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Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on food hub location decisions and generate effective facility location solutions.

Mathematical optimization and econometric models have been commonly used to identify hub location decisions, and each is associated with specific strengths to handle uncertainty. This paper develops an optimization model and a hurdle model of the US fresh produce sector to compare the hub location solutions between these two modeling approaches.

Econometric modeling and mathematical optimization are complementary approaches. While there is a divergence between the results of the optimization model and the econometric model, the optimization solution is largely confirmed by the econometric solution. A combination of the results of the two models might lead to improved decision-making.

This study suggests a future direction in which model development can move forward, for example, to explore and expose how to make the existing modeling techniques easier to use and more accessible to decision-makers.

The models and results provide information that is currently limited and is useful to help inform sustainable decisions of various stakeholders interested in the development of regional food systems, regional infrastructure investment and operational strategies for food hubs.

This study sheds light on how the application of complementary modeling approaches improves the effectiveness of facility location solutions. This study offers new perspectives on elaborating key features to encompass facility location issues by applying interdisciplinary approaches.

The purpose of this study is to provide a harmonisation framework for the diverse accounting practices by extractive industries.

The study takes a three-stage approach. The first involves a comprehensive literature review of the historical evolution of accounting regulations by extractive industries. The second involves constructing an accounting practice index for extractive industries. The third involves constructing a harmonisation framework.

The accounting practice index provides empirical evidence of the wide diversity of accounting practices by extractive industries. Analysis of the literature review addresses the several attempts by accounting and regulatory bodies to standardise the diverse practices of accounting by extractive industries and reasons for the lack of successful standardisations. The authors extract lessons from these previous attempts and propose a harmonisation framework.

The proposed harmonisation framework can be used to align together the diverse accounting practices by extractive industries and enhance comparability and consistency of accounting figures and statements produced by these industries. Harmonising the diverse accounting practices is crucial for investment decision-making.

The harmonisation framework is the first of its kind that could enhance the comparability of accounts of extractive industries’ firms and be used to harmonise diverse accounting practices by other industries.