By En Hao Lim
While aggregate demand (AD) has recovered to pre-pandemic levels with Central Bank quantitative easing and unleashed pent-up demand [1] , production chain disruptions (PCDs) remain prevalent. This essay analyses its varying impacts on consumers, firms, governments, and financial institutions, recommending optimal responses accordingly.
PCDs have incited scarcity in critical factors of production (638% jump in key material shortages[2]), forcing firms to bid higher prices for inputs, raising cost of production by 10-40% [3] and causing supply to plummet (S0→S1). Given low price elasticity of demand for consumer goods like food/technologies due to heavy reliance during global lockdowns [4], expenditure/revenue increases (0P0E0Q0→0P1E1Q1), hurting consumers but benefiting producers.
However, cost savings reaped from internal economies of scale means most firms operate under an oligopolistic market structure. Despite a rise in marginal cost (MC0→MC1), given firms’ kinked demand curve, profit-maximizing prices and output remain at Pe and Qe.
A payoff matrix between competing oligopolists further demonstrates such price rigidity - the dominant strategy of charging lower prices means that upon reaching a Nash equilibrium, prices are unlikely to change. Yet, consumer prices have only surged alongside PCDs. The Grossman-Hart-Moore model of incomplete contracts resolves this. Asset ownership increases investment incentives [5], spurring vertical integration - especially amongst complementary assets [6] - to maximize efficiency when PCDs drive up external market transaction costs.
The 300% increase in merger & acquisitions [7] with global M&A values topping 5.63 trillion [8] exemplifies such integration and market consolidation.
Contrasting perfectly competitive firms with absolute monopolies, heightened market dominance undeniably leads to higher prices (Ppc→Pm) for consumers.
Secondly, the initial Nash equilibrium fails to account for rising costs across both firms. Utilizing the Bertrand competition model, an increase in MC shifts the respective firms’ Reaction Function (RF), obtaining a Nash equilibrium of higher prices.
The Cournot competition model displays similar outcomes - uniformly higher MC lowers their respective RFs, leading to lower output and by Law of Demand, higher prices. Hence, consumers are undeniably hurt by PCD-induced price surges, whereas the impact on firms varies based on the extent of cost increases. To further examine this, we turn to another major source of PCDs slowing international trade - labour shortages [9].
Despite job vacancies rising 33% from Q4 2019, labour shortages persist [11].
To model the impacts of COVID-induced labour disruptions, consider employees’ best response function: 𝐵𝑅𝐹 = 𝐹(𝑤, 𝑎, 𝑏, 𝑑), 𝑤h𝑒𝑟𝑒 𝑤 = 𝑤𝑎𝑔𝑒, 𝑎 = 𝑑𝑖𝑠𝑢𝑡𝑖𝑙𝑖𝑡𝑦 𝑜𝑓 𝑒𝑓𝑓𝑜𝑟𝑡, 𝑏 = 𝑢𝑛𝑒𝑚𝑝𝑙𝑜𝑦𝑚𝑒𝑛𝑡 𝑏𝑒𝑛𝑒𝑓𝑖𝑡𝑠, 𝑑 = 𝑒𝑚𝑝𝑙𝑜𝑦𝑚𝑒𝑛𝑡 𝑑𝑢𝑟𝑎𝑡𝑖𝑜𝑛 With 3 million workers fearful of COVID-19 and excess mortality increasing 60% [12] (a) has risen. Meanwhile, generous unemployment benefits - US$300 weekly supplements and US$1400 of stimulus checks [13] - elevated (b). In contrast, (d) has fallen as risk-averse businesses seek short-term employment contracts instead [14].
Given that ∂𝐵𝑅𝐹/∂𝑎 < 0, ∂𝐵𝑅𝐹/∂𝑏 < 0, ∂𝐵𝑅𝐹/∂𝑑 > 0 , BRFi falls to BRFu - isocost curve tangent to BRF falls, signaling lower effort/wage ratios and thus, productivity. Reservation wage increases (A→B), raising the aggregate wage-setting curve, while shortage-induced competition for workers raises the price-setting curve. At the new equilibrium, wages are higher (Wi→Wn), but employment falls (Ei→En).
Since labour constitutes up to 70% of firms’ operating costs [15]and remains vital to modern supply chains [16], lower productivity-to-wage levels arising from labour-related PCDs incur substantial costs to firms. Meanwhile, despite households receiving higher wages (Wn), greater unemployment (En) alongside already surging prices reduces net purchasing power.
How should firms respond to and guard against PCD-induced surge in costs?
