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Based on the resource bricolage theory, we investigate the impact of proactive market orientation and responsive market orientation on firms’ disruptive green innovation. We also examine the impact of resource bricolage on disruptive green innovation and the mediating role of resource bricolage.

Quantitative data were collected from 232 firms in China. Structural equation modelling was used to test hypotheses.

The result show that proactive market orientation had positive effect on firm’s disruptive green innovation, whereas responsive market orientation had negative effect on firm’s disruptive green innovation. In addition, resource bricolage positively promotes firm’s disruptive green innovation. Resource bricolage played a mediating role between proactive market orientation and disruptive green innovation. Resource bricolage had a suppressing effect between responsive market orientation and disruptive green innovation.

This study makes up for the deficiency of the existing research on the relationship between market orientation and enterprise disruptive green innovation, improves the guidance mechanism of disruptive green innovation.

This study investigates whether the visualization of agricultural products influences consumers’ purchase intentions in the context of farmer-assisted livestreaming in China. Moreover, it explores the moderating effect of packaging functionality and the mediating effect of consumer trust.

Consumers in China from multiple social media platforms participated in this survey, which yielded 333 valid responses for analysis.

The results revealed a positive relationship between the video presentation about the agricultural production process and consumers’ purchase intention, which is mediated by consumers’ trust. Meanwhile, packaging functionality moderates the relationship between agricultural product visualization and consumers’ purchase intentions as well as the indirect effect of consumers’ trust.

This study extends the application of the stimulus-organism-response (SOR) model to the field of farmer-assisted livestreaming. By building a more detailed model, this study adds to knowledge on the influencing mechanisms of consumers’ purchase intentions in farmer-assisted livestreaming.

The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.

This paper aims to examine whether managerial sentiment, extracted from annual reports, is associated with corporate risk-taking in the context of Chinese companies. This study expands the vein of literature on overconfidence theory.

By leveraging textual analysis on Chinese listed companies’ annual reports, the authors construct firm-level managerial sentiment during 2007 and 2021 to examine how managerial sentiment influences corporate risk-taking after control for firm characteristics. Corporate risk-taking is denoted by corporate investment engagements: capital expenditures and net fixed asset investment.

Results show that incentives for corporate risk-taking are likely to increase with the positive managerial sentiment and decrease with the negative sentiment in companies’ annual reports. Positive managerial sentiment is associated with over-/under-investment and low/high investment efficiency. Further additional tests show that the managerial sentiment effect only holds during low economic uncertain years and samples of private-owned firms. Furthermore, the robust tests indicate that there is no endogenous issue between managerial sentiment and corporate risk-taking.

Annual report textual-based managerial sentiment may not perfectly reflect managers’ lower frequency sentiment (e.g. weekly, monthly and quarterly sentiment). Future studies could attempt to capture managers’ on-time sentiment by using media sources and corporate disclosures.

To the best of the authors’ knowledge, this paper is the first research to provide insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach of measuring managerial sentiment might be a solution to monitoring managerial class.

This paper contributes to the literature on accounting and finance studies, adding another piece of empirical evidence on content analysis by examining a unique language and institutional context (i.e. China). Besides, the paper notes that in line with the English version disclosure, based on Chinese semantic words, managerial sentiment in the Chinese-speaking world has magnitude on corporate decisions. The research provides insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach to measuring managerial sentiment may be a practical solution to monitoring managerial class.

Based on the resource-based view (RBV) theory, this study examines how supply chain digitalisation affects firms’ performance by enabling firms to build supply chain agility and innovation capability.

Drawing from the dataset of 271 firms in the United Arab Emirates (UAE), we used structural equation modelling to validate the models. Mediation and moderation analyses were performed to test the research hypotheses.

The results suggest a positive correlation between supply chain digitalisation and a company’s performance, fully mediated by both supply chain agility and innovation capability. The interplay between supply chain agility and innovation capability has the potential to result in unfavourable outcomes for a firm’s performance. These results provide valuable insights into supply chain management during digital transformation.

The study advances the extant research on the antecedents of a firm’s performance by incorporating supply chain digitalisation and mediating mechanisms of supply chain agility and innovation capability that serve as a conduit between supply chain digitalisation and a firm’s performance based on RBV.

This study aims to examine whether and how corporate sustainability capability influences energy efficiency through competitive intensity and slack resource availability.

The authors applied a two-wave research design and administered a survey questionnaire to senior-level managers of 78 ISO-14001 and ISO-50001 certified manufacturing companies. The authors use a multi-method approach for data analysis. AMOS 23 software was applied for covariance-based structural equation modeling. In addition, SPSS 25 software was applied for hierarchical regression analysis to examine the causal relationships in the model.

The finding reveals that corporate sustainability capabilities, which include energy-saving opportunities, seizing energy-saving opportunities and resource reconfiguration, significantly improve firms’ energy efficiency. In addition, competitive intensity and slack resource availability positively moderated the relationship between corporate sustainability capability and energy efficiency.

To the best of the authors’ knowledge, this study is the first to examine the link between corporate sustainability capability and energy efficiency in developing countries such as Pakistan. Although the influence of various corporate sustainability capabilities on sustainable performance has been widely examined in the literature, the role of corporate sustainability capability has been limitedly explored with energy efficiency. This study extends the literature by adding to the knowledge of corporate sustainability capability that enhances boundary conditions in developing countries.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This study aims to examine whether the newly available auditor tenure information is associated with non-GAAP earnings, as the recent requirement to disclose the initial year of auditor-client relationship in audit reports may give the impression that longer auditor tenure may be related to lower audit quality.

Using a sample of firm-quarters from 2017 to 2020, the authors conduct both univariate and regression analyses. We use hand-collected data for auditor tenure, SEC comment letters, and non-GAAP variables.

First, the authors find that the likelihood of disclosing non-GAAP earnings monotonically increases with auditor tenure on a univariate basis. Second, auditor tenure is negatively associated with aggressive non-GAAP reporting. Third, the authors document evidence of aggressive reporting in general; that is, items excluded in calculating non-GAAP earnings are associated with future performance. However, the association declines with longer auditor tenure. Finally, the authors report evidence that the likelihood of receiving an SEC comment letter that contains non-GAAP comments decreases with longer auditor tenure.

The results show that regulators need to consider both GAAP and non-GAAP disclosures’ costs and benefits when enacting auditor tenure regulation. Investors can benefit from the findings in evaluating the quality of non-GAAP earnings. The findings are also relevant to the SEC when allocating limited resources in monitoring non-GAAP reporting.

To the best of the authors’ knowledge, this is the first study showing that auditor tenure is associated with the quality of non-GAAP earnings. Given that financial reporting quality should be understood as a comprehensive system comprising both mandatory and voluntary disclosures, this study complements the literature that examines the effect of auditor tenure on financial reporting quality using GAAP reporting.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.