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Managing knowledge is relevant for the innovativeness of an organization. The innovation of the organization currently aligns with the environment and applies green innovation concepts. Knowledge management (KM) is a key to fostering green innovation and to saving the environment from unnecessary pollution. In line with this, this study aims to evaluate the relationship between KM and green innovation in the literature from 2000 to 2023 synthesize and suggest future directions.

This study used the preferred reporting items for systematic review and meta-analysis technique to identify eligible articles. The papers were identified from the Web of Science core collection and ScienceDirect databases. The results were presented using tables, graphs and the co-occurrence of citations was analyzed using VOSviewer software.

From the review, the authors were assured that there is a strong relationship between KM practices and green innovation in different organizations. Some papers were supported by different theories. From the total of 48 papers, 16 have not mentioned the theories applied in their studies. The geographical distribution of the papers is asymmetrical. Asian and European scholars published more papers. The papers distribution across publishers also varies. For instance, Elsevier and Emerald Group Publishing Ltd. published 29 papers and the remaining papers were published in BMC, Springer, Frontiers Media Sa, IEEE-Inst Electrical Electronics Engineers Inc., MDPI, Routledge Journals and Taylor & Francis Ltd. Major themes were identified and future research directions were forwarded.

The limitation of this review is the authors generated the papers from two databases (WoS and ScienceDirect). This paper does not consider other databases (Scopus, dimensions, etc.) papers. This can be considered as a limitation of this review.

The review is original by integrating PARISMA and bibliometric analysis method (VOS Viewer). The paper tried to explore the role of KM on green innovation.

Online portfolio selection sequentially allocates wealth among a set of assets and aims to maximize the investor’s cumulative return in the long run. Various existing algorithms in the finance and accounting area adopt an indirect approach to exploit one asset characteristic through the channel of assets’ expected return and thus cannot fully leverage the power of various asset characteristics found in the literature. This study aims to propose new algorithms to overcome this issue to enhance investment performance.

We propose a parameterized portfolio selection (PPS) framework, which directly incorporates multiple asset characteristics into portfolio weights. This framework can update parameters timely based on final performance without intermediate steps and produce efficient portfolios. We further append L1 regularization to constrain the number of active asset characteristics. Solving the PPS formulation numerically, we design two online portfolio selection (OLPS) algorithms via gradient descent and alternating direction method of multipliers.

Empirical results on five real market datasets show that the proposed algorithms outperform the state of the arts in cumulative returns, Sharpe ratios, winning ratios, etc. Besides, short-term characteristics are more important than long-term characteristics, and the highest return category is the most important characteristic to improve portfolio performance.

The proposed PPS algorithms are new end-to-end online learning approaches, which directly optimize portfolios by asset characteristics. Such approaches thus differ from existing studies, which first predict returns and then optimize portfolios. This paper provides a new algorithmic framework for investors’ OLPS.

This study aims to improve detection efficiency of fluorescence biosensor or a graphene field-effect transistor biosensor. Graphene field-effect transistor biosensing and fluorescent biosensing were integrated and combined with magnetic nanoparticles to construct a multi-sensor integrated microfluidic biochip for detecting single-stranded DNA. Multi-sensor integrated biochip demonstrated higher detection reliability for a single target and could simultaneously detect different targets.

In this study, the authors integrated graphene field-effect transistor biosensing and fluorescent biosensing, combined with magnetic nanoparticles, to fabricate a multi-sensor integrated microfluidic biochip for the detection of single-stranded deoxyribonucleic acid (DNA). Graphene films synthesized through chemical vapor deposition were transferred onto a glass substrate featuring two indium tin oxide electrodes, thus establishing conductive channels for the graphene field-effect transistor. Using π-π stacking, 1-pyrenebutanoic acid succinimidyl ester was immobilized onto the graphene film to serve as a medium for anchoring the probe aptamer. The fluorophore-labeled target DNA subsequently underwent hybridization with the probe aptamer, thereby forming a fluorescence detection channel.

This paper presents a novel approach using three channels of light, electricity and magnetism for the detection of single-stranded DNA, accompanied by the design of a microfluidic detection platform integrating biosensor chips. Remarkably, the detection limit achieved is 10 pm, with an impressively low relative standard deviation of 1.007%.

By detecting target DNA, the photo-electro-magnetic multi-sensor graphene field-effect transistor biosensor not only enhances the reliability and efficiency of detection but also exhibits additional advantages such as compact size, affordability, portability and straightforward automation. Real-time display of detection outcomes on the host facilitates a deeper comprehension of biochemical reaction dynamics. Moreover, besides detecting the same target, the sensor can also identify diverse targets, primarily leveraging the penetrative and noninvasive nature of light.

