Authenticity in co-design: empowering non-design-expert clients in practice

PurposeThis paper aims to share how an Asian university enhanced students’ global competence through international business study missions (BSMs). More specifically, it focuses on how the design of these BSMs enabled “deep” learning beyond industry tourism and how 21st-century competencies such as “global competence” can be acquired through participation in short-term, faculty-led study missions.Design/methodology/approachUsing the case study approach, it critically analyzes the learning goals and objectives, design decisions, implementation details and learning outcomes underlying three BSMs led by three instructors from the same university to the USA (New York), Germany (Berlin and Stuttgart) and South Korea (Seoul).FindingsThe study shows that students gained global competencies related to specific fields of study such as the creative industries, urban sustainability and entrepreneurship. It shows how design choices such as destination, range of organizations, length of individual visits, range of pedagogical techniques, intensity of preparation and quality of management contribute to students’ acquisition of global competencies.Research limitations/implicationsThis research presents a subset of case studies that may limit the generalization of the findings; the bias that results from an unrepresentative, opportunistic sample (selection bias); and lack of quantitative causality in a qualitative evaluation.Practical implicationsThe course design described here provides practical information for designing study abroad “deep” learning goals, objectives and outcomes focusing on global competence.Originality/valueThe detailed case studies of three instructors from different disciplines to achieve the country’s education vision of globally competent students.

A detailed theoretical analysis has been made of the factors which affect the positions of the hyperfine lines in electron spin resonance spectra. The deviations from the usual high-field-approximation formulas are found to depend on the relaxation and line-broadening interactions [H1(t)] as well as on the well-known corrections to the high-field approximation that result from the exact solution of the time-independent static Hamiltonian [Ho]. The time-dependent processes H1(t) make a direct dynamic contribution to the frequency shifts, and in addition they alter the frequency spectrum of the static Hamiltonian. This latter effect arises because the dynamics of the system are properly determined by the total Hamiltonian Ho+H1(t), not just by the time-independent part Ho. The theory is developed in terms of the Redfield—Abragam relaxation-matrix formulation, but simple models are also treated by a limited but more easily handled procedure based on the modified Bloch equations. The most interesting results predicted by the theory occur when there is a large alternating linewidth effect arising from modulations of the isotropic hyperfine splittings. Usually, the dynamic frequency shifts are less than the linewidths, but, when there is a large alternating linewidth effect, the dynamic shift is large compared to the width of the narrow lines in the spectrum even though it is still small compared to the width of the broad lines. The alternating linewidth phenomenon also changes the static frequency shift, e.g., in the case of two nuclei of spin I=1 it causes the mean relative static shift in the positions of the sharp lines to be a factor of 3 greater than in the absence of an alternating linewidth effect. The theory indicates that experimental studies of the frequency shifts and linewidths in appropriate systems should make it possible to determine both the magnitude of the mean-square fluctuations in hyperfine splittings and the correlation time characteristic of the fluctuating motions. The experimental determination of these two quantities, which appear only as adjustable parameters in previous theories, should make it possible to obtain considerable information about the inter- and intramolecular factors which influence the instantaneous structure of free radicals. It has been rigorously shown that, when the width variations among a group of degenerate or nearly degenerate transitions are small, the net shift is determined by the average value of the shifts, both static and dynamic, of all the components involved in the set of degenerate transitions. Unresolved shifts from proton splittings (or from other nuclei with spin I=½) usually cause all the hyperfine lines to be shifted by the same amount, independent of whether or not the width variations are small. Normally, the shifts arising from the effects of tumbling motions on the intramolecular, anisotropic, electron—nuclear, magnetic-dipole interactions are small, as are those arising from the cross term between the dipolar and g-tensor interactions.

Summary and Discussion The findings suggest that stressed individuals feel significantly better after exposure to nature scenes rather than to American urban scenes lacking nature elements. Compared to the influences of the urban scenes, the salient effect of the nature exposures was to increase Positive Affect — including feelings of affection friendliness, playfulness, and elation. The increase in positive affect produced by the nature scenes is consistent with the finding that the nature exposures also significantly reduced Fear Arousal. According to psychological theories, a reduction in arousal or activation produces pleasurable feelings if an individual is experiencing stress or excessive arousal (Berlyne, 1971, pp. 81–82). In contrast to the nature scenes, the urban views tended to work against emotional well‐being. The major effect of the urban scenes was to significantly increase Sadness. There was also a consistent but non‐significant tendency for the urban scenes to‐aggravate feelings of Anger/...