To temper existing shocks, besides sourcing alternative inputs, firms should maximise short-term production scheduling agility via strategic product prioritization [17]. By expressing its products’ marginal profit curves as functions with approximated probability parameters and utilizing nonlinear programming [18], firms can determine the profit-maximizing output combination given varying sets of material constraints, guaranteeing efficient production execution despite unpredictably erratic supply chains. With regards to labour costs, as 𝑃 = 𝑃𝐿 − 𝑊, where P=profits, PL=product of labour, W=wages, when (W) rises, firms must increase efficiency, boosting (PL) to maintain (P). Active monitoring ensures that firms identify inefficiencies and react accordingly, implementing stopgap measures like re-organising warehouses and optimizing purchase-order workflows. Firms can track aforementioned efficiency levels via Pettersson efficiency index [19]: 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 = 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 * [(1 − 𝐶𝑜𝑠𝑡𝑠)/𝑁𝑒𝑡 𝑆𝑎𝑙𝑒𝑠] while 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 = 𝑑𝑒𝑙𝑖𝑣𝑒𝑟𝑦 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛 * 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 * 𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑟 𝑠𝑎𝑡𝑖𝑠𝑓𝑎𝑐𝑡𝑖𝑜𝑛
In the long term, firms can invest in digital infrastructure to enhance resilience and prevent unexpected PCDs. Utilizing blockchain to map transactions along complex production chains enables transparent risk assessment [20], lowering costs by 45% [21]; incorporating internet-of-things via interconnected sensors feeds reliable, real-time data towards this decentralized, blockchain interface [22]; employing Artificial Intelligence within aforementioned mathematically programmed Decision Support Systems (DSS) boosts efficiency by 15% through Petri nets, multi-agent systems [23] and machine learning [24]. Simultaneously, investing in additive manufacturing technologies can boost profitability by 7% [25] and reduce reliance on international suppliers. By modeling Expected Total Cost (ETC) of investments as: 𝐸𝑇𝐶 = 𝑆𝑢𝑛𝑘 𝑐𝑜𝑠𝑡𝑠 + 𝐼𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 𝐹𝑎𝑖𝑙𝑢𝑟𝑒 𝐶𝑜𝑠𝑡𝑠 − 𝐶𝑜𝑠𝑡 𝑆𝑎𝑣𝑖𝑛𝑔𝑠 [26] and obtaining: δ 𝑤h𝑒𝑛 ∂/∂δ (𝐸𝑇𝐶) = 0, 𝑤h𝑒𝑟𝑒 δ = 𝑠𝑐𝑜𝑝𝑒 𝑜𝑓 𝑃𝐶𝐷 𝑣𝑜𝑙𝑎𝑡𝑖𝑙𝑖𝑡𝑦 𝑐𝑜𝑣𝑒𝑟𝑒𝑑 𝑏𝑦 𝑎 𝑔𝑖𝑣𝑒𝑛 𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 firms can approximate the optimal level of investment where profit is maximized.
Impact on governments and financial institutions
While unemployment rates have gradually recovered alongside the re-opening of economies[27] , boosting AD, PCDs continue to wreak havoc on 2 key macroeconomic indicators: economic growth and inflation rates.
Given exorbitant resource and labour costs for firms, Keynesian AS shifts left, leading to stagflation - shrinking GDP (Y0→Y1) despite price inflation (P0→P1).
Utilising Quah-Vahey’s AD-AS vector autoregression (VAR) model, cost-push supply shocks lead to approximately 13% increase in aggregate prices and 21% fall in GDP [28], reinforcing these disastrous impacts of PCDs.
To further examine long-term impacts on economic growth, consider the Solow-Swan model and Romer’s endogenous growth model: ∆𝐴 = 𝐹(𝐾𝑎, 𝐿𝑎, 𝐴) 𝑤h𝑒𝑟𝑒 𝐴 = 𝑒𝑥𝑖𝑠𝑡𝑖𝑛𝑔 𝑡𝑒𝑐h𝑛𝑜𝑙𝑜𝑔𝑦; 𝐾𝑎, 𝐿𝑎 = 𝑐𝑎𝑝𝑖𝑡𝑎𝑙, 𝑙𝑎𝑏𝑜𝑢𝑟 𝑖𝑛𝑣𝑒𝑠𝑡𝑒𝑑 𝑖𝑛 𝑡𝑒𝑐h𝑛𝑜𝑙𝑜𝑔𝑦
Given substantial capital withdrawals, net corporate reinvestment fell $726 billion between 2020 Q1-Q2 [29], lowering Ka, ∆A, and thus, overall production function. Meanwhile, a 12.4% increase in consumer panic buying [30] lowers savings rate and thus, investment curve. Assuming constant depreciation, long-run GDP would fall further (Y0→Y1).
