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The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.

The chapter aims to reflectively discuss a participatory research project concerning the future of higher education in Hungary. This project can be understood as an ongoing methodological experiment which attempts to engage teachers and students, in order to reveal how key stakeholders think about the future of higher education. In line with this, this methodologically oriented chapter shows how different participatory methodologies can be combined in a so-called backcasting framework. This approach starts by describing the present situation, then moves beyond the present conditions so as to identify the cornerstones of an ideal future state. On the one hand, the chapter gives a detailed introduction to how our participatory research process was set up and what particular methodologies we used during this process. On the other hand, it critically reflects on the methodological and ethical challenges involved.

While many characteristics of food consumption have been examined, little attention has been given to the health potential of consuming from local food communities. Local food communities, including community supported agriculture (CSA) are food initiatives, which try to respond to the healthy food, environmental or socioeconomic challenges of the food system. As a step toward understanding local food communities, this study sets out to examine the health-related adaptivity and self-management practices of CSA participation.

The qualitative research approach, which included semi-structured interviews (n = 35), was designed to discover the potential for being healthy: the ability to adapt and to self-manage among CSA participants. The data were analyzed using thematic analysis.

The results suggest that local food communities can influence health-related adaptivity and self-management in the following themes: awareness of product origins; enhanced food-management capability; expanding applicability and usability of the food environment; and strengthening one's food-related self-image.

Increasing the presence of local food communities might be part of developing strategies to evaluate the health effects of the local food environment and to encourage consumers to take responsibility for their own health.

This study extends the food consumption literature to include new knowledge about how local food communities facilitate individual efforts to enhance their own potential for health as well as improving understanding of the mechanisms that underpin a healthy diet.

The literature review of post-harvest supply chain (PHSC) losses is carried out and analyzed in this paper followed by bibliometric analysis of the literature.

The literature survey is performed across various dimensions such as PHSC losses, PHSC risks and PHSC sustainability (waste management and waste reduction). One hundred thirty research articles during the period of 1989–2020 were considered for the review.

The PHSC losses have been identified in this literature survey. The calculation and mitigation strategies stated by various researchers in the literature are addressed. The important loss mitigation dynamics are also presented to reduce the PHSC losses and to improve food availability.

The major focus is given on the PHSC of agriculture produces. However, research articles from fish and meat supply chain are excluded as they follow a different perishability curve.

The current work will add value to the agriculture supply chain literature, provide a platform for PHSC losses and provide assistance/guideline toward loss calculation, loss mitigation, improved rural employability, improved rural entrepreneurship and improved revenue generation.

The performed research will assist the researchers, entrepreneurs and farmers to understand the current scenario of food wastage at different stages of the supply chain better. It will provide the guidelines for calculation and mitigation of various stated PHSC losses. This study will be helpful to enhance food availability and food security in post-coronavirus crisis.

The paper explores and highlights PHSC loss calculations and mitigation strategies to identify the postharvest loss situation and better utilization of fresh produces.

This study aims to identify the key factors that influence the intention and behavior of Chinese consumers toward purchasing organic food. The extended theory of planned behavior (TPB) model is adopted as the underlying theory to explore the relationship between attitudes (ATT), subjective norms (SN) and perceived behavioral control (PBC) on consumers’ intention and behavior to buy organic food. Trust (TR) and the moderating role of short food supply chain preferences (SFSCPs) were integrated to address the research gap.

Three hundred three questionnaire responses were received from organic food buyers in China using a convenience sampling method. Structural equation modeling was used to analyze the data and to examine the relationship between the various constructs.

The results demonstrated that the purchase intention (PI) of Chinese consumers correlates positively with ATT, SN, PBC and TR. Additionally, the results show that consumers’ SFSCPs positively moderate the relationship between PI and purchase behavior (PB).

The findings of this study provide valuable insights for marketers to develop compelling messages that evoke positive ATT, establish consumer TR and integrate short food supply chains to drive PB. The study can also be useful to policymakers and other supply chain participants.

