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This paper aims to explore pathways in which adaptation challenges may occur. Focus is on the barriers to adaptation, challenges to adaptation and maladaptation with reference to smallholder farmers in the Southern African Development Community region.

Bibliometric analysis techniques were used to track the literature on smallholder farmers’ adaptation challenges. Web of Science was the main data source. A total of 41 articles were retained for analysis and exported into Visualization of Similarities Viewer Software where the development of research on the subject, co-occurrence of keywords analysis, top publishers, citations and total link strength was done.

Results indicate that research on smallholder farmers’ adaptation challenges is not new but has gained more consideration post-2020. The main adaptation challenges emanate from perception barriers and constraints based on determinants of adoption, limitations for resilience building and achieving sustainable adaptation as well as contestations around Climate Smart Agriculture technologies.

Effective design of adaptation policies should center on prioritizing the needs of the local people. This would reduce the occurrences of smallholder farmers’ adaptation challenges, promote resilience building and contribute toward achieving sustainable adaptation.

It is equally important to document adaptation challenges. However, adaptation challenges are rarely shared with the same enthusiasm as its successes. This work focuses on the matter with the intention of conscientizing smallholder farmers to reduce the risk of repeating the same adaptation mistakes.

Computing seepage discharge in earth dams involves inherent complexities and challenges that require the use of probabilistic algorithms to accurately capture their uncertain characteristics and identify optimal solutions. This study aims to investigate the impact of uncertainty in seepage flow estimation using a novel hybrid approach, combining the analysis of Laplacian equations with the probabilistic finite element method (PFEM) and a metaheuristic algorithm.

To achieve this purpose, a finite element-based FORTRAN program was developed to model the problem using the Galerkin finite element method, which was validated using laboratory findings. Subsequently, Monte Carlo loops were incorporated into each model, consisting of 2000 iterations and the probability distribution function and cumulative distribution function were computed for each sub-model. A total of 138 earth dams were analysed to investigate the influence of different characteristics on seepage, including variations in dam geometry, soil permeability and water levels (both downstream and upstream). Effective seepage flow (ESF), was introduced in both deterministic and probabilistic models.

The findings indicated that the downstream slope has a more significant impact on ESF than the upstream slope, with a difference of 1.29%. Additionally, the ratio of dam height to bottom width (H/B) directly affects the ESF, resulting in a 20% increase in ESF for every 16% increase in H/B.

This study introduces a novel hybrid approach for estimating seepage flow in earth dams by integrating the Unlike traditional deterministic models, which often overlook the inherent .PFEM with a metaheuristic algorithman advanced uncertainties in seepage characteristics, this research effectively captures these uncertainties throughprobabilistic framework.

The paper aims to close a literature gap by proposing a comprehensive conceptual soft skills competency framework for enhancing graduate intern employability through the cultivation of employability capital.

The study employed a theoretical inquiry and delved into the existing literature on employability, soft skills competencies and employability capital to establish a comprehensive foundation to formulate the conceptual framework. A content analysis of existing empirical studies was conducted to derive a generic list of employers’ required soft skills. A Delphi technique was employed to harness expert consensus and insights into the derived framework.

Employability capital can be cultivated in the setting of work-integrated learning programmes and synergised through emotional and social intelligence interventions to enhance soft skills competency and graduate employability.

The soft skills identified may overlook other important skills required by employers. Increasing participation in the Delphi study could yield additional valuable insights. Validation of the framework is needed in practical settings to understand its effectiveness and applicability to real-world organisational needs.

This study significantly enhances understanding of the role of employability capital in soft skills competency development and graduate employability through work-integrated learning programs and self-development. In addition, the framework has the potential to positively impact the employer-employee relationship.

The key theoretical contribution is a soft skill development framework that offers employers and graduates a means to identify and address deficiencies through WIL and self-development.

This paper aims to investigate the entrepreneurial behaviours exhibited by commercial smallholder farmers in Zimbabwe, focusing on their socio-economic characteristics, and considers their implication for outcomes of livelihood resilience in a resource-constrained and turbulent rural context.

The study used survey data collected from 430 smallholder farmers in Masvingo province, Zimbabwe. Using a two-step cluster analysis, the study constructed a typology of farmers based on their entrepreneurial behaviour and socio-economic characteristics.

