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This chapter outlines a design-science perspective of entrepreneurship. It zooms in on the junction between present and future to distinguish entrepreneurship as a natural and as an artificial phenomenon. While the current study of entrepreneurship speaks to the former, it has been silent on the latter. The chapter discusses design as a distinct mode of research, opportunity as a design artifact, and the generative power of recursive action to make the case for problematizing entrepreneurial action as a focus of research. It then defines its research questions, discusses the logic and process for addressing them, and outlines the nature of research outputs.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

Researchers and practitioners working within transdisciplinary research projects face specific challenges when addressing representation of evidence-based concepts across complex occurrences, particularly when delivering a visitor experience design and documentary film encompassing an extensive cultural and natural heritage timeline period. In this chapter, these challenges are explored from the contrasting points of view of the view of the principal investigator and design lead and the filmmaker and researcher within an ongoing transdisciplinary research project Portalis, which is funded by the ERDF through The Ireland Wales Cooperation Programme.

The Portalis visitor experience design promotes and supports citizen science-based climate action behavioural change within six distinct Irish and Welsh cross-border coastal communities. It explores whether there are any parallels with how we can adapt to climate change now, with a focus on the resilience and innovation evidenced within Waterford's earliest settlements during and after South East Ireland's earlier climate change periods. The design research and the filmic documentation of archaeological and geological surveys is employed to map the story of these early post-glacial settlements 10,000 years ago along the Waterford Estuary. Interwoven through this mapping is a demonstration of how those living along the Estuary are preserving their maritime heritage through citizen science led engagement and community initiatives.

Adding a deep resonance to the research project, singular to Waterford, a new vision is called for; an acknowledgement of Waterford City and its Estuary as an area of unique conservation and growth and a recognition of this much travelled waterway as a designated and protected cultural landscape. A successful transdisciplinary approach creates a rich and accessible resource towards recognising the Estuary's cultural and marine heritage in city planning for the future. In so doing, it broaches the so-called rural-urban divide, adds to the global community of practice and allows for reflection on how urban planning can learn from our past in this context.

Mixed methods research (MMR) represents an alternative methodological approach, combining qualitative and quantitative research styles, and enabling researchers to explore complex phenomena in detail. This chapter provides a critical view of mixed methods research and its application in social science research, with examples from tourism and hospitality used to guide those aiming to undertake mixed-methods research projects. The chapter provides insight into the characteristics of MMR, distinguishing it from a multi-method approach. It also provides a detailed explanation of different MMR designs and highlights the advantages and challenges of adopting a mixed-methods approach. Moreover, the chapter discusses approaches to analysis which are pivotal to MMR design. Finally, the chapter concludes with recommendations for researchers hoping to adopt a mixed-methods approach.

Significant advances in digital technologies impact both organisations and knowledge workers alike. Organisations are now able to effectively analyse significant amounts of data, while accomplishing actionable insight and data-driven decision-making through knowledge workers that understand and manage greater complexity. For decision-makers to be in a position where sufficient information and data-driven insights enable them to make informed decisions, they need to better understand fundamental constructs that lead to the understanding of deep knowledge and wisdom. In an attempt to guide organisations in such a process of understanding, this research study focuses on the design of an organisational transformation framework for data-driven decision-making (OTxDD) based on the collaboration of human and machine for knowledge work. The OTxDD framework was designed through a design science research approach and consists of 4 major enablers (data analytics, data management, data platform, data-driven organisation ethos) and 12 sub-enablers. The OTxDD framework was evaluated in a real-world scenario, where after, based on the evaluation feedback, the OTxDD framework was improved and an organisational measurement tool developed. By considering such an OTxDD framework and measurement tool, organisations will be able to create a clear transformation path to data-driven decision-making, while applying the insight from both knowledge workers and intelligent machines.

Rather than organize as traditional firms, many of today’s companies organize as platforms that sit at the nexus of multiple exchange and production relationships. This chapter considers a most basic question of organization in platform contexts: the choice of boundaries. Herein, I investigate how classical economic theories of firm boundaries apply to platform-based organization and empirically study how executives made boundary choices in response to changing market and technical challenges in the early mobile computing industry (the predecessor to today’s smartphones). Rather than a strict or unavoidable tradeoff between “openness-versus-control,” most successful platform owners chose their boundaries in a way to simultaneously open-up to outside developers while maintaining coordination across the entire system.

This chapter conceptualizes computational methods across three related, yet distinct approaches: (1) Social Simulation, (2) Data Science, and (3) Big Data. Group communication research is then situated and reviewed along these three lines of research. Although some areas have considerable visibility (e.g., network analysis, text mining), some areas are less visible in group communication research (e.g., Social Simulation, Big Data designs). The chapter concludes with suggestions for issues regarding reliability, validity, and ethics.