Today, it has been broadly acknowledged in the CCI community that children are not only active learners and users of technology, but can also actively participate in the design process. However, it remains challenging to analyze children's experiences and creative contributions resulting from co-design activities (e.g. stories, paper prototypes, enacted ideas). Broadly speaking, a distinction can be made between researchers looking for inspiration in the form of useful design ideas, and researchers that take a more interpretative stance by looking beyond the surface level of children's ideas to better understand and empathize with them. This knowledge about children is often used to more accurately define the problem space at the early stages of design. Both perspectives to co-design can be seen as the opposite ends of the same continuum, and many researchers combine aspects of both depending on where they are in the design process (e.g. defining the design problem, prototyping stage). This workshop will explore different ways to analyze children's (0 to 18 years) experiences and contributions in co-design activities, the perceived benefits and challenges of these approaches, and will serve as a venue for synthesizing productive practices that will move the CCI community forward.

Architectural value can be seen in aesthetic form to make that physical form easy to recognize by surrounding people. For instance, iconic buildings can make cities easily known, historic buildings that capture the commemoration of famous events and people, and galleries and museums that hold and display cultural values and serve as places of focus and inspiration that bring people (communities) together (Scerri et al. 2016). Aesthetic value is a subjective evaluation; as researcher’s view the value can be defined as the beauty of the physical form, function, components, details and others. Value of the aesthetic can be obtained through the contribution of identity, vision and reputation as ways in which groups, institutions, and cities express an ideas, ambitions and intentions (Scerri et al. 2016). Other than that, architectural value able to create “sense of welcoming” for the destination and make the area rich in culture. Cultural value creates a sense of place by connecting location, context and patterns of historical development incorporating cultural symbolism and social meaning (Hayllar et al. 2008). The aesthetic and cultural value creates intangible social and community benefits while architecture value creates tangible benefits to a destination. This paper will describe researcher’s methodology consist of site study, method of research including qualitative and quantitative instruments which is describe in detail. It also identifies sampling for data collection process, purposive sampling used because it has special relevance in this study. It is very important to ensure that this research is not misleading with the objective. In addition, purposive sampling signifies strategic choices about with whom, where and how they can give information through the research. All information obtained is based on several instruments to get views from various aspects and angles. The researcher found a research gaps; the value of architecture is not widely mentioned in many studies as it is a subjective subject for assessment and the tourism industry does not emphasize the importance of architecture, whereas it is a key element of the industry’s success. In conclusion, this research plays important role in explaining the key components of the study which can be a guide for another researcher. The study will conduct to analyze value of physical structure as tourism attraction and explore urban tourism elements which is an important factor to forecast tourist motivation in urban area for tourism activities. Thus, the activities will contribute to the economic growth of the place.

– An increasing number of companies are experimenting with ‘designerly ways of innovating’ to improve the agility, speed and hit rate of their innovation activities. Co-design activities are emerging as part of a design-led innovation approach. Whilst there is extensive academic literature on design process performance metrics, they have rarely been applied by organisations that are testing co-design activities, possibly due to the time and effort that is required to apply them. This paper begins to address this challenge by developing a tailored suite of design process performance metrics. Some basic guidelines from the academic literature and the results of a practitioner survey inform the selection of metrics. We go on to apply the metrics to real-world projects within companies that are trialling technology-supported co-creation sessions. The metrics and the insights into their development and application are likely to prove useful to other design researchers and practitioners that wish to evaluate the benefits of adopting co-design activities as part of a design-led innovation approach.

An artificial intelligence (AI) design decision model is constructed to improve the efficiency of design decision evaluation and avoid the influence of the decision preference on product design and development. Using the concept of AI, the proposed model is based on a data set of product modeling design schemes, and the data set is marked with product modeling semantics. The deep learning residual network (ResNet) algorithm is used to train the data set to improve the accuracy of design decisions, transform the general design decision problem into the semantic recognition problem of design scheme images, and eliminate the design decision preference to the greatest extent. The validity and the feasibility of the proposed AI design decision-making method based on the ResNet algorithm are verified via an example of motorcycle modeling design decision-making.

