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The most important advance in system design is the development of modeling and simulation methods to predict complex performance before prototypes are developed. New systems are developed in a spiraling approach; as more is learned about the system, design changes are proposed and evaluated. This approach allows the engineering team to “spin out” early versions of the system for preliminary evaluation, permitting changes to be made to the system design without incurring unacceptable cost. Because of the complexity of human performance, current modeling techniques provide only a first approximation. However, it has been demonstrated that even simple, inexpensive modeling approaches are useful in uncovering workload and performance problems related to developing systems (Barnes & Beevis, 2003). More important, these models can serve as the basis for operator simulation experiments that verify and also calibrate the original models. Furthermore, early field tests and system of systems demonstrations that can validate these results under actual conditions are becoming an increasingly significant part of the early design process. Fig. 1 illustrates this interdependence indicating a spiraling process throughout the design starting with simple predictive methods and progressing to more expensive validation methods. These iterations should continue until most of the soldier's variance is accounted for, and before any formal soldier testing is conducted. Fig. 1 presents the ideal combination of techniques; not all systems can be evaluated this thoroughly but more cost-effective modeling and simulation tools combined with realistic field exercises should make this approach more the norm as future unmanned systems are developed (Barnes & Beevis, 2003). In the remainder of this chapter, several case studies are presented to illustrate how the techniques in Fig. 1 have been applied in UAV programs.

Real-time simulation trials involving operational air traffic controllers are an essential stage in the validation of new ideas and computer assistance tools for air traffic control. This paper describes the business and technical background to such trials and then highlights two statistical issues which continue to complicate the design and reporting of trials:

Reconciling objective, subjective, quantitative and qualitative data: striking the right balance between controlled measurement and expert opinion;

Correlation and independence in sequences of data: designing cost-effective trials without over-sampling.

This chapter examines the development of an Entrepreneurship Education initiative (Triple E: Employability, Enterprise and Entrepreneurship) in the Higher Education context. The initiative is further contextualised by a dynamic policy framework concerning widening access as a major priority for the Scottish Government. In addition, the initiative is based on innovation in contemporary pedagogical design and further policy drivers supporting the development of graduates with an enterprising mind-set and graduate attributes (articulated by employers) and interpreted by academics and public sector stakeholders as relevant for graduate labour market competitiveness. The chapter examines Entrepreneurship Education literature and presents a case study which examines pedagogical design and normative assumptions, participant progression, (students and staff) and the engagement of external stakeholders. The case study describes and analyses the key design principles for inclusive and accessible Entrepreneurship Education within the context of widening participation policy. A discussion on the practice of achieving inclusive and accessible Entrepreneurship Education explores intra-institution policy, drivers enablers and cultural and resource constraints. The chapter concludes with a summary of the design principles on inclusivity and accessibility in Entrepreneurship Education and discusses attempts to mitigate the challenges presented by a widening participation policy.

“Shared purpose,” understood as a widely shared commitment to the organization’s fundamental raison d’être, can be a powerful driver of organizational performance by providing both motivation and direction for members’ joint problem-solving efforts. So far, however, we understand little about the organization design that can support shared purpose in the context of large, complex business enterprises. Building on the work of Selznick and Weber, we argue that such contexts require a new organizational form, one that we call collaborative. The collaborative organizational form is grounded in Weber’s value-rational type of social action, but overcomes the scale limitations of the collegial form of organization that is conventionally associated with value-rational action. We identify four organizational principles that characterize this collaborative form and a range of managerial policies that can implement those principles.

Fashion/textile small- to medium-sized enterprises (SMEs) are currently adding value to previously discarded textile waste by applying practical skills, knowledge and expertise to rework and reuse this material. As a result, sustainable design strategies such as zero-waste pattern-cutting, design for disassembly and upcycling are beginning to emerge. However, the scope for redesign will always be limited and the complete lifecycle of the material used needs to be considered at the front-end of the innovation process, to optimise material lifespans and reduce consumer waste. Further work is also required to inspire and educate the next generation of designers to the creative potential of reuse, and help the industry to understand its viability, scalability and role in the future. This chapter explores how the principals of the circular economy might support business model innovation within fashion and textiles. To this end, an exploratory canvas tool for SMEs, ‘Circular by Design’, was devised to aid SMEs to embrace closed-loop systems and to identify the most appropriate sustainable design strategies for their business.

Quality Function Deployment (QFD) proposes to take into account the “voice of the customer,” through a list of customer needs, which are (qualitatively) mapped to technical requirements in House One. But customers do not perceive products in this space, nor do they not make purchase decisions in this space. Marketing specialists use statistical models to map between a simpler space of customer perceptions and the long and detailed list of needs. For automobiles, for example, the main axes in perceptual space might be categories such as luxury, performance, sport, and utility. A product’s position on these few axes determines the detailed customer requirements consistent with the automobiles’ position such as interior volume, gauges and accessories, seating type, fuel economy, door height, horsepower, interior noise level, seating capacity, paint colors, trim, and so forth. Statistical models such as factor analysis and principal components analysis are used to describe the mapping between these spaces, which we call House Zero.

