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This study aims to explore the overall relationship between a boundary spanner and a partner firm, i.e. boundary spanner closeness to partner firm. Drawing on consumer-service provider relationship literature and the tripartite model of affect-behavior-cognition, the authors identify three key dimensions of such closeness, namely, boundary spanners’ relational ties, customer-specific capabilities and accommodative behaviors, and examine their effects on exchange outcomes in turbulent versus stable environments.

The paper examines the effects of three dimensions of boundary spanner closeness on various exchange outcomes (i.e. retailers’ cooperation, satisfaction and willingness for investment) using two industries as exemplars, characterized by distinct levels of environmental turbulence – the retailing networks of a major cell phone company and a petroleum company in China.

The results indicate that the three dimensions individually and jointly affect exchange outcomes and the interplay of customer-specific capabilities and relational ties affect exchange outcomes differently across industry turbulence.

The existing literature lacks a comprehensive understanding of the function of boundary spanners, which serve as a key relational interorganizational governance component. By identifying three key dimensions of boundary spanner closeness and examining their effectiveness in promoting exchange outcomes, this study advances the understanding of the role of boundary spanners in interorganizational governance.

This paper aims to clarify an important nuance by proposing that people attribute human mind to brands on two distinct dimensions: think and feel.

Eight studies were conducted to first develop and validate the 14-item Brand Anthropomorphism Questionnaire, and then to investigate how the two subscales, think or feel dimensions, influence consumer moral judgment of brands.

This research developed a 14-item Brand Anthropomorphism Questionnaire with two subscales, which are psychometrically sound and show discriminant validity with regard to existing brand constructs. Furthermore, think or feel brand anthropomorphism dimensions can predict consumers’ moral judgment of brands.

The present research offers preliminary evidence about the value of distinguishing between think brand and feel brand in consumer moral judgment. Further research could investigate other potential impact of the two dimensions, and possible antecedents of think/feel dimensions.

Managers can use the scale for assessment, planning, decision-making and tracking purposes. In addition, in the event of brand scandal or brand social responsibility activities, public-relations efforts can use the findings to earn or regain the trust of consumers, as this research demonstrates that marketers can shape (tailor) the feel or think dimensions of brand perception to change consumers’ moral judgment of the brands.

This research makes theoretical contribution to the brand anthropomorphism literature by differentiating the two dimensions and exploring the influence of anthropomorphism of consumer moral judgment.

The utterly un-nostalgic person is probably a non-existent being. At both a personal and collective level, we explore how nostalgia is experienced and in demand during times of transition, disjuncture, conflict and uncertainty. This chapter explores the emotion of nostalgia and connects it specifically to the current corona pandemic – the challenges of lockdowns and social distancing measures on interaction, feelings of loneliness and a generalised sense of uncertainty and despair, and also a rise of nostalgia as a possible response to these challenges. The predominant view of nostalgia put forth in this chapter is that nostalgia has the capacity to provide a great deal of benefit (meaning, hope, direction and purpose) to individuals, groups, institutions and societies at large. Indeed, nostalgia can be a tranquil feeling in a fearful world. We relate nostalgia to studies and experiences from the pandemic period and speculate on how the so-called ‘corona crisis’ may impact feelings of nostalgia in the post-pandemic world – perhaps even a nostalgia and longing for the pandemic period itself.

If the corona pandemic has in fact sparked a new (or renewed) interest in nostalgia in contemporary society due to the corona pandemic, it may indeed prove to be a positive thing, particularly if it makes it easier for people to deal with current feelings of adversity and anxiety. We suggest the nostalgia mood that is generated and perpetuated by the continuing twists and turns of the corona pandemic may – in the short and long run – prove useful in coping with and giving meaning to the problems and perplexing circumstances of life, rather than being a regressive phenomenon. Perhaps, something good may, in the end, grow from something bad?

New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

Although there have been considerable discussions on the business value of adopting blockchain in supply chains, it is unclear whether such blockchain-enabled supply chains (BESCs) can help firms mitigate the negative impact resulting from the recent COVID-19 pandemic. This study aims to answer this important question.

The authors conduct an event study to quantify the financial effects of the COVID-19 pandemic and compare the differences in such effects between treatment firms that have adopted BESCs and matched control firms that have not adopted BESCs. The authors also perform a regression analysis to examine how the role of BESCs in mitigating COVID-19's negative impact varies across firms with different levels of supply chain leanness and complexity. The analysis is based on 88 treatment firms and 88 matched control firms, all of which are publicly listed on the US stock markets.

The test results suggest that although both the treatment and control firms are negatively affected by the COVID-19 pandemic, the effect is less negative for the treatment firms compared to the control firms, demonstrating the role of BESCs in mitigating the negative impact caused by the COVID-19 pandemic. Moreover, the mitigating role of BESCs is more pronounced for firms with lean and complex supply chains.

