Search results

This paper aims to explore the impact of domestic market fragmentation on the innovation performance of enterprises and its mechanism from the perspective of market segmentation, a government behavior with Chinese characteristics.

In order to verify the theoretical hypothesis proposed in the previous article, that is, whether domestic market fragmentation can effectively improve the innovation performance of enterprises, this paper bases on the data of listed companies from 2010 to 2016, empirically testing the theoretical hypothesis by constructing a measurement model.

Domestic market fragmentation has a significant inhibitory effect on enterprise innovation performance. Domestic market fragmentation has heterogeneous effects on innovation performance of enterprises and regions. It is undeniable that domestic market fragmentation does have a certain support effect on state-owned enterprises but the support effect is achieved by distorting regional resource allocation and creating an unfair market environment.

Firstly, this paper explores the impact mechanism of domestic market fragmentation on corporate innovation performance from the perspective of market segmentation, a government behavior with Chinese characteristics, so as to expand and enrich the relevant research on enterprise innovation. Secondly, from the perspective of corporate innovation performance, this paper provides new evidence for the “curse effect” of domestic market fragmentation. Thirdly, this paper tries to shake the domestic market fragmentation support theory from the perspective of distortion effect brought by the “hand of support” of domestic market fragmentation.

This study aims to optimize the preparation conditions and modify the nanofiltration (NF) membranes to prepare high-performance polysulfone/sulfonated polysulfone composite nanofiltration (PSF/SPSF-NF) membranes through interfacial polymerization.

Investigating the impacts of anhydrous piperazine (PIP) concentration, trimesoyl chloride (TMC) concentration and basement membrane type on NF membrane performance, the optimal membrane was prepared. In addition, nano-SiO₂ was added to the active separation layer to modify the NF membranes.

The comprehensive performance of PSF/SPSF-NF membranes was optimized when the concentration of PIP was 0.75 Wt.% and the concentration of TMC was 0.15 Wt.%, at which time the water flux was 66.1 L·m⁻²·h⁻¹ and the retention rate of Na₂SO₄ was 98.1%. The comprehensive performance of polysulfone/sulfonated polysulfone-SiO₂ nanofiltration (PSF/SPSF-SiO₂-NF) membranes was optimized when the blending ratio of nano-SiO₂ to PIP was 2:3, with a pure water flux of 81.9 L·m⁻²·h⁻¹ and a Na₂SO₄ retention rate of 95.9%. Compared to polysulfone nanofiltration (PSF-NF) membranes and PSF/SPSF-NF membranes, NF membranes with nano-SiO₂ increased the flux recovery rate by 22.9% and 8.7%.

PSF/SPSF-SiO2-NF membrane exhibits excellent antifouling properties.

There is currently no literature available on the preparation of NF membranes using polysulfone/sulfonated polysulfone (PSF/SPFS) as a substrate. This provides a method for modifying NF membranes, starting with the modification of the basement membrane and then modifying the active separation layer.

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.

As a consequence of the proposal of the Carbon Neutral and Carbon Peak policy in 2020, the Chinese Government is paying more attention to developing sustainability performance. This study aims to assess the direct influence of country-level and corporate anti-corruption measures on environmental, social and governance (ESG) and its three dimensions, besides ascertaining the moderating role of firm size.

This study used the system generalized method of moments on a sample of 820 Chinese listed firms from 2012 to 2021.

The findings show that country-level and corporate corruption negatively affect ESG performance. Corporate anti-corruption measures have a more pronounced positive influence on the sustainability performance of small firms than large firms due to the limited resources, lower political position and weaker refusal power of small firms.

The study has great implications for governments, corporate boards and ESG rating agencies. Government and corporate boards should mitigate the risks of country-level and corporate corruption to attain sustainable development goals. Rating agencies should add country-level and corporate corruption into the ESG evaluation system.

Some empirical results have proven that anti-corruption measures help reduce the emission of carbon dioxide, but few evidence shows how country-level and corporate corruption affect ESG and its three dimensions.