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Since the performance of vehicular users and cellular users (CUE) in Vehicular networks is highly affected by the allocated resources to them. The purpose of this paper is to investigate the resource allocation for vehicular communications when multiple V2V links and a V2I link share spectrum with CUE in uplink communication under different Quality of Service (QoS).

An optimization model to maximize the V2I capacity is established based on slowly varying large-scale fading channel information. Multiple V2V links are clustered based on sparrow search algorithm (SSA) to reduce interference. Then, a weighted tripartite graph is constructed by jointly optimizing the power of CUE, V2I and V2V clusters. Finally, spectrum resources are allocated based on a weighted 3D matching algorithm.

The performance of the proposed algorithm is tested. Simulation results show that the proposed algorithm can maximize the channel capacity of V2I while ensuring the reliability of V2V and the quality of service of CUE.

There is a lack of research on resource allocation algorithms of CUE, V2I and multiple V2V in different QoS. To solve the problem, one new resource allocation algorithm is proposed in this paper. Firstly, multiple V2V links are clustered using SSA to reduce interference. Secondly, the power allocation of CUE, V2I and V2V is jointly optimized. Finally, the weighted 3D matching algorithm is used to allocate spectrum resources.

Of critical concern to the world is the need to reduce consumption and waste of natural resources. This study provides a multi-level exploration of the ways situational and transformational links between levels and challenges are related to the adoption and utilization of material flow cost accounting in Vietnam, to encourage green productivity.

Based on triangulation of public documents at different institutional levels and a set of semi-structured interviews, situational and transformational links and challenges for material flow cost accounting in Vietnam are examined using purposive and snowball sampling of key actors.

Using a multi-level framework the research identifies six situational and transformational barriers to implementation of material flow cost accounting and suggests opportunities to overcome these. The weakest links identified involve macro-to meso-situational and micro-to macro-transformational links. The paper highlights the dominance of meso-level institutions and lack of focus on micro transformation to cut waste and enable improvements in green productivity.

The paper identifies ways for companies in Vietnam to reduce unsustainability and enable transformation towards sustainable management and waste reduction.

The paper is the first to develop and use a multi-level/multi-time period framework to examine the take-up of material flow cost accounting to encourage transformation towards green productivity. Consideration of the Vietnamese case builds understanding of the challenges for achieving United Nations Sustainable Development Goal number 12, to help enable sustainable production and consumption patterns.

While much attention has been given to work-related factors influencing turnover intention through affective commitment, little focus has been directed to non-work factors affecting the service industry. Hence, this study aims to investigate the impact of links, fit and sacrifice, representing off-the-job embeddedness in the community, on turnover intention in the hospitality industry of Ghana: Sub-Sahara Africa using the theory of conservation of resources (COR) and social exchange. The model has been extended to include affective commitment as the mediating mechanism.

A multi-wave technique was used to collect data through a questionnaire from 341 full-time frontline hospitality employees in Ghana. The responses were analysed using AMOS software structural equation modelling.

The findings show that links, fit and sacrifice significantly influence employees’ turnover intentions. Moreover, it has been observed that affective commitment decreased the negative relationship and partly mediated the main relationship between the dimensions of off-the-job embeddedness and turnover intention.

The study’s results and academic, practical implications and limitations are discussed for future research.

This study emphasises the theory of COR to demystify community factors employees deem as valued resources, which lighten up their commitment to their organisation and decrease their intent to leave.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

This paper aims to investigate how a US firm’s political landscape affects the integration of environmental, social and governance (hereafter ESG) measures in CEO compensation contracts, thereby affecting the firm’s ESG performance and credit rating.

Based on the results of state senatorial and presidential elections and the location of a US firm’s headquarters, the authors categorize whether a firm has a political environment that is predominantly Democratic (blue) or Republican (red). The empirical analyses are based on a sample of US firms in the period 2014–2021.

The authors find that firms in blue states are more likely to link CEO compensation to ESG performance measures. Further, the results show that firms in blue states with ESG-linked compensation contracts have better ESG performance. Lastly, the authors find evidence that a firm’s ESG performance has a positive impact on its credit rating, but the impact is weakened if firms in red states link ESG performance to executive compensation.

To the best of the authors’ knowledge, this is the first research that explores how a firm’s political environment affects the use of ESG performance measures in CEO compensation contracts. Furthermore, the authors contribute to the literature by showing evidence that the political environment interacts with the impact of ESG-linked compensation incentives on the firm’s ESG performance and, thus, its credit rating.

The purpose of this study is to examine the underexplored link between entrepreneurship education (EE) and graduate employability in the higher education (HE) sector in the United Kingdom (UK).

The study draws on a thematic content analysis of semi-structured interviews with 45 professionals in UK HE, representing the “supply” side of EE.

The findings demonstrate a unidirectional link between EE and employability outcomes. This link is affected by societal, stakeholder-related, and teaching and learning-related factors.

