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The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is: how could big data transform smart city transport operations? In answering this question the authors present initial results from a Markov study. However the authors also suggest caution in the transformation potential of big data and highlight the risks of city and organizational adoption. A theoretical framework is presented together with an associated scenario which guides the development of a Markov model.

A model with several scenarios is developed to explore a theoretical framework focussed on matching the transport demands (of people and freight mobility) with city transport service provision using big data. This model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services.

This modelling study is an initial preliminary stage of the investigation in how big data could be used to redefine and enable new operational models. The study provides new understanding about load sharing and optimization in a smart city context. Basically the authors demonstrate how big data could be used to improve transport efficiency and lower externalities in a smart city. Further how improvement could take place by having a car free city environment, autonomous vehicles and shared resource capacity among providers.

The research relied on a Markov model and the numerical solution of its steady state probabilities vector to illustrate the transformation of transport operations management (OM) in the future city context. More in depth analysis and more discrete modelling are clearly needed to assist in the implementation of big data initiatives and facilitate new innovations in OM. The work complements and extends that of Setia and Patel (2013), who theoretically link together information system design to operation absorptive capacity capabilities.

The study implies that transport operations would actually need to be re-organized so as to deal with lowering CO₂ footprint. The logistic aspects could be seen as a move from individual firms optimizing their own transportation supply to a shared collaborative load and resourced system. Such ideas are radical changes driven by, or leading to more decentralized rather than having centralized transport solutions (Caplice, 2013).

The growth of cities and urban areas in the twenty-first century has put more pressure on resources and conditions of urban life. This paper is an initial first step in building theory, knowledge and critical understanding of the social implications being posed by the growth in cities and the role that big data and smart cities could play in developing a resilient and sustainable transport city system.

Despite the importance of OM to big data implementation, for both practitioners and researchers, we have yet to see a systematic analysis of its implementation and its absorptive capacity contribution to building capabilities, at either city system or organizational levels. As such the Markov model makes a preliminary contribution to the literature integrating big data capabilities with OM capabilities and the resulting improvements in system absorptive capacity.

The application of digital twins to optimise operations and supply chain management functions is a bourgeoning practice. Scholars have attempted to keep pace with this development initiating a fast-evolving research agenda. The purpose of this paper is to take stock of the emerging research stream identifying trends and capture the value potential of digital twins to the field of operations and supply chain management.

In this work we employ a bibliometric literature review supported by bibliographic coupling and keyword co-occurrence network analysis to examine current trends in the research field regarding the value-added potential of digital twin in operations and supply chain management.

The main findings of this work are the identification of four value clusters and one enabler cluster. Value clusters are comprised of articles that describe how the application of digital twin can enhance supply chain activities at the level of business processes as well as the level of supply chain capabilities. Value clusters of production flow management and product development operate at the business processes level and are maturing communities. The supply chain resilience and risk management value cluster operates at the capability level, it is just emerging, and is positioned at the periphery of the main network.

This is the first study that attempts to conceptualise digital twin as a dynamic capability and employs bibliometric and network analysis on the research stream of digital twin in operations and supply chain management to capture evolutionary trends, literature communities and value-creation dynamics in a digital-twin-enabled supply chain.

The purpose of this paper is to explore how the sourcing process of the electric sports car sector is changing with respect to competitive advantage, required capabilities and emerging opportunism.

The case study data collection covered the period from January till August 2017, which implies a total period of eight months. The empirical analysis implies a sequence of 20 conducted interviews with senior managers, team leaders and operational employees from various organizational departments and functions within Company A, various suppliers and experts from the automobile industry as well as primary and secondary literature.

This work makes a contribution to the operations capability literature. It highlights the important role that sourcing will play to achieving strategic advantage in the electric sports car segment. Four key operational capabilities are emerging in the operating model. The first links to “capacity” and the ability of suppliers to be locally based so that they can deliver high-quality products and services in the minimum time (optimizing the “time-value” configuration). The second is the “design” of the supplier network. The third relates to “supplier management.” Finally, the fourth capability relates to the ability of the firm to “integrate” and “align” their marketing and IT planning processes with their sourcing process.

Throughout the adaption of a sourcing framework and its extension to consider operational capabilities, the authors have begun to answer the research question of how the sourcing process for the supply of new electric powertrain components is being transformed. These initial findings, the authors intend to expand with more advanced case study work with the firm that will involve empirical modeling of process efficiency and inventory management.

The work closes the gap regarding the need for practical application tools, designed for process managers, who are being confronted by turbulent, unpredictable and fast moving technological-driven market environments. Although the sourcing framework was developed to test the impact of the electric mobility trend, it can likewise be applied for the sourcing of components in other fast changing environments as well.

The paper raises the issues of the social role of the smart city planners in providing city spaces to enable the servicing of electric vehicles and to assist their production by developing the skills, capacity and capabilities of local city populations which will be needed to sustain and scale up any locally based operating model of electric vehicle production and servicing.

Although much has been written about the technological challenges of electric vehicles and the rise of new entrants such as Tesla to challenge the dominance of the sports car manufacturer’s very little work to data have explored the business-to-business (B2B) dimensions. The focus has been largely with the business-to-consumers (B2C) market.

Challenge-based learning (CBL) has gained acceptance as a contemporary and progressive teaching pedagogy that provides a holistic and inclusive experience to learners in higher education (HE) institutions. However, its lack of appeal to non-STEM subjects and the need for further development, particularly concerning improved approaches, have been recognized. It seems that CBL runs the risk of becoming a portmanteau pedagogy that blends aspects of problem-based learning, project-based learning, and situated learning, as opposed to its development as an effective pedagogy tool. This points to a lack of a formal implementation framework, code of practice, and standard procedures for its delivery. We argue that blending a design thinking (DT) pedagogy with CBL can potentially provide the stability that CBL currently lacks. At the same time, it also presents a more inclusive proposition to potential non-STEM audiences. Thus, in this chapter, we seek to interrogate the intersectionality between CBL and DT literature in the context of HE teaching and learning with a view of establishing CBL as a pedagogy in its own right. We attempt to achieve this by systematically analyzing the separate literature to reveal the synergies and common touchpoints.