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Large scale research infrastructures (LSRIs) are rising in the competitive and globalized research environment, since they offer to external researchers-users, inputs and services for cutting-edge, large scale researches. Such researches would not be possible with usual infrastructures and budgets of single universities and research institutions. However, despite the strategic relevance acknowledged to LSRI by the nascent literature and by national policymakers, there is a lack of understanding of configurations and key performances of a LSRI. This paper aims to bridge this gap by identifying key morphologies of LSRIs and analysing their performances.

The research is carried out adopting a mixed research methodology, merging a literature review with a survey conducted on a sample of 11 LSRIs; they provided the data set for the parametrization of a morphological matrix.

The research led to the identification of seven LSRIs morphologies, with different performance linked to their structure.

To the best of the authors’ knowledge, this paper originally proposes the data set needed to develop a morphological analysis of LSRIs.

The main aim of this study is to explore the appropriate factors in measuring COVID-19-induced supply chain disruptions and the impact of these disruptions on the economic vulnerability of small-scale farmers in Sri Lanka.

The findings revealed that most of the farmers have continued to cultivate even during the pandemic despite several challenges which affected their economic status. Therefore, it is concluded that COVID-19-induced transportation and demand disruptions exacerbated the economic vulnerability of small-scale farmers over the disruptions in supply and production.

The findings of this study are crucial for formulating novel policies to improve the sustainability of the Sri Lankan agricultural sector and alleviate the poverty level of Agri-communities in the countryside. As farming is a vital sector in the economy, increased attention ought to be given on facilitating farmers with government-encouraged loans or allowances for their financial stability. Further, the respective government authorities should develop programs for importing and distributing adequate quantities of fertilizers among all the farmers at controlled prices so that they can continue their operations without any interruption. Moreover, the government could engage in collaboratively work with private organizations to streamline the Agri-input supply process. There should be a government initiative for critical consideration of the issues of farming families and their continued motivation to engage in agriculture. Thus, farmers' livelihoods and agricultural prosperity could be upgraded through alternative Agri-inputs and marketing strategies, providing financial assistance, encouraging innovative technology, etc.

Despite the significance and vulnerability of the vegetable and fruit sector in Sri Lanka, there is a limitation in the empirical studies conducted on the supply chain disruptions caused by COVID-19 measures and their implications on the farmers' livelihood. Furthermore, previous empirical research has not employed adequate quantitative tools to analyze the situation or appropriate variables in evaluating COVID-19-induced disruptions. Hence, the current study explored the appropriate factors for measuring COVID-19-induced supply chain disruption using exploratory factor analysis. Then, the impact of those factors on the economic vulnerability of the small scale farmers was revealed through the ordinal logistics regression analysis.

This study aims to investigate the potential positive effects of cause-related marketing (CRM) campaigns that show evidence of commitment to espoused causes. It examines whether consumers respond positively when a CRM campaign promises to deliver proof of the espoused cause.

This study adopted the grounded theory approach to conceptualize the promised impact evidence construct. A promised impact evidence scale was developed and validated using robust qualitative and quantitative methods, including item response theory estimates.

The study provides evidence for promised impact evidence as a reflective second-order latent construct. The promised impact evidence scale demonstrates strong internal consistency, reliability and validity. In addition, this study posits that promised impact evidence is an antecedent of advertising trust, purchase intention, advertising credibility and persuasive and selling intent.

This study positioned the promised impact evidence scale against the theoretical underpinnings of the persuasion knowledge model. Specifically, this scale contributes to existing knowledge because it applies the persuasion knowledge model in CRM campaigns by adopting an acceptance focus, as opposed to the rejection focus used in developing persuasion knowledge model scales.

This aim of this study is to identify the ways of helping public authorities bring about change to environmentally sustainable household food practices.

The authors identified the practices involved in this concept from the consumer perspective and measured their diffusion among French households. The analyses were conducted following two successive data collection campaigns comprising 571 and 501 respondents in France. The methodology involved two complementary scaling techniques: factor analysis and item response theory.

The results show that consumers understand sustainable food through five food practices: buying and cooking products with sustainable attributes, anti-waste storage, self-production, plant protein consumption and anti-waste cooking.

The findings suggest that while at the individual level people appear to have incorporated anti-waste practices into their daily lives, at the household level, there is still work to be done for improving diets and stimulating the production of home-grown food. It is also worth noting that the emerging vision typically involves sustainable foods that are organic, locally grown, seasonal, based on fair trade and packaging-free.