In the era of the digital economy, the digital innovation ecosystem is an important vehicle to alleviate enterprises' resource and capability constraints and thus improve their digital innovation performance. Embedding digital innovation ecosystems for survival and development opportunities has become a new strategic choice for enterprises. However, how digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises has not yet been fully revealed. This study examines whether digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises through ambidextrous capabilities (exploration and exploitation) and the moderating role of strategic flexibility.

A field survey was conducted in China, collecting survey data from 578 complementary enterprises in advanced manufacturing industries embedded in digital innovation ecosystems. This study applies multiple regression analysis to verify the relevant hypotheses.

The results confirmed that (1) digital innovation ecosystem embeddedness has a significant positive effect on complementary enterprises' digital innovation performance; (2) Ambidextrous capabilities play a partial mediating role in the relationship between digital innovation ecosystem embeddedness and complementary enterprises' digital innovation performance. (3) Strategic flexibility positively moderates the effect of digital innovation ecosystem embeddedness on ambidextrous capabilities and digital innovation performance.

The findings, intended to guide enterprises that complement the digital innovation ecosystem to achieve digital innovation and performance improvement, highlight the importance of eco-embedded strategies, ambidextrous capabilities and strategic flexibility.

The finding enriches antecedent research on digital innovation performance and provides practical insights for firms to embed themselves in digital innovation ecosystems to improve performance.

The purpose of this study is to adjust the electronic transport performance of zinc oxide–silicon dioxide (ZnO-SiO₂) film by the construction of a grain boundary barrier.

ZnO-SiO₂ thin films were prepared on glass substrates by a simple sol-gel method. The crystal structure of ZnO and ZnO-SiO₂ powders were tested by X-ray diffraction with copper (Cu) Kα radiation. The absorption spectra of ZnO and ZnO-SiO₂ films were recorded by a ultraviolet-visible spectrophotometer. The micro electrical transport performance of ZnO-SiO₂ thin films were investigated by conductive atomic force microscope and electrostatic force microscope.

The results show that the current of ZnO-SiO₂ film decrease, indicating that the mobility of ZnO-SiO₂ film is greatly decreased, owing to the formation of the grain boundary barrier between ZnO and SiO₂. The phase variation of ZnO-SiO₂ film increases due to the electron accumulation at grain boundaries.

ZnO and ZnO-5SiO₂ thin films prepared on glass substrates by a simple sol-gel method were first studied by CAFM and EFM. The band gaps of ZnO and ZnO-5SiO₂ is ∼3.05 eV and 3.15 eV, respectively. The barrier height of ZnO-5SiO₂ film increased by ∼0.015 eV after introducing SiO₂. The phase variation intensity increased to a certain extent after doping SiO₂, due to the increased GB barrier. ZnO-5SiO₂ film will be a promising ETL candidate in the application of QLEDs field.

This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the underlying economic and political factors associated with local government have influenced the quality of CSER.

The authors used 234 environmentally sensitive companies listed on the Shanghai and Shenzhen Stock Exchanges during 2013 and 2015 as the research sample to test the relationship between CSER and local government’s political connection and economic prioritisation and the potential mediating effect of local economic prioritisation.

The analysis provides evidence that local/provincial government’s political geographical connectedness with the central government has directly and positively influenced the level of CSER, while local prioritisation of economic development has a direct but negative effect on CSER in China. In addition, local/provincial prioritisation of economic development has mediated the relationship between local–central political geographical connectedness and CSER.

While local/provincial governments are heavily influenced by the coercive pressure from the central government, they also act in their own political and economic interests in overseeing CSER at the local level. This study raises the question about the effectiveness of the top-down approach to improving CSER in China and suggests that the central government may need to focus more on coordinating and harmonising different local/provincial governments’ interests to enable achieving a common sustainability goal.

The authors provide evidence revealing how the economic and political contexts of local government have played a significant role in shaping CSER in China. More specifically, this paper addresses a gap in the literature by highlighting the importance of local government oversight power for CSER development and how such oversight is determined by local prioritisation of economic development and political geographical connectedness of local and central governments.

Sustainable development is inseparable from rational and responsible use of resources and promotion of green entrepreneurship. The contemporary green development agenda encompasses climate, economic, technical, social, cultural, and political dimensions. International efforts to greening the global development are conducted by the major economies, including China as the world’s largest consumer of energy and the biggest emitter of greenhouse gases. China is aware of its environmental problems, as well as of its part of the overall responsibility for the accomplishment of the sustainable development goals. By means of the decarbonization efforts, the latter are integrated both into the national development agenda (the concept of ecological civilization) and China’s international initiatives (the greening narrative within the Belt and Road Initiative). Over the past decade, China has made a breakthrough on the way to promoting green entrepreneurship and greening of its development (better quality of air and water, renewable energy, electric vehicles, and organic farming). On the other hand, emissions remain high, agricultural land loses productivity, and freshwater resources degrade due to climate change. In conventional industries (oil, coal mining, and electric and thermal energy), decarbonization faces an array of impediments. In this chapter, the authors summarize fundamental provisions of China’s approach to building an ecological civilization and measures to reduce emissions and achieve the carbon neutrality status within the nearest decades. The analysis of obstacles to the decarbonization of the economy and possible prospects for the development of green entrepreneurship summarizes China’s practices for possible use in other countries.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

We examine whether the social capital of the area where a firm’s headquarters is located affects that firm’s credit rating. Given that credit rating agencies only infrequently visit a firm’s headquarters, it is pertinent to investigate whether this soft information is considered.

