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South Africa’s wool industry plays an important role in the agricultural sector. The wool industry provides a valuable source of income for farmers who practice sustainable farming practices. However, wool farmers face numerous challenges, such as wool contamination, dirty wool and producing good-quality wool. Good-quality wool is determined by fibre diameter, clean yield, vegetable matter and staple length. This study aims to address these challenges.

A multiple regression analysis of price (R/kg) of White wool and Merino wool was applied to four variables fibre diameter: vegetable matter, clean yield and staple length. The analysis was based on the data for the 2009–2019 data from Cape Wools auctions.

Fibre diameter, clean yield and staple length, with exception of vegetable matter, made a statistically significant contribution to the determination of wool price after all other independent variables were controlled for (p < 0.05). A one-unit (micron) increase in fibre diameter resulted in a 0.404-unit decrease in wool price (R/kg). A one-unit (mm) increase in staple length resulted in a 0.022-unit increase in wool price (R/kg). There was no statistically significant association between vegetable matter and wool price. A one-unit increase in clean yield was associated with a 0.111-unit increase in wool price (R/kg).

Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool.

Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool.

In a developing country such as South Africa, this study is important for the following reason. It is understanding the wool characteristics that have the most significance influence on the determination of wool price for Merino wool and White wool might effectively help the wool farmers to adapt their production systems to improve the wool characteristics that determine wool price.

This study identified a need for a study to be conducted on all wool classes.

Studies on the coronavirus disease 2019 (COVID-19) tracing apps have mostly focused on how to optimize adoption and continuous use, but did not consider potential long-term effects of their introduction. This study aims to analyse whether the characteristics of the recent introduction of tracing apps may negatively impact individuals' attitudes and intentions to adopt future tracking technology.

In an online experiment across three countries (Australia, Germany, UK), the authors measured how perceived benefits of COVID-19 tracing apps as well as specific government and campaign-related factors affect privacy concerns, attitude towards future tracking apps and intention to adopt. The authors manipulated the type of provider (governmental vs private) and the type of beneficiaries of the future tracking technology app (the individual alone or also the public) as determinants of adoption.

The authors find that privacy concerns towards the COVID-19 tracing apps negatively impact attitude and intention to adopt future tracking apps. Future adoption is more likely if the app is provided by the government, whereas additional benefits to the public do not positively stimulate adoption. Second, the study analyzed different factors, including perceptions on governments and the app introduction, as well as perceived benefits.

Taking the introduction of COVID-19 apps in different countries as a basis, the authors link both perceived benefits and contextual factors to privacy concerns, attitudes towards and intention to adopt the related technology in the future. The authors hereby clarify the responsibility of governmental actors who conduct large-scale technology introductions for the future diffusion of related technologies.

This paper proposes adequate strategies that companies, public administrators and organisations in the education industry can undertake to successfully face the challenges of digital transformation in a regional innovation system. This research considers stakeholders that operate in the Tyrol–Veneto macroregion (the Tyrol, South Tyrol and Veneto areas), a significant case of moderately innovative European macroregion.

This study undertakes explorative research based on a qualitative method. It adopts a place-based multi-stakeholder approach to emphasise the role of three categories of stakeholders (companies, educational system and regional governments) in facing digital changes. More precisely, interviews with 60 stakeholders from the Tyrol–Veneto macroregion were conducted and examined via both text mining analysis and content analysis. First, correspondence factor analysis was performed using IRaMuTeQ software to identify homogeneous subsets of concepts (pillars–i.e., macroareas of strategic actions). Second, two coding phases were implemented using NVivo software to detect strategic fields of action and specific strategic actions undertaken to address the challenges of digital transformation.

The results highlight that digital transformation is a pervasive challenge of regional innovative system that requires a multifaceted set of strategic actions falling into three main pillars. The first pillar, named “culture and skills”, includes three strategic fields of action as follows: digital education, talents and digital culture. The second pillar, named “infrastructures and technologies”, points out the need of information, interaction and artificial intelligence as key strategic fields of action. The third pillar, named “ecosystems”, highlights the importance of investing in medium- to long-term visions, partnerships and life quality. In brief, this study shows that standalone interventions are insufficient to tackle digital transformation from a systemic perspective. Moreover, this study outlines the potential contribution of each category of stakeholder to foster the digitalisation of the Tyrol–Veneto macroregion.