Although the value of universities’ initiatives connecting EE and employability for economic development is emphasized, the study does not provide direct empirical evidence for this effect. Macroeconomic research is needed.

EE and employability would benefit from knowledge exchange between universities’ stakeholders and a broader understanding of what constitutes a valuable graduate outcome.

The study reveals the benefits of EE on a micro level. Participation in EE supports the connection between individual investments in HE and employability.

Based on human capital theory, many policymakers regard EE as a vehicle through which the relationship between investments in HE and career success on a micro level and economic growth on a macro level can be nurtured. Challenging this logic, the study highlights the potential of institutional theory to explain a contextualization of the link between EE and employability on a national level.

Previous research has explored the link between sustainability disclosure and reputation but produced contradictory results. This study aims to clarify the sustainability disclosure–reputation relationship through a quantitative analysis of the correlations between these variables reported in empirical research papers. The second objective was to determine how various moderators affect the sustainability disclosure–reputation link.

The meta-analysis was based on a systematic review of the literature covering empirical research on the corporate sustainability disclosure and reputation relationship. A total of 92 articles were meta-analyzed to compile their findings on four extrinsic moderators: company size, ownership, stock listing status and activity sector.

The findings confirm that a significant positive correlation exists between corporate sustainability disclosure and reputation. The moderator analysis also revealed that companies’ different characteristics can explain researchers’ divergent results.

The results have considerable practical relevance for organizational management. First, they can motivate managers to improve and disclose their company’s social and environmental impacts to strengthen their reputation, which in turn will help accelerate the achievement of the Sustainable Development Goals. Second, the findings can ensure organizations develop disclosure and reputation management strategies adapted for each firm’s size, ownership, stock listing status and activity sector.

The results have considerable practical relevance for organizational management. First, they can motivate managers to improve and disclose their company’s social and environmental impacts to strengthen their reputation, which in turn will help accelerate the achievement of the Sustainable Development Goals. Second, the findings can ensure organizations develop disclosure and reputation management strategies adapted for each firm’s size, ownership, stock listing status and activity sector.

To the best of the authors’ knowledge, this meta-analysis is the first to clarify the link between disclosure and reputation, which makes a unique contribution to the field of social and environmental accounting. A larger sample of primary research was collected, and key extrinsic moderators were examined to explain prior studies’ contradictory findings.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

This study uses relationship marketing theory to explore affective and calculative commitment as mediators in the delight–loyalty link. Furthermore, it investigates the role of perceived employee service delivery skills, perceived value and trust in the relationships between delight, affective commitment, calculative commitment and loyalty.

A descriptive research approach was applied, and the data were collected from 332 retail banking customers in an emergent market who are overall satisfied with their bank. A self-administered questionnaire collected data from 332 respondents who adhered to the stipulated requirements to participate in the study. These respondents were selected through purposive and convenience sampling. The constructs’ interrelationships were analysed via structural equation modelling. The measurement and structural models were also assessed.

Affective and calculative commitment and delight impact loyalty. Both affective commitment and calculative commitment were found to mediate the relationship between delight and customer loyalty.

The study enhances an understanding of the role of affective and calculative commitment in strengthening the delight–loyalty link from a relationship marketing theory perspective.

The study provides guidance to the retail banking industry in emerging markets on the importance of affective and calculative commitment in strengthening the delight–loyalty link. It further informs retail banks of the need to provide banking customers with products and service value that exceed their expectations to strengthen their future commitment and loyalty to their bank.

Guided by relationship marketing theory, the role of affective and calculative commitment in mediating the delight–loyalty link in an emerging market context is uncovered.

Building on social exchange theory (SET), the main aim of this paper is to empirically study the impact of high-commitment work practices (HCWPs) systems on radical innovation. Additionally, the paper examines the mediating roles of employee innovative work behaviour (IWB) and knowledge sharing (KS) in the relationship between HCWPs and radical innovation.

Using a survey questionnaire, data were collected from employees working in pharmaceutical, manufacturing and technological industries in Jordan. A total of 408 employees participated in the study. Structural equation modelling (SEM) using AMOS v28 was employed to test the research hypotheses.

This research found that HCWPs in the form of a bundle of human resource management (HRM) practices are significant for employee IWB and KS. However, similar to previous studies, this paper failed to find a direct significant impact for HCWPs on radical innovation. Rather, the impact was mediated by employee IWB. Additionally, this paper found that HCWPs are significant for KS and that KS is significant for employee IWB.

Distinctively, this paper considered the mediating effect of employee IWB on radical innovation. Extant research treated IWB as a consequence of organisational arrangements such as HRM practices; this paper considered IWB as a foundation and source for other significant organisational outcomes, namely radical innovation. Additionally, the paper considered employees' perspectives in studying the relationship between HRM, KS, IWB and radical innovation.