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The objective of this paper is to study the efficacy of the ASPECTSS Design Index's concepts as drivers of design intervention for educational environments for students on the autism spectrum. Based on the seven principles of acoustics, spatial sequencing, escape spaces, compartmentalization, transitions, sensory zoning and safety, ASPECTSS formed the basis for a preliminary post-occupancy evaluation (POE) and survey of an existing school environment.

Concepts drawn from the review of other strategies for autism spectrum disorder (ASD) friendly design were integrated with the seven ASPECTSS principles to create a design framework and consequent design retro-fit for a Pre-K-12th grade public school for students on the autism spectrum. The following design interventions were proposed: colour-coding based navigation; acoustical treatments in key circulation spaces; introduction of transition alcoves; classroom reorganisation using compartmentalization principles and the introduction of escape spaces for de-escalation. Specifically, a classroom template of modules of ASPECTSS-compliant layouts was provided to all staff. The efficacy and impact of these interventions were assessed using a whole campus online staff survey with further probing using classroom observations and subsequent interviews.

The results show alignment between the implementation of the ASPECTSS informed design interventions and responses to nine of the Likert scale items were all significantly lower than the middle response, indicating a high degree of satisfaction from survey respondents. These questions and responses related to the colour scheme facilitating ease of navigation for visitors of the school, the acoustics of the building successfully mitigating sound magnification and subsequently student distractibility, the organisation of the classrooms enhancing learning and the de-escalation zones allowing improved management of disruptive behaviours in the classroom.

This study focuses primarily on the Autism ASPECTSS Design Index as a framework for assessing classroom efficacy. Other tools and frameworks may produce different insights. A single school site was studied. Validation of these findings in other school environments is necessary before generalising these strategies at scale. The use of qualitative tools, primarily teacher and staff surveys, provides one lens into the efficacy of these design strategies. Further research using measurable biometric indicators such as heart-rate and stress levels measured through wearable technology could provide a first step towards the triangulation of these findings.

These findings could help provide more standardised best practices for designing learning environments for autism, potentially providing supportive strategies with real impact on learning quality, skill development and knowledge acquisition in school environments. This could potentially have economic implications by supporting more efficient progress for autistic students through their school curriculum.

Similar to economic impact, if validated and generalised, these findings could help with sense of accomplishment, general mental health improvement, alleviation of family stress and potential reduction of stigma in the autism community.

There is a slowly emerging field of design guidance for autism schools, but very little empirical evidence on the measurable efficacy of these strategies. This research provides one type of such evidence, as measured by the perceived impact from the point of view of staff and teachers at the school.

The purpose of this paper is to explore the emergence of innovation in smart service systems to conceptualize how actor’s relationships through technology-enabled interactions can give birth to novel technologies, processes, strategies and value. The objectives of the study are: to detect the different enablers that activate innovation in smart service systems; and to explore how these can lead dynamically to the emergence of different innovation patterns.

The empirical research adopts an approach based on constructivist grounded theory, performed through observation and semi-structured interviews to investigate the development of innovation in the Italian CTNA (Italian acronym of National Cluster for Aerospace Technology).

The identification and re-elaboration of the novelties that emerged from the analysis of the Cluster allow the elaboration of a diagram that classifies five different shades of innovation, introduced through some related theoretical propositions: technological; process; business model and data-driven; social and eco-sustainable; and practice-based.

The paper embraces a synthesis view that detects the enabling structural and systems dimensions for innovation (the “what”) and the way in which these can be combined to create new technologies, resources, values and social rules (the “how” dimension). The classification of five different kinds of innovation can contribute to enrich extant research on value co-creation and innovation and can shed light on how given technologies and relational strategies can produce varied innovation outcomes according to the diverse stakeholders engaged.

Microbusinesses are better able to assist many disadvantaged groups in finding employment and breaking the cycle of poverty because they require less initial capital and employ a large number of poor people in developing economies. Women run and own the majority of micro-businesses in urban Ethiopia. This study aims to investigate women’s microbusiness participation decisions and the effect on poverty in the Wolaita zone southern Ethiopia.

A cross-sectional study was carried out using a mixed-methods research approach. A total of 384 women who owned micro-businesses were chosen using a systematic random sampling technique, while 36 women were purposefully chosen for qualitative data analysis. Data were gathered through survey questionnaires, in-depth interviews and focus group discussions. The collected data were analyzed by using a propensity score matching technique as well as contextual analysis.

The study discovered that women’s participation in registered micro-businesses had a higher and more beneficial impact on their food, non-food and overall consumer spending than women’s participation in unregistered microbusinesses, which helped to reduce poverty. Besides, overall women’s participation in micro-business increased their decision-making power and enabled them to provide resources for their families food and non-food consumption, with registered micro-business participants reaping the greatest benefits.

This research focused on the effects of women’s micro-entrepreneurship on poverty in low-income communities. Rather than providing food, clothing and/or other aid to women in disadvantaged communities, the authors asserted that assisting women and their micro-businesses allows them to be self-sufficient in terms of food and clothing as a long-term solution to poverty reduction. As a result, policymakers can use our findings to gain a better understanding of how women’s micro-entrepreneurship affects poverty reduction, allowing them to develop more effective anti-poverty initiatives. This study’s findings are novel and add to the body of knowledge in Ethiopia and the sub-Saharan African region.