This paper focus on House One. Two important steps of the product development process using House One are: (1) setting technical targets; (2) identifying the inherent tradeoffs in a design including a position of merit. Utility functions are used to determine feature preferences for a product. Conjoint analysis is used to capture the product preference and potential market share. Linear interpolation and the slope point formula are used to determine other points of customer needs. This research draws from the formal mapping concepts developed by Nam Suh and the qualitative maps of quality function deployment, to present unified information and mapping paradigm for concurrent product/process design. This approach is the virtual integrated design method that is tested upon data from a business design problem.

Globalization should provide firms with an opportunity to leverage their know-how and reputation across countries to create value. However, it remains challenging for them to actually capture that value using traditional Intellectual Property (IP) tools. In this paper, we document the strong growth in patents, trademarks, and industrial designs used by firms to protect their IP globally. We then show that IP protection remains fragmented; the quality of IP applications might be questionable; and developing a comprehensive IP footprint worldwide is very costly. Growing numbers of applications are causing backlogs and delays in numerous Patent and Trademarks Offices and litigation over IP rights is expensive, with an uncertain outcome. Moreover, local governments can succeed in transferring value to local firms and influencing global market positions by using IP laws and other regulations. In essence, the analysis shows a global IP environment that leaves much to be desired. Despite these challenges, there are successful strategies to capture value from know-how and reputation by leveraging an array of IP tools. These strategies have important implications for management practice, as we discuss in our concluding section. Global companies will need to organize cross-functional value capture teams focused on appropriating value from their know-how and reputation by combining different institutional, market, and nonmarket tools, depending on the institutional and business environment in a particular region.

Over the past few years, mathematical and computational models of organizations have attracted a great deal of interest in various fields of scientific research (see Lin & Carley, 1993 for review). The mathematical models have focused on the problem of quantifying the structural (mis)match between organizations and their tasks. The notion of structural congruence has been generalized from the problem of optimizing distributed decision-making in structured decision networks (Pete, Pattipati, Levchuk, & Kleinman, 1998) to the multi-objective optimization problem of designing optimal organizational structures to complete a mission, while minimizing a set of criteria (Levchuk, Pattipati, Curry, & Shakeri, 1996, 1997, 1998). As computational models of decision-making in organizations began to emerge (see Carley & Svoboda, 1996; Carley, 1998; Vincke, 1992), the study of social networks (SSN) continued to focus on examining a network structure and its impact on individual, group, and organizational behavior (Wellman & Berkowitz, 1988). Most models, developed under the SSN, combined formal and informal structures when representing organizations as architectures (e.g., see Levitt et al., 1994; Carley & Svoboda, 1996). In addition, a large number of measures of structure and of the individual positions within the structure have been developed (Roberts, 1979; Scott, 1981; Wasserman & Faust, 1994; Wellman, 1991).

HyFlex course design is an effective instructional course design that combines active and transformative learning techniques. HyFlex course design encourages active learning by focusing on interactive activities, discussions, and collaboration. It also allows learners to collaborate effectively and flexibly as a community, providing peer support and opportunities for authentic dialogue and learning experiences. HyFlex course design provides the opportunity for transformative learning through its ability to offer personalized educational experiences to individuals. It facilitates greater customization of the learning experience, allowing individual learners to access tailored educational modules, offer personalized educational experiences to individuals, and effectively develop and build independent and critical thinking skills. This conceptual review, supported by implications from HyFlex literature and triangulated with experts' views undertaking a Delphi study, facilitates understanding the current state of research in HyFlex course design and future application strategies. Existing research has identified HyFlex courses as a promising means of engaging students in active learning. Allowing students to learn through flexibly predesigned mixed online and in-person experiences enables higher levels of student autonomy and supports students in taking more ownership of their learning. This approach can facilitate an understanding of how HyFlex courses can improve active learning practices in higher education. The review study findings identify the reported alignment issues and challenges, suggest four strategies and actions for policymakers and stakeholders, and provide a suggested research agenda for bridging identified research gaps.

Future research can provide evidence of the benefits of HyFlex course design and how flexible course design can address the challenges of traditional face-to-face courses, such as reduced student engagement, lack of student-centered approaches, and limited support for different learning styles. Further research can focus on strategies that can be used to promote active learning in HyFlex courses. Moreover, research can investigate how this kind of course design can equip educators with the skills and knowledge needed to design and implement effective and meaningful active learning experiences. Finally, research can assess the potential impact of HyFlex course design on student outcomes, including performance, satisfaction, and engagement.

Purpose — This study proposes an optimal survey design method for multi-day and multi-period panels that maximizes the statistical power of the parameter of interest under the conditions that non-linear changes in response to a policy intervention over time can be expected.

Design/methodology/approach — The proposed method addresses balances among sample size, survey duration for each wave and frequency of observation. Higher-order polynomial changes in the parameter are also addressed, allowing us to calculate optimal sampling designs for non-linear changes in response to a given policy intervention.

Findings — One of the most important findings is that variation structure in the behaviour of interest strongly influences how surveys are designed to maximize statistical power, while the type of policy to be evaluated does not influence it so much. Empirical results done by using German Mobility Panel data indicate that not only are more data collection waves needed, but longer multi-day periods of behavioural observations per wave are needed as well, with the increase in the non-linearity of the changes in response to a policy intervention.

Originality/value — This study extends previous studies on sampling designs for travel diary survey by dealing with statistical relations between sample size, survey duration for each wave, and frequency of observation, and provides the numerical and empirical results to show how the proposed method works.