An increased understanding of the factors influencing Chinese organic food consumption can contribute to promoting healthier food choices, supporting sustainable agriculture and fostering environmentally friendly consumption habits.

This research contributes to the existing pool of knowledge by incorporating TR into the conventional TPB. The study also introduces SFSCP as a moderating variable on the relationship between PI and PB.

The food industry and its distribution solutions often lie at the center of sustainability-related arguments. However, little is known about the dynamic role of business capabilities for sustainable transformations in the context of local food distribution. Accordingly, this study aims to investigate how dynamic capabilities drive sustainable supply chain management (SSCM) business practices in short food supply chains (SFSCs) through the professionalization and expansion of online distribution channels.

The present study analyzes sustainability-related practices at six online distribution channels selling local food products in Germany and Austria. By applying a cross-case study and theory-elaboration approach, the study analyzes empirical data derived from these businesses and provides insights into how dynamic capabilities can facilitate SSCM practices within SFSCs. Hereby, potential pathways for a sustainable transformation in this industry context are deduced through abductive reasoning.

The empirical findings provide evidence that supply chain orientation, coordination, innovation practices and strategies are highly relevant for SFSCs seeking to reach upscaling effects in regional markets. However, because SFSCs may not be able to reach mass markets without weakening their own sustainability performance, the present study recommends addressing sustainability inefficiencies in the region and developing further expansion potentials through replication in other regions. In this approach, related and necessary SSCM dynamic capabilities were identified and validated based on the empirical findings.

Although SFSCs include sustainability aspects at their core – particularly regarding resource usage, environmental friendliness and social-standard assurance – missing distribution-related capabilities limit growth such that these businesses often remain in a niche. To address this issue, the study builds on dynamic capabilities theory by identifying and describing core SSCM practices and capabilities; moreover, this study is among the first to elaborate empirically on the use of dynamic capabilities theory in this specific industry context.

The purpose of this paper is to investigate the significant supply chain issues in the small and medium-sized enterprise (SME) food industry. The objectives are to identify the major themes and the dynamic evolution of SME food supply chain (FSC) issues, the current research trends, the different modelling approaches used in SME FSC, and the most addressed SME food sector.

In all, 3,733 published articles from 2002 to 2018 in the Clarivate Analytics Web of Science database were collected, from which 1,091 articles were shortlisted for the review. The authors used bibliographic coupling combined with co-word analysis to identify the historical relations of the research themes that emerged during the periods 2002–2014 and 2002–2018.

This research identified five major research themes such as production and distribution in alternative food networks, relationship, safety and standards in the FSC, greenhouse gas (GHG) emission impact of the farm food system, traceability and product quality in FSC and asymmetric price transmission in the FSC. Among the identified themes, GHG emission impact of the farm food system and traceability and product quality in the FSC have received increasing attention in recent years. The dairy sector is the most addressed sector (36 per cent), followed by fruits and vegetables (27 per cent), meat and poultry (18 per cent), seafood (10 per cent) and grains and oilseed (8 per cent). It is also identified that the dairy sector has received significant attention in the “GHG Emission impact of farm food system” theme. Similarly, meat and poultry sectors have received much attention in the “Traceability and product quality in the food supply chain” theme. Also, the authors identified that the empirical modelling approaches are the most commonly used solution methodology, followed by the conceptual/qualitative methods in the SME FSC.

This study maps and summarizes the existing knowledge base of supply chain issues in the SME food sector. The results of this review provide the major research areas, most commonly used approaches and food sectors addressed. This study also highlights the research gaps and potential future research direction.

The purpose of this paper is to present an alternative approach to facilities and built asset management adaptation planning to climate change based on a hybrid backcasting/forecasting model. Backcasting envisions a future state and examines alternative “pathways of approach” by looking backwards from the future state to the present day. Each pathway is examined in turn to identify interventions required for that pathway to achieve the future state. Each pathway is reviewed using forecasting tools and the most appropriate is selected. This paper describes the application of this approach to the integration of climate change adaptation plans into facilities and built asset management.

