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Sailing toward sustainability is becoming the strategic focus of shipping firms. Drawing on organizational information processing theory (OIPT) and the theory of planned behavior (TPB), we investigated the impact of digital transformation (DT) on shipping firms’ sustainable management performance and the boundary conditions guiding this relationship.

The authors examined the hypotheses by employing hierarchical linear modeling on two-wave time-lagged data from 189 shipping firm employees in China.

The results suggest that a shipping firm’s DT is positively associated with its sustainable management performance and that the relationship is strengthened by having better cross-functional and customer coordination mechanisms. Furthermore, our three-way interaction analyses show that while injunctive norms in a shipping firm’s networks can strengthen the contingency roles of both cross-functional and customer coordination mechanisms, descriptive norms alone significantly influence customer coordination.

Drawing on organizational information processing and planned behavior theories, the present research provides new insights into leveraging DT for sailing toward sustainable success. Moreover, this study extends the current understandings of the boundary conditions of the relationship between DT and sustainable management performance by showing the two-way and three-way interaction effects of coordination mechanisms and subjective norms. The findings of the present research can be utilized as effective strategies for promoting sustainable management performance.

This study aims to (1) validate the efficacy of contractual and relational governance in enhancing operational performance and (2) explore the influence of product complexity on the effectiveness of these governance mechanisms, thereby determining the optimal approach for varying levels of product complexity.

By utilizing a comprehensive theoretical framework encompassing transaction cost economics, social exchange theory and contingency theory, this research explores the intricate interplay between governance mechanisms, product complexity and operational performance, drawing insights from a dataset comprising 246 responses within Mainland China’s manufacturing sector. To rigorously test the proposed hypotheses, this study employed a hierarchical regression analysis.

The findings of this study are summarized as follows: (1) while both contractual governance and relational governance have a significant impact on operational performance, relational governance is found to be more effective than contractual governance in enhancing operational performance; and (2) the moderation effect of product complexity is evident, as it weakens the impact of contractual governance while simultaneously enhancing the positive influence of relational governance on operational performance.

The study uncovers a moderation effect of product complexity on the relationship between governance mechanisms and operational performance. This finding adds an original contribution to the literature by highlighting how product complexity can interact with governance strategies, providing practical insights for industries dealing with varying levels of product complexity.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

The blue and green firms are notable contributors to sustainable development. Similar to other businesses in circular economies, blue and green firms also face financing constraints. This paper aims to assess whether blue and green lending help in optimizing the interest rate spreads and the likelihood of default.

This analysis is based on an unbalanced panel of banks from 20 eurozone countries for eleven years between 2012 and 2022. The key indicators of banking include interest rate spread and a market-based probability of default. The paper assesses how these indicators are influenced by exposure to green and blue firms after controlling for several exogenous factors.

The results show a positive relationship between green and blue lending and spread, while there is a negative link with the probability of default. This confirms that the blue and green exposure positively supports the credit portfolio both in terms of profitability and risk management.

The banking system is among the key contributors to corporate finance and to enable continuous access to sustainable finance, the banking firms must be incentivized. While many studies analyze the impact of green lending, to the best of the authors’ knowledge, this study is among the very few that extend this analysis to blue economy firms.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such as climate change, environmental pollution and damage to biodiversity have failed to clearly identify and drive the potential benefits of these policies on health. The conducted study assesses and demonstrates how specific environmental policies and instruments influence perceived human health in order to ensure input for a data-driven decision process.

The study was conducted for the 2004–2020 period in European Union (EU) countries with the use of dynamic panel data modeling. Verification of specific policies' impact on dependent variables allows to indicate this their effectiveness and importance. As a result of the computed dynamic panel data models, it has been confirmed that a number of significant and meaningful relationships between the self-perceived health index and environmental variables can be identified.

There is a strong positive impact of environmental taxation on the health index, and the strength of this relationship causes effects to be observed in the very short term, even the following year. In addition, the development of renewable energy sources (RES) and the elimination of fossil fuels from the energy mix exert positive, although milder, effects on health. The reduction of ammonia emissions from agriculture and reducing noise pollution are other health-supporting factors that have been shown to be statistically valid. Results allow to identify the most efficient policies in the analyzed area in order to introduce those with the best results or a mix of such measures.

The results of the authors' research clearly indicate the health benefits of measures primarily aimed at improving environmental factors, such as environmental taxes in general. The authors have also discovered an unexpected negative impact of an increase in the share of energy taxes in total taxes on the health index. The presented study opens several possibilities for further investigation, especially in the context of the rapidly changing geopolitical environment and global efforts to respond to environmental and health challenges. The authors believe that the outcome of the authors' study may provide new arguments to policymakers pursuing solutions that are not always easily acceptable by the public.

The purpose of this study is to investigate the benefits and challenges of implementing circular economy (CE), as well as shed light on the influence of procurement strategy in CE implementation in construction projects.

A qualitative research approach with abductive reasoning was adopted. The empirical data were collected from the construction industry in the United Arab Emirates (UAE).

The results reveal that clients, consultants and contractors have limited awareness, knowledge and motivation to implement CE in construction projects. The absence of incentives to design projects following CE principles, lack of involvement of contractors and suppliers, non-use of materials that use CE principles and current procurement strategies are the main challenges for the implementation of CE in the UAE.

Previous research offers limited knowledge on CE and its implementation in construction projects particularly from a procurement strategy perspective. The findings of the study provide new knowledge of the benefits, challenges and role of procurement strategy for implementing CE. It is suggested that collaborative and partnering-based procurement methods are needed to facilitate the effective implementation of CE.