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The present paper aims at understanding how horizontal network collaborations between small and medium enterprises (SMEs) can be designed and implemented to take advantage of a supply chain finance (SCF) perspective.

This study presents an SCF literature background identifying four literature gaps, and in response to them it adopts an action research approach. The empirical analysis is developed on a network-case study: a horizontal collaboration project between small businesses of the Italian wine industry and their supply chains.

SMEs can play an active role in developing – in terms of design and implementation – their collaborative networks by taking advantage of an SCF perspective for themselves, and their customers, based on the reorganization of relationships interface processes. Taking this perspective can be a concrete and crucial way to sustain the development of SMEs and their supply chains in an actual competitive context.

The paper identifies the theoretical gaps in the literature, suggests new research areas that deserve to be more deeply investigated and connects case-related results to the key concepts. The empirical part presents a real case application that proposes a complete roadmap for managers and practitioners who wish to experience similar projects.

This network-case study storyline, presenting an overview of ten years of meetings, with related purposes, is suggesting a roadmap for design and implementation of horizontal network as managerial implications. These kinds of active research projects, with a collaborative mixed team of academics and practitioners, and involving a multilayer group of participants, are positive examples for closing the bridge between companies and academia, which enhance this network of small businesses active in trying to improve their competitiveness working together.

The value of the paper is to embrace a supply chain-oriented perspective for an SME, independent of the financial system and based on inventory flow management. Very little literature focuses on inventory-based research within the SCF framework, designed for real implementation in horizontal network collaboration by entrepreneurial ventures.

This study aims to investigate whether firms purchase directors' and officers' liability (D&O) insurance when the country-level economic policy uncertainty (EPU) is high.

This study uses D&O insurance data from Chinese listed firms between 2003 and 2019 to conduct regression analyses to examine the association between D&O insurance and EPU.

The results show that government EPU, despite being an exogenous factor, increases the likelihood of firms' purchasing D&O insurance, and this effect is more pronounced when firms are exposed to great share price crash risk and high litigation risk, suggesting that firms intend to purchase D&O insurance possibly due to the accentuated stock price crash risk and litigation risk associated with EPU. In addition, the results indicate that the effect of EPU on the D&O insurance purchase decision is moderated by the provincial capital market development and internal control quality.

The study highlights the role of uncertain economic policies in shareholder approval of D&O insurance purchases.

The study enriches the literature on the determinants of D&O insurance purchases by documenting novel evidence that country-level EPU is a key institutional factor shaping firms' decisions to purchase D&O insurance.

The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.

The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.

This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.

By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

The fashion sector is complex. It involves multiple actors with distinct and potentially conflicting interests, forming a value ecosystem. Thus, knowing the interested parties and belonging to the fashion sector may be a means to promote technological innovation, such as products with wearables. The purpose of this paper to identify the participants of the fashion ecosystem from the perspective of wearable technologies and develop a conceptual model.

The present work aims to identify the participants (actors) and develop a conceptual model of the fashion ecosystem from the perspective of wearable technologies. The systematic literature review is the recommended method to qualitatively analyze documents and identify the interested parties (actors) in the fashion sector in order to design the proposed conceptual model.

From the studies, the conceptual model of the fashion value ecosystem was designed, and the wearable product was considered its core business. The studies identified addressed ecosystems of fashion value in general but not specific to wearable products and their relations with other complementary industries.

The model was designed using secondary data only. Its validation is relevant through interviews with experts.

In terms of relevance, when conducting a systematic literature review, there were no studies that included wearable technologies in the fashion ecosystems discussed and their relations with other industries. The topic of wearables is an emerging subject that needs further research aiming to insert this technology in productive sectors.

This paper aims to examine the mediating role of knowledge sharing (KS) on the relationship between the transformational leadership (TL) and innovation in banks.

Quantitative analysis was conducted by using the structural equations modeling with AMOS 24 to examine the influence of the mediating role of KS on the TL–innovation relationship. Data were collected from 310 employees at 27 banks in Lebanon.

The research highlights that leaders exhibiting transformational behavior were able to promote knowledge-sharing culture that enhances the generation of new ideas, products and processes. The findings confirmed that KS mediates the association of TL and innovation.

The findings point to how TL mobilizes employees to engage in innovative products and processes by encouraging a knowledge-sharing culture.

The research findings advance the understanding of how TL stimulates innovation and highlights the benefits gained by cultivating KS to generate more innovative outcomes.

Exploring the intrinsic connection between the ecological environment and the digital economy and empirically testing how the level of digital economic development affects the ecological environment. Using the entropy weighting method to analyze the weights of the indicators in the digital economic development level and ecological environment system to explore the factors that have the greatest impact on the ecological environment in the indicator system of the digital economic development level so as to deepen the theoretical understanding of the relationship between the level of development of the digital economy and the ecological environment. Explore the regional heterogeneity of the level of development of the digital economy to promote the healthy development of China’s ecological environment proving the difference in the level of development of the digital economy in the east west and central regions of China and the difference in the effect on the ecological environment.