During the First World War, the Russian-Turkish border, also known as the Caucasian Front or Eastern Front, extended from the Black Sea to the northern regions of Iran. The defense of this front was assigned to the Ottoman Third Army, led by Mahmud Kâmil Pasha. The Ottoman Empire had a strategic interest in the Caucasus region, aiming to maintain influence in the area if Russian power were to be established there. Additionally, they sought to utilize an Independent North Caucasus as a buffer in case of changes in the geopolitical situation. To further these goals, between August and October of 1914, regiments supporting the Ottoman army were dislocated along the Russian-Turkish border. These regiments were coordinated by the Istanbul center of the Teşkilat-ı Mahsusa organization. Three headquarters were established in strategic locations: Erzurum, Van, and Trabzon. This strategic planning and organization were indicative of the Ottoman Empire's efforts to assert control over the Caucasus region and to prepare for potential conflicts and shifts in power dynamics during the First World War. Such strategic planning testifies to the Ottoman Empire’s efforts to establish control over the Caucasian region and to prepare for potential conflicts and shifts in power dynamics during the First World War. Within the framework of the article, we aimed to explore recent publications concerning the organization known as Teşkilat-I Mahsusa, which has gained significant traction. We sought to shed light on the activities of the Erzurum branch, focusing on key details from the memoirs of Arif Cemil (Denker) and Ebulhindili Cafer Bey.

This vital volume clearly explains cutting-edge theories and views on strategic management in applied management fundamentals in the hospitality and tourism industry. The author discusses the latest in strategic thinking and provides information on implementing models within specific contexts, such as culture and profit and nonprofit organizations. He also looks at the political, economic, social, and technological changes that significantly affect tourism and hospitality. The volume is distinguished by its thoughtful analysis and review of related hospitality case studies and the management approaches employed and sheds light on ever-the emerging management and operation issues in the tourism and hospitality sector.  The book employs an abundance of case studies that illustrate the concepts and models discussed, with examples from such heavyweights in the industry as Disney and Euro Disney, Aer Lingus, British Airways, Four Seasons, Holiday Inn, Marriot, Sofitel, Starwood Hotels, and more. Key features of the book include: Cutting-edge approach: Applies advanced and recent strategic management views to the tourism and hospitality field. Critical treatment: Provides critical discussions about whether and how strategic models/theories can be applied in the hospitality and tourism field. Sensitive to specific contexts: As the tourism and hospitality industry has become one of the largest industries worldwide, discusses how strategic management concepts can be applied in different cultures and profit and nonprofit tourism organizations. Extensive case studies: Provides supporting case studies related to the strategy content, context, and process from international industries such as Aer Lingus, Accor, Marriott and Ryanair. Organization of the book: Each of the chapters within the case study sections employs a thorough pedagogic structure consisting of a concise introduction, examples and case analysis, discussion points, exercises, and further reading.  This book is designed to provoke thought and debate about strategic management and myriad other issues. It will be valuable for students, academics, universities offering hospitality and tourism, and hospitality and tourism professionals.

Integrating innovative marketing strategies in sustainable tourism development is imperative to meet the evolving demands of modern travelers. This research explores the efficacy of experiential marketing and technology integration in promoting sustainability within the tourism industry. Employing a literature review approach, this study critically examines the existing literature on innovative marketing strategies, collaborative initiatives, and methodological advancements in sustainable tourism marketing. The findings underscore the significance of experiential marketing in fostering environmental stewardship, promoting cultural authenticity, and cultivating lasting emotional connections with tourists. Moreover, the study highlights the pivotal role of technology integration, mainly through digital platforms and big data analytics, in enhancing destination competitiveness and disseminating information about eco-friendly tourism offerings. Collaborative initiatives such as destination partnerships and community-based tourism projects are also identified as effective mechanisms for promoting sustainability and equitable tourism development. Furthermore, the research emphasizes the need for interdisciplinary collaborations, innovative methodologies, and critical engagement with power dynamics and equity issues to advance knowledge and inform evidence-based policies and practices in sustainable tourism marketing. Overall, this study contributes to a deeper understanding of the complex interplay between marketing strategies, sustainability practices, and destination outcomes in the tourism industry.

BackgroundWeight management services have not always benefitted everyone equally. People who live in more deprived areas, racially minoritised communities, those with complex additional needs (e.g., a physical or mental disability), and men are less likely to take part in weight management services. This can subsequently widen health inequalities. One way to counter this is to co-design services with under-served groups to better meet their needs. Using a case study approach, we explored how co-designed adult weight management services were developed, the barriers and facilitators to co-design, and the implications for future commissioning.MethodsWe selected four case studies of adult weight management services in Southwest England where co-design had been planned, representing a range of populations and settings. In each case, we recruited commissioners and providers of the services, and where possible, community members involved in co-design activities. Interviews were conducted online, audio-recorded, transcribed verbatim, and analysed using thematic analysis.ResultsWe interviewed 18 participants (8 female; 10 male): seven commissioners, eight providers, and three community members involved in co-designing the services. The case studies used a range of co-design activities (planned and actualised), from light-touch to more in-depth approaches. In two case studies, co-design activities were planned but were not fully implemented due to organisational time or funding constraints. Co-design was viewed positively by participants as a way of creating more appropriate services and better engagement, thus potentially leading to reduced inequalities. Building relationships– with communities, individual community members, and with partner organisations– was critical for successful co-design and took time and effort. Short-term and unpredictable funding often hindered co-design efforts and could damage relationships with communities. Some commissioners raised concerns over the limited evidence for co-design, while others described having to embrace “a different way of thinking” when commissioning for co-design.ConclusionsCo-design is an increasingly popular approach to designing health in services but can be difficult to achieve within traditional funding and commissioning practices. Drawing on our case studies, we present key considerations for those wanting to co-design health services, noting the importance of building strong relationships, creating supportive organisational cultures, and developing the evidence base.

