourist arrivals projected to reach 30.5 million by 2028 and the sector supporting around 40 million jobs. At the same time, global AI spending is forecast to exceed $300 billion by 2026, and McKinsey estimates that generative AI could add between $2.6 trillion and $4.4 trillion annually to the world economy. Against that backdrop, the authors set out to answer a deceptively simple question: which factors actually convert AI-powered personalization into satisfied, loyal guests?

The research team, led by Prashant Chaudhary of Dr. Vishwanath Karad MIT World Peace University, together with Nilesh Kate and Sujoy Kumar Jana of the Pune Institute of Business Management and Pradip Padhye of Symbiosis International University, built a conceptual model containing seven constructs: service quality, expectancy, response time, perceived value, customer experience, perceived risk and customer satisfaction. Drawing on models such as the European Customer Satisfaction Index and expectancy-value theory, they formulated twelve hypotheses about how these variables interact. Data were collected through a structured questionnaire distributed via Google Forms using convenience sampling, with all respondents over 18 years old and most drawn from southern India. The instrument comprised twenty-five items rated on five-point Likert scales, covering everything from the punctuality of AI-driven services to perceptions of price fairness and data privacy.

Methodologically, the analysis was rigorous by the standards of survey-based hospitality research. Confirmatory factor analysis verified the measurement model, with fit indices including the Chi-square/degree of freedom ratio, the Comparative Fit Index, the Tucker-Lewis Index and the root mean square error of approximation all falling within acceptable ranges. Reliability was strong: the Cronbach’s alpha of 0.870 comfortably exceeded the conventional 0.70 threshold, and both convergent validity, with construct reliability above 0.7 and average variance explained above 0.5, and discriminant validity were established. The team then applied structural equation modelling using IBM AMOS 20.0 and SPSS 22.0 to test the causal structure implied by their hypotheses, examining standardized path coefficients across the full network of relationships.

The headline finding is striking in its clarity. Perceived value emerged as the strongest and most consistent predictor of customer satisfaction, with a standardized path coefficient of 0.65. In other words, guests who felt that AI-assisted hospitality services delivered cost-effectiveness, convenience and benefits worth the price paid were the ones most satisfied and most inclined toward loyalty. Service expectancy, in turn, was the strongest predictor of perceived value at 0.60, and also significantly shaped perceived risk at 0.25. This chain, from expectancy through value to satisfaction, formed the backbone of the supported model and suggests that how much customers believe in and engage with AI technologies fundamentally determines how much value they perceive, and therefore how satisfied they become.

Response time told a more complicated story. It significantly influenced perceived value with a negative coefficient of −0.10, a counter-intuitive result the authors interpret as reflecting a preference for empathetic, human-like interaction over sheer automated speed. Faster AI-mediated responses were associated with somewhat lower perceived value in this sample, hinting that pure automation without warmth may feel hollow to guests who still crave human connection. At the same time, response time positively shaped perceived risk at 0.39, indicating that slower AI responses heightened worries about privacy and reliability. These nuanced dynamics suggest that the tempo of AI service delivery matters, but not in the simplistic way that faster-is-always-better intuition would predict.

Perhaps the most provocative results are the ones that failed to materialize. Seven of the twelve hypotheses were rejected. Service quality showed no significant direct effect on perceived value, perceived risk or customer experience, a pattern the authors attribute partly to shared-variance suppression, since expectancy and response time, which correlated moderately with service quality, absorbed much of the explanatory power. Customer experience likewise had no significant direct effect on satisfaction, and perceived risk did not significantly predict satisfaction at all. The authors caution that the perceived risk items were worded in a reassuring, trust-oriented direction rather than as threat measures, so the null result should be read as evidence that trust was already accounted for through expectancy and value, not that privacy concerns are irrelevant to Indian consumers.

These departures from Western findings carry real theoretical weight. Prior studies, including work by Wirtz and colleagues on frontline service robots and research highlighting customer discomfort with automation-driven lack of transparency, have emphasized the risks and ethical complexities of AI in service settings. The Indian data instead suggest a region-specific pattern: when the value proposition of AI, such as efficient, personalized and convenient service, is tangible and evident, consumers demonstrate a higher tolerance for AI-related risk and data privacy concerns. The young, price-conscious, largely student-dominated sample, 66 percent of whom were students aged mostly between 18 and 30, may amplify this utilitarian orientation, and the authors are careful to flag the convenience sampling and southern-India concentration as limitations that warrant caution in generalizing to older or non-student segments.

