Digital technologies are often portrayed as disruptive levers for decarbonisation, yet many digital green initiatives improve transparency and efficiency without redesigning how environmental value is authorised, coordinated, and appropriated. We address this puzzle by theorising green digital business model innovation as the evolution of venture-level configurations under multi-domain selection in policy-steered sustainability transitions. Building on the activity-system view of business models and on innovation-studies, we define business model radicality as coupled reconfiguration across content, structure, and governance rather than technology novelty alone. We further theorise a cross-domain convergence requirement: configurations are retained only when they align simultaneously with institutional role allocations, market interfaces, technological infrastructures, and ecological verification demands. A comparative longitudinal study of three blockchain-enabled initiatives in China’s energy-finance nexus shows that radical disintermediation is screened out early when any single domain withholds authorisation or credible settlement, whereas incumbent-compatible configurations are retained through sequencing, interpretive pruning, and boundary-spanning alignment work. The study contributes to innovation studies by treating business models as meso-level selection objects, sharpening configuration-level radicality, and explaining why digital green opportunities often remain incremental in regulated transition systems.

Despite strong GDP growth and a favourable demographic profile, India faces an impending jobs crisis. A large share of the workforce remains employed in lowproductivity agriculture, while many new labour market entrants are absorbed into the persistently large informal sector. By contrast, China's rapid ascent was driven by manufacturing-led, export-oriented industrialisation, underpinned by large inflows of foreign direct investment and sustained technology transfer. India's manufacturing base remains modest in contrast. The bulk of well-paid, formal employment continues to be concentrated in the high-skill services sector. This paper contrasts the development trajectories of these two economies and identifies several underutilised jobs-growth levers in India: manufacturing, goods exports, manufacturing-oriented foreign direct investment and innovation. All of these remain underdeveloped, yet together they offer a pathway to more labour-absorbing, durable growth. Leveraging them effectively would be central to achieving India's 'Viksit Bharat 2047' ambition of attaining high-income status. The scale of India's challenge to employ eight to ten million labour-market entrants per year implies that job creation must become an explicit policy priority. This calls for greater trade openness, particularly with Asia and Europe, to integrate India into Asia-centric global supply chains as an alternative to China. Labour market reform is equally critical, making the effective implementation of the new labour codes essential. Strengthening innovation ecosystems and realigning education and skills policies to support industrialisation are also key. Without these structural shifts, India's current pattern of jobless growth risks transforming its demographic dividend into a long-term liability.

This article views the economic development history of New China as a history of openness and constant adjustment. We examine China’s economic development and early open policies from 1953 to 1978, analyze how the nation navigated between planned and open economic models during the formative period. Through a comprehensive review ofthe key Chinese and Western scholarship, investigates major initiatives including the Soviet-assisted 156 Projects, First Five-Year Plan, The policy of Eight Characters and the later “Four Three Plan” of the Western engagement. The study highlights both achievements and challenges, particularly in industrial growth and technology transfer, while assessing the impact of critical events like the Sino-Soviet split. Statistical analysis and quantitative models demonstrate how these early experiments with economic openness, despite ideological constraints and operational difficulties, established crucial institutional and technological foundations for China’s subsequent reform and modernization. The findings offer valuable insights into China’s unique development path and its implications for emerging economies.

The development of industrialization runs through the history of the People’s Republic of China. In the early years of the founding of the People’s Republic of China, the Soviet Union provided important help for China’s industrialization construction, capital lending, talent training and technology transfer. By analyzing the proportion of China’s industrial output value in the total output value and the output of major industrial products during the period of the Soviet Union, it shows that the assistance of the Soviet Union had a very positive role in promoting the realization of ChinaIs industrialization, and helped China to lay the foundation of industrialization.In addition, some problems in accepting the Soviet Union’s aid to China also deserve our attention when promoting the new industrialization. The research explores both the internal and external factors that led to China’s acceptance of Soviet assistance.The study examines the political, economic, and historical contexts that created a favorable environment for such aid, analyzes the various modes and scales of the assistance implemented, and presents statistical data that underscore the transformative social and economic achievements derived from this partnership.Furthermore, the paper highlights the contributions of quantitative analyses in understanding the aid’s impact, discusses the experiences and lessons learned from the Soviet aid period, and assesses the evolving dynamics of Sino—Soviet relations,particularly the gradual divergence in economic development models. The findings shed light on how Soviet aid laid the groundwork for China’s industrialization while also foreshadowing future ideological and developmental separations.

This paper asks whether a personally experienced bubble crash leaves a lasting imprint on investment style. We study this in China’s stock market, where two technology-growth booms —the 2014–2015 Internet boom and the 2025–2026 AI hardware boom—share a similar narrative but are separated by a decade of generational turnover. Following managers across the mutual funds they run from 2013Q1 to 2026Q1, we compare those who lived through the 2015 crash with otherwise similar managers who entered afterwards. We find that the caution of veteran managers reflects a scar rather than a symptom of ageing. Conditional on age and career length, managers who lived through the 2015 crash hold more value exposure and chase technology stocks less when prices have been rising, and this reluctance deepens with how much the crash hurt them—crash-window tenure, performance shortfalls, redemption pressure—rather than with age. These demand differences reach asset prices as well: stocks held disproportionately by managers without bubble memories carry significantly higher subsequent left-tail risk, whereas crash-experienced ownership stabilises the stock, particularly when ownership is broad. Heterogeneous institutional beliefs rooted in career experience therefore shape not only how managers invest but also the crash risk of the assets they hold.

