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This study builds on the extant research of the authors on illegal rural enterprise (IRE). However, instead of taking a single or micro case approach within specific sections of the farming and food industries we examine the concept holistically from a macro case perspective. Many IRE crimes simply could not be committed without insider knowledge and complicity, making it essential to appreciate this when researching or investigating such crimes.

Using data from published studies, we introduce the theoretical concept of “Shadow infrastructure” to analyse and explain the prevalence and endurance of such criminal enterprises. Using a multiple case approach, we examine data across the cases to provide an analysis of several industry wide crimes—the illicit halal meat trade; the theft of sheep; the theft of tractors and plant; and the supply of illicit veterinary medicines.

We examine IRE crimes across various sectors to identify commonalities in practice and in relation to business models drawing from a multidisciplinary literature spanning business and criminology. Such enterprises can be are inter-linked. We also provide suggestions on investigating such structures.

We identify academic and practical implications in relation to the investigation of IRE crime and from an academic perspective in relation to researching the phenomenon.

This study combines data from numerous individual studies from a macro perspective to provide practical solutions to a multifaceted problem.

No study has investigated the effects of different parameters on publication bias in meta-analyses using a machine learning approach. Therefore, this study aims to evaluate the impact of various factors on publication bias in meta-analyses.

An electronic questionnaire was created according to some factors extracted from the Cochrane Handbook and AMSTAR-2 tool to identify factors affecting publication bias. Twelve experts were consulted to determine their opinion on the importance of each factor. Each component was evaluated based on its content validity ratio (CVR). In total, 616 meta-analyses comprising 1893 outcomes from PubMed that assessed the presence of publication bias in their reported outcomes were randomly selected to extract their data. The multilayer perceptron (MLP) technique was used in IBM SPSS Modeler 18.0 to construct a prediction model. 70, 15 and 15% of the data were used for the model's training, testing and validation partitions.

There was a publication bias in 968 (51.14%) outcomes. The established model had an accuracy rate of 86.1%, and all pre-selected nine variables were included in the model. The results showed that the number of databases searched was the most important predictive variable (0.26), followed by the number of searches in the grey literature (0.24), search in Medline (0.17) and advanced search with numerous operators (0.13).

The results of this study can help clinical researchers minimize publication bias in their studies, leading to improved evidence-based medicine.

To the best of the author’s knowledge, this is the first study to model publication bias using machine learning.

This paper aims to prompt ideas amongst readers (especially librarians) about how they can become active partners in knowledge dissemination amongst concerned user groups by implementing 3D printing technology under the “Makerspace.”

The paper provides a brief account of various tools and techniques used by veterinary and animal sciences institutions for information dissemination amongst the stakeholders and associated challenges with a focus on the use of 3D printing technology to overcome the bottlenecks. An overview of the 3D printing technology has been provided following the instances of use of this novel technology in veterinary and animal sciences. An initiative of the University Library, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, to harness the potential of this technology in disseminating information amongst livestock stakeholders has been discussed.

3D printing has the potential to enhance learning in veterinary and animal sciences by providing hands-on exposure to various anatomical structures, such as bones, organs and blood vessels, without the need for a cadaver. This approach enhances students’ spatial understanding and helps them better understand anatomical concepts. Libraries can enhance their visibility and can contribute actively to knowledge dissemination beyond traditional library services.

The ideas about how to harness the potential of 3D printing in knowledge dissemination amongst livestock sector stakeholders have been elaborated. This promotes creativity amongst librarians enabling them to think how they can engage in knowledge dissemination thinking out of the box.

Online food delivery applications (OFDAs) provide an expedient platform, and consumers’ access to food has been drastically altered, especially during and after the COVID-19 pandemic. This study aimed to completely explore the attributes that influence consumers' purchase intention and how an app's aesthetics can evoke feelings that predict continuous usage intentions for OFDAs. The food industry, especially restaurants, heavily relies on mobile technology to facilitate critical online food delivery during the pandemic crisis.

The data for this study are gathered from 477 food consumers located in the federal capital territory (FCT) of Islamabad, Pakistan, through convenient sampling by developing a self-administrated online survey. SmartPLS is used for structural equation modeling to test the proposed research model and perform bootstrapping and algorithmic analysis.

Our findings revealed that perceived value positively predicted consumers’ purchase intentions. Moreover, perceived value mediates the association of information quality, familiarity, time-saving, usability and reputation with purchase intentions and fear of COVID-19 moderates the relationship between perceived value and purchase intention.

