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Effective cooperative communication and knowledge management capabilities are particularly important in the cross-team cooperation. Based on the social exchange theory, this paper aims to further explore the role and influence mechanism of cooperative communication and knowledge sharing on co-innovation performance in open innovation projects (OIPs).

This paper takes China’s high-tech enterprises as the research object by using a paired questionnaire survey based on 168 pairs of OIPs. Hayes’ PROCESS programme and the bootstrap technique are used to test the hypothesis model and the significance of the mediation effect.

This study finds that cooperative communication is an effective mechanism for the internal and external interaction of OIPs. Knowledge sharing plays an intermediary role in the relationship between cooperative communication and co-innovation performance; both explicit knowledge sharing and tacit knowledge sharing have a significant positive impact on co-innovation performance. And the impact of cooperative communication on co-innovation performance is based on effectively promoting the knowledge sharing of partners.

This research incorporates cooperative communication, knowledge sharing and co-innovation performance into a unified research framework to study the co-innovation at the project level, enriches the research scenario on the mechanism of cooperative behaviour, deepens the understanding of the role and influence mechanism of cooperative communication and knowledge sharing on co-innovation performance in OIPs, verifies the mediating role of knowledge sharing to co-innovation, and also helps extend the social exchange theory to a new research setting.

Organizations are fast adopting new technologies such as automation, analytics and artificial intelligence, collectively called intelligent automation, to drive digital transformation. When adopting intelligent automation, there is a need to understand the success factors of these new technologies and adapt agile software development (ASD) practices to meet customer expectations. The purpose of this paper is to explore the success factors of intelligent automation and create a framework for managers and practitioners to meet dynamic business demands. Total interpretive structural modeling (TISM) framework is a suitable approach to integrate quantitative measurement with qualitative semi-structured interviews capturing the context of the individual organization environment.

This paper identified agility factors and their interrelationships using a TISM framework. TISM results were validated using a one-tailed t-test to confirm the interrelationships between factors. Furthermore, the agility index of a case project organization was assessed using a graph-theoretic approach (GTA) to identify both the triggering factors for agility success and improvement proposals.

Results showed that leadership vision, organization structure and program methodology were driving factors. The TISM model was validated statistically and the agility index of the intelligent automation case project organization was calculated to be79.5%. Here, a GTA was applied and the triggering factors for improvement of the agility index were identified.

The limitations of the study are described along with the opportunities for future research as the field evolves through the rapid innovation of technology and products.

The increasing role of digital transformation in enterprise strategy and operations requires practitioners to understand how ASD practices must be planned, measured and/or improved over time through the implementation of automation, analytics and artificial intelligence programs. The TISM digraph provides a framework of hierarchical structure to organize the influencing factors, which assists in achieving organizational goals. This study highlights the driving factors which contribute to the success of intelligent automation projects and project organizations.

This is a first attempt to analyze the interrelationships among agility factors in intelligent automation projects (IAP) using TISM and the assessment of the agility index of a case IAP organization using a GTA.

Using a sample of manufacturing firms listed in China between 2007 and 2019, first, this paper aims to examine whether peer firms influence corporate trade credit supply. Next, the authors examine the channels through which peer firms influence corporate trade credit supply by testing the predictions of rivalry and information theories. Furthermore, the authors examine the heterogeneity of the industry peer effect on corporate trade credit supply. Finally, the authors examine the economic consequences of the industry peer effect on corporate trade credit supply.

The sample includes all manufacturing firms listed on both the Shanghai and Shenzhen securities exchanges for the sample period from 2007 to 2019, and the data come from the China Stock Market & Accounting Research database. The authors use the fixed effects method to examine the industry peer effect on trade credit supply. The results are robust to a series of robustness tests. To address the potential endogeneity problem, the authors adopt appropriate instruments by estimating instrumental variable models (two-stage least square). The authors use Heckman’s two-stage model to mitigate the sample selection bias.

The authors provide strong empirical evidence showing that the industry peer effect on trade credit supply exists in the manufacturing sector. It is also found that both competitive rivalry-based and information-based theories can provide explanations of the industry peer effect on trade credit supply. This process is both active imitation and passive reaction. Additional analysis suggests that the industry peer effect on trade credit supply is more pronounced for state-owned firms, firms with low customer concentration and firms with high geographical proximity. The amplification effect and spillover effect are the economic consequences of the industry peer effect on trade credit supply. In other words, the trade credit supply based on peer effect will not only increase the liquidity risk of the firm per se but also induce and increase the liquidity risk of the industry.

The study makes some important contributions. First, the authors find robust evidence that peer firms’ trade credit supply is an important factor in explaining corporate trade credit supply, which extends the literature by connecting the firm’s trade credit supply with the peer effect. Second, the study provides a new micro-perspective for understanding that firms use trade credit supply as a tool of competition, which proves the importance of rivals’ decision-making as a determinant of corporate decisions. Third, the authors examine the industry peer effect on trade credit supply, which not only helps to guide firms to pay more attention to the potential risk and spillover effects of the trade credit supply decision-making relevance but also helps to clarify the industry interaction phenomenon of corporate decision-making behavior. It is an important practical significance to play a role as a bridge between the microlevel of the firm and the meso-level of the industry. Finally, the study provides inspiration for the formulation of industry norms and policies.

Because the nanocrystalline core is widely used in power electronic equipment, and the excitation waveform of its working mode is complex, the vibration at medium and high frequencies cannot be ignored. Therefore, this study aims to study the vibration mechanism of nanocrystalline strip and the vibration characteristics of nanocrystalline magnetic ring under different excitation waveforms.