Based on the panel data of 30 provinces in China from 2013 to 2021 this paper fits the index system of digital economy development level with three factors. A digital infrastructure digital industry and digital application combines environmental pollution and energy consumption to construct ecological environment indicators and explored the impact of digital economy development level on the ecological environment by using the entropy weight method and the random effect model.

The findings indicate that the degree of digital economic development has a positive and significant impact on promoting the healthy development of the ecological environment, in which the digital industry has the greatest impact on the ecological environment. Meanwhile, the improvement of industrial structure also has a positive effect on the improvement of the ecological environment, whereas the level of human capital inhibits the healthy development of the ecological environment, and the governmental support fails to effectively and significantly promote the improvement of the ecological environment. Furthermore, the empirical research indicates that the level of digital economy development has obvious regional heterogeneity on the healthy development of the ecological environment: the eastern and central regions have a significant effect, while the western region has a less significant effect.

Although domestic and foreign scholars and experts have conducted sufficient studies on the ecological environment and the development level of digital economy respectively, there are few studies on the empirical analysis of the positive significance and regional heterogeneity of the impact of the development level of digital economy on the ecological environment, which can be supplemented and referred to in this study. At the same time, it also provides intellectual support for our country to achieve high-quality development of digital economy and efficient governance of ecological environment.

In the post-pandemic period and following widespread inoculation against the infection, this research aims to pinpoint the variables that affect consumers' behavioural intentions (BIs) towards online food delivery (OFD) services. The study goes further to investigate the potential impact of vaccine confidence (VC) in modifying the association between consumers' BI to utilise OFD services and their actual usage behaviour (UB).

Using information gathered through a structured questionnaire from 372 Indian customers, a proposed model based on the technology acceptance model (TAM) and theory of planned behaviour (TPB) models was put to the test using structural equation modelling (SEM).

Results demonstrate that perceptions of ease of use, attitude (ATT) and perceived behavioural control (PBC) have a favourable and significant impact on behaviour intention amongst Indian OFD users. Contrary to what the TAM and TPB models had predicted, perceived usefulness (PU) and subjective norms (SN) did not significantly affect the BI of the sample of Indian OFD users. Furthermore, the association between BI and actual UB of OFD users is not moderated by the consumers' VC.

The study contributes by shedding light on the variables that affect Indian OFD users' BIs after the coronavirus disease 2019 (COVID-19) pandemic era and mass immunisation and whether VC has a role to play in affecting consumer behaviour, which will aid OFD service providers, eateries and marketers in redesigning their marketing plans.

The present study is the first in making a literary contribution through analysis of the moderating effect of VC on the relationship between BI and actual UB. Additionally, this study presents evidence from India, one of the first nations to implement widespread COVID-19 inoculation.

The purpose of this paper is to measure Chinese industries’ eco-efficiency during 2006-2013. The Chinese industry attained rapid achievement in recent decades, but meanwhile, overconsumption of energy and environmental pollution have become serious problems. To solve these problems, many research studies used the data envelopment analysis (DEA) to measure the Chinese industry’s eco-efficiency. However, because the target set by these works is usually the furthest one for a province to be efficient, it may hardly be accepted by any province.

This paper builds a new “closest target method” based on an additive DEA model considering the undesirable outputs. This method is a mixed-integer programming problem which can measure the ecological efficiency of provinces and more importantly guide the province to perform efficiently with minimum effort.

The results show that the eco-efficiency of Chinese provinces increased at the average level, but the deviations remained at a larger value. Compared to the “furthest” target methods, the targets by the approach proposed by this study are more acceptable for a province to improve its performance on both economy and environment counts.

This study is the first attempt to introduce the closest targets concept to measure the eco-efficiency and set the target for each provincial industry in China.

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.

This paper aims to investigate the relationship between green human resource management (GHRM) practices and employee innovative work behaviour in the hospital. Although previous studies have examined the association between GHRM and various organisational outcomes, its nexus with employee innovative work behaviour has been largely unexplored.

This study used a quantitative approach and tested hypotheses. The research design adopted both an explanatory and descriptive approach since there were limited past data or studies to reference. The study population was human resource and administrative managers at Korle Bu Teaching Hospital who have implemented GHRM practices. The sample size consisted of 264 respondents, selected using simple random sampling. Data were collected through structured questionnaires.

The collected data were analyzed using descriptive statistics, correlation and regression analysis. The results revealed that green training, green hiring and green compensation were significant predictors of innovative work behaviour among employees.

This study contributes to the understanding of the impact of GHRM practices on employee innovative work behaviour in the healthcare sector. The study recommends that organisations should view their training investments as financial investments and focus on hiring individuals with strong environmental sensibilities. Additionally, effective reward criteria should be developed to promote GHRM practices.