Meanwhile, widening credit default swap spreads [31] amidst PCDs implies heightened corporate default risk due to uncertain profit margins and financial imbalances [32], prompting withdrawals of investments in firms (bonds, shares etc.) while elevating demand for real assets like gold. Given positive correlations between these speculative asset dealings and inflation [33], aggregate prices surge further, placing pressure on various financial institutions - private investors struggle to profit with weighted average cost of capital (WACC) rising due to higher implied risk, while Central Banks struggle to keep inflation below target levels of 2%.
How should governments and financial institutions respond to and guard against PCDs?
To temper the immediate impacts of PCDs, governments must ease port congestion by subsidizing material-handling equipment like push-back racks, increasing storage space by 25%-55% [34] , or installing “virtual gates” via Bluetooth Low-Energy sensors and cellular-based telematics platforms, boosting transparency within port management [35].
Given the interconnectivity of production chains [36], individual spikes in productivity create ripple benefits for entire ports. Hence, positive externalities generated by aforementioned equipment means Qs-Qm of under-installation in the free market. Targeted government subsidies shifts PMCm to PMCg, re-gaining ABC of welfare.
Moving forward, governments must actively monitor cyclical fluctuations to preemptively identify threats, preventing future PCDs. Two macroeconomic indicators can be utilised - total cyclical fluctuations (TCF) and good market unbalance (GMU). 𝑇𝐶𝐹 = 𝑌𝑑 + 𝑌𝑠 while 𝐺𝑀𝑈 = 𝑌𝑑 − 𝑌𝑠, 𝑤h𝑒𝑟𝑒 𝑌𝑑, 𝑌𝑠 = 𝑑𝑒𝑚𝑎𝑛𝑑 𝑎𝑛𝑑 𝑠𝑢𝑝𝑝𝑙𝑦 𝑐𝑜𝑚𝑝𝑜𝑛𝑒𝑛𝑡𝑠 𝑜𝑓 𝑜𝑢𝑡𝑝𝑢𝑡 𝑟𝑒𝑠𝑝𝑒𝑐𝑡𝑖𝑣𝑒𝑙𝑦 with components differentiated via matching effects on output and contrasting effects on price [37].
By inputting historical TCF and GMU data into structural VAR models, governments can extrapolate current trends to forecast imminent economic imbalances, enabling adoption of appropriate prevention measures. When projected TCF<0 and GMU>0, contractionary supply shocks are likely, serving as a warning signal.
Simultaneously, governments should encourage reshoring of production facilities via subsidies, upskilling programs and competition policies [38] ,preventing future PCDs. Utilizing scenario-driven stochastic simulations to model impacts of “grey rhino” events like COVID-19 [39], governments can weigh between potential benefits of preventing PCDs through reshoring and its costs of reduced comparative advantages, determining the optimal level of reshoring to support.
Finally, PCDs have resulted in 62% loss in finances [40], leaving firms scrambling for liquid cash [41]. Utilizing the Hicks-Hansen model, Liquidity-Money curve shifts left alongside higher liquidity preferences, prompting Central Banks to raise interest rates (i0→i1) . Moreover, consider Taylor’s rule: 𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑅𝑎𝑡𝑒 = 𝑁𝑒𝑢𝑡𝑟𝑎𝑙 𝑅𝑎𝑡𝑒 + 0. 5(𝐼𝑟 − 𝐼𝑒) + 0. 5(𝑌𝑟 − 𝑌𝑒), where Ir Ie represent current and ideal inflation rates, whereas Yr Ye represent current and ideal GDP growth.
Given PCD-induced surges in inflation rates reducing informativeness of prices, price-level elasticity of AD lowers (ADe→ADi) [42], translating to a significant increase in prices (P0→Pi) and smaller fall in output (Y0→Yi) when AS falls. Since Ir rises more than Yr falls, hiking interest rates would be the optimal response to this destructively cyclical nature of inflation. Meanwhile, despite WACC increasing, private investors can capitalize on lower equity prices to obtain greater returns once prices rebound in the long-term.
Conclusion PCDs, alongside other catastrophes like 2008’s financial crisis, have repeatedly called into question the legitimacy of economic analysis. Yet, as espoused by John Maynard Keynes, “it is better to be roughly right, than precisely wrong”. While economic theories and mathematical models may never predict outcomes perfectly, it is perhaps the closest we can attain as a guide for mankind.