First, the electromagnetic vibration mechanism between nanocrystalline strips is analyzed by finite element analysis, and the force of the magnetic ring with and without air gap is compared and analyzed. Then, the vibration of nanocrystalline magnetic ring under different excitation waveforms such as sine wave, triangular wave, symmetric rectangular wave and asymmetric rectangular wave is analyzed by experimental method. The acceleration time domain waveform measured by the experiment is analyzed by fast Fourier transform, and the vibration is analyzed according to the spectrum.

Because of the increase of magnetic flux leakage, the volume force density and the Maxwell force on the surface of the nanocrystalline magnetic ring will increase after the air gap is opened, resulting in the intensification of vibration. Under symmetric/asymmetric rectangular wave excitation, the vibration acceleration varies with the duty cycle. Due to the influence of harmonic excitation, the relationship between the main frequency of vibration and the excitation frequency is not two times, and its multiple decreases with the increase of excitation frequency.

The research and analysis of this paper can promote the application of new magnetic materials in electrical equipment in small and medium-sized and medium- to high-frequency fields.

The deployment of artificial intelligence (AI) technologies in travel and tourism has received much attention in the wake of the pandemic. While societal adoption of AI has accelerated, it also raises some trust challenges. Literature on trust in AI is scant, especially regarding the vulnerabilities faced by different stakeholders to inform policy and practice. This work proposes a framework to understand the use of AI technologies from the perspectives of institutional and the self to understand the formation of trust in the mandated use of AI-based technologies in travelers.

An empirical investigation using partial least squares-structural equation modeling was employed on responses from 209 users. This paper considered factors related to the self (perceptions of self-threat, privacy empowerment, trust propensity) and institution (regulatory protection, corporate privacy responsibility) to understand the formation of trust in AI use for travelers.

Results showed that self-threat, trust propensity and regulatory protection influence trust in users on AI use. Privacy empowerment and corporate responsibility do not.

Insights from the past studies on AI in travel and tourism are limited. This study advances current literature on affordance and reactance theories to provide a better understanding of what makes travelers trust the mandated use of AI technologies. This work also demonstrates the paradoxical effects of self and institution on technologies and their relationship to trust. For practice, this study offers insights for enhancing adoption via developing trust.

Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.

The purpose of this paper is to present an up-to-date survey on the non-orthogonal multiple access (NOMA) technique with co-operative strategy, a fast-evolving fifth-generation (5 G) technology. NOMA is used for serving many mobile users, both in power and code domains. This paper considers the power-domain NOMA, which is now discussed as NOMA.

The first part of the paper discusses NOMA-based cooperative relay systems using different relay strategies over different channel models. In various research works, the analytical expressions of many performance metrics were derived, measured and simulated for better performance of the NOMA systems. In the second part, a brief introduction to diversity techniques is discussed. The multiple input and multiple output system merged with cooperative NOMA technology, and its future challenges were also presented in this part. In the third part, the paper surveys some new conceptions such as cognitive radio, index modulation multiple access, space-shift keying and reconfigurable intelligent surface that can be combined with NOMA systems for better performance.

The paper presents a brief survey of diverse research projects being carried out in the field of NOMA. The paper also surveyed two different relaying strategies that were implemented in cooperative NOMA over different channels and compared several performance parameters that were evaluated and derived in these implementations.

The paper provides a scope for recognizable future work and presents a brief idea of the new techniques that can be united with NOMA for better performance in wireless systems.

Based on the chain liability and green halo effects, this study uses the perspective of multi-tier supply chain management to examine the impact mechanism and boundary conditions of suppliers' green innovation types on consumers' willingness to participate in value co-creation with focal firms from the perspective of multi-tier supply chain management.

Using four situational experiments, 660 participants were recruited in Credamo, and SPSS 23.0 was used for data analysis. Experiments 1a and 1b verify the effect of suppliers' green innovation on consumers' willingness to participate in value co-creation with focal firms; experiment 2 examines the mediating effect of green sincerity perception; and experiment 3 explores the moderating effect of innovation proactiveness.

The results show that suppliers' green innovation efforts are more sincere when they are substantive (vs. symbolic), thereby generating higher value co-creation intentions. As a driving force, innovation proactiveness moderates the influence of suppliers' green innovation types on consumer's willingness to co-create value with focal firms.

This study enriches the literature on green supply chain management (GSCM) and consumers' willingness to co-create value. Furthermore, this study provides firms with practical guidance to improve marketing performance and green innovation practices through multilevel GSCM.

This study aims to address how to facilitate more community members making purchases in social commerce communities. The research is expected to shed new light on the underlying process by which individuals’ social networks influence their purchases in social commerce communities.

An online survey and secondary archive data are presented to confirm all the hypotheses.

Community members’ out-degree ties show a positive effect on their attachment to other members, as well as to the community. Community members’ attachment to the community has a positive influence on their purchases made in the e-commerce modules of social commerce communities and mediates the effect of their attachment to community members. The study establishes a theoretical framework to reveal how community members’ social networks influence their purchases in social commerce communities.

The findings of this study provide new insights for managers and designers of new social commerce communities to inspire them to achieve their goal of keeping consumers making purchases in the e-commerce modules of social commerce communities.

Firstly, this study draws on attachment theory to explain why community members make purchases in a social commerce community. Then, the study enriches the research on social network ties and attachment theory by initially integrating the social network perspective with attachment theory to examine the effects of social network ties on different types of attachment.