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Recent studies suggested that owner dynamic capabilities (ODCs) enabling public owners of megaprojects to activate, orchestrate and reorganize resources to uncertainties were beneficial to improving the project resilience of megaprojects. However, most of them pay insufficient attention to the specific context of long cycles and deep uncertainty in megaprojects, neglecting the causal complexity that different dimensions of ODCs and learning mechanisms interact with each other in terms of enhancing project resilience. Therefore, this study aims to systematically unveil the complex causality among ODCs, learning mechanisms and project resilience of megaprojects.

This study introduces a configurational perspective to explore how multi-dimensional ODCs combine to improve project resilience in megaprojects along with different organizational learning mechanisms and learning orientations. Based on 330 ODC events in 19 construction megaprojects, a multi-temporal crisp-set qualitative comparative analysis method is adopted to extract configurations of ODCs for project resilience improvement and unveil their evolution features over the whole megaproject lifecycle.

Six configurations are identified for improving project resilience in megaprojects, including cognition-dominant, cognition-deficient, transformation-dominant, innovation-driven, value-co-creation and exploitative-transformation configurations. The results also indicate that distinct megaproject stages appeal to corresponding ODC configurations for project resilience improvement under unique uncertain contexts.

This study not only makes theoretical contributions to the literature on dynamic capability and project resilience in the megaproject management field but also provides useful practical guidance for public owners of megaprojects to better utilize ODCs for project resilience improvement.

To fill the gap, this article examines the inter-governmental collaboration mechanisms behind the platform curtain.

Behind the curtain is to look at what makes things happen backstage. For collaborative e-governance platforms, scholars have assumed that technological factors and user characteristics are the determinants for platform success. Little attention has been paid to the issue of how multiple governments, acting as platform co-builders and co-operators, interact and collaborate backstage to provide integrated e-services.

Based on data from survey questionnaires sent to government employees, the results show that governments’ information processing capacities cannot directly affect collaboration; however, these capacities can impact collaboration via the mediating variable of horizontal relations. In addition, we found that higher-ranking authorities are better suited to intervene once horizontal relations have been established and that more adaptable organizations are better at forming horizontal relations with peers. For governments participating in collaborative e-governance platforms, our findings are practically applicable.

The research question reads as: How do various government departments acting as platform co-builders and co-operators judge their collaboration performance, and what collaboration mechanisms contribute to it? We study this research question by constructing a conceptual model based on the Organizational Information Processing Theory (OIPT) and the Collaborative Governance Theory (CGT), both suggesting information processing capacities, organizational flexibility, horizontal relations and vertical intervention as indispensable factors influencing collaboration performance in ICT-supported groupwork. We propose and test four hypotheses on the relationships among these four factors to reveal the inter-governmental collaboration mechanisms for cross-government platformisation projects.

This paper aims to examine whether CEOs with an engineering background increase corporate investment efficiency (CIE). The authors further investigate the role of engineering directors on boards of the above association.

Drawing from upper-echelon theory, which suggests that corporate outcomes are a reflection of its top management characteristics, the authors hypothesise a positive association between engineer CEOs and CIE and a positive moderation role of the proportion of engineer directors on boards in the above association. The authors examine this link using a sample of Australian Securities Exchange 200 firms from 2015 to 2022. Engineer CEO data is hand-collected from corporate annual report biographies and investment efficiency is a measure that captures whether the investments are maintained at optimal levels relative to industry-year benchmarks, following the approaches of Biddle et al. (2009), Chen et al. (2011) and the average values of both models.

The results indicate support for the hypotheses, revealing that firms managed by engineer CEOs have higher investment efficiency than their counterpart firms. This association is exacerbated in the presence of a higher proportion of engineer directors on boards. The results are robust to year and industry-fixed effects, propensity score matching, alternative measures of investment efficiency and robust standard errors. Our results also remain valid for an industry sub-sample using certain industries in which engineering expertise maybe more desirable (e.g. metals and mining).

By showing that engineer CEOs are significantly associated with CIE, the authors contribute to upper-echelon literature examining the link between CEO characteristics and corporate outcomes, particularly, investment decision efficiency. The influence of engineering background on corporate outcomes is less examined in the literature; thus, the authors contribute to this thin literature.

The findings are informative to potential investors in evaluating firms’ investment efficiency before investing in firms. For example, firms with engineer CEOs are likely to maintain efficient investment levels in future years.