Foot Notes
1 Dixon-Fyle, Sundiatu et. al. “The consumer demand recovery and lasting effects of COVID-19.” McKinsey Global Institute. March 17, 2021. Accessed November 15, 2021. https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/the-consumer-demand-recovery-an d-lasting-effects-of-covid-19 2 Burnson, Patrick. “Record-Breaking Supply Chain Disruptions and Supply Shortages.” Supply Chain Management Review. August 12, 2021. Accessed November 18, 2021. https://www.scmr.com/article/record_breaking_supply_chain_disruptions_and_supply_shortages 3 Leonard, Matt. “CPGs report higher supply chain costs with no signs of dropping this year.” Supply Chain Dive. March 16, 2021. Accessed November 16, 2021. https://www.supplychaindive.com/news/manufacturing-warehouse-cost-pandemic-covid-labor-amaz on-mckinsey-survey/596792/
4 López-Navarro, Jimena and Panezi, Argyri. “Our increased reliance on digital platforms during COVID-19 and beyond.” Lawahead. Accessed November 15, 2021. https://lawahead.ie.edu/our-increased-reliance-on-digital-platforms-during-covid-19-and-beyond/
5 Grossman, SJ and Hart, Oliver. “The Cost and Benefits of Ownership: A Theory of Vertical and Lateral Integration. Harvard DASH. 1986. https://dash.harvard.edu/bitstream/handle/1/3450060/Hart_CostsBenefits.pdf;jsessionid=25254A470A6E4815A7 32CC2D8E7EA9FF?sequence=4 6 Hart, Oliver and Moore, John. “Property Rights and the Nature of the Firm.” Harvard Dash. 1990. Accessed November 20, 2021. https://dash.harvard.edu/bitstream/handle/1/3448675/Hart_PropertyRights.pdf
7 Kooli, Chokri and Lock Son, Melanie. “Impact of COVID-19 on Mergers, Acquisitions & Corporate Restructurings”. MDPI. August 16, 2021. Accessed November 21, 2021. https://www.mdpi.com/2673-7116/1/2/8/htm 8 Barbaglia, Pamela, Sen, Anirban and Wu, Kane. “Global M&A activity smashes all-time records to top $5 trillion in 2021.” Reuters. December 21, 2021. Accessed December 22, 2021. https://www.reuters.com/markets/europe/global-ma-activity-smashes-all-time-records-top-5-trillion-2021-2021-12- 20/
9 Conerly, Bill. “The Labor Shortage Is Why Supply Chains Are Disrupted.” Forbes. July 7, 2021. Accessed November 23, 2021. https://www.forbes.com/sites/billconerly/2021/07/07/the-labor-shortage-is-why-supply-chains-are-disrupted/ 10 Williamson, Chris. “Global manufacturing subdued by supply constraints, but pressures from Delta wave show signs of easing.” IHS Markit. October 1, 2021. Accessed November 25, 2021. https://ihsmarkit.com/research-analysis/global-manufacturing-subdued-by-supply-constraints-but-pressures-from- delta-wave-show-signs-of-easing-oct21.html 11 Wolf, Michael. “The global labor shortage: How COVID-19 has changed the labor market.” Deloitte. August 23, 2021. Accessed November 22, 2021. https://www2.deloitte.com/xe/en/insights/economy/global-labor-shortage.html
12 Wolf, Michael. “The global labor shortage: How COVID-19 has changed the labor market.” Deloitte. August 23, 2021. Accessed November 22, 2021. https://www2.deloitte.com/xe/en/insights/economy/global-labor-shortage.html 13 Hansen, Sarah. “How Much Money You Will Get From Stimulus Checks, Unemployment Benefits And Everything Else Inside Biden's $1.9 Trillion Relief Bill.” Forbes. March 11, 2021. Accessed November 24, 2021. https://www.forbes.com/sites/sarahhansen/2021/03/11/how-much-money-you-will-get-from-stimulus-checks-une mployment-benefits-and-everything-else-inside-bidens-19-trillion-relief-bill/?sh=4815a753f3de 14 Baker, Mary. “9 Future of Work Trends Post-COVID-19.” Gartner. April 29 2021. Accessed November 24, 2021. https://www.gartner.com/smarterwithgartner/9-future-of-work-trends-post-covid-19
