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This paper contributes to the social pillar of sustainable supply chain management. It does so by investigating how women managers in the maritime sector handle work-family conflict, thereby acting as institutional entrepreneurs to create a work-family balance logic. The maritime sector is a male-dominated supply chain management environment, which suffers from a talent gap of a lack of women executives. One reason for this problem is work-family balance issues that deter women from staying in the workforce.

The authors interviewed 35 women working as port managers in different developing countries. The authors analyzed their strategies in coping with the conflict between family and work to create a work-family balance logic.

The authors found four different types of strategies to handle work-family conflicts. Responses showed that women executives in this sector can be institutional entrepreneurs. Based on the findings, the authors were able to confirm and contribute to the existing model proposed by Silva and Nunes (2021) on sustainable supply chain logic. The authors also provided recommendations for these women as institutional entrepreneurs and for policymakers to retain women talent in the supply chain management.

The research focuses on a specific supply chain management sector, which is the maritime sector. It also relies exclusively on interview data.

The authors propose recommendations to develop a work-family balance logic and retain talented women in the supply chain industry based on monitoring equality and supporting their need for a work-family balance, both in the short and long terms.

The authors interviewed women executives in one of the most male dominated sectors. The authors studied their ability to cope with work-family conflicts and identified four ways to create a work-family balance logic. These findings enabled us to show the contribution and limits of women executives as institutional entrepreneurs for work family balance logics in male dominated sectors.

The purpose of this paper is to contribute to bridging the gap between researchers and practitioners. It does so by comparing the various models of academic-practitioner collaboration and introducing Dewey’s democratic experimentalism as a promising alternative.

The conceptual implications are drawn from an analysis and discussion of the literatures in the field of organizational knowledge production, co-production and Deweyan studies.

Democratic experimentalism offers a much needed platform for a collaborative relationship between academics and practitioners that leads to knowledge that is rigorous and relevant to practice.

While the current models of academic-practitioner collaboration provide mechanisms for knowledge co-production, the Dewey’s democratic experimentalism goes further to emphasize the nature of the relationship between academics and practitioners in such common endeavor to ensure that all of them are equal co-creators of knowledge.

Although the international business literature has examined leader traits that are desirable in different cultures, it has not examined critical behaviors or managerial attributions of credit and blame. Credit and blame attributions have important consequences for the desirability of leadership across cultures. Arguing that these types of managerial attributions are likely to have a strong impact on what constitutes desirable leadership; the authors examine them in five countries, namely, USA, France, India, Turkey and Vietnam. The purpose of this paper is to contribute by examining the influence of credit and blame attributions on subordinate satisfaction and leadership perceptions (desirability), unaddressed in the literature.

The model was tested using questionnaire responses of subordinates in a variety of business organizations, from the five countries indicated, including manufacturing, telecommunication, financial and other services.

Using the implicit leadership theory, the authors contribute by demonstrating the importance of these attributions for leadership perceptions in five different cultures. The results are supportive of the hypotheses and suggest the important moderating role of subordinate performance for leadership perceptions. The authors discuss findings in the context of the literature, highlight contributions and identify limitations and future directions.

Using the implicit leadership theory, the authors contribute by demonstrating the importance of these attributions for leadership perceptions in five different cultures.

The purpose of this paper is to analyze the different classifications of existing reference documents related to corporate social responsibility (CSR) and to propose a complementary approach of this subject in regard to ISO26000.

The publication of ISO 26000 in November 2010, an International Standard providing guidelines for CSR, seems to have modified the landscape of reference documents by bringing up the issue of legitimacy in the overview of the standards. The paper analyzes four different classifications of existing reference documents related to CSR in order to understand their approach.

The issue of the purpose and legitimacy of tools evoked by ISO 26000 experts enables this paper to propose a complementary approach to existing classifications, by positioning the main tools related to CSR in relation to each other.

This article presents a comparison of existing classification of CSR standards in regard to ISO26000.

This study aims to investigate the relationship between dynamic capabilities and sustainable business performance in Vietnamese small- and medium-sized enterprises (SMEs), focusing on the mediating role of digitalization strategies. Specifically, the authors seek to explore whether and how the three critical characteristics of dynamic capabilities (DCs) – sensing, seizing and transforming capabilities – are linked to business model innovation (BMI) or sustained performance and what dimensions contribute to their development and adoption in digitalization strategies.

The authors analyse a sample of 596 Vietnamese SMEs using a validated measurement framework to explore the three clusters of DCs activities and their contributions to digitalization strategies, BMI and sustainable business performance across economic, social and environmental dimensions.