The practical implications for hotel chains, budget accommodations and online travel platforms are nonetheless concrete. The findings recommend that hospitality operators integrate AI into systems, processes and communication channels to raise service expectancy, and blend AI-powered analytics with human intervention to achieve something approaching hyper-personalization. AI tools enhanced with multilingual capabilities can break language barriers in booking experiences, while automation frees human staff for tasks requiring empathy and creativity. According to a Dun & Bradstreet survey cited in the study, 100 percent of surveyed Indian organizations have AI projects underway, around 73 percent report measurable returns, and 69 percent plan to increase AI investments. An Adobe survey of more than 5,000 Asia-Pacific consumers found that nearly 95 percent of Indian consumers trust AI-powered technologies to improve their experience, a strikingly higher figure than in New Zealand at 54 percent or Australia at 57 percent.

Ultimately, the study’s novelty lies in identifying perceived value and service expectancy, rather than service quality alone, as the critical levers through which AI integration can lift consumer satisfaction and loyalty in emerging markets such as India. The authors propose a revised, more parsimonious model in which expectancy and response time act primarily through perceived value and risk to drive satisfaction, and they call for future research using stratified national samples, risk-worded measurement instruments, and longitudinal or experimental designs to establish causality. For an industry racing toward digital transformation in the post-pandemic landscape, the message is clear: algorithms and chatbots may deliver the service, but it is the perception of value, carefully calibrated and honestly communicated, that wins the guest. AI, deployed strategically and blended with human ingenuity, becomes a catalyst for loyalty, but only when guests can see, in hard terms, what the technology is worth to them.

Subject of Research: The effects of artificial intelligence-enabled personalization on customer satisfaction and customer experience in the Indian hospitality industry

Article Title: The effects of artificial intelligence enabled personalization on customer satisfaction and customer experience in the Indian hospitality industry

Article References: Chaudhary, P., Kate, N., Jana, S. K., & Padhye, P. (2026). The effects of artificial intelligence enabled personalization on customer satisfaction and customer experience in the Indian hospitality industry. Discover Artificial Intelligence, 6(1), Article 1183. https://doi.org/10.1007/s44163-026-02250-8

Image Credits: AI Generated

DOI: 10.1007/s44163-026-02250-8

Keywords: artificial intelligence, hospitality industry, customer satisfaction, customer experience, personalization, perceived value, India, structural equation modelling, service quality, perceived risk, loyalty, emerging markets

The study, spanning April 2015 to December 2024, addresses a methodological gap that has plagued earlier attempts to link sustainability scores with returns. Many prior studies simply correlated ESG ratings with stock performance, a approach vulnerable to confounding by well-known return drivers such as firm size, valuation and profitability. Karkaria and colleagues instead embedded ESG directly into the workhorse frameworks of modern empirical finance: the Fama–French three-factor and five-factor models, which explain stock returns through market exposure, size, value, profitability and investment factors. By augmenting these models with a dedicated ESG factor, the authors could test whether sustainability information carries explanatory power beyond everything mainstream asset pricing already accounts for.

The construction of the ESG factor itself followed the characteristic-based portfolio approach that has become the gold standard since Fama and French popularized it in the early 1990s. Stocks within each BRICS market were sorted into portfolios based on their ESG characteristics, and the return spread between high-ESG and low-ESG portfolios became the factor’s empirical return series. This design matters because it converts a subjective rating into a tradable return stream—precisely the kind of object that asset pricing theory is built to evaluate. If that spread earns a persistent premium that standard factors cannot explain, financial economists have good reason to treat ESG as a distinct dimension of risk or mispricing rather than noise.

The statistical tests the authors deployed are the field’s harshest judges. The Gibbons, Ross and Shanken F-statistic, a classical test of whether a multifactor model’s pricing errors are jointly zero, evaluated whether augmented models outperformed the standard ones. Spanning tests asked an even more pointed question: can the existing Fama–French factors fully reproduce, or ‘span,’ the returns to the ESG factor? If ESG returns were spanned, they would contain no information beyond size, value, profitability, investment and the market itself. The spanning tests rejected that proposition, confirming that ESG returns are not fully absorbed by the conventional factor zoo. Factor-loading estimates and Sharpe ratio comparisons across model specifications pointed in the same direction, consistent with ESG carrying a priced risk premium in these markets.