This research work has significant implications for researchers, web developers, app designers, delivery services, restaurants and other enterprises as it demonstrates the importance of aesthetically pleasing OFDAs in eliciting positive emotions and bolstering consumers’ intentions to continue using the app for efficient food delivery services.

This study expanded the application of the technology acceptance model (TAM) and attention, interest, desire and action (AIDA) by examining consumers’ purchase intentions in the context of OFDAs. Further, the successful utilization of TAM enhanced the understanding of consumer perceptions and behavioral intentions about the usage of OFDAs.

The purpose of this paper is to design and manufacture an intelligent 3D printed sensor to monitor the re-occurrence of diaphragmatic hernia (DH; after surgery) in bovines as an Internet of Things (IOT)-based solution.

The approach used in this study is based on a bibliographic analysis for the re-occurrence of DH in the bovine after surgery. Using SolidWorks and ANSYS, the computer-aided design model of the implant was 3D printed based on literature and discussions on surgical techniques with a veterinarian. To ensure the error-proof design, load test and strain–stress rate analyses with boundary distortion have been carried out for the implant sub-assembly.

An innovative IOT-based additive manufacturing solution has been presented for the construction of a mesh-type sensor (for the health monitoring of bovine after surgery).

An innovative mesh-type sensor has been fabricated by integration of metal and polymer 3D printing (comprising 17–4 precipitate hardened stainless steel and polyvinylidene fluoride-hydroxyapatite-chitosan) without sacrificing strength and specific absorption ratio value.

This paper aims to examine the global pattern of growth and development of eHealth research based on publication headcount, and analysis of the characteristics, of the keywords used by authors and indexers to represent their research content during 1945–2019.

This study adopted a bibliometric research design and a quantitative approach. The source of the data was Elsevier’s Scopus database. The search query involved multiple search terms because researchers’ choice of keywords varies very significantly. The search for eHealth research publications was limited to conference papers and research articles published before 2020.

eHealth originated in the late 1990s, but it has become an envelope term for describing much older terms such as telemedicine, and its variants that originated much earlier. The keywords were spread through the 27 Scopus Subject Areas, with medicine (44.04%), engineering (12.84%) and computer science (11.47%) leading, while by Scopus All Science Journal Classification Health Sciences accounted for 55.83% of the keywords. Physical sciences followed with 30.62%. The classifications social sciences and life sciences made only single-digit contributions. eHealth is about meeting health needs, but the work of engineers and computer scientists is very outstanding in achieving this goal.

This study demonstrates that eHealth is an unexplored aspect of health literature and highlights the nature of the accumulated literature in the area. It further demonstrates that eHealth is a multidisciplinary area that is attractive to researchers from all disciplines because of its sensitive focus on health, and therefore requires pooling and integration of human resources and expertise, methods and approaches.

This study aims to assess the household food insecurity in Malaysia during the initial phase of the movement control order (MCO) to provide insights into the prevalence and predictors of food insecurity in this context.

The research used an online cross-sectional survey between March 28 and April 28, 2020. The study collected data from the Radimer/Cornell Hunger Scale and a food insecurity instrument. Analytical tools included chi-square and logistic regression models.

Of the 411 participating households, 54.3% were food-secure, while 45.7% experienced varying food insecurity. Among these, 29.9% reported mild hunger-associated food insecurity, 8.5% experienced individual food insecurity and 7.3% reported child hunger. The study identified predictors for food insecurity, including household income, as those with total income of < RM 2,300 had 13 times greater odds (odds ratio [OR] 13.8; confidence interval [CI] 5.9–32.1; p < 0.001) than those with income of RM 5,600, marital status as divorced (OR 4.4; 95% CI 1.0–19.9; p-value = 0.05) or married (OR 1.04; 95% CI 0.52–2.1) compared to those who are single. Self-employed respondents had three times greater odds of living in a household experiencing food insecurity (OR 3.58; 95% CI 1.6–7.7; p-value = 0.001) than those in the private sector (OR 1.48; 95% CI 0.85–2.61) or experiencing job loss (OR 1.39; 95% CI 0.62–3.1) compared with those who reported being in full-time government employment.

This study acknowledged limitations, such as not considering various dimensions of food insecurity, such as coping strategies, nutritional support, diet quality and well-being, due to the complexity of the issue.

The study underscores the importance of targeted support for vulnerable groups and fostering collaborative efforts to address household food insecurity during crises like the MCOs.

