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Maritime transportation plays an important role in facilitating both the global and regional merchandise trade, where accurate trend prediction is crucial in assisting decision-making in the industry. This paper aims to conduct a macro-level study to predict world vessel supply and demand.

The automatic autoregressive integrated moving average (ARIMA) is used for the univariate vessel supply and demand time-series forecasting based on the data records from 1980 to 2021.

For the future projection of the demand side, the predicted outcomes for total vessel demand and world dry cargo vessel demand until 2030 indicate upward trends. For the supply side, the predominant upward trends for world total vessel supply, oil tanker vessel supply, container vessel supply and other types of vessel supply are captured. The world bulk carrier vessel supply prediction results indicate an initial upward trend, followed by a slight decline, while the forecasted world general cargo vessel supply values remain relatively stable. By comparing the predicted percentage change rates, there is a gradual convergence between demand and supply change rates in the near future. We also find that the impact of the COVID-19 pandemic on the time-series prediction results is not statistically significant.

The results can provide policy implications in strategic planning and operation to various stakeholders in the shipping industry for vessel building, scrapping and deployment.

This paper aims to integrate insights from the behavioral theory of the firm and the dynamic capabilities perspective to explain how the historical and social attainment discrepancies motivate firms to change. Specifically, this paper proposes that a negative historical attainment discrepancy encourages the firm to engage in strategic change to solve its performance problems. In contrast, this paper advanced that a positive social attainment discrepancy motivates strategic change as a mechanism to bolster the firm’s position within the industry. Further, this paper integrated the moderating effects of industry dynamism and industry munificence.

This paper tests hypotheses using panel data on 2,435 US public firms over the years from 1996 to 2018. This paper uses a fixed-effects regression model to empirically test these hypotheses.

This paper finds empirical support for the effects of both the negative historical attainment discrepancy and the positive social attainment discrepancy on the firm’s tendency to engage in strategic change. As for the hypothesized moderating effects, this paper finds that industry munificence accentuated the effects of both attainment discrepancies on the firm’s tendency to engage in strategic change. However, the results do not support the hypothesized moderating effect of industry dynamism on either of these attainment discrepancies.

This paper contributes to the research on the separate effects of historical and social comparisons within the context of strategic change. Further, the paper bolsters our understanding of how performance feedback increases the firm’s tendency to change. Finally, the paper integrates theoretical views from the behavioral theory of the firm and the dynamic capabilities perspective on how socially high-performing firms may build and sustain their competitive advantage through organizational change.

The aim of this research is to explore the impact of digital resilience on firms' international performance. Using internal operation efficiency and innovation as channel variables, this paper explores the relationship between digital resilience and international firm performance of Chinese listed firms.

The research design follows a quantitative approach. Using firm-level panel data from 2007 to 2020, this paper tests the hypotheses between digital resilience and international firm performance through internal efficiency and innovation.

The results note that digital resilience has a positive effect on internationalization while operation efficiency is a channel through which digital resilience promotes internationalization. Digital resilience also facilitates innovation by improving research and development (R&D) efficiency and matching innovation collaborators.

This paper is one of the first to explore digital resilience in the context of internalization and international firm performance. This paper extends the notion of resource-based view (RBV) to examine the relationship between digital resilience, internal efficiency and innovation on international firm performance.

Quality 4.0 is essential to the Industry 4.0 framework, notably in the electronics sector. It evaluates product quality in real-time using automatic process controls, quality tools and procedures. The implementation of Quality 4.0 criteria in the electronics industry is the subject of this study’s investigation and analysis. In this study, nine Customer Requirements (CRs) and 18 Design Requirements (DRs) have been defined to adopt Quality 4.0, aiming to increase yield while reducing defects. This study has developed a Quality 4.0 framework for effective implementation, incorporating the People, Process and Technology categories.

Many CRs and DRs of Quality 4.0 exhibit interdependencies. The Analytic Network Process (ANP) considers interdependencies among the criteria at various levels. Quality Function Deployment (QFD) can capture the customer’s voice, which is particularly important in Quality 4.0. Therefore, in this research, we use an integrated ANP-QFD methodology for prioritizing DRs based on the customers' needs and preferences, ultimately leading to better product and service development.

According to the research findings, the most critical consumer criteria for Quality 4.0 in the electronics sector are automatic systems, connectivity, compliance and leadership. The Intelligent Internet of Things (IIOTs) has emerged as the most significant design requirement that enables effective control in production. It is observed that robotics process automation and a workforce aligned with Quality 4.0 also play crucial roles.

Existing literature does not include studies on identifying CRs and DRs for implementing Quality 4.0 in the electronics industry. To address this gap, we propose a framework to integrate real-time quality measures into the Industry 4.0 context, thereby facilitating the implementation of Quality 4.0 in the electronics industry. This study can provide valuable insights for industry practitioners to implement Quality 4.0 effectively in their organizations.

The complexity of citizenship behavior in organizations has long been a focus of research. Traditional methodologies have been predominantly used to address this complexity. This paper aims to tackle the problem using a cutting-edge technological tool: business process mining. The objective is to enhance citizenship behaviors by leveraging primary data collected from 326 white-collar employees in the Indian service industry.