15 “The Biggest Cost of Doing Business: A Closer Look at Labor Costs.” Paycor. December 24, 2020. Accessed November 25, 2021. https://www.paycor.com/resource-center/articles/the-biggest-cost-of-doing-business-a-closer-look-at-labor-costs/ 16 Bustamante, Felipe et. al. “Navigating the labor mismatch in US logistics and supply chains.” McKinsey Global Institute. December 10, 2021. Accessed December 13, 2021. https://www.mckinsey.com/business-functions/operations/our-insights/navigating-the-labor-mismatch-in-us-logisti cs-and-supply-chains 17 Aryapadi, Manik et. al. “Ten steps retailers can take to shock-proof their supply chains.” McKinsey Global Institute. November 11, 2021. Accessed November 26, 2021. https://www.mckinsey.com/industries/retail/our-insights/ten-steps-retailers-can-take-to-shock-proof-their-supply-c hains 18 “Profit Maximization Via Nonlinear Programming.” Smartdrill Data Mining. Accessed November 26, 2021. https://smartdrill.com/pdf/Nonlinear%20Programming.pdf 19 Pettersson, Annelie. “Measurements of efficiency in a Supply chain.” November, 2008. Accessed November 28, 2021. https://www.diva-portal.org/smash/get/diva2:999780/FULLTEXT01.pdf
20 Min, Hokey. “Blockchain technology for enhancing supply chain resilience.” Kelley School of Business. 2018. Accessed November 29, 2021. https://fardapaper.ir/mohavaha/uploads/2021/07/Fardapaper-Blockchain-technology-for-enhancing-supply-chain-r esilience.pdf 21 Stackpole, Beth. “5 supply chain technologies that deliver competitive advantage.” MIT Sloan School of Management. February 14, 2020. Accessed December 1, 2021. https://mitsloan.mit.edu/ideas-made-to-matter/5-supply-chain-technologies-deliver-competitive-advantage 22 Deshpande, Vinayak and M. Swaminathan, Jayashankar. “Supply Shortages: Here to Stay? The Roles Government and Emerging Tech Should Be Playing.” Kenan Institute of Private Enterprise. September 15, 2021. Accessed December 1, 2021. https://kenaninstitute.unc.edu/kenan-insight/supply-shortages-here-to-stay -the-roles-government-and-emerging-tech-should-be-playing/ 23 Baryannis, George, Dani, Samir and Validi, Sahar. “Decision Support Systems and Artificial Intelligence in Supply Chain Risk Management.” Springer. February, 2019. Accessed December 3, 2021. https://www.researchgate.net/publication/329784099_Decision_Support_Systems_and_Artificial_Intelligence_in_ Supply_Chain_Risk_Management 24 Aeni, Samira et. al. “Application of Machine Learning in Supply Chain Management: A Comprehensive Overview of the Main Areas.” Hindawi. June 22, 2021. Accessed December 3, 2021. https://www.hindawi.com/journals/mpe/2021/1476043/ 25 Aryapadi, Manik et. al. “Ten steps retailers can take to shock-proof their supply chains.” McKinsey Global Institute. November 11, 2021. Accessed November 26, 2021. https://www.mckinsey.com/industries/retail/our-insights/ten-steps-retailers-can-take-to-shock-proof-their-supply-c hains 26 Hadidi, Laith A, Rawabdeh, Ibrahim. “Economic analysis for agility in manufacturing environment.” January, 2008. Accessed December 6, 2021. https://www.researchgate.net/publication/220170984_Economic_analysis _for_agility_in_manufacturing_environment
27 Rouse, Cecilia. “The Employment Situation in October.” The White House. November 5, 2021. Accessed December 3, 2021. https://www.whitehouse.gov/cea/written-materials/2021/11/05/the-employment-situation-in-october/
28 Aucremanne, Luc and Wouters, Raf. “A structural VAR approach to core inflation and its relevance for Monetary Policy.” Accessed December 5, 2021. https://www.bis.org/publ/bisp05_p7.pdf
29 “Net domestic investment: Private: Domestic business.” Fred Economic Data. Accessed December 7, 2021. https://fred.stlouisfed.org/series/W790RC1Q027SBEA 30 Barua, Akrur and Levin, David. “State of the US consumer: December 2021.” Deloitte. December 13, 2021. Accessed December 15, 2021. https://www2.deloitte.com/us/en/insights/economy/consumer-pulse/state-of-the-us-consumer.html 31 Rueda, Manuel. “Credit-Spread Behavior Throughout the Crisis.” MSCI. Accessed December 10, 2021. https://www.msci.com/insights-gallery/covid-19-impact-on-credit 32 Aramonte, Sirio and Avalos, Fernando. “Corporate credit markets after the initial pandemic shock.” BIS Bulletin. July 1, 2020. Accessed December 10, 2021. https://www.bis.org/publ/bisbull26.pdf 33 Pangannavar, Arjun Yallappa. “Manipulation Theory of Inflation: A Research Study on Components of General Price Rise.” November, 2014. Accessed December 13, 2021. https://www.researchgate.net/publication/270648 368_Manipulation_Theory_of_Inflation_A_Research_Study_on_Components_of_General_Price_Rise
