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This paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.

The authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.

The authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).

This paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.

This research establishes an evaluation index system and calculation method for the China's maritime power construction index (CMPCI). It has conducted practical tests on the progress of China's maritime power construction since the 12th–13th Five-Year Plans. This paper conducts a phased study on the construction of China's maritime power based on the CMPCI evaluation results; it expands the relevant achievements in the research field of quantitative research in China's maritime power construction. The verification results are consistent with the actual situation.

Fully reflect the guiding role of national marine policies in the new development stage, guide the transformation of China's marine management model. The CMPCI is a quantitative evaluation of the overall development level of China's maritime power construction over a certain period of time. The CMPCI in this article aims to comprehensively reflect the changes in the construction of China's maritime power, strives to cover various fields it encompasses. This study focuses on objective statistical data analysis, supplemented by multisource data, to objectively and fairly measure the level of CMPCI.

It fully reflects the highlights of marine science and technology, social democracy and strategic emerging industries. This research dynamically quantifies the trajectory of China's maritime power construction, synthetic reflecting the country's macroeconomic policy guiding function. Guiding the transformation of the marine resources utilization, marine economy development, marine scientific research and marine rights and interests maintenance and effectively serving the decision-making needs of the government.

Renal failure is an end-stage consequence after persistent hyperglycemia during diabetic nephropathy (DN), and the etiology of DN has been linked to oxidative stress. The purpose of this research was to determine the beneficial synergistic effects of S-Allyl Cysteine (SAC) and Taurine (TAU) on oxidative damage in the kidneys of type 2 diabetic rats induced by hyperglycemia.

Experimental diabetes was developed by administering intraperitoneal single dose of streptozotocin (STZ; 65 mg/kg) with nicotinamide (NA; 230 mg/kg) in adult rats. Diabetic and control rats were treated with SAC (150 mg/kg), TAU (200 mg/kg) or SAC and TAU combination (75 + 100 mg/kg) for four weeks. The estimation of body weight, fasting blood glucose (FBG), oral glucose tolerance test (OGTT), oxidative stress markers along with kidney histopathology was done to investigate the antidiabetic potential of SAC/TAU in the NA/STZ diabetic group.

The following results were obtained for the therapeutic efficacy of SAC/TAU: decrease in blood glucose level, decreased level of thiobarbituric acid reactive substances (TBARS) and increased levels of GSH, glutathione-s-transferase (GST) and catalase (CAT). SAC/TAU significantly modulated diabetes-induced histological changes in the kidney of rats.

SAC/TAU combination therapy modulated the oxidative stress markers in the kidney in diabetic rat model and also prevented oxidative damage as observed through histopathological findings.

The present study focused on examining the effect of treated wastewater (TWW) on soil chemical properties. Also, efforts were made to compare the soil chemical properties under TWW irrigation with that under groundwater (GW).

During the years 2021 and 2022, surface and subsurface soil samples were randomly collected in triplicate by using an auger fortnightly at two depths (20 and 40 cm) from the selected spot areas to represent the different types of irrigation water sources: TWW and GW. Samples of the GW and the TWW were collected for analysis.

This study examines the impact of TWW on soil characteristics and the surrounding environment. TWW use enhances soil organic matter, nutrient availability and salt redistribution, while reducing calcium carbonate accumulation in the topsoil. However, it negatively affects soil pH, electrical conductivity and sodium adsorption ratio, although remaining within acceptable limits. Generally, irrigating with TWW improves most soil chemical properties compared to GW.

In general, almost all of the soil’s chemical properties were improved by irrigating with TWW rather than GW. Following that, wastewater is used to irrigate the soil. Additionally, the application of gypsum to control the K/Na and Ca/Na ratios should be considered under long-term TWW and GW usage in this study area in order to control the salt accumulation as well as prevent soil conversion to saline-sodic soil in the future. However, more research is needed to thoroughly investigate the long-term effects of using TWW on soil properties as well as heavy metal accumulation in soil.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

The purpose of this paper is to identify the existing measure instruments for dynamic capabilities (DCs) in order to understand the tendencies of quantitative studies on DCs as well as to evaluate the reliability and validity of these scales.

To accomplish this objective, the authors conducted a systematic review of literature on DCs.

Main findings indicate that quantitative research works on DCs have focused on the relationship between DCs, innovation, organization performance, knowledge management and absorptive capacity. Findings also show that efforts to measure DCs quantitatively are recent and lack reliable methodology.

One limitation of this research is that the authors conducted the systematic review on two databases. However, the authors conducted the research on the two most used databases in management research.

Findings show that academicians have plenty of room to work on quantitative research works on DCs as well as to develop robust scales to measure this construct in diverse business sectors.

This paper is the first to analyze the existing scales that measure DCs.

This paper aims to investigate the relationship linking hard technology innovation with the high-quality development (HDP) of SRDI firms. SRDI firms are typically classified as medium-sized to moderately scaled businesses renowned for their specialized, refinement, differentiation and innovation (SRDI), with a focus on providing exceptional products or services to gain a competitive advantage in specific market segments. These firms are dedicated to expanding market share and enhancing innovation capacities both locally and globally. The research also aims to scrutinize the contextual effects of digital transformation within this framework.

Hard technology innovation consists of three essential components: innovative characteristics, newly developed technology-based intellectual property rights and the volume of R&D initiatives. The evaluation of HDP was performed utilizing the entropy method, with a specific emphasis on assessing value creation and value management capabilities. Subsequently, this study explores the impact of technological innovation on the HDP of firms using a dual-dimension fixed effects model.

Every aspect of hard technology innovation is essential for promoting the HDP of businesses. The digital transformation of businesses exerts a heterogeneous moderating influence in this process. This is evident in the constructive impact on the connection between innovation attributes and the volume of fruitful R&D initiatives, as well as the HDP of firms. Conversely, the moderating effect is deemed insignificant in the association between new technology-based intellectual property and HDP.

This research delves deeper into the underlying mechanisms that underlie the promotion of HDP through hard technology innovation, thereby expanding the scope of our exploration on the HDP of SRDI firms. It establishes a theoretical framework and practical directives for achieving enhanced development quality amidst the evolving landscape of digital transformation within firms.

This paper aims to examine the impact of adverse personality traits (alexithymia, social inhibition, negative affectivity) and supervisor knowledge hiding on individual knowledge hiding. This study also explores the moderating role of positive affectivity.

Partial least squares path modeling and data collected from 518 Polish employees with higher education and extensive professional experience recruited via an Ariadna survey panel were used to test the research hypotheses.

Two dimensions of alexithymia were considered: difficulty identifying feelings (DIF) and difficulty describing feelings (DDF). DIF has a direct impact on individual hiding, whereas DDF has an indirect impact, via social inhibition. Negative affectivity is a predictor of social inhibition, which enhances knowledge hiding. Positive affectivity slightly weakens the positive and strong effect of supervisor knowledge hiding on subordinate knowledge hiding.

Because alexithymia, social inhibition and negative affectivity may predispose employees to knowledge hiding, managers should identify these personality traits among job applicants and hired employees to make appropriate employment decisions. Moreover, managers should be aware that hiding knowledge by a supervisor may be imitated by subordinates.

Based on conservation of resources theory, this study investigates previously unexplored relationships among alexithymia, social inhibition, affectivity and knowledge hiding.