The purpose of this article is to posit an alternative learning design approach to the technology-led magnification and multiplication of learning and to the linearity of curricular design approaches such as a constructive alignment. Learning design ecosystem thinking creates complex and interactive networks of activity that engage the widest span of the community in addressing critical pedagogical challenges. They identify the pinch-points where negative engagements become structured into the student experience and design pathways for students to navigate their way through the uncertainty and transitions of higher education at-scale.

It is a conceptual paper drawing on a deep and critical engagement of literature, a reflexive approach to the dominant paradigms and informed by practice.

Learning design ecosystems create spaces within at-scale education for deep learning to occur. They are not easy to design or maintain. They are epistemically and pedagogically complex, especially when deployed within the structures of an institution. As Gough (2013) argues, complexity reduction should not be the sole purpose of designing an educational experience and the transitional journey into and through complexity that students studying in these ecosystems take can engender them with resonant, deeply human and transdisciplinary graduate capabilities that will shape their career journey.

The paper is theoretical in nature (although underpinned by rigorous evaluation of practice). There are limitations in scope in part defined by the amorphous definitions of scale. It is also limited to the contexts of higher education although it is not bound to them.

This paper challenges the dialectic that argues for a complexity reduction in higher education and posits the benefits of complexity, connection and transition in the design and delivery of education at-scale.

Algorithmic and computational thinking are necessary skills for designers in an increasingly digital world. Parametric design, a method to construct designs based on algorithmic logic and rules, has become widely used in architecture practice and incorporated in the curricula of architecture schools. However, there are few studies proposing strategies for teaching parametric design into architecture students, tackling software literacy while promoting the development of algorithmic thinking.

A descriptive study and a prescriptive study are conducted. The descriptive study reviews the literature on parametric design education. The prescriptive study is centered on proposing the incomplete recipe as instructional material and a new approach to teaching parametric design.

The literature on parametric design education has mostly focused on curricular discussions, descriptions of case studies or studio-long approaches; day-to-day instructional methods, however, are rarely discussed. A pedagogical strategy to teach parametric design is introduced: the incomplete recipe. The instructional method proposed provides students with incomplete recipes for parametric scripts that are increasingly pared down as the students become expert users.

The article contributes to the existing literature by proposing the incomplete recipe as a strategy for teaching parametric design. The recipe as a pedagogical tool provides a means for both software skill acquisition and the development of algorithmic thinking.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

The purpose of this paper is to explore how process management (PM) can support small- and medium-sized enterprises (SMEs) in pursuing sustained competitive advantage. For this purpose, a dynamic capabilities (DC) lens was used.

A narrative literature review and a multiple case study with an action research approach at two road freight transport companies were used.

PM provides structure and system thinking to support the development of competitive advantage. Concerning PM, management of knowledge, management style and process orientation are key factors for the generation of competitive advantage for SMEs.

This study contributes to PM literature by studying its support for and implementation at SMEs. Furthermore, the study contributes to the literature on DC by providing concrete examples of activities linked to such capabilities.

This study contributes to practitioners by providing examples of implementing PM and identifying competitive advantage, connected with PM elements.

This study has social and environmental implications for the quality of life of the Swedish people.

This paper contributes to clarifying the connection between the research fields of quality management and DC to explore how PM can support SMEs in pursuing sustained competitive advantage.

Educational design patterns offer practical strategies that can be shared and adapted to address problems in teaching and learning. This article explores how educational design patterns for connected learning at scale at an Australian university may be adapted to a Vietnamese higher education context.

12 educational design patterns that address the challenges of active learning and large teaching team management are discussed. The authors then critically reflect on their cross-cultural adaptation for the higher education context, from an Australian to a Vietnamese university.

Transitioning from passive to active learning strategies and effectively leading large teaching teams present similar challenges across our contexts. Educational design patterns, when dynamically adapted, may assist educators to teach skills that are critical for work and the future. Higher education institutions globally could enhance their practices by incorporating international best practice approaches to educational design.

The Connected Learning at Scale (CLaS) educational design patterns explored in this article offer solution-oriented strategies that promote a more active learning experience. This paper identifies adaptations for educators, especially those in Vietnamese higher education that respect traditional structures, cultural nuances and resource limitations in implementation.

Whilst educational design patterns are well-researched in the Western contexts, few studies analyse design patterns in an Asian, and in particular the Vietnamese context. More research is needed in the cross-cultural adaptation of educational design patterns that joins practice and theory.

This paper explores how adaptive organizations, companies capable of continuously adapting their organizational model, dynamically solve the universal problems of organizing.

The authors applied grounded theory to data acquired from six interpretative case studies, collected in two rounds of interviews (15 in total), then completing and validating the study’s evidence through triangulation with several secondary data sources.

In adaptive organizations, polyarchies and intrapreneurial employees are essential to shape the division of labour, leading to high levels of autonomy and empowering individuals and teams, while reducing bureaucracy and hierarchy. In terms of the integration of effort, digital solutions are preferred to social proof in the provision of information, while the authors note that incentives are always geared towards developing strong higher-order dynamic capabilities.

This paper has some limitations that could be addressed in future research, including longitudinal studies to analyse the link between the universal problems of organizing and a company's dynamic capabilities.

Adaptive organizations go beyond tech firms in responding to the universal problems of organizing work by making specific use of digital technologies.

The paper studies how companies should organize themselves so that they continuously adapt to an ever-changing competitive environment.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.