This study is among the first to provide empirical evidence on the mitigating role of BESCs during the COVID-19 pandemic, highlighting the importance of adopting blockchain in supply chains with high uncertainties and disruption risks.

Leader–member exchange (LMX) relationship is a crucial context for individuals’ generation of creative ideas. Unlike the fruit research between LMX quality and employee creativity, the relationship between LMX ambivalence and employee creativity is scarce. This study thus aims to examine the effect of LMX ambivalence on employee creativity.

This study conducted an on-site survey of research and development teams in China and distributed paired questionnaires with a time lag of one month. Data from 116 leaders and 484 subordinates were collected and analyzed.

The results showed that LMX ambivalence was directly negatively or indirectly negatively related to employee creativity via self-efficacy. Employee cynicism acted as a potential personal moderator of the effect of LMX ambivalence, specifically, employee cynicism attenuated the negative influence of LMX ambivalence on employee creativity via self-efficacy.

This study extends our knowledge of the complex effects of LMX relationships by empirically exploring whether and how LMX ambivalence influences employee creativity, with self-efficacy introduced as one crucial underlying mechanism. Meanwhile, this study enriches the existing cynicism literature by demonstrating the role of employee cynicism as a buffer in the relationship between LMX ambivalence and employee creativity.

Green innovation (GI) in megaprojects has become a significant research topic that attracts both megaproject management scholars' and practitioners' attention. Green transformational leadership (GTL) is acknowledged as an important antecedent to GI in the permanent context. However, limited research investigates the mechanism and condition of how GTL effectively affects GI in the temporary (i.e. megaproject) context. This study seeks to examine the mechanism and condition of GTL in improving GI by assessing the mediating role of green knowledge sharing (GKS) and the moderating effect of innovation climate (IC).

Regression analysis was performed on data obtained from 303 experts who have been involved in megaprojects.

GTL has a significant positive impact on two aspects of GI, including green product innovation (GPDI) and green process innovation (GPCI). Besides, GKS mediates the relationship between GTL and the two aspects of GI. Moreover, IC plays a significantly positive moderating role in the relationship between GTL and GKS and the relationship between GKS and the two aspects of GI.

This study adds knowledge to the theory and practice by unveiling the “black box” between GTL and GI in the temporary (i.e. megaproject) context. First, this study extends the continuing discussion on the direct effect of GTL on GI to the temporary (i.e. megaproject) context. Second, this study facilitates the understanding of the mechanism to generate better GI performance considering the mediating role of GKS and the moderating effect of IC in the temporary (i.e. megaproject) context. The results can illuminate megaproject practitioners on generating better GI performance.

Decision-making, reinforced by artificial intelligence (AI), is predicted to become potent tool within the domain of supply chain management. Considering the importance of this subject, the purpose of this study is to explore the triggers and technological inhibitors affecting the adoption of AI. This study also aims to identify three-dimensional triggers, notably those linked to environmental, social, and governance (ESG), as well as technological inhibitors.

Drawing upon a six-step systematic review following the preferred reporting items for systematic reviews and meta analysis (PRISMA) guidelines, a broad range of journal publications was recognized, with a thematic analysis under the lens of the ESG framework, offering a unique perspective on factors triggering and inhibiting AI adoption in the supply chain.

In the environmental dimension, triggers include product waste reduction and greenhouse gas emissions reduction, highlighting the potential of AI in promoting sustainability and environmental responsibility. In the social dimension, triggers encompass product security and quality, as well as social well-being, indicating how AI can contribute to ensuring safe and high-quality products and enhancing societal welfare. In the governance dimension, triggers involve agile and lean practices, cost reduction, sustainable supplier selection, circular economy initiatives, supply chain risk management, knowledge sharing and the synergy between supply and demand. The inhibitors in the technological category present challenges, encompassing the lack of regulations and rules, data security and privacy concerns, responsible and ethical AI considerations, performance and ethical assessment difficulties, poor data quality, group bias and the need to achieve synergy between AI and human decision-makers.

Despite the use of PRISMA guidelines to ensure a comprehensive search and screening process, it is possible that some relevant studies in other databases and industry reports may have been missed. In light of this, the selected studies may not have fully captured the diversity of triggers and technological inhibitors. The extraction of themes from the selected papers is subjective in nature and relies on the interpretation of researchers, which may introduce bias.

The research contributes to the field by conducting a comprehensive analysis of the diverse factors that trigger or inhibit AI adoption, providing valuable insights into their impact. By incorporating the ESG protocol, the study offers a holistic evaluation of the dimensions associated with AI adoption in the supply chain, presenting valuable implications for both industry professionals and researchers. The originality lies in its in-depth examination of the multifaceted aspects of AI adoption, making it a valuable resource for advancing knowledge in this area.

Aerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy.

The bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency.

Experimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method.

The position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision.

The proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy.

The proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry.

A combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.