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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.

COVID-19 has caused critical supply chain problems, especially in sustainable supply chain management, but very few empirical studies have been explored how to improve the firm sustainability through supply chain endeavours such as supply chain agility to manage the impacts of COVID-19. This paper aims to develop a model to incorporate supply chain agility and supply chain relationships that link firm sustainability to mitigate the impacts of the pandemic.

The authors conducted an online survey and collected 203 valid responses from businesses in the United Arab Emirates, and employed an exploratory factor analysis, mediated regression analysis and structural equation modelling methodology to test the models and hypotheses.

The authors find that the adoption of supply chain agility can improve supply chain relationships and positively impact sustainability. Meanwhile, supply chain relationships partially mediate the relationship between supply chain agility and sustainability. In addition, sustainability mitigates the impacts of COVID-19 pandemic on supply chains.

The results provide fruitful insights and implications for the challenges and uncertainties caused by the pandemic post COVID-19 and provide several directions for further research.

This study aims to apply an electrochemical grinding (ECG) technology to improve the material removal rate (MRR) under the premise of certain surface roughness in machining U71Mn alloy.

The effects of machining parameters (electrolyte type, grinding wheel granularity, applied voltage, grinding wheel speed and machining time) on the MRR and surface roughness are investigated with experiments.

The experiment results show that an electroplated diamond grinding wheel of 46# and 15 Wt.% NaNO₃ + 10 Wt.% NaCl electrolyte is more suitable to be applied in U71Mn ECG. And the MRR and surface roughness are affected by machining parameters such as applied voltage, grinding wheel speed and machining time. In addition, the maximum MRR of 0.194 g/min is obtained with the 15 Wt.% NaCl electrolyte, 17 V applied voltage, 1,500 rpm grinding wheel speed and 60 s machining time. The minimum surface roughness of Ra 0.312 µm is obtained by the 15 Wt.% NaNO₃ + 10 Wt.% NaCl electrolyte, 13 V applied voltage, 2,000 rpm grinding wheel speed and 60 s machining time.

Under the electrolyte scouring effect, the products and the heat generated in the machining can be better discharged. ECG has the potential to improve MRR and reduce surface roughness in machining U71Mn.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0341/

This study aims to test the compensatory consumption theory with the explicit hypothesis that China's new-rich tend to waste relatively more food.

In this study, the authors use Heckman two-step probit model to empirically investigate the new-rich consumption behavior related to food waste.

The results show that new-rich is associated with restaurant leftovers and less likely to take them home, which supports the compensatory consumption hypothesis.

Understanding the empirical evidence supporting compensatory consumption theory may improve forecasts, which feed into early warning systems for food insecurity. And it also avoids unreasonable food policies.

This research is a first attempt to place food waste in a compensatory-consumption perspective, which sheds light on a new theory for explaining increasing food waste in developing countries.

The link between relationship typologies and effectiveness of conflict resolution approaches remains to be tested despite its significance in conflict management in construction project delivery. By using the four relationships attributes based on the group attachment theory, the purpose of the study was to explore the cluster of relationships among project teams and organisations and the performance of conflict management strategies across these clusters in the Ghanaian construction industry.

Using a deductive questionnaire survey in the Ghanaian construction industry, a total of 137 responses were gathered and analyzed using cluster analysis, mean scores and ANOVA to reveal the relationship clusters and performance of conflict management strategies across these clusters.

The results revealed eight relationship clusters that exist among project teams and organisations with distinct influence of roles & tasks function, cognition, emotions and behavior attributes across the relationship clusters. In the aspect of the effectiveness of conflict management strategies, it was noted that the performance of these strategies were significantly different across the groups. For instance, integrating as a conflict management strategy was deemed to be effective in resolving conflict in unitary, adversarial, pluralist, mutuality, collaborative and partnering relationship clusters. In the case of coopetitive and coercive relationships, the performance of integrating as a conflict management strategy was less effective. This study thus has empirically proved that, different relationship clusters of teams and organizations exist within the Ghanaian construction industry, and that they perform different roles & tasks functions, cognition, emotions and behavioural attributes in their formation. Additionally, the performance effectiveness of conflict management strategies differed across the relationship clusters.

