Big data technologies (BDT) are the latest instalments in a long line of technological disruptions credited with advancing the field of supply chain management (SCM) from a purely clerical function ...to a strategic necessity. Yet, despite the wave of optimism about the utility of BDT in SCM, the origins of value in a BDT-enabled supply chain are not well understood. This study examines the generative mechanisms of value creation in such a supply chain by a two-pronged approach. First, we interrogate the theoretical raisons d'être of BDT in SCM. Second, we examine the evidence that support the value-added potential of BDT in SCM informed by extant empirical and quantitative studies (EQS). Taken together, our analyses reveal three key findings. First, in extending the dynamic capabilities perspective, we deduced that micro-founded rather than macro-founded studies tend to be more instructive to practice. Second, we discovered that the generative mechanisms of value in a BDT-enabled supply chain operate at the level of supply chain processes. And thirdly, we found that resilience and agility are the most important dynamic capabilities that have emerged from current BDT-enabled SCM research. Insights for policy, practice, theory, and future research are discussed.
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.
The fourth Industrial Revolution is driving the creation of a more connected ecosystem. Organizations are now re-shaping their strategies to become increasingly transparent, including their supply ...chain management (SCM). The area of supply chain digitalization is starting to attract growing attention; however, its research status remains unclear. We set out, in 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 12,709 references was first conducted followed by a qualitative content analysis. Results point at a tentative future research agenda featuring five paths: data science-enabled SCM, supply chain agility, humanizing manufacturing through digital manufacturing strategy, Omni-channel and Internet of Things, and resource-based view and beyond.
The growth of cities in the 21st century has put more pressure on resources and conditions of urban life. There are several reasons why the health-care industry is the focus of this investigation. ...For instance, in the UK various studies point to the lack of failure of basic quality control procedures and misalignment between customer needs and provider services and duplication of logistics practices. The development of smart cities and big data present unprecedented challenges and opportunities for operations managers; they need to develop new tools and techniques for network planning and control. Our paper aims to make a contribution to big data and city operations theory by exploring how big data can lead to improvements in transport capacity sharing. We explore using Markov models the integration of big data with future city (health-care) transport sharing. A mathematical model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services. The results from our analysis of 13 different sharing/demand scenarios are presented. A key finding is that the probability for system failure and performance variance tends to be highest in a scenario of high demand/zero sharing.
Average annual percentage rates of change (APR) in maple syrup prices (average gallon equivalent price in the United States) in seven northeastern United States and their aggregated region were ...determined for the years 1916 to 2012. The price trend lines were then compared on state-by-state and region-by-state bases. Maple syrup prices across all states and the region as a whole were increasing nominally at significant average annual rates. Nominal APRs ranged from 3.42 percent for Maine to 4.13 percent for New Hampshire, with the price in the combined region increasing at a rate of 3.96 percent annually. Real prices (discussed in 2012 constant dollars) were appreciating at significant annual rates in all areas except Maine. Real APRs ranged from 0.46 percent for Maine to 1.12 percent for New Hampshire, and the regional price was increasing at 0.95 percent annually. Whereas the region's all-time high price of $40.38 was obtained nominally in 2008, the real price actually reached its highest point in 1987 ($53.89). Two other real price peaks were observed regionally: 1947 ($41.17) and 1972 ($45.31). No differences in trend line intercepts and slopes were found across the region. Obtaining price information for any one location has historically provided producers and processors a reasonable expectation of market activities occurring in the greater region.
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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).
Social implications
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.
Originality/value
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.
This editorial article provides an overview of the scope, aims and objectives of the SI. It also outlines the key categorising themes which have been used to organise the eight papers selected for ...publication.
The notion of smart cities is growing in prominence in the digital economy. The integration of urban infrastructures with information and communication technologies enables the development of new ...operations models. Digitised infrastructures offer opportunities for public and private organisations to design and deliver more customer-centric products or services, particularly for those that require geographical proximity with consumers in the online to offline (O2O) context. A framework is developed and used to analyse three case examples. These cases illustrate the emergence of new operations models and, demonstrate how smart cities are redefining the characteristics of operations models around their scalability, analytical output and connectivity. We also explore the feasibility, vulnerability and acceptability of each new operation. This paper contributes to our understanding of how smart cities can potentially transform operational models, and sets out a research agenda for operations management in smart cities in the digital economy.
PDF