The results revealed that commercial smallholder farmers are heterogeneous in terms of their entrepreneurial behaviours. Four clusters were identified: non-entrepreneurial, goal-driven, means-driven and ambidextrous. Beyond their entrepreneurial behaviours, these clusters significantly differ in the socio-economic characterises (gender, age, education levels, farm size, proximity to the market and social connection) and farm performance (seasonal sales per hectare and farm income per hectare).

The typology framework relating farmers’ entrepreneurial behaviours to their socio-economic characteristics and business performance is important to tailor and therefore improve the effectiveness of farmer entrepreneurship programmes and policies. In particular, tailoring farmer entrepreneurship education is crucial to distribute land, finance and market resources in purposive ways to promote a combination of smallholder farmers’ effectual and causal behaviours at an early stage of their farm ventures.

Researchers still know little about which farmers’ behaviours are entrepreneurial and how these behaviours manifest in action during their commercial farm activities. This research leverages effectuation and causation theory to unveil previously overlooked distinctions on farmers’ entrepreneurial behaviours, thereby enhancing a more grounded understanding of farmer entrepreneurship in a resource-constrained context.

This study aims to propose a comprehensive framework for assessing circular economy (CE) performance in the agri-food sector. It identifies those indicators that should be used to measure circularity regarding CE strategies, applies them at a microeconomic level and examines the impact of key business determinants (financial, internalization, knowledge, awareness and digitalization).

A literature review was conducted with a focus on CE strategies and related indicators. The framework obtained is applied on a Spanish agri-food sector survey to provide an empirical CE analysis at firm level. A partial least squares based-structural equation modelling method is applied.

The research suggests a set of circularity indicators to assess CE strategies at micro level. The findings reveal the heterogeneity of CE sub-indicators related to narrowing, slowing, closing and regenerating strategies. It also highlights the strong effects that the drivers tested have on CE, especially awareness and knowledge.

This study provides a framework that can guide public policies and business decisions in sectors with significant environmental impacts. It provides a conceptual framework that explains which CE indicators should be considered by governments and regulators when developing policies that seek to promote circular strategies.

In the case of companies, the results show that acquiring more environmental awareness and knowledge is essential for promoting more sustainable work habits that enhance CE.

The paper offers a novel contribution to the CE literature by introducing a multidimensional indicator framework comprehensively applied to the agri-food sector, integrating miscellaneous pillars of circular strategies and business determinants.

The purpose of this study is to add to the currently limited research on individual level people analytics (PA) adoption by focusing on a vital resource in the implementation of PA, namely the technology used for PA. We draw on the unified theory of acceptance and use of technology (UTAUT) to examine antecedents of the use of technology for PA.

This study uses latent profile analysis to examine how different antecedents of PA (technology) adoption jointly act among 279 users of a specific PA technology.

This study identifies four user profiles, that we labeled the skeptic diplomats, the optimistic strugglers, the optimists, and the enthusiasts. These profiles relate to differences in user satisfaction and the frequency and versatility of PA technology use. This study demonstrates that performance benefits, social influence, required effort, and facilitating conditions jointly affect the use of PA technology, but that the latter two might be the most influential factors.

This study offers recommendations to practitioners and organizations on which actions by managers and the organization can be taken to support the use of PA technology.

Compared to previous research, we take a different approach by applying latent profile analysis to examine the combined effect of antecedents on user behavior and user satisfaction. In addition to a different analytical approach, we also extend existing research on individual PA adoption by focusing on actual behaviors and behavioral intention.

The purpose of the review is to synthesize the research on materiality measures of sustainability reporting and highlight how preparers, users, auditors, regulators and other stakeholders assess or determine the materiality in sustainability reporting. The review further summarizes the findings on consequences and determinants of material disclosures in sustainability reporting. Several directions for future research are also discussed.

This study provides a systematic review of materiality measures developed in the context of sustainability reporting. This synthesis of the literature summarizes the existing methodologies of measuring materiality. It also evaluates the strength and limitations of existing methods and approaches of measuring materiality in sustainability disclosures.

We find that the ex post materiality measures are simplistic and unidirectional in nature and ex ante materiality measures lack external validity and are generally narrow in focus – for example, focused on single firms or industries. Another major limitation in the current literature is the absence of robust empirical investigation of double materiality in sustainability reporting and a vast majority of the measures are developed without stakeholder engagement. Lastly, we document that the findings on determinants of material disclosure are fragmented and inconclusive and that the literature on consequences of material disclosure is rather un-explored.