Despite the growing importance of digital transformation, few studies have investigated its precise effects on firm efficiency. This research explores the differential effects of digital transformation on the profitability and marketability of manufacturing firms.

We analyze the relationship between digital transformation and firm efficiency using a dataset of Chinese-listed manufacturing firms from 2011 to 2023.

The results indicate that digital transformation improves marketability and has a U-shaped relationship with profitability. Moreover, industry competition amplifies the positive effect of digital transformation on marketability but attenuates its U-shaped effect on profitability. In contrast, media coverage attenuates the positive effect of digital transformation on marketability and amplifies its U-shaped effect on profitability.

While the existing conclusion about the efficiency of digital transformation is inconsistent, this research enriches the literature on digital transformation and provides insights for improving firm efficiency in terms of both profitability and marketability.

The Ukrainian conflict, a real-world case study, vividly illustrates the threat autocratic regimes pose to democratic systems on a global scale, symbolizing a battle between freedom and authoritarianism. It is a stark reminder of the destabilizing effects of the spread of autocracy. This trend has replaced the previous wave of global democratic expansion and puts international peace and ecological sustainability at risk. Through a meticulous and comprehensive examination of contemporary autocratic rise, this study presents compelling evidence that clarifies the harmful outcomes of democratic erosion in emerging autocracies and their negative influence on global peacekeeping efforts and environmental preservation initiatives. In essence, this research study underscores the complex interplay between conflict and harmony and the dynamics of autocratic proliferation and democratic decline, all of which collectively shape the landscape of global security and environmental sustainability initiatives.

Recent accounting research using data envelopment analysis (DEA) measures firm performance using accounting measures from annual reports, which are readily available from electronic databases (e.g. Demerjian et al., 2013; Schwab, 2022). This approach differs from conventional DEA studies that analyse productivity and use internal data about physical quantities of production inputs and outputs. Using accounting measures instead of physical measures presents challenges as accounting measures aggregate physical quantities using unknown but fluctuating prices. This raises the issue of what these DEA models measure. This study aims to examine how price variability influences DEA results when measuring firm performance and identifies implications for future accounting research.

This study uses a Cobb–Douglas function to simulate physical data for input and output quantities, which are then priced to form accounting measures that incorporate different levels of price variability. These simulated accounting data are used to estimate DEA results. The results using physical data and accounting data are compared to identify the impact of increasing levels of price variation and sample size on the comparability of DEA results.

The study confirms the theoretical argument that accounting measures can be used in DEA to measure productivity when prices are identical across a sample of firms. Moreover, where price variability is low, large samples can also reliably estimate productivity when using accounting measures. This measure of productivity fundamentally underpins financial performance and provides a new dimension of firm performance that can be measured by accounting measures. However, where price variability is high, DEA using accounting measures cannot estimate productivity and can only be used for benchmarking financial performance. In this case, DEA provides an alternative measure for financial performance, which incorporates multiple dimensions and can extend traditional financial analysis approaches by providing a more comprehensive measure.

Despite calls for investigation (Camanho et al., 2024; Färe et al., 2017; Zelenyuk, 2020), evidence has been scarce regarding the impact of price variability when using accounting measures in DEA. Understanding this impact is key to understanding the nature of DEA results produced using accounting measures, as this can affect the interpretation and use of those results. This study is the first to focus on the impact of price variability on accounting measures within DEA and suggests new avenues for accounting research using this performance measurement method.

Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial for measuring the development progress and guiding continual improvements of HSM-GI. Since this process of HSM-GI can be regarded as complex and interactive, a holistic picture is often required to describe the interrelations of its antecedents and consequences. In this respect, this study aims to construct a causality network indicator system and proposes a synergy evaluation method for HSM-GI.

Firstly, based on the Driver force-State-Response (DSR) causal-effect framework, this study constructs a holistic indicator system to analyze the interactions between environmental and human concerns of HSM-GI. Secondly, owing to the imprecision of human cognition and synergy interaction in the evaluation process, a flexible hesitant fuzzy (HF) superiority-inferiority synergetic evaluation method is presented. This method quantifies the strengths of causal relationships and expresses the incentives and constraints attitudes of humans. Finally, the proposed framework is applied to six HSMs in the electronic technology industry.