The study highlights the pivotal role of sensing, seizing and transforming capabilities in the adoption of digitalization strategies, BMI, as well as in promoting sustainable business performance. Firstly, sensing capability profoundly influences product digitalization strategy, whereas seizing capability has the greatest impact on process digitalization strategy. Secondly, sensing and transforming capabilities significantly contribute to BMI. Thirdly, both process and product digitalization strategies exert a significant positive influence on sustainable business performance, especially the environmental dimension. Finally, the study exhibits the indirect impacts of seizing and sensing capabilities on sustainable business performance through product and process digitization strategies.

This study extends recent research by investigating the DCs underlying a firm’s digitalization strategies and contribute to ongoing calls for further investigation in the DCs literature. This research design, which draws from a validated measurement framework, responds to recent calls to broaden the toolkit used in DCs research. The practical implications of this study can benefit SMEs in Vietnam and beyond as they seek to enhance their digitalization strategies and achieve sustainable competitive advantage.

In the dynamic landscape of 2023, global challenges are amplified by escalating conflicts and the COVID-19 aftermath. Developing nations like Vietnam face a critical juncture, requiring diversified economies for enhanced livelihoods and poverty reduction. However, this growth necessitates increased energy consumption, potentially escalating carbon emissions. Green innovation (GI) emerges as a beacon of hope, offering products and services designed for a minimal carbon footprint. Beyond socio-economic advancement, GI aligns with sustainable development goals. This study aims to  examine the influence of knowledge management (KM) and digitalization (DG) on GI, particularly in sustainable competitive advantage.

Using structural equation modeling and drawing upon a survey administered to 301 Vietnamese enterprises.

The findings illuminate diverse underpinnings between green product and process innovation, unravel the intricate relationship between KM, DG and GI, and provide crucial insights for firms seeking sustainable competitive edges.

This multidimensional approach significantly enriches the understanding of these pivotal elements in contemporary business landscapes.

Terrestrial laser scanning (TLS) point clouds have been widely used in deformation measurement for structures. However, reliability and accuracy of resulting deformation estimation strongly depends on quality of each step of a workflow, which are not fully addressed. This study aims to give insight error of these steps, and results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. Thus, the main contributions of the paper are investigating point cloud registration error affecting resulting deformation estimation, identifying an appropriate segmentation method used to extract data points of a deformed surface, investigating a methodology to determine an un-deformed or a reference surface for estimating deformation, and proposing a methodology to minimize the impact of outlier, noisy data and/or mixed pixels on deformation estimation.

In practice, the quality of data point clouds and of surface extraction strongly impacts on resulting deformation estimation based on laser scanning point clouds, which can cause an incorrect decision on the state of the structure if uncertainty is available. In an effort to have more comprehensive insight into those impacts, this study addresses four issues: data errors due to data registration from multiple scanning stations (Issue 1), methods used to extract point clouds of structure surfaces (Issue 2), selection of the reference surface S_ref to measure deformation (Issue 3), and available outlier and/or mixed pixels (Issue 4). This investigation demonstrates through estimating deformation of the bridge abutment, building and an oil storage tank.

The study shows that both random sample consensus (RANSAC) and region growing–based methods [a cell-based/voxel-based region growing (CRG/VRG)] can be extracted data points of surfaces, but RANSAC is only applicable for a primary primitive surface (e.g. a plane in this study) subjected to a small deformation (case study 2 and 3) and cannot eliminate mixed pixels. On another hand, CRG and VRG impose a suitable method applied for deformed, free-form surfaces. In addition, in practice, a reference surface of a structure is mostly not available. The use of a fitting plane based on a point cloud of a current surface would cause unrealistic and inaccurate deformation because outlier data points and data points of damaged areas affect an accuracy of the fitting plane. This study would recommend the use of a reference surface determined based on a design concept/specification. A smoothing method with a spatial interval can be effectively minimize, negative impact of outlier, noisy data and/or mixed pixels on deformation estimation.

Due to difficulty in logistics, an independent measurement cannot be established to assess the deformation accuracy based on TLS data point cloud in the case studies of this research. However, common laser scanners using the time-of-flight or phase-shift principle provide point clouds with accuracy in the order of 1–6 mm, while the point clouds of triangulation scanners have sub-millimetre accuracy.

This study aims to give insight error of these steps, and the results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds.

The results of this study would provide guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. A low-cost method can be applied for deformation analysis of the structure.

Although a large amount of the studies used laser scanning to measure structure deformation in the last two decades, the methods mainly applied were to measure change between two states (or epochs) of the structure surface and focused on quantifying deformation-based TLS point clouds. Those studies proved that a laser scanner could be an alternative unit to acquire spatial information for deformation monitoring. However, there are still challenges in establishing an appropriate procedure to collect a high quality of point clouds and develop methods to interpret the point clouds to obtain reliable and accurate deformation, when uncertainty, including data quality and reference information, is available. Therefore, this study demonstrates the impact of data quality in a term of point cloud registration error, selected methods for extracting point clouds of surfaces, identifying reference information, and available outlier, noisy data and/or mixed pixels on deformation estimation.