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The purpose of this research is to investigate the causal mechanisms that explain the relationship between the long-term buyer–supplier relationship and buyer performance. Building on the growing body of research on social capital in supply chain management (SCM), the authors examine how a buyer achieves superior performance in forming the enduring partnership with a supplier through two different forms of supplier embeddedness: buyer–supplier dyadic embeddedness and supplier external embeddedness.

The bootstrapping method is utilized in data analysis to examine the mediating effects of the two different forms of supplier embeddedness simultaneously on the linkage between the duration of buyer–supplier relationships and buyer performance outcomes.

The authors find that the two forms of supplier embeddedness serve as distinct conduits for the buyer to translate the long-term buyer–supplier relationship into performance effectiveness. Notably, dyadic embeddedness only mediates the linkage between the duration of buyer–supplier relationships and buyer economic performance, while supplier external embeddedness solely mediates the linkage between the duration of buyer–supplier relationships and buyer innovation performance.

This study empirically demonstrates that different forms of supplier embeddedness may benefit a buyer differentially when directed at distinct performance goals. If a buyer can leverage both buyer–supplier dyadic embeddedness and supplier external embeddedness, the buyer will overcome value creation limitations of social capital from a single source, obtaining more comprehensive performance benefits sought by developing long-term buyer–supplier relationships.

The purpose of this paper is to review the food supply chain management (FSCM) in terms of systems and implementations so that observations and lessons from this research could be useful for academia and industrial practitioners in the future.

A systematical and hierarchical framework is proposed in this paper to review the literature. Categorizations and classifications are identified to organize this paper.

This paper reviews total 192 articles related to the data-driven systems for FSCM. Currently, there is a dramatic increase of research papers related to this topic. Looking at the general interests on FSCM, research on this topic can be expected to increase in the future.

This paper only selected limited number of papers which are published in leading journals or with high citations. For simplicity without generality, key findings and observations are significant from this research.

Some ideas from this paper could be expanded into other possible domains so that involved parties are able to be inspired for enriching the FSCM. Future implementations are useful for practitioners to conduct IT-based solutions for FSCM.

As the increasing of digital devices in FSCM, large number of data will be used for decision-makings. Data-driven systems for FSCM will be the future for a more sustainable food supply chain.

This is the first attempt to provide a comprehensive review on FSCM from the view of data-driven IT systems.

This paper reviews the literature on zombie firms to provide a holistic view by delineating their formation, impact, widespread nature, prevention and policy implications.

This paper uses a systematic literature review methodology, in which 76 papers published in journals ranked on the Australian Business Deans Council (ABDC) 2022 list were reviewed. The study period was from 2000 to 2022.

Among the main findings, the widespread problems of zombie firms were evident. The authors found that consistent support, either in the form of government grants or a weak financial framework, was responsible for their formation. The suboptimal performance of factors of production, depressed job creation, low innovation and overall negative impact on economic activity are the consequences of zombification. This can be controlled by ensuring better bankruptcy codes, focused on government assistance, technology use and better due diligence by banks.

This review serves as a reference point for future researchers as a cohesive and holistic study presenting a full picture of the problem, so that the proposed solutions are robust and tenable.

This review is among the initial attempts to comprehensively study published work on zombie firms in terms of analyzing their region-specific nature, with an emphasis on definition, causes, impact and prevention.

In the context of the Industry 4.0, this paper aims to investigate the state of the art of Italian manufacturing, focusing the attention on the implementation of intelligent predictive maintenance (IPdM) and 4.0 key enabling technologies (KETs), analyzing advantages and limitations encountered by companies.

A survey has been developed by the University of Parma in cooperation with the Italian Workers' Compensation Authority (INAIL) and was submitted to a sample of Italian companies. Overall, 70 answers were collected and analyzed.

Results show that the 54% of companies implemented smart technologies, increasing quality and safety, reducing the operating costs and sometimes improving the process' sustainability. However, IPdM was implemented only by the 37% of respondents: thanks to big data collection and analytics, Internet of Things, machine learning and collaborative robots, they reduced downtime and maintenance costs. These changes were implemented mainly by large companies, located in northern Italy. To spread the use of IPdM in Italian manufacturing, the high initial investment, lack of skilled labor and difficulties in the integration of new digital technologies with the existing infrastructure are the main obstacles to overcome.

The article gives an overview on the current state of the art of 4.0 technologies implementation in Italy: it is useful not only for companies that want to discover the implementations' advantages but also for institutions or research centres that could help them to solve the encountered obstacles.

The use of social media tools by companies is common, but the links between the use of multiple social media tools by companies and stock price changes are largely unknown. Therefore, this study aims to analyze the value-relevance of social media activities on Facebook (FB), Instagram (IG), LinkedIn (LI), Twitter (TW) and YouTube (YT).

Stock market data and hand-picked social media data in this study were collected from Finland, a small language area with consistent International Financial Reporting Standards (IFRS) reporting practices, in the expectation of better comparability and lower noise in the data.This study uses correlation, regression and factor analyses for a sample of 105 Finnish public limited companies listed on the Nasdaq Helsinki stock exchange.

This paper finds evidence that social media activity is an important area of analysis and that the activity and popularity of a company in social media are value-relevant variables in forecasting stock prices.

