Search results

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

Customer referral programs (CRPs) are popular; however, they often generate low referral rates. The authors propose that certain CRP referral tasks may hinder consumers’ referral likelihood. This study aims to explore the effects of referral tasks (communication content and approach) on customers’ referral likelihood on social platforms and the role of self-construal.

This study establishes a theoretical model based on online social platforms and conducts three scenario-based experiments. The authors obtain data from consumers on Sojump platform and test the hypotheses using analysis of variance (ANOVA) analysis and mediation analysis in SPSS. The valid sample sizes for these three experiments are 288, 203 and 214, respectively.

Three experimental studies indicate that communication content and approach have a significant effect on referral likelihood. Furthermore, the effect of communication content on referral likelihood depends on the communication approach. Self-construal plays a moderating role in the effect of communication content and approach on perceived social costs.

CRPs typically involve tasks and rewards; consumers are asked to complete a referral task and then receive a reward. Both tasks and rewards can affect an individual’s willingness to participate; however, existing studies on CRP focus primarily on the reward component. To the best of the authors’ knowledge, this is the first study to systematically investigate the role of referral tasks (communication content and approach) in CRPs. The authors extend the related research by examining the impact of referral tasks on consumers’ willingness to recommend. In addition, this study introduces self-construal into CRPs research.

This paper identifies the development of and gaps in knowledge in various management disciplines, including international marketing in relation to political ties in emerging markets, based on a systematic review of the related literature. The paper develops a synthesized integrative framework and provides a research agenda and pathways for future research.

The study adopts the systematic literature review protocol to investigate the ways in which political ties have been examined in the management literature in various disciplines, such as international business, marketing, entrepreneurship, strategy, innovation, and organization. In total, 114 articles published in peer-reviewed journals from 2000 to 2022 were analyzed.

The authors believe that studying the impact of political ties on firm outcomes is timely and important as interest in this area of research is growing rapidly. The review reveals that the diverse conceptual and methodological approaches adopted in different management disciplines have resulted in inconclusive and mixed findings on the relationship between political ties and performance.

This is one of the few systematic literature reviews of political ties and firm performance in emerging markets. The authors clarify some of the ambiguities around the subject and offer a path forward for developing current understanding and insights. The study also highlights the major perspectives in management and clarify the similarities and differences in the conceptualization of political ties. In addition, the authors develop an integrative framework of the political ties–performance link in emerging markets.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

This study aims to elucidate the process and internal mechanism of place identity construction in traditional villages under the impact of tourism by taking Cuandixia village as a case. The research methods comprise participatory observation and in-depth interviews with the residents. The main results are as follows: the impact of tourism on traditional villages is mainly reflected in space reconstruction, livelihood change, social relations restructuring and culture change; under the impact of tourism, the representation of residents’ identity construction shows complexity, with positive and negative effects; and the place identity construction of residents affects their perception of and attitudes toward tourism. Moreover, self-esteem and self-efficacy principles play a key role in their perception of tourism. This study provides some reference for further investigation of the tourism development model and the mental mechanism of residents in traditional villages.

In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

The study aimed to analyze the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong Province.

A conceptual model of the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong province is established, which takes the business model as the mediating variable and political association as the moderating variable. Multivariate statistical analysis and the MacKinnon confidence interval method were used to analyze 418 questionnaires.

The results show that both relational embeddedness and structural embeddedness have significant positive effects on the innovation performance of high-tech enterprises in Guangdong Province. The business model has a partial mediating effect between relationship embeddedness, structure embeddedness, and innovation performance of high-tech enterprises in Guangdong Province, respectively. Political relevance has a significant negative moderating effect on the relationship between the relationship embeddedness and innovation performance of high-tech enterprises in Guangdong Province, but the moderating effect on structural embeddedness and innovation performance of high-tech enterprises in Guangdong province has not been verified.

The study of this paper also has some shortcomings: very few data research samples exist; the external factors affecting the performance of high-tech enterprises in Guangdong Province need to be further refined. The research scale needs further improvement.

In this paper, embedding theory, transaction cost theory, resource dependence theory, rent-seeking theory, new institution theory and uncertainty management theory were integrated by system attempt to reveal the mediating and moderating roles of business model and political relevance, respectively, between network embeddedness behavior and entrepreneurial innovation performance of high-tech enterprises. The research conclusions expand the relevant research in the field of entrepreneurial innovation. At the same time, the research results provide theoretical support and reference for the innovative growth of high-tech enterprises and government behavior decision-making in Guangdong province.

Network embeddedness will have a profound impact on the entrepreneurial innovation performance of high-tech enterprises. Existing research has overlooked discussing this issue from the perspective of internal and external influencing factors within the enterprise. Therefore, this study addresses this issue by (1) introducing the business model as the mediating variable from an internal perspective of the enterprise, (2) introducing political association as the moderating variable from an external perspective of the enterprise and (3) 418 original questionnaires of high-tech enterprises in Guangdong Province were used to test the effect of the study variables.

The purpose of this paper is to investigate the potential of NFTs in revolutionizing innovation management and information systems. Innovations done by firms are blatantly used by other firms to develop cheap knock-off. This leads to huge economic loses to the firm investing in research and development activities. Firms are in need of trusted, immutable and verifiable means of storing information which cannot be used by others, even if publically available without their consent. Non-fungible tokens (NFTs) appear to be one such solution to this problem that has recently attracted a lot of investor interest. Using NFTs the information is tokenized and is stored in a secure manner.

Through this scoping review, the authors investigate the influence of NFTs towards the innovation management from the dual aspects of management and information systems. This scoping review is underpinned by the five-stage framework by Arksey and O’Malley. The five stages of Arksey and O’Malley’s framework were used in this analysis to classify the literature through five stages of identifying the initial research questions; locating relevant studies; study selection; charting the data; and compiling, summarizing and reporting the results.

This study suggests that NFTs on the blockchain have significant potential to revolutionize innovation management and information systems. Theoretical frameworks used in investigating the role of digital tokens in blockchain management are mainly based on contracts, diversity theory, portfolio theory and faking likelihood theory. The study reveals gaps in the literature, particularly in the under-researched areas of behavioural psychology and social psychology theories. The appropriate regulation and regulation authority for different types of digital tokens are required. The study also presents archetypes that represent patterns in the current landscape of blockchain tokens, which have significant potential for future research and practical applications.

This study is unique in its approach to assessing the future of NFTs in the field of innovation and information management. While many existing reviews have focused on describing the progress and development of NFTs in the past, this study takes a forward-looking perspective and projects the future potential of NFTs. This innovative approach allows for a deeper understanding of the potential impact of NFTs in various fields such as entrepreneurship, innovation management and tokenomics. Therefore, this study contributes to the literature on NFTs by providing insights and recommendations for future research and practical applications.

This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge.

In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks.

Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology.

This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.