PurposeUsing the constructal law of physics this study aims to provide guidance to future scholarship on global supply chain management. Further, through two case studies the authors are developing, the authors report interview findings with two senior VPs from two multi-national corporations being disrupted by COVID-19. This study suggests how this and recent events will impact on the design of future global supply chains.Design/methodology/approachThe authors apply the constructal law to explain the recent disruptions to the global supply chain orthodoxy. Two interviews are presented from case studies the authors are developing in the USA and UK – one a multi-national automobile parts supplier and the other is a earth-moving equipment manufacture. Specifically, this is an exploratory pathway work trying to make sense of the COVID-19 pandemic and its impact on supply chain scholarship.FindingsAdopting the approach of Bejan, the authors believe that what is happening today with COVID-19 and other trade disruptions such as Brexit and the USA imposing tariffs is creating new obstacles that will redirect the future flow of supply chains.Research limitations/implicationsIt is clear that the COVID-19 response introduced a bullwhip effect in the manufacturing sector on a scale never-before seen. For scholars, the authors would suggest there are four pathway topics going forward. These topics include: the future state of global sourcing, the unique nature of a combined “demand” and “supply shortage” bullwhip effect, the resurrection of lean and local production systems and the development of risk-recovery contingency strategies to deal with pandemics.Practical implicationsSupply chain managers tend to be iterative and focused on making small and subtle changes to their current system and way of thinking, very often seeking to optimize cost or negotiate better contracts with suppliers. In the current environment, however, such activities have proved to be of little consequence compared to the massive forces of economic disruption of the past three years. Organizations that have more tightly compressed supply chains are enjoying a significant benefit during the COVID-19 crisis and are no longer being held hostage to governments of another country.Social implicationsAn implicit assumption in the press is that COVID-19 caught everyone by surprise, and that executives foolishly ignored the risks of outsourcing to China and are now paying the price. However, noted scholars and epidemiologists have been warning of the threats of pandemics since the severe acute respiratory syndrome (SARS) virus. The pundits would further posit that in their pursuit of low-cost production, global corporations made naive assumptions that nothing could disrupt them. Both the firms the authors have interviewed had to close plants to protect their workforce. It was indicated in the cases the authors are developing that it is going to take manufacturers on average one month to recover from 4–6 days of disruption. These companies employ many thousands of people, and direct and ancillary workers are now temporarily laid off and face an uncertain future as/when they will recover back to normal production.Originality/valueUsing the constructal law of physics, the authors seek to provide guidance to future scholarship on global supply chain management. Further, through two case studies, the authors provide the first insight from two senior VPs from two leading multi-national corporations in their respective sectors being disrupted by COVID-19. This study is the first indication to how this and recent disruptive events will impact on the design of future global supply chains. Unlike the generic work, which has recently appeared in HBR and Forbes, it is grounded in real operational insight.

This discussion paper aims to set out the key challenges and opportunities emerging from distributed manufacturing (DM). We begin by describing the concept, available definitions and consider its evolution where recent production technology developments (such as additive and continuous production process technologies), digitisation together with infrastructural developments (in terms of IoT and big-data) provide new opportunities.To further explore the evolving nature of DM, the authors, each of whom are involved in specific applications of DM research, examined within a workshop environment emerging DM applications involving new production and supporting infrastructural technologies. This paper presents these generalizable findings on DM challenges and opportunities in terms of products, enabling production technologies, and the impact on the wider production and industrial system. Industry structure and location of activities are examined in terms of the democrat impact on participating network actors.The paper concludes with a discussion on the changing nature of manufacturing as a result of DM, from the traditional centralised, large scale, long lead-time forecast driven production operations, to a new DM paradigm where manufacturing is a decentralised, autonomous near end-user driven activity. A forward research agenda is proposed that considers the impact of DM on the industrial and urban landscape.

BackgroundThere is mixed evidence to support current ambitions for mobile health (mHealth) apps to improve chronic health and well-being. One proposed explanation for this variable effect is that users do not engage with apps as intended. The application of analytics, defined as the use of data to generate new insights, is an emerging approach to study and interpret engagement with mHealth interventions.ObjectiveThis study aimed to consolidate how analytic indicators of engagement have previously been applied across clinical and technological contexts, to inform how they might be optimally applied in future evaluations.MethodsWe conducted a scoping review to catalog the range of analytic indicators being used in evaluations of consumer mHealth apps for chronic conditions. We categorized studies according to app structure and application of engagement data and calculated descriptive data for each category. Chi-square and Fisher exact tests of independence were applied to calculate differences between coded variables.ResultsA total of 41 studies met our inclusion criteria. The average mHealth evaluation included for review was a two-group pretest-posttest randomized controlled trial of a hybrid-structured app for mental health self-management, had 103 participants, lasted 5 months, did not provide access to health care provider services, measured 3 analytic indicators of engagement, segmented users based on engagement data, applied engagement data for descriptive analyses, and did not report on attrition. Across the reviewed studies, engagement was measured using the following 7 analytic indicators: the number of measures recorded (76%, 31/41), the frequency of interactions logged (73%, 30/41), the number of features accessed (49%, 20/41), the number of log-ins or sessions logged (46%, 19/41), the number of modules or lessons started or completed (29%, 12/41), time spent engaging with the app (27%, 11/41), and the number or content of pages accessed (17%, 7/41). Engagement with unstructured apps was mostly measured by the number of features accessed (8/10, P=.04), and engagement with hybrid apps was mostly measured by the number of measures recorded (21/24, P=.03). A total of 24 studies presented, described, or summarized the data generated from applying analytic indicators to measure engagement. The remaining 17 studies used or planned to use these data to infer a relationship between engagement patterns and intended outcomes.ConclusionsAlthough researchers measured on average 3 indicators in a single study, the majority reported findings descriptively and did not further investigate how engagement with an app contributed to its impact on health and well-being. Researchers are gaining nuanced insights into engagement but are not yet characterizing effective engagement for improved outcomes. Raising the standard of mHealth app efficacy through measuring analytic indicators of engagement may enable greater confidence in the causal impact of apps on improved chronic health and well-being.

While the literature highlights a wide variety of potential citizen science project outcomes, no prior studies have systematically assessed performance against a comprehensive set of criteria. Our study is the first to propose a novel framework for assessing citizen science projects against multiple dimensions of success. We apply this framework to a sample of projects forming part of the online Zooniverse platform and position these projects against a 'success matrix' measuring both contribution to science and public engagement levels relative to others in the sample. Our results indicate that better performing projects tend to be those which are more established, as well as those in the area of astronomy. Implications for citizen science practitioners include the need to consider the impact of core competencies on project performance, as well as the importance of relationships between the central organisation and science teams.

The fourth Industrial Revolution is driving the creation of fully connected ecosystem. Organizations are now reshaping their strategies to become fully transparent, including their supply chain management. The area of supply chain digitalisation is starting to attract growing attention; however, its research status remains unclear. We set out this study to understand what constitutes the underlying structure of its research, what topics have been investigated, what areas need further attention, how the existing literature can be classified, and how the discipline can move forward. We applied a mixed-method approach using both quantitative and qualitative techniques to achieve this. A bibliometric analysis of 331 articles with 12709 references was first conducted to discover the underlying knowledge foundation and evolution of supply chain digitalisation, current attention, and grouping of research into distinct clusters. Further, a qualitative review through content analysis was performed to interrogate our quantitative results. Research implications, and directions for future research are also discussed.