The research offers insights into how to address household food insecurity and its impact on society.

It identifies predictors, quantifies increased odds and emphasizes the necessity of targeted policies and collaborative approaches for fostering resilient recovery and promoting well-being in vulnerable populations.

The purpose of this study is to provide information on how citizens in nine countries across Europe perceive egg product quality and the importance of a product's sustainability attributes (animal welfare, country of origin and production method) in egg purchases.

The data were gathered in 2021 via an online survey in nine European countries (Finland, the United Kingdom, France, Italy, Belgium, Germany, the Netherlands, Romania and Denmark). A total of 3,601 responses were collected. As methods of analysis, exploratory factor analysis (EFA), independent samples t-test, paired samples t-test and one-way analysis of variance (ANOVA) were conducted when investigating the quality dimensions of egg products and the differences amongst the sociodemographic groups.

Citizens in European countries considered animal welfare aspects, production method and country of origin important when purchasing egg products. Citizens' perceived quality of egg products was related to two dimensions (i.e. product properties and responsible production), and there were differences in perceptions by sociodemographic groups (i.e. age, gender, education and country of residence). Responsible production was most valued by younger women with higher education. Also in the Netherlands and Romania, citizens had stronger preferences for product properties compared to responsible production, whilst in Germany, responsible production was appreciated more than product properties.

The study provides new information on citizens' perceived egg product quality and the role of a product's sustainability attributes in egg purchases. Furthermore, the results bring novel insights on the differences in perceptions amongst citizens living in nine European countries.

After the completion of this case study, students will be able to understand the importance of being close to local people when embarking on social business; understand that clear purpose and good decision-making can lead to great outcomes; and learn that innovation is crucial to ensure sustainability of both business and impact.

The case highlights the journey of Laiterie du Berger (LDB), a social enterprise in the agribusiness industry and the challenges faced as it expands and innovates. LDB’s roots lie in its commitment to social impact, aiming to uplift the Fulani livestock farmers and address socioeconomic issues. The company’s business model prioritizes people over profits, focusing on sustainable development and poverty alleviation. The LDB case showcases the challenges and opportunities in the agribusiness industry. LDB’s commitment to social impact, demonstrated through its support for farmers and sustainable farming practices, has been integral to its success. As the company expands and innovates, it faces critical decisions that require balancing financial growth with social responsibility. By embracing development, innovation and collaboration, LDB can continue to be a catalyst for positive change in the agribusiness industry while staying true to its roots and the principles that have defined its journey.

This case study is designed for bachelor’s and master’s degree students in the field of entrepreneurship and innovation, as well as MBA students. The case focuses on social entrepreneurship with the example of an agribusiness company located in Senegal, prioritizing social impact and quality of life. The case study explores the dynamics of the sector, including expansion strategy, innovation initiatives and the dilemma of balancing social mission and profit that social entrepreneurs may be facing. By analyzing this real-world situation of LDB, students will have the opportunity to enhance their decision-making skills.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship

Guided by the salutogenic model of health and well-being, this study aims to use empirical measures of sense of coherence (SOC) and generalized resistance resources (GRRs) to gain a better understanding of the facilitators of successful transition and integration of refugees to Canada and relate these findings to current program development and delivery for the settlement of refugees.

Survey research and structural equation modeling.

The authors found that newcomers with a stronger SOC were more likely to report successful integration outcomes. GRRs were found to have both direct and indirect effects on the positive settlement of refugees, with the SOC acting as a strong mediator of indirect effects.

Owing in part, to the disruption caused by the global pandemic, the authors’ data collection period was protracted and the final sample size of 263 is smaller than the authors would have preferred. Another limitation of this study has to do with its cross-sectional design, which limits the articulation of cause-and-effect relationships among the variables.

In terms of program development and delivery for the settlement of refugees, the authors’ results provide further evidence that refugee participation in socially valued decision-making represents a key determinant of healthy resettlement.

Much research on refugee settlement originates within “a pathogenic paradigm” that focuses on the stressors and obstacles encountered by people who have been displaced. Taking its cue from Israeli health sociologist, Aaron Antonovsky’s salutogenic model of health and well-being, this study uses empirical measures of Antonovsky’s interrelated concepts of SOC and GRRs to gain a better understanding of the facilitators of successful transition and integration of refugees to a prairie province in Canada and relate these findings to current program development and delivery for the settlement of refugees.