In order to test whether social capital affects firms’ credit ratings, we estimate the following model using an ordinary least squares regression: Rating_it = β₀ + β₁ Social Capital_it + ∑ Controls_it + Industry fixed Effects_i + State−year fixed effects_it + ε_it. We follow recent accounting and finance research and measure societal-level social capital at the county level (Jha & Chen, 2015; Cheng et al., 2017; Hasan et al., 2017a, b; Jha, 2017; Hossain et al., 2023). We use four inputs to calculate social capital: (1) voter turnout in presidential elections, (2) the census response rate, (3) the number of social and civic associations and (4) the number of nongovernmental organizations in each county.

W provide evidence that social capital has a causal effect on credit ratings. Interesting is that this effect is not merely localized to firms near credit rating agencies. We also find that the effect of social capital on credit ratings is concentrated among firms with moderate levels of default risk. For firms with extremely low or extremely high default risk, social capital appears irrelevant to credit ratings, suggesting that social capital plays a larger role in more ambiguous contexts or when greater judgment is required. We demonstrate that the effect of social capital on credit ratings disappears when the rating agency has extensive experience in a particular region. This result is consistent with rating agencies stereotyping certain regions of the USA and using that information to inform their ratings when they have less experience in the region. Finally, we find that while social capital is associated with credit ratings, it has no association with future defaults.

Though we cautiously followed prior studies and were confident in our data construction process, it is possible that we are measuring social capital with error.

Our findings suggest that credit rating agencies could benefit from reevaluating how they incorporate non-financial information, such as social capital, into their assessment processes, potentially leading to more nuanced and equitable credit ratings. Additionally, firms could use these insights to bolster their engagement with local communities and stakeholders, thereby enhancing their creditworthiness and attractiveness to investors as part of a broader corporate strategy. The findings also underline the need for regulatory frameworks that foster transparency and the inclusion of social factors in credit evaluations, which could lead to more comprehensive and fair financial reporting and rating systems.

Recognizing that social capital can influence economic outcomes like credit ratings may encourage both communities and firms to invest more in building and maintaining social networks, trust and civic engagement. By demonstrating how social capital impacts credit ratings, our research highlights the potential to address inequalities faced by regions with lower social capital, guiding targeted social and economic development initiatives. Moreover, understanding that regional social capital can influence credit ratings might affect public perception and trust in the impartiality and accuracy of these ratings, which is essential for maintaining market stability and integrity.

Our research provides fresh insights into how social capital, an intangible asset, influences credit ratings – a topic not extensively explored in existing literature. This sheds light on the dynamics between social structures and financial outcomes. Methodologically, our use of the 9/11 attacks as an exogenous shock to measure changes in social capital introduces a novel approach to study similar phenomena. Additionally, our findings contrast with prior studies such as Jha and Chen (2015) and Hossain et al. (2023), by delving deeper into how proximity and familiarity impact financial assessments differently, enriching academic discourse and refining existing theories on the role of local knowledge in financial decisions.

The study aims to explore how fashion visual symbols influence consumers' inclination for repurchasing. It attempts to investigate the intricate interplay among three essential variables (social presence, collective excitement and cultural identification) from the perspective of Interaction Ritual Chains theory. Meanwhile, an attempt is made to reveal the underlying patterns in these relationships, fully harnessing the positive impact of fashion brand visual symbols in brand marketing.

This study employs a quantitative research methodology, administering an online survey in China, from which 381 valid responses were collected by simple random sampling. The acquired data were subjected to structural equation model and hypotheses testing.

The analysis reveals that heightened visual symbol perception significantly strengthens consumers' social presence, consequently elevating the probability of collective excitement. This establishes a mediated chain model, reinforcing repurchase intention. Additionally, the moderation effect analysis indicates that cultural identification negatively moderates both direct paths in the mediated chain model, with particularly pronounced effects for low cultural identification.

This study establishes a closed-loop system in fashion brand product marketing, continuously enhancing the intimacy and interactive willingness between consumers, as well as between consumers and the brand. The objective is to increase brand repurchase rates. Additionally, the research provides valuable recommendations and strategies for fashion brands to adapt to Chinese consumer demands, strengthen emotional attachment between consumers and the brand, and achieve sustainable development in the realm of fashion consumption.