34 “3 Advantages To Using Pushback Pallet Racking Solutions.” Advance. Accessed December 10, 2021. https://advancestorageproducts.com/3-advantages-to-using-pushback-pallet-racking-solutions/ 35 Stanton, Mark. “How Combating Port Congestion Can Impact Global Supply Chains.” Food Logistics. August 27, 2021. Accessed December 15, 2021. https://www.foodlogistics.com/transportation/ocean-ports-carriers/article /21602673/powerfleet-how-combating-port-congestion-can-impact-global-supply-chains 36 “Increasing interconnectivity of global supply chains drives business interruption risk and losses.” Continuity Central. December 14, 2021. Accessed December 17, 2021. https://www.continuitycentral.com/index.php/news/business-continuity-news/744-increasing-interconnectivity-of-gl obal-supply-chains-drives-business-interruption-risk-and-losses
37 Pagliacci, Carolina. “Are We Ignoring Supply Shocks? A Proposal for Monitoring Cyclical Fluctuations.” CEMLA. April, 2016. Accessed December 16, 2021. https://www.cemla.org/PDF/investigacion/inv-2016-11-21.pdf 38 Barbieri, Paolo et. al. “Post-pandemic reconfiguration from global to domestic and regional value chains: the role of industrial policies.” June 24, 2021. Accessed December 14, 2021. https://unctad.org/system/files/non-official-document/diaeia2021d2a3_en.pdf 39 Bezpalov, Valery V. et. al. “Supply Chain Management and Risk Management in an Environment of Stochastic Uncertainty (Retail).” MDPI. November 4, 2021. Accessed December 15, 2021. https://www.mdpi.com/2227-9091/9/11/197
40 Kolmar, Chris. “17 stunning supply chain statistics [2021]: Facts, figures and trends.” Zippia. September 28, 2021. Accessed December 17, 2021. https://www.zippia.com/advice/supply-chain-statistics/#:~:text=Between %202019%2D2020%2C%20overall%20supply,massive%2062%25%20loss%20in%20finances. 41 Alicke, Knut, Azcue, Xavier and Barriball, Edward. “Supply-chain recovery in coronavirus times—plan for now and the future.” McKinsey Global Institute. March 18, 2020. Accessed December 15, 2021. https://www.mckinsey.com/business-functions/operations/our-insights/supply-chain-recovery-in-coronavirus-times -plan-for-now-and-the-future
42 Ball, Laurence and Romer, David. “Supply-chain recovery in coronavirus times—plan for now and the future.” April, 2003. Accessed December 18, 2021. https://eml.berkeley.edu/~dromer/papers/jmcb03.pdf
Bibliography
Aeni, Samira et. al. “Application of Machine Learning in Supply Chain Management: A Comprehensive Overview of the Main Areas.” Hindawi. June 22, 2021. Accessed December 3, 2021. https://www.hindawi.com/journals/mpe/2021/1476043/
Alicke, Knut, Azcue, Xavier and Barriball, Edward. “Supply-chain recovery in coronavirus times—plan for now and the future.” McKinsey Global Institute. March 18, 2020. Accessed December 15, 2021. https://www.mckinsey.com/business-functions/operations/our-insights/supply-chain-rec overy-in-coronavirus-times-plan-for-now-and-the-future
Aramonte, Sirio and Avalos, Fernando. “Corporate credit markets after the initial pandemic shock.” BIS Bulletin. July 1, 2020. Accessed December 10, 2021. https://www.bis.org/publ/bisbull26.pdf
Aryapadi, Manik et. al. “Ten steps retailers can take to shock-proof their supply chains.” McKinsey Global Institute. November 11, 2021. Accessed November 26, 2021. https://www.mckinsey.com/industries/retail/our-insights/ten-steps-retailers-can-take-to- shock-proof-their-supply-chains
Aucremanne, Luc and Wouters, Raf. “A structural VAR approach to core inflation and its relevance for Monetary Policy.” Accessed December 5, 2021. https://www.bis.org/publ/bisp05_p7.pdf
Baker, Mary. “9 Future of Work Trends Post-COVID-19.” Gartner. April 29 2021. Accessed November 24, 2021.