In recent years, children’s mental health problems, including Attention Deficit Hyperactivity Disorder (ADHD), have been a growing phenomenon. However, there are limited examples of designing for and with children with ADHD. This work views conditions such as ADHD through the lens of neurodiversity as different cognitive styles, focusing on “coolabilities” and enhanced competences instead of disabilities. This paper explores how to engage children with ADHD in co-design activities. Taking the Diversity for Design (D4D) framework as a starting point, an adaptation of the framework for ADHD was first driven by theoretical considerations and three expert interviews, followed by an empirical study consisting of three co-design workshops with four male participants (aged 7–10). Based on observations and audio recordings from the co-design workshops, a qualitative analysis was carried out. Our results show that when their needs, preferences, and individual desires are taken into account, children with ADHD can be meaningfully engaged in co-design activities. By offering an adapted version of the D4D framework tailored for ADHD, designers can structure the environment and provide scaffolds so that children with ADHD can become active participants in co-design workshops. This research informs the design community on how to engage and involve children with ADHD into the design process.

This paper reports the challenges of designers developing an SMS service for and with a vulnerable user group; homeless people; and their supporting agencies in London. It also describes the deployed methods in the design process. Co-design activities were performed with homeless people in and outside their living environments such as streets; a hostel and a day centre. The first author engaged with them as an insider (volunteer) or an outsider (designer or facilitator). This paper highlights how co-design activities in the inside and outside environments of a vulnerable user group affect the engagement of this group. Furthermore; the paper discusses ethical issues and the different roles (insider-outsider; volunteer-professional) designers are confronted with in this particular situation. We finally recommend designers to allow participants to share ownership of the project and carefully consider their capabilities of engagement.

This academic journal aims to provide a comprehensive documentation of the architecture, design decisions, and implementation details of an ingestion framework.The framework facilitates efficient and reliable data ingestion from heterogeneous sources into a target system, enabling organizations to leverage their data for various analytical purposes.The journal elaborates on the key components of the ingestion framework, highlighting the architectural design choices made, and discussing the implementation aspects involved.Through this documentation, readers can gain insights into the framework's functionality, scalability, and applicability in different use cases.