Perhaps the most striking findings emerged from the cross-country analysis, which revealed heterogeneous rather than uniform patterns of ESG pricing across the BRICS bloc. Within each market, portfolios of low-ESG firms displayed significantly negative loadings on the ESG factor, while high-ESG portfolios showed significantly positive loadings—a clean, internally consistent signature that ESG characteristics divide firms along a priced dimension. The effect was most pronounced in Brazil and China, suggesting that in these economies sustainability disclosures convey information that investors meaningfully price. In Brazil, decades of environmental regulation and deforestation-related scrutiny have made ecological performance a salient business risk, while China’s state-driven push toward green finance and carbon intensity targets has similarly sharpened investor attention to ESG profiles.

The study also uncovered a subtle substitution effect with implications for how sustainable investing frameworks are built in emerging markets. In India and China, the ESG factor effectively substituted for the investment factor of the five-factor model—the component that captures differences in firms’ asset growth and investment aggressiveness. In practical terms, ESG information in those two markets appears to encode some of the same economic content that investment patterns otherwise capture, perhaps because conservatively managed, low-growth firms are also those with stronger governance and sustainability commitments. Across all five markets, however, ESG augmented the five-factor model, adding explanatory power even where full substitution did not occur.

Why should these results matter beyond the seminar room? Trillions of dollars in institutional capital now flow through ESG-screened mandates, and the academic controversy over whether ESG investing sacrifices, enhances, or leaves unchanged returns remains unresolved, particularly for emerging markets where disclosure standards and enforcement vary widely. The BRICS economies represent a critical test bed: they combine rapid industrialization, evolving regulatory regimes, and increasingly sophisticated capital markets. If ESG is a priced factor there, then asset managers constructing portfolios for these regions are implicitly taking or hedging ESG risk whether they intend to or not, and mean-variance optimization that ignores the factor may be quietly mis-specified.

The market-dependent nature of the findings is itself a contribution. Much of the ESG-finance literature, dominated by US and European data, implicitly assumes that results generalize across geographies. This study’s evidence that ESG pricing relevance in BRICS asset markets is contingent rather than universal cautions against transplanting conclusions from developed markets. It also gives sustainable-investment practitioners a map of where ESG integration is most likely to improve portfolio efficiency—and where it may add cost without commensurate information value. The authors frame this as insight into where and how ESG integration meaningfully improves sustainable investing frameworks across these heterogeneous economies.

Methodologically, the paper’s triangulated evidence—GRS tests for model completeness, spanning regressions for factor redundancy, factor-loading significance, and out-of-sample-style Sharpe ratio comparisons—represents a template that future studies of other emerging regions can adopt. The decade-long window captures a period of dramatic change in ESG disclosure: the rise of mandatory sustainability reporting in parts of Asia, the growth of global ESG data providers, and the post-2015 surge in climate-related investor pressure following the Paris Agreement. That the ESG factor retained incremental pricing power through this evolving landscape strengthens the case that its effects are structural rather than transient.

Limitations and open questions remain, as the authors acknowledge through their careful framing. ESG ratings from different providers correlate imperfectly, and disclosure-based scores may reflect what firms report rather than what they do—a concern amplified in markets with weaker disclosure enforcement. The authors’ published version, released as open access under a Creative Commons license and citable through its permanent DOI, invites replication across other emerging-market blocs and with alternative ESG data sources. Still, the central message stands: in the BRICS world, sustainability information is not financial decoration. It loads onto returns in statistically significant, economically interpretable ways, and any serious account of asset pricing in these rapidly growing economies now has to reckon with ESG as a factor in its own right.

Subject of Research: Whether ESG disclosures function as a priced risk factor in asset pricing models across BRICS equity markets

Article Title: Nexus between ESG disclosures and asset pricing efficiency in BRICS markets

Article References: Dusmanta, K., V R, K., & Mohanty, S. P. (2026). Nexus between ESG disclosures and asset pricing efficiency in BRICS markets. Discover Sustainability. https://doi.org/10.1007/s43621-026-04712-6

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04712-6

Keywords: ESG, asset pricing, BRICS markets, Fama–French models, sustainable investing, emerging markets, risk premium, portfolio returns, factor models, sustainability, capital markets, financial economics