https://www.gartner.com/smarterwithgartner/9-future-of-work-trends-post-covid-19
Ball, Laurence and Romer, David. “Supply-chain recovery in coronavirus times—plan for now and the future.” April, 2003. Accessed December 18, 2021. https://eml.berkeley.edu/~dromer/papers/jmcb03.pdf
Barbaglia, Pamela, Sen, Anirban and Wu, Kane. “Global M&A activity smashes all-time records to top $5 trillion in 2021.” Reuters. December 21, 2021. Accessed December 22, 2021. https://www.reuters.com/markets/europe/global-ma-activity-smashes-all-time-records-t op-5-trillion-2021-2021-12-20/
Barbieri, Paolo et. al. “Post-pandemic reconfiguration from global to domestic and regional value chains: the role of industrial policies.” June 24, 2021. Accessed December 14, 2021. https://unctad.org/system/files/non-official-document/diaeia2021d2a3_en.pdf
Barua, Akrur and Levin, David. “State of the US consumer: December 2021.” Deloitte. December 13, 2021. Accessed December 15, 2021. https://www2.deloitte.com/us/en/insights/economy/consumer-pulse/state-of-the-us-con sumer.html
Baryannis, George, Dani, Samir and Validi, Sahar. “Decision Support Systems and Artificial Intelligence in Supply Chain Risk Management.” Springer. February, 2019. Accessed December 3, 2021. https://www.researchgate.net/publication/329784099_Decision_Support_Systems_and _Artificial_Intelligence_in_Supply_Chain_Risk_Management
Bezpalov, Valery V. et. al. “Supply Chain Management and Risk Management in an Environment of Stochastic Uncertainty (Retail).” MDPI. November 4, 2021. Accessed December 15, 2021. https://www.mdpi.com/2227-9091/9/11/197
Burnson, Patrick. “Record-Breaking Supply Chain Disruptions and Supply Shortages.” Supply Chain Management Review. August 12, 2021. Accessed November 18, 2021. https://www.scmr.com/article/record_breaking_supply_chain_disruptions_and_supply_ shortages
Bustamante, Felipe et. al. “Navigating the labor mismatch in US logistics and supply chains.” McKinsey Global Institute. December 10, 2021. Accessed December 13, 2021. https://www.mckinsey.com/business-functions/operations/our-insights/navigating-the-la bor-mismatch-in-us-logistics-and-supply-chains
Conerly, Bill. “The Labor Shortage Is Why Supply Chains Are Disrupted.” Forbes. July 7, 2021. Accessed November 23, 2021. https://www.forbes.com/sites/billconerly/2021/07/07/the-labor-shortage-is-why-supply-c hains-are-disrupted/
Deshpande, Vinayak and M. Swaminathan, Jayashankar. “Supply Shortages: Here to Stay? The Roles Government and Emerging Tech Should Be Playing.” Kenan Institute of Private Enterprise. September 15, 2021. Accessed December 1, 2021. https://kenaninstitute.unc.edu/kenan-insight/supply-shortages-here-to-stay-the-roles-g overnment-and-emerging-tech-should-be-playing/
Dixon-Fyle, Sundiatu et. al. “The consumer demand recovery and lasting effects of COVID-19.” McKinsey Global Institute. March 17, 2021. Accessed November 15, 2021. https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/the-cons umer-demand-recovery-and-lasting-effects-of-covid-19
Grossman, SJ and Hart, Oliver. “The Cost and Benefits of Ownership: A Theory of Vertical and Lateral Integration. Harvard DASH. 1986. https://dash.harvard.edu/bitstream/handle/1/3450060/Hart_CostsBenefits.pdf;jsessioni d=25254A470A6E4815A732CC2D8E7EA9FF?sequence=4
Hadidi, Laith A, Rawabdeh, Ibrahim. “Economic analysis for agility in manufacturing environment.” January, 2008. Accessed December 6, 2021. https://www.researchgate.net/publication/220170984_Economic_analysis_for_agility_i n_manufacturing_environment
Hart, Oliver and Moore, John. “Property Rights and the Nature of the Firm.” Harvard Dash. 1990. Accessed November 20, 2021. https://dash.harvard.edu/bitstream/handle/1/3448675/Hart_PropertyRights.pdf
Hansen, Sarah. “How Much Money You Will Get From Stimulus Checks, Unemployment Benefits And Everything Else Inside Biden's $1.9 Trillion Relief Bill.” Forbes. March 11, 2021. Accessed November 24, 2021. https://www.forbes.com/sites/sarahhansen/2021/03/11/how-much-money-you-will-get-f rom-stimulus-checks-unemployment-benefits-and-everything-else-inside-bidens-19-trill ion-relief-bill/?sh=4815a753f3de “Increasing interconnectivity of global supply chains drives business interruption risk and losses.” Continuity Central. December 14, 2021. Accessed December 17, 2021.
https://www.continuitycentral.com/index.php/news/business-continuity-news/744-incre asing-interconnectivity-of-global-supply-chains-drives-business-interruption-risk-and-lo sses
Kolmar, Chris. “17 stunning supply chain statistics [2021]: Facts, figures and trends.” Zippia. September 28, 2021. Accessed December 17, 2021. https://www.zippia.com/advice/supply-chain-statistics/#:~:text=Between%202019%2D2 020%2C%20overall%20supply,massive%2062%25%20loss%20in%20finances.
