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The purpose of this study is to investigate the relationship between artificial intelligence (AI) and decision making in the development of AI-related capabilities. We investigate if and how AI-driven decision making has an impact on firm performance. We also investigate the role played by environmental dynamism in the development of AI capabilities and AI-driven decision making.

We surveyed 346 managers in the United States using established scales from the literature and leveraged p modelling to analyse the data.

Results indicate that AI-driven decision making is positively related to firm performance and that big data-powered AI positively influences AI-driven decision making. Moreover, there is a positive relationship between big data-powered AI and the development of AI capability within a firm. It is also found that the control variables of firm size and age do not significantly affect firm performance. Finally, environmental dynamism does not have a positive and significant moderating effect on the path connecting big data-powered AI and AI-driven decision making, while it exerts a positive moderating effect on the development of AI capability to strengthen AI-driven decision making.

These findings extend the resource-based view by highlighting the capabilities developed within the firm to manage big data-powered AI. This research also provides theoretically grounded guidance to managers wanting to align their AI-driven decision making with superior firm performance.

The popularity of Management Control Systems (MCS) has increased due to rising uncertainty in business operations. They help companies implement strategies, manage information and incentivize managers with common goals. Therefore, the research aims to take stock of the evolution of studies on MCS adoption, identifying trends and future avenues.

While a few systematic literature reviews have investigated the implications of MCS adoption amid specific contexts, a comprehensive bibliometric analysis of the whole research stream is lacking. Consequently, our study analyzes relevant scientific literature on the topic of MCS from 1970 to 2022, through the use of VOSviewer, R Bibliometrix and Latent Dirichlet Allocation to visualize the bibliometric results.

The study provides a comprehensive overview of key emerging topics in MCS literature and the ways in which they have developed over the decades, along with a structured research agenda built upon the literature gaps found amid current and past scientific production. It does so by analyzing scientific production from multiple bibliometric aspects and advanced text-mining techniques to extract common emerging themes from the dataset.

To the best of the authors’ knowledge, no attempt has yet been made to synthesize MCS literature through a bibliometric review. The bibliometric perspective on MCS enhances scholars' understanding of the historical path and future trends of the literature stream, while helping practitioners update existing MCS conceptualizations in light of contemporary changes.

This study aims to holistically explore the intersection of sustainable supply chain management, carbon accounting and life cycle assessment (LCA). The purpose of this study is to derive state-of-the-art knowledge of this landscape and use it to build a structured research agenda that can help to further develop this field.

Seventy-eight distinct contributions, identified through a rigorous, transparent and replicable search protocol, are analyzed through a systematic literature review. Additionally, bibliometric information on the studies is extracted from the Scopus database and visualized through the use of VOSViewer and RStudio.

This study outlines the current state-of-the-art knowledge across three spheres of supply chain management, synthesizing the extant literature into several nascent themes – namely, the significance of Scope 3 emissions; how LCA can be integrated into carbon accounting and sustainability disclosures, the differences between countries and industries in terms of carbon emissions and policies for a concerted effort toward carbon reduction.

Several practical implications can be drawn from the research for both practitioners and policymakers. The research provides a comprehensive, bird’s eye view on the discrepancies between different industries and countries in terms of carbon emissions, along with how carbon accounting should move toward strategic and predictive adoption.

The results show that adopting life cycle thinking can contribute to more transparent monitoring of carbon emissions in supply chains; however, its use in sustainability reporting needs to become more widespread, encompassing not only the carbon footprints of products and services but also the organization as a whole.

Using bibliographic and critical qualitative analyses, this study reviews the literature on LCA in sustainable supply chain management and carbon accounting. To the best of the authors’ knowledge, this review is the first attempt to synthesize this relevant and rapidly growing nexus between the three literature streams mentioned above.