The study focuses on two main processes: training and creativity, with the ultimate goal of fostering organizational citizenship behavior (OCB), both in its overall manifestation (OCB-O) and its individual components (OCB-I). Seven different machine learning algorithms were used: artificial neural, behavior, prediction network, linear discriminant classifier, K-nearest neighbor, support vector machine, extreme gradient boosting (XGBoost), random forest and naive Bayes. The approach involved mining the most effective path for predicting the outcome and automating the entire process to enhance efficiency and sustainability.

The study successfully predicted the OCB-O construct, demonstrating the effectiveness of the approach. An optimized path for prediction was identified, highlighting the potential for automation to streamline the process and improve accuracy. These findings suggest that leveraging automation can facilitate the prediction of behavioral constructs, enabling the customization of policies for future employees.

The findings have significant implications for organizations aiming to enhance citizenship behaviors among their employees. By leveraging advanced technological tools such as business process mining and machine learning algorithms, companies can develop more effective strategies for fostering desirable behaviors. Furthermore, the automation of these processes offers the potential to streamline operations, reduce manual effort and improve predictive accuracy.

This study contributes to the existing literature by offering a novel approach to addressing the complexity of citizenship behavior in organizations. By combining business process mining with machine learning techniques, a unique perspective is provided on how technological advancements can be leveraged to enhance organizational outcomes. Moreover, the findings underscore the value of automation in refining existing processes and developing models applicable to future employees, thus improving overall organizational efficiency and effectiveness.

This study aims to investigate an intersecting single-walled structure fabricated using wire-arc directed energy deposition (waDED). Because of the highly complex geometrical features of this structure, characterisation is used to identify potential weak points and provide a benchmark for future complex components.

A structural component with a process-specific design is built using additive manufacturing of an Al-Mg alloy and analysed using micro-computed tomography. Scans are carried out at different resolutions and subsequently compared to microsections. The chemical composition and hardness are also examined. These investigations provide an enhanced understanding of defects and overall quality of the manufactured parts.

The results show that very high-quality parts can be achieved using ER5183 alloy, even in intersecting areas. Defects in these regions are primarily caused by converging and diverging waDED paths and discontinuous waDED operations.

In addition to demonstrating the feasibility of complex structures using waDED, this study provides an overview of problem areas and potential improvements in waDED manufacturing.

This study aims to carry out a systematic literature review (SLR) on the integration of Lean, Industry 4.0 and the supply chain or the Lean Supply Chain (LSC) 4.0. The research analyses the current research on the LSC 4.0 concept in an increasingly digitalised world. The authors present the benefits, motivations, critical success factors and challenges of integrating the LSC with Industry 4.0 technologies within this emerging area of research.

An SLR is carried out on how Lean can be integrated with Supply Chain 4.0. Using the search strings of “Lean Supply Chain 4.0,” “Lean Supply Chain Management 4.0” and “Lean Supply Chain Digitalisation,” a review of published literature was carried out via searches on academic databases.

Industry 4.0 has a synergistic effect on the LSC and, depending on the technology and sector applied in, can complement and enhance the LSC. Similarly, the LSC is a precursor for digitalisation. There are considerable implications in the LSC 4.0 for green and sustainable processes.

Organisations can use this study to understand what the LSC 4.0 means to industry, the benefits and motivating factors for implementation, the critical success factors (CSFs) to implementation and the challenges for implementation.

This study adds to state of the art around the LSC 4.0 and future directions in this nascent research area. This study will aid organisations in understanding how Lean, supply chain management and Industry 4.0 can be integrated.

This study aims to examine how women entrepreneurs in Kazakhstan's male-dominated sectors utilize the concept of positionality to navigate and redefine gender norms, focusing on their engagement with entrepreneurial masculinities and femininities. It explores the transformative potential of their strategic actions on gender dynamics within the entrepreneurial ecosystem.

Employing qualitative research through 27 in-depth interviews, this study adopts constructivist grounded theory to delve into how women entrepreneurs interact with gender norms within their entrepreneurial context. This approach highlights the dynamic interplay between gender norms and the strategies employed by women entrepreneurs to navigate these challenges.

The findings reveal that women entrepreneurs actively employ and navigate entrepreneurial masculinities and femininities as strategies to challenge traditional gender roles. Their approaches vary from conforming to, challenging and creatively redefining the gendered expectations encountered in their entrepreneurial journey. This demonstrates their agency in reshaping gender norms and contributing to the diversity of gender performances within the domain of entrepreneurship.

While focused on Kazakhstan, the study's findings suggest broader implications for understanding gender dynamics in entrepreneurship across different cultural contexts. Future research could extend this inquiry to varied sociocultural settings, employing post-structuralist and ethnographic methodologies to further explore the performance of gender roles and the negotiation of belonging in entrepreneurial contexts.

By foregrounding the concept of positionality, this study enriches the dialogue on gender dynamics within entrepreneurship, offering fresh perspectives on the agency of women entrepreneurs in male-dominated sectors. It illustrates how gender identities and performances are not fixed but are actively constructed and negotiated, contributing to the evolving landscape of entrepreneurial masculinities and femininities.