Kooli, Chokri and Lock Son, Melanie. “Impact of COVID-19 on Mergers, Acquisitions & Corporate Restructurings”. MDPI. August 16, 2021. Accessed November 21, 2021. https://www.mdpi.com/2673-7116/1/2/8/htm
Leonard, Matt. “CPGs report higher supply chain costs with no signs of dropping this year.” Supply Chain Dive. March 16, 2021. Accessed November 16, 2021. https://www.supplychaindive.com/news/manufacturing-warehouse-cost-pandemic-covi d-labor-amazon-mckinsey-survey/596792/
López-Navarro, Jimena and Panezi, Argyri. “Our increased reliance on digital platforms during COVID-19 and beyond.” Lawahead. Accessed November 15, 2021. https://lawahead.ie.edu/our-increased-reliance-on-digital-platforms-during-covid-19-an d-beyond/
Min, Hokey. “Blockchain technology for enhancing supply chain resilience.” Kelley School of Business. 2018. Accessed November 29, 2021. https://fardapaper.ir/mohavaha/uploads/2021/07/Fardapaper-Blockchain-technology-fo r-enhancing-supply-chain-resilience.pdf
“Net domestic investment: Private: Domestic business.” Fred Economic Data. Accessed December 7, 2021. https://fred.stlouisfed.org/series/W790RC1Q027SBEA
Pagliacci, Carolina. “Are We Ignoring Supply Shocks? A Proposal for Monitoring Cyclical Fluctuations.” CEMLA. April, 2016. Accessed December 16, 2021. https://www.cemla.org/PDF/investigacion/inv-2016-11-21.pdf
Pangannavar, Arjun Yallappa. “Manipulation Theory of Inflation: A Research Study on Components of General Price Rise.” November, 2014. Accessed December 13, 2021. https://www.researchgate.net/publication/270648368_Manipulation_Theory_of_Inflatio n_A_Research_Study_on_Components_of_General_Price_Rise
Pettersson, Annelie. “Measurements of efficiency in a Supply chain.” November, 2008. Accessed November 28, 2021. https://www.diva-portal.org/smash/get/diva2:999780/FULLTEXT01.pdf
“Profit Maximization Via Nonlinear Programming.” Smartdrill Data Mining. Accessed November 26, 2021. https://smartdrill.com/pdf/Nonlinear%20Programming.pdf
Rouse, Cecilia. “The Employment Situation in October.” The White House. November 5, 2021. Accessed December 3, 2021. https://www.whitehouse.gov/cea/written-materials/2021/11/05/the-employment-situatio n-in-october/
Rueda, Manuel. “Credit-Spread Behavior Throughout the Crisis.” MSCI. Accessed December 10, 2021. https://www.msci.com/insights-gallery/covid-19-impact-on-credit
Stackpole, Beth. “5 supply chain technologies that deliver competitive advantage.” MIT Sloan School of Management. February 14, 2020. Accessed December 1, 2021. https://mitsloan.mit.edu/ideas-made-to-matter/5-supply-chain-technologies-deliver-com petitive-advantage
Stanton, Mark. “How Combating Port Congestion Can Impact Global Supply Chains.” Food Logistics. August 27, 2021. Accessed December 15, 2021. https://www.foodlogistics.com/transportation/ocean-ports-carriers/article/21602673/po werfleet-how-combating-port-congestion-can-impact-global-supply-chains
“The Biggest Cost of Doing Business: A Closer Look at Labor Costs.” Paycor. December 24, 2020. Accessed November 25, 2021. https://www.paycor.com/resource-center/articles/the-biggest-cost-of-doing-business-a- closer-look-at-labor-costs/
“3 Advantages To Using Pushback Pallet Racking Solutions.” Advance. Accessed December 10, 2021.
https://advancestorageproducts.com/3-advantages-to-using-pushback-pallet-racking-s olutions/
Williamson, Chris. “Global manufacturing subdued by supply constraints, but pressures from Delta wave show signs of easing.” IHS Markit. October 1, 2021. Accessed November 25, 2021. https://ihsmarkit.com/research-analysis/global-manufacturing-subdued-by-supply-const raints-but-pressures-from-delta-wave-show-signs-of-easing-oct21.html
Wolf, Michael. “The global labor shortage: How COVID-19 has changed the labor market.” Deloitte. August 23, 2021. Accessed November 22, 2021. https://www2.deloitte.com/xe/en/insights/economy/global-labor-shortage.html
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