This study highlights the importance of developing digital culture and skills before investing in digital infrastructure and technology in a moderately innovative macroregion. Companies should alter their vision before reconfiguring their business models, invest in smart working and establish contacts with start-ups. In addition, this study recommends that public administration should mainly invest in digital education and partnerships, while, in terms of education and training organisations, it suggests providing digital skills to several cohorts of both students and workers. Policy implications call for the creation of new occasions of cooperation among stakeholders by fostering “table talks” as strategic and policy actions and by making more financial resources available to encourage the digital transformation processes.

The results of this study may be adapted to the characteristics of other regional innovative systems and used as a reference point in terms of the improvement of business, market and local development.

The purpose of this paper is to identify actions and guidelines for enabling and fostering the Industry 4.0 adoption, as well as to understand the role of three ecosystem actors in these actions (i.e. companies, educational organizations and regional policy makers).

52 semi-structured expert interviews in the Tyrol-Veneto cross-border macro-region were carried out and interpreted using the innovation ecosystem concept. In particular, drawing from this latter, six ecosystem building blocks were identified and used to analyze the interviews' content.

The findings allow not only to build a comprehensive framework for action to support Industry 4.0 adoption, but also to confirm the importance of exploring Industry 4.0 through the lens of the ecosystem concept. Indeed, the authors show that R&D activities should be complemented with interorganizational actions, such as training and networking, and that all ecosystem actors should be involved in the Industry 4.0 adoption.

This is among the few studies that adopt the innovation ecosystem perspective to explore best practices for Industry 4.0 adoption, thus overcoming the weakness of existing papers based on a firm-level perspective. It also complements previous ecosystem-based research on Industry 4.0 by exploring the technology adoption side, rather than the technology provision one, and by considering the adoption of a wide set of technologies.

This study explores ongoing research into self-mapped learning pathways that students utilize to move through a course when given two modalities to choose from: one that is instructor-led and one that is student-directed.

Process mining analysis was utilized to examine and cluster clickstream data from an online college-level History course designed with dual modality choices. This paper examines some of the results from different approaches to clustering the available data.

By examining how often students interacted with others, whether they were more internal or external facing with their pathway choices, and whether or not they completed a learning pathway, this study identified five general tactics from the data: Individualistic Internal; Non-completing Internal; Completing, Interactive Internal; Completing, Interactive, and Reflective and Completing External. Further analysis of when students used each tactic led to the identification of four different strategies that learners utilized during class sessions.

The results of this analysis could potentially lead to the creation of customizable design models that can assist learners as they navigate modality choices in learner-centered or less-structured learning design methodologies.

Few courses are designed to give the learners the options to follow the instructor or create their own learning pathway. Knowing how to identify what choices a learner might take in these scenarios is even less explored. Preliminary data for this paper was originally presented as a poster session at the Learning Analytics and Knowledge conference in 2019.

Policy makers, professional associations and scholars continue to advocate for the integration of enhanced clinical experiences for future teachers’ preparation. These recommendations reflect the growing recognition that few events in preservice teachers’ education are more significant than their experiences in the classrooms of veteran peers. Aware of the fact that the field of teacher education needs examples of effective clinical experiences, the authors examined the “critical, project-based” (CPB) model, employing Photovoice activities in a dropout prevention course in a secondary education partner school at the beginning of the COVID-19 pandemic. This paper aims to discuss the aforementioned objective.

Aware that the field of teacher education needs examples of effective clinical experiences, the authors examined the CPB model, employing Photovoice activities in a dropout prevention course in a secondary education partner school at the beginning of the COVID-19 pandemic. In this article they detail a practitioner research examination that explores the experiences of 12 preservice middle/high school teachers, reporting on these individuals’ considerations of general pedagogies, writing instruction strategies and teaching personas.

Results suggest that preservice teachers might best identify pedagogical practices that are consistent with their nascent teaching identities via experiences that occur in school-university partnerships in which future teachers are positioned as pedagogues.

This manuscript explores the use of the “CPB” clinical experience model, identifying the impacts of this approach for preparing future teachers.