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The objective of this paper is to contribute to Australian berry supply chains with a relevant identification regarding the possible data driven interventions that stakeholders can take while the berries are in transit.

An exploratory series of semi-structured interviews was conducted through six Australian experts in the industry with more than 20 years of experience in Australian berry supply chains and the Australian perishable food industry, to identify key possible in-transit interventions that could be implemented in the Australian berry industry.

The analysis of the interviews revealed a total of 18 possible in-transit interventions. An important finding is that in-transit interventions are made possible by the use of real-time data gathered through IoT devices such as Active Radio Frequency Identification, Time and Temperature Indicators interacting with Wireless Sensor Networks. Another key finding is that Australian berry growers and retailers do possess the technologies and the resources necessary to make in-transit interventions possible, however they have yet applied these technologies to operational decision-making and interventions based on the product, rather focussing on supply chain transactions and events.

Since the research focusses on an Australian context, its findings may or may not be applicable to other countries. The research is exploratory in nature, and its findings should be verified by future research, in particular to test whether the in-transit interventions proposed here can be implemented in a cost-efficient way.

To the authors' knowledge, this publication is the first known academic article to provide a clear understanding of the Australian berry industry from a supply chain and logistics perspective, and the first to explore possible data driven in-transit interventions in perishable food supply chains.

The aim of this paper is to present the first diffusion analysis of ISO/IEC 27001, the fourth most popular ISO certification at global level and the most important standard for information security.

To achieve the purposes, the authors applied Grey Models (GM) – Even GM (1,1), Even GM (1,1,α,θ), Discrete GM (1,1), Discrete GM (1,1,α) – complemented by the relative growth rate and the doubling time indexes on the six most important countries in terms of issued certificates.

Results show that a growing trend is likely to be expected in the years to come and that China will lead at country level.

The study contributes to the scientific debate by presenting the first diffusive analysis of ISO/IEC 27001 and by proposing a forecasting approach that to date has found little application in the field of international standards.

Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).

A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.

The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.

The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.