By aligning the relationship attributes to the dynamics of relationship clusters experienced in project teams and organisations, relationship quality, suitability and effectiveness of conflict management strategies can be optimized. The findings can inform project teams and stakeholders to develop fit-for-purpose relationship attributes among teams and organisations to enhance team effectiveness, relationship quality and conflict management in the industry.

Healthy and adaptive strategies for regulating emotions and coping with the demands of their jobs can help school-level leaders mitigate the factors and forces heightening the emotional aspects of their work, stave off the negative effects of work intensification and achieve wellness. As with most individuals in most professions, school-level leaders use several different strategies to manage their emotions and cope with the stresses associated with their work. Some of these coping strategies are associated with positive outcomes including situation selection and exercising autonomy over their workday, talking to colleagues, reappraisal, humour, controlled breathing, exercise and engaging in hobbies outside of work. However, even the most experienced and effective school-level leaders demonstrate a proclivity for engaging in coping strategies associated with maladaptive and negative outcomes. These maladaptive strategies include worrying about events over which they have little or no control, masking one's emotions using expressive suppression, using thought suppression to deal with symptoms of emotional exhaustion, distraction, manipulating the emotions of others as well as use of illegal or prescription drugs, alcohol and other forms of self-medication. This chapter concludes with a discussion of how there can be some overlap between these strategies in practice and how they are classified.

Pre-construction of a project comprises stages that are pivotal for the procurement performance. It is defined as the duration from the project's initiation to construction. However, Private Public Partnerships (PPPs) have been subjected to a long pre-construction, thereby leading to an inefficient development process. Therefore, the purpose of this paper is to pay attention to the influencing factors elongating the pre-construction duration.

Based on data of 5,677 PPP projects between 2009 and 2021 in China, the authors adopt the Accelerated Failure Time (AFT) model in duration analysis to empirically analyze the following underlying dynamics determining the duration of PPP pre-construction stages: (1) policy uncertainty; (2) corruption; and (3) procurement method selection. To observe the influencing paths more specifically, the authors divided the pre-construction duration into the pre-tendering period and tendering period and regressed them separately.

The results indicate that the pre-construction duration is significantly prolonged with increased policy uncertainty and corruption degree as well as the use of tendering methods. Meanwhile, the above factors have a greater impact on the pre-tendering period than the tendering period.

The contribution of this study is twofold: (1) theoretically, this paper provides new evidence on the impact of PPP policy uncertainty, corruption and procurement method selection on the pre-construction duration. It complements empirical studies on the factors elongating the time efficiency of PPPs projects. (2) In practice, it provides a specific path for the government to improve the time efficiency of PPPs.

Continuity of care and access to primary care have been identified as important contributors to improved health outcomes and reduced reincarceration among people who are justice-involved. While the disproportionate burden of health concerns among incarcerated populations is well documented, less is known about their health service utilization, limiting the potential for effective improvements to current policy and practice. This study aims to examine health status and health care utilization among men recently released from a superjail in a large metropolitan area to better understand patterns of use, risk factors and facilitators.

Participants included adult men (n = 106) matched to a general population group (n = 530) in Ontario, Canada, linked to medical records (88.5% linkage) to examine baseline health status and health utilization three-months post-release. The authors compared differences between the groups in baseline health conditions and estimated the risk of emergency department, primary care, inpatient hospitalization and specialist ambulatory care visits.

Superjail participants had a significantly higher prevalence of respiratory conditions, mental illness, substance use and injuries. Substance use was a significant risk factor for all types of visits and emergency department visits were over three times higher among superjail participants.

This empirical case is illustrative of an emerging phenomenon in some regions of the world where emergency departments serve as de facto “walk-in clinics” for those with criminal justice involvement. Strategic approaches to health services are required to meet the complex social and health needs and disparities in access to care experienced by men released from custody.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.