Not all social media activities are necessarily equally important for managers and investors. Focus on visual messages in social media is recommended.

The findings of this study highlight the value-relevance of using multiple visual social media channels, particularly IG and YT. This paper suggests avenues for future research and for analyzing social media information.

Understanding customers is critical for service researchers and practitioners. Today, customers are increasingly active online, and valuable information about their opinions, experiences and behaviors can be retrieved from a variety of online platforms. Online customer information creates new opportunities to design personalized and high-quality service. This paper aims to review how netnography as a method can help service researchers and practitioners to better use such data.

A systematic review and analysis were conducted on 321 netnography studies published in marketing journals between 1997 and 2017.

The systematic review reveals that netnography has been applied in a variety of ways across different marketing fields and topics. Based on the analysis of existing netnography literature, empirical, theoretical and methodological recommendations for future netnographic service research are presented.

This paper shows how netnography can offer service researchers unprecedented opportunities to access naturalistic online data about customers and, hence, why it is an important method for future service research.

Netnographic research can help service firms with, for example, service innovation, advertising and environmental scanning. This paper provides guidelines for service managers who want to use netnography as a market research tool.

Netnography has seen limited use in service research despite many promising applications in this field. This paper is the first to encourage and support service researchers in their use of the method and aims to stimulate interesting future netnographic service research.

To address the problem that the current train operation mode that train selects one of several offline pre-generated control schemes before the departure and operates following the scheme after the departure, energy-saving performance of the whole metro system cannot be guaranteed.

A cooperative train control framework is formulated to regulate a novel train operation mode. The classic train four-phase control strategy is improved for generating specific energy-efficient control schemes for each train. An improved brute force (BF) algorithm with a two-layer searching idea is designed to solve the optimisation model of energy-efficient train control schemes.

Case studies on the actual metro line in Guangzhou, China verify the effectiveness of the proposed train control methods compared with four-phase control strategy under different kinds of train operation scenarios and calculation parameters. The verification on the computation efficiency as well as accuracy of the proposed algorithm indicates that it meets the requirement of online optimisation.

Most existing studies optimised energy-efficient train timetable or train control strategies through an offline process, which has a defect in coping with the disturbance or delays effectively and promptly during real-time train operation. This paper studies an online optimisation of cooperative train control based on the rolling optimisation idea, where energy-efficient train operation can be realised once train running time is determined, thus mitigating the impact of unpredictable operation situations on the energy-saving performance of trains.

Evidence from previous literature indicates that adopting a new innovative technology has a positive impact on a company’s business performance. Much less work has been carried out into examining whether a technology adoption has impact on corporate reputation. This paper aims to examine the latter topic in a context where social media is the channel used to share news about the introduction of a new technology. The empirical setting of the study consists of five retail companies located in the USA that decided to include Bitcoin as a payment platform.

Twitter data were used to measure how sharing news about the adoption of new technology could affect the reputation of the companies selected, keeping a clear distinction between the volume of data relating to social media responses and the sentiment expressed in the tweets. A panel vector autoregression model was used to incorporate series of data relating to news items, volume and sentiment.

The results show that the news about the adoption of a new technology has a positive impact on both the volume of tech-related tweets and the sentiment expressed in the tweets themselves, although the patterns of these two effects are different. The resulting impact decreases after a few days, both in volume and in sentiment.

The analysis has limitations that future research could address by extending and diversifying the examined companies and the social media used as data sources. The research suggests that managers in medium-sized companies can leverage on the introduction of new technologies that have a direct impact on their customers and gain reputational benefits in terms of immediate visibility.

The research introduces an additional dimension of analysis to the current stream of corporate reputation. Although the literature has already covered the dynamics of response to events on Twitter, by focusing on the adoption of the new Bitcoin technology, the paper provides novel insights.

This article analyses the trend in women digital financial inclusion in Nigeria using some digital financial inclusion indicators obtained from the global Findex database for the year 2014, 2017 and 2021. The study also analyses the relationship between women digital financial inclusion and economic growth.

The data were analysed using the two-stage least squares (2SLS) and generalised method of moments (GMM) regression estimation methods. The women digital financial inclusion indicators are the percentage of women who (1) own a mobile money account, (2) made a digital payment, (3) received digital payments, (4) made or received a digital payment, (5) own a credit card and (6) own a debit card.

The trend analysis shows a sustained, although small, improvement in women mobile money account ownership during the period, while the other indicators witnessed a decrease in 2017 and an increase in 2021, except for women credit card ownership which remained at the same level during the period examined. There is a significant positive relationship between women digital financial inclusion and economic growth. Internet usage has a significant positive effect on women digital financial inclusion in Nigeria.

Greater digital financial inclusion for women can accelerate economic growth in Nigeria. Policymakers should encourage investment in fintech and broaden access to the Internet to increase women digital financial inclusion and economic growth in Nigeria. Policymakers and practitioners in Nigeria should also work collaboratively to increase digital financial inclusion for women due to its potential to increase economic growth in Nigeria.

Existing studies did not analyse the trends in women digital financial inclusion. Existing studies did not empirically analyse the impact of women digital financial inclusion on economic growth in Nigeria. The present study fills this gap in the literature.

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.

This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.

The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.

This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.