Identification of design solutions for a built environment that caters to the human needs at all levels, and more specifically, to the needs of the clients and the society, is the main task addressed by architectural design. Architectural design is a prime example of a design task that is characterized by a high degree of complexity. Architectural design problems by definition entail relationships between decisions and objectives that are all but transparent. For the decision-maker to be able to guide design towards fulfilling objectives, a ‘closed-loop’ approach where variations in design solutions are generated and evaluated in an iterative process is employed. Due to the sheer number of alternative solutions to problems of even a moderate scale (due to combinatorial explosion), it is only feasible to iterate over a minuscule fraction of possible solutions. Design intuition of the professionals involved in design is a strong driving force behind the identification of design direction, in which alternatives are explored as part of the preliminary design process. This is an approach that depends on the human cognitive capabilities to navigate the design space and identify potentially promising solutions. Regardless, the complexity associated with architectural design often poses significant challenges to human cognition. Human cognition, while formidable in its ability to flexibly and efficiently navigate challenging environments, is faced with difficulties in addressing the complexity factors outlined previously, namely: the excessive (combinatorially explosive) number of potential solutions to architectural problems, the complex and non-linear relations between objects and their properties and the conflicting nature of design goals that architectural design entails. Thus, design professionals are often faced with the real threat that their decisions may be biased due to the natural limitations of human cognition acting in complex environments.<br/><br/>Due to the reasons highlighted above, a systematic approach to design space exploration must be undertaken, to maximize the potential for discovering optimal solutions to design problems. Due to the nature of such problems that entail multiple conflicting objectives, a single best solution is generally not attainable. Nonetheless, best-tradeoff solutions are distinguished and highly desirable for such multi-objective design problems. The field of Computational Intelligence, and within that in particular Evolutionary Computation-based (EC) intelligent approaches, offer a lucrative option as decision-support tools in design, as they are able to efficiently address the aforementioned proponents of design complexity. EC approaches are able to navigate the design space efficiently and systematically, considering multiple conflicting objectives and hard constraints, and being able to deal with arbitrary relations between design decision variables and design objectives. <br/><br/>In today's setting, products of architecture must lead the way to a sustainable and environmentally friendlier society. As such, the performance of buildings has become the main driving force behind the design process, being referred to as ``performance-driven design''. This initiative emphasizes the quantitative evaluation of a design's function in accordance with established design objectives, related to aspects such as energy performance, visual and thermal comfort, cost and environmental footprint, etc. Simulation-based tools that enable accurate design evaluation are gaining ground and offering valuable insight into the performance of buildings. Nonetheless, making decisions in this multi-objective environment is not trivial, and, as stipulated above, may be challenging to human cognition. Thus, in today’s setting where the quantitative performance of buildings keeps gaining ground, the research on the application of EC in architectural design is high on the scientific agenda.<br/><br/>Recognizing the impact design complexity has on architectural design and the potential that EC-based approaches offer in addressing it, this thesis proposes a comprehensive computational intelligence decision support system that combines components based on intelligence with ones based on cognition, with the ultimate aim of enabling decision-makers manage design complexity and improve decision making. In particular, this thesis adopts the theoretical standpoint that efficient navigation of an unknown environment assumes a fusion of intelligence and cognition. In this sense, and given the already widespread adoption of intelligent approaches (such as EC mentioned above), the main contribution of this thesis is to endow the intelligent approach with cognitive facilities, so as to improve its efficiency to the point that it is readily applicable to the early stages of the architectural design process.<br/><br/>Fusion of intelligent with cognitive approaches, as outlined in the approach proposed by this thesis, offers the unique advantage of a decision support approach that is both powerful, owing to the extensive capabilities of intelligent search algorithms, and flexible, owing to the extensive knowledge modeling capabilities of cognitive approaches. As such, it is uniquely suited to the early conceptual design stage where the need to explore large design spaces, flexibly redefine the design problem, and satisfy preferences that are not included in the primary design goals, are all paramount.<br/><br/>Thus, the word ``comprehensive'' as it appears on this thesis' title obtains a twofold meaning: On one hand comprehension as in the combination of computational intelligence and cognition in a single approach; on the other hand, as in \\textit{comprehension} of the environment, the result of an intelligent and cognitive approach to understanding.<br/><br/>Firstly, it seeks to address the excessive computational burden associated with the use of modern high-fidelity simulation software in architecture, to render computational optimization more approachable. There is a clear trend in modern design practice to employ accurate simulation-based performance assessment tools from the very early stages of design. The use of such tools provides a valuable advantage to the decision-maker, in endowing objective awareness regarding the performance of a design solution. On the other hand, such tools are associated with a heavy computational burden, which may limit their application to the conceptual design stage. There exist methods to alleviate the computational burden through the use of computational cognitive machine learning tools, also known as surrogate modeling. However, training of surrogate models can be time-consuming itself, thus limiting the application. This thesis proposes a surrogate model that is modular in that it considers each space of the building in question as a separate entity, encoded through generic variables, and as such promotes model reuse in different design cases.<br/><br/>Secondly, it seeks to advance the state of the art on post-Pareto decision support by proposing a cognitive machine-learning based approach that enables the decision-maker to combine near-optimality with preferences regarding concrete features of the design solution. Post-Pareto decision making is an important step of the decision-making process, that seeks to identify a best-tradeoff solution among the possible ones that best matches the decision-maker's preferences in terms of performance. Such preferences are termed second-order because they follow design objectives in terms of importance. Nonetheless, it is often in architectural design that preferences are expressed in terms of design properties and not performance. Due to the non-linearity between the objective function space and the decision variable space that dictates object properties, it is challenging to exercise decision making using second-order preferences. Here the contribution of this thesis is a machine cognitive approach that learns the underlying relationships between object properties, distinguishing those that are relevant when the object is optimal with respect to design objectives. In other words, only imposing relations that are relevant to achieve optimality, it enables the expression of preferences by the decision-maker that are minimally constrained.<br/><br/>The main output of this thesis is a comprehensive decision support framework; it is a framework, in the sense that it comprises a set of methods and implemented tools that seek to augment decision making in architectural design; it is termed comprehensive in that it employs computational cognition and machine learning to augment the intelligent decision support capabilities throughout the design decision support process. It is also generic and applicable as-is to a wide spectrum of architectural design problems. In the context of this thesis, validation of the proposed approach is performed mainly in case studies relevant to facade design, recognizing this design topic as a complexity-exhibiting exemplar in architectural design practice.