The study explains the connections and differences between the various materiality measures. We document that materiality is measured in two distinct ways, ex ante and ex post and often times without stakeholder engagement. Moreover, given that a vast majority of the measures rely on manual content analysis, we find that they suffer from reproducibility and scalability.

Through the review of several journal articles on the adoption of information and communication technologies (ICTs) and how it impacts students’ motivation to continue with their studies or to drop out of their academic program, this study aims to review the literature on the impact of ICTs on student motivation at a university.

This paper is based on a systematic literature review steered by the PRISMA guidelines. This paper uses both Durban University of Technology subscription-based and publicly available papers. The research articles examined were published between 2018 and 2023 in Scopus, Web of Science and ScienceDirect.

Reviewed literature bespeaks that ICTs can increase student motivation by enhancing interactive, engaging and individualized learning. Digital technologies that engage students and offer a more engaging learning environment include instructional apps, online simulations and multimedia content. Using ICTs may be useful in lowering university dropout rates.

The systematic review yielded valuable insights for both academic research and real-world applications in education regarding the Durban University of Technology. The study offers a comprehensive analysis of the nexus between ICTs and student motivation.

This study aims to delve into the role that telehealth plays in mitigating health inequities faced by forcibly displaced Ukrainians amidst the ongoing conflict.

A retrospective cross-sectional study design was implemented, using data procured from the electronic health records of the Likarnya online project. The research approach integrated descriptive statistics, visual data representations and inferential analyses, including chi-square tests, odds ratio calculations and logistic regression tests.

The analysis revealed a predominance of female users (77.1%) and a high prevalence of health-care access barriers (69.7%). General practice/internal medicine consultations constituted the majority of referrals (72.93%), with a notable 78.66% of cases achieving closure. A significant prevalence rate was observed concerning chronic conditions relative to acute presentations. Statistical analyses uncovered significant associations between case severity and health-care access barriers, with moderate and severe cases demonstrating elevated odds of encountering obstacles to care. Age emerged as a crucial predictor of health-care access difficulties, highlighting the particular vulnerabilities faced by older displaced individuals.

This study highlights the potential of telemedicine in reducing health-care access disparities of displaced populations in conflict zones. Furthermore, this study brings to light pivotal insights concerning demographic and clinical variables that influence patterns associated with health-care services attainability. These findings serve as a clarion call for targeted interventions explicitly tailored for older individuals and those with severe health conditions. Hence, the findings provide a foundation upon which forthcoming academic endeavours alongside strategic policy formulation may be constructed.

This study aims to develop a maturity model to assess manufacturing companies’ adoption of digital technologies for energy efficiency and to formulate strategies to facilitate progress toward higher maturity levels. To achieve this goal, the study will identify and analyze the challenges inherent in the adoption and implementation of digital technologies for energy efficiency.

This study used a mixed methodology, combining analysis of the literature for building a maturity model and a questionnaire for validating the model and developing strategies for advancing maturity. The questionnaire was answered by 101 Swedish manufacturing companies.

The findings reveal that the aluminum industries and iron and steel industries exhibit higher maturity levels in adopting digital technologies. Most companies are intermediate adopters utilizing core technologies such as the Internet of things, cloud and big data for energy use monitoring, analysis and reporting. A smaller subset of companies, identified as leading adopters, reached the highest maturity level, integrating artificial intelligence, predictive analytics and machine learning into their energy management systems to optimize both production and energy use. A key challenge identified is the “lack of knowledge” regarding the adoption and implementation of these technologies.

It is essential to emphasize that the developed maturity model does not prioritize the adoption of multiple types of digital technologies. From a maturity standpoint, what truly matters is how effectively the information obtained from digital technologies is utilized in energy efficiency and energy management work to create knowledge and, thus, add value to the organization.

The maturity model and the strategies for advancing maturity related to the adoption of digital technology for energy efficiency are designed to be applicable to all types of manufacturing industries regardless of what sector or country the company is active in. The model can also be used by academia or other actors interested in evaluating the maturity level for the adoption of digital technologies for energy efficiency in companies in the manufacturing industry. The developed strategies offer guidance on determining which activities to undertake within the organization based on its current level of maturity.

This study’s main contributions are: (1) the maturity model to assess digital technology adoption for energy efficiency, (2) a set of strategies to advance maturity in adoption and (3) empirical investigation of maturity levels in the adoption of digital technologies for energy efficiency in 101 Swedish manufacturing companies.