The driving force and state of the HSM-GI system exhibit an upward trend, while the response continues to decline due to changing market demands. The order and synergy degree have shown an increasing trend during 2021–2023, particularly significant for BOE and Haier Smart Home. HSM-GI systems with higher scores mostly have functional coordination and a coherent synergy structure.

This study demonstrates the proposed approach’s applicability and assists policymakers in formulating targeted strategies for green innovation systems.

The purpose of this study is to undertake a systematic literature review (SLR) on intellectual capital disclosure (ICD), focusing on its role in fostering competitive advantage.

Following the SLR process, the study identified 84 papers published in high-ranking journals over a 19-year span, providing insights into descriptive outcomes, research limitations and future research directions.

The results show that ICD research peaked in 2022, with the Journal of Intellectual Capital leading with the highest number of ICD publications. Resource-based theory was found to be the most applied theoretical framework, with developed country-specific research receiving the most attention. The use of small sample size, a lack of longitudinal studies, reliance on a single source of data, unsuitability of control variables and a lack of comparative studies with firms operating in developing countries are the main limitations that have been noted.

This study faces constraints, primarily stemming from the selective keyword utilization and exclusive Scopus database reliance. It omits non-English papers, conference proceedings and books, potentially overlooking relevant insights.

The findings offer valuable insight for researchers, emphasizing the need for research on intellectual capital (IC) across diverse industries. Furthermore, our findings urge regulators to mandate global IC reporting to mitigate information asymmetry, while also prompting managers to enhance IC-related practices and reporting for more stakeholders’ trust.

This study provides a comprehensive overview of over two decades of ICD literature, synthesizing previous studies, identifying gaps and outlining potential directions for scholars and industry professionals in the context of competitiveness.

Based on the social exchange theory, this study aims to investigate the influence of green supplier development (GSD) on supplier green innovativeness (SGI), the mediating role of buyer–supplier cooperation and the moderating role of preferred customer status (PCS).

This study uses stratified regression analysis to test the hypothesized relationships with data collected from 385 Chinese high-tech manufacturing enterprises.

The results of regression analysis show that GSD has a significant positive effect on buyer–supplier cooperation and SGI; buyer–supplier cooperation plays a partially mediating role between GSD and SGI; PCS strengthens the positive relationship between buyer–supplier cooperation and SGI and enhances the mediating role of buyer–supplier cooperation between GSD and SGI.

Supplier participation in green innovation is of great significance to the green development transformation of China’s manufacturing industry. This study reveals the positive impact of GSD on enhancing SGI and provides specific suggestions for manufacturing enterprises to realize efficient supplier management and build mutually beneficial and win-win cooperative relationships.

This study enriches and expands the related research on SGI antecedents and reveals the mediating mechanism and boundary conditions therein, which better makes up for the lack of attention to GSD in the existing research on supplier management and can provide lessons and references for the subsequent related researches targeting the enhancement and utilization of SGI.

This paper aims to examine the effects of both transient and chronic loneliness on consumers’ variety-seeking (VS) behavior and to identify the various underlying mechanisms involved.

Four studies were adopted to clarify how transient and chronic loneliness affect consumers’ VS behavior.

Both transient and chronic loneliness promote consumers’ VS behavior. More importantly, the effect of transient loneliness on VS behavior is driven by perceived loss of control, whereas the effect of chronic loneliness on VS behavior is driven by need for uniqueness and sensation-seeking.

To the best of the authors’ knowledge, this research is the first to explore the differential roles of transient and chronic loneliness on VS behavior, which may open new avenues for future research. First, future research could investigate moderators that influence the impacts of transient and chronic loneliness on VS behavior. Second, future research could examine different participant populations and use cognitive neuroscience techniques to further verify the differential roles of these two types of loneliness on VS behavior.

This research contributes to marketing practice by providing practical guidance on how to effectively design different marketing strategies to promote VS for consumers with different types of loneliness. For consumers with transient loneliness, marketers can benefit from a concerted focus on improving consumers’ sense of control. Yet, for consumers with chronic loneliness, marketing strategies that improve consumers’ need for uniqueness will be more effective.

This research contributes to the literature on loneliness and consumer behavior, which has largely overlooked the distinct roles of different types of loneliness (i.e. transient vs chronic loneliness) in influencing consumer behavior. Specifically, this paper conducted a comparative analysis of the impacts of transient and chronic loneliness on consumers’ VS behavior and proposed that transient and chronic loneliness promote consumers’ VS behavior through divergent underlying mechanisms.