The development of industrialization runs through the history of the People’s Republic of China. In the early years of the founding of the People’s Republic of China, the Soviet Union provided important help for China’s industrialization construction, capital lending, talent training and technology transfer. By analyzing the proportion of China’s industrial output value in the total output value and the output of major industrial products during the period of the Soviet Union, it shows that the assistance of the Soviet Union had a very positive role in promoting the realization of ChinaIs industrialization, and helped China to lay the foundation of industrialization. In addition, some problems in accepting the Soviet Union’s aid to China also deserve our attention when promoting the new industrialization. The research explores both the internal and external factors that led to China’s acceptance of Soviet assistance. The study examines the political, economic, and historical contexts that created a favorable environment for such aid, analyzes the various modes and scales of the assistance implemented, and presents statistical data that underscore the transformative social and economic achievements derived from this partnership. Furthermore, the paper highlights the contributions of quantitative analyses in understanding the aid’s impact, discusses the experiences and lessons learned from the Soviet aid period, and assesses the evolving dynamics of Sino—Soviet relations, particularly the gradual divergence in economic development models. The findings shed light on how Soviet aid laid the groundwork for China’s industrialization while also foreshadowing future ideological and developmental separations.

This paper examines the intricate relationship between China’s First Five-Year Plan (1953–1957) and the extensive Soviet aid that played a pivotal role in shaping early industrialization and economic policy in New China. Drawing upon both Chinese and Western literature, the study reviews the evolution of planned economy practices and Soviet economic assistance, analyzes the process of plan formulation and the formulation of key industrial targets, and assesses the quantitative and qualitative impact of Soviet aid on the successful implementation of the plan. By employing a multi-perspective literature review, archival research, and statistical data analysis, the paper identifies that Soviet technology, machinery, and planning expertise contributed significantly, estimates suggest that Soviet aid accounted for 30-40% of the capital inputs in key sectors and that this collaboration was instrumental in achieving heavy industry targets before the advent of reform and opening-up policies. Furthermore, the paper explores the subsequent divergence in the economic models of China and the Soviet Union, offering lessons on dependency, technology transfer, and the political dimensions of foreign aid. The findings not only contribute to our understanding of the early stages of China’s economic development but also shed light on the broader dynamics of Cold War-era international economic cooperation.

This paper studies whether financial technology (FinTech) changes loan contract design by reducing banks’ reliance on collateral in corporate lending. Using loan-level data on Chinese listed firms from 2007 to 2023 and exploiting the People’s Bank of China’s 2019 FinTech Development Plan as a quasi-natural experiment, we find that banks with stronger pre-policy FinTech capability significantly reduce secured lending after the policy shock. In the benchmark specification, the probability that a loan is secured falls by 1.64 percentage points, or about 2.7% relative to the baseline secured-loan share. The result is robust to alternative loan classifications, matching procedures, alternative measures of FinTech adoption, aggregated lending outcomes, and alternative inference procedures. The pattern is more pronounced among small and medium-sized enterprises, lower-tier branches, and branches located outside bank headquarters’ cities, where borrower information is likely to be more limited. Supplementary analyses are consistent with FinTech reducing banks’ information-production costs and suggest that technological proximity to FinTech-active peers may amplify the collateral-reducing effect. Overall, the evidence indicates that FinTech can enhance banks’ screening capacity and shift lending decisions away from reliance on asset-based guarantees toward information-based credit assessment.

Technology firms are often financed on narratives about products, contracts, customers, and technological progress well before these developments appear in accounting statements. We ask when such narratives become economically informative. Our central idea is that narratives should matter more once they can be linked to later verifiable outcomes rather than treated as stand-alone text.Using listed Chinese technology firms, we develop a validated corporate narrative framework for bank-affiliated investment, a setting in which investors must screen with soft information ex ante and then monitor hard realization and downside risk ex post. We use GPT-5.1 to extract business claims from management discussion, investor-relations records, exchange Q&A, and earnings-roadshow materials, and to label later claim–evidence pairs as support, partial support, conflict, duplicate, or irrelevant. We then connect these labels to official announcements, procurement awards, permits, project updates, and negative-event disclosures to construct a validated firm-month signal. The broad merged panel contains 592 firms and 30,169 firm-month observations; the main return tests use 576 firms and 18,230 firm-month observations over 2022–2024. A simple production rule that combines a low-narrative-premium component with hard-narrative and hard-event anchors, together with a separate downside-risk gate, delivers an implementable annualized long-short return of 8.93% in bank-invested firms after trading costs. The signal is much weaker in non-bank firms, predicts future gross-margin improvement more strongly than future ROE, and improves downside screening.

The parking reservation systems (PRS), as an intelligent system, was adopted to address urban parking difficulties. However, the parking reservation system has not been widely adopted in China due to the reasons such as the imperfect system and the uncontrollable parking behaviour of users. This study examines the impact of users' non-compliant behaviour on intentions to reuse PRS. Non-compliant behaviours include not arriving or leaving parking spaces not as scheduled, negatively affecting subsequent users. The Technology Acceptance Model (TAM) was expanded by adding perceived risk, social influence, and behavioral attitude. A survey involving 702 PRS users from multiple Chinese cities was conducted. Structural Equation Modelling (SEM) was used for analysis Results show that perceived risk—such as occupied reserved spaces and extra fees from time deviations—significantly reduces behavioral attitudes and reuse intentions. Conversely, perceived usefulness, ease of use, and social influence positively influence both attitudes and reuse intentions. Importantly, the findings highlight that behavioral uncertainty, particularly users’ deviations from scheduled parking times, is a critical source of perceived risk that undermines trust and long-term engagement. Effectively managing this uncertainty through improved system flexibility and reliability is therefore essential to promoting the sustained adoption of PRS.