This readme file was generated on 2025-04-30 by Katharine Jones General information Title of dataset: Improving food supply chain resilience: a case study of chicken tikka masala Author Name: Katharine Jones ORCID: 0000-0002-6549-5804 Institution: Cranfield University Address: College Road, Wharley End, Bedford MK43 0AL Email: kate.jones.511@cranfield.ac.uk Author / Supervisor Information Name: Dr Kenisha Garnett ORCID: 0000-0001-9767-2062 Institution: Cranfield University Address: College Road, Wharley End, Bedford MK43 0AL Email: k.garnett@cranfield.ac.uk Author / Supervisor Information Name: Professor Paul J Burgess ORCID: 0000-0001-8210-3430 Institution: Cranfield University Address: College Road, Wharley End, Bedford MK43 0AL Email: p.burgess@cranfield.ac.uk Date of data collection: 19-12-23 to 28-03-24 Geographic location of data collection: UK Information about funding sources that supported the collection of the data: 1. UK Research and Innovation > Natural Environment Research Council grant no. 2754639 2. Quadram Institute Bioscience grant no. 43266FSRN-2023S26 SHARING/ACCESS INFORMATION Licenses/restrictions placed on the data: Data supporting this study cannot be made available due to legal and commercial restrictions. FILE OVERVIEW File list: 1. Interview instrument : list of key questions and prompt questions used in semi-structured interviews 2. Survey instrument : list of survey questions in online survey completed by participants using Qualtrics 3. Plausible future scenarios: a set of four narrative scenarios produced for the online workshop incorporating qualitative data gathered through survey and interview responses describing possible future disruptions that could impact the supply chain. File format: .pdf Relationship between files: some participants completed both the interview and the survey. Results were analysed alongside each other. Additional related data collected: data collected via open discussions in plenary and small groups during an online workshop conducted via Cranfield University's Grenville Turner Studio. These were analysed alongside the data gathered in interviews and survey. Some participants in the workshop also took part in the interview and/or survey. METHODOLOGICAL INFORMATION ## Description of methods used for collection/generation of data: The research employs an embedded case study approach comprising online surveys, online and face-to-face interviews, and an online workshop with supply chain actors across three supply chain tiers. A purposive sampling approach was used, from participants meeting the key criterion of supplying components of, or being customers of, the company manufacturing chicken tikka masala. 15-tier one suppliers were initially identified and encouraged to recommend their suppliers or customers to participate using a snowball recruitment technique. The resultant sample was nine tier-one and one tier-two participants. Participants were allocated a participant number and invited to self-assign a functional one- or two-word ‘tag’ from a pre-defined list that best represented their supply chain role: distributor, supplier, transporter, exporter, procurer, retailer, wholesaler, manufacturer, importer, processor, producer. All data associated with each participant was then pseudo-anonymised using the participant number, tag, and removing any references to specific products, companies and locations that could constitute data that could enable the identification of individuals or companies participating. Interviews were conducted by the author (KJ) and recorded and transcribed using Otter.ai (audio only) and / or Microsoft Teams (audio and video). Interviews were conducted online or in person and recorded using Microsoft Teams (if online) or Otter (if in person) and transcripts generated automatically. QA involved manually checking accuracy by comparing the transcripts generated by Otter / Microsoft Teams against the audio or video interviews. The online workshop was facilitated by the authors (KJ and PJB) and supported by independent facilitators. It was conducted and recorded via the Cranfield University Grenville Turner Online Suite, video recorded and text transcript created. It was conducted under the Chatham House Rule. During the workshop, plausible future scenarios were analysed in small groups to elucidate potential vulnerabilities and impacts to the supply chain. As part of the consent process, participants were requested to ensure confidentiality of others' participation in the research, if/when another participant's involvement in the research became known to them through the process of taking part. ## Methods for processing the data: A thematic analysis approach was used by the author (KJ) to process and analyse data collected. This was conducted manually (no software was used). The theoretical framework was used as the basis for categorising and analysing data. Data was first cleaned to ensure quality control of transcriptions, anonymised and then data familiarisation took place. A coding framework was developed and applied to the data, to systematically identify meaningful segments of data representing key patterns and themes in the data and assigning descriptive labels to them. The initial coding framework was iteratively refined and expanded, producing overarching categories, which were subsequently interpreted in relation to their broader implications. Final themes were supply chain management, resilience perceptions and strategy, and barriers and enablers. VERSIONING Changelog is within this readme file. Each step that will change the output files is listed below. Each change to this document is additionally listed below. Version 1 created 2025-04-30