The researchers worked with various stakeholders as part of a participatory research team to identify climate change adaptations that may be required to ensure the continued performance of a new educational building over its life cycle. The team identified 2020, 2040 and 2080 year end-goals and assessed alternative pathways of approach. The most appropriate pathways were integrated into the facilities and built asset management plan.

The paper outlines a conceptual framework for formulating long term facilities and built asset management strategies to address adaptation to climate change.

The conceptual framework is validated by a single research case study, and further examples are needed to ensure validity of the approach in different facilities management contexts.

This is the first paper to explore backcasting principles as part of facilities and built asset management planning.

The article applies the citizen science phenomenon – i.e. lay people involvement in research endeavours aimed at pushing forward scientific knowledge – to healthcare. Attention is paid to initiatives intended to tackle the COVID-19 pandemic as an illustrative case to exemplify the contribution of citizen science to system-wide innovation in healthcare.

A mixed methodology consisting of three sequential steps was developed. Firstly, a realist literature review was carried out to contextualize citizen science to healthcare. Then, an account of successfully completed large-scale, online citizen science projects dealing with healthcare and medicine has been conducted in order to obtain preliminary information about distinguishing features of citizen science in healthcare. Thirdly, a broad search of citizen science initiatives targeted to tackling the COVID-19 pandemic has been performed. A comparative case study approach has been undertaken to examine the attributes of such projects and to unravel their peculiarities.

Citizen science enacts the development of a lively healthcare ecosystem, which takes its nourishment from the voluntary contribution of lay people. Citizen scientists play different roles in accomplishing citizen science initiatives, ranging from data collectors to data analysts. Alongside enabling big data management, citizen science contributes to lay people's education and empowerment, soliciting their active involvement in service co-production and value co-creation.

Citizen science is still underexplored in healthcare. Even though further evidence is needed to emphasize the value of lay people's involvement in scientific research applied to healthcare, citizen science is expected to revolutionize the way innovation is pursued and achieved in the healthcare ecosystem. Engaging lay people in a co-creating partnership with expert scientist can help us to address unprecedented health-related challenges and to shape the future of healthcare. Tailored health policy and management interventions are required to empower lay people and to stimulate their active engagement in value co-creation.

Citizen science relies on the wisdom of the crowd to address major issues faced by healthcare organizations. The article comes up with a state of the art investigation of citizen science in healthcare, shedding light on its attributes and envisioning avenues for further development.

Ongoing environmental threats have intensified the need for firms to take big leaps forward to operate in a manner that is both ecologically sustainable and socially responsible. This paper aims to assess the degree to which firms are adopting citizen science as a tool to achieve sustainability and social responsibility targets.

This study applies a qualitative content analysis approach to assess the current presence of citizen science in sustainability and social responsibility reports issued by Globescan sustainability leaders and by firms ranked by the Fortune 500 and Fortune Global 500.

While the term itself is mostly absent from reports, firms are reporting on a range of activities that could be classified as a form of “citizen science.”

Citizen science can help firms achieve their corporate sustainability and corporate social responsibility goals and targets. Linking sustainability and social responsibility efforts to this existing framework can help triangulate corporate efforts to engage with stakeholders, collect data about the state of the environment and promote better stewardship of natural resources.

Supporting citizen science can help firms work toward meeting UN Sustainable Development Goals, which have highlighted the importance of collaborative efforts that can engage a broad range of stakeholders in the transition to more sustainable business models.

This paper is the first to examine citizen science in a corporate sustainability and social responsibility context. The findings present information to support improvements to the development of locally relevant science-based indicators; real-time monitoring of natural resources and supply chain sustainability; and participatory forums for stakeholders including suppliers, end users and the broader community.