Managing Disruptions and the Ripple Effect in Digital Supply Chains: Empirical Case Studies

Author(s):  
Ajay Das ◽  
Simone Gottlieb ◽  
Dmitry Ivanov
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings COVID-19 has had a dramatic and damaging effect on supply chains and distributors. This briefing considers why, and what strategies there may be to cope. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.


Glimpse ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 70-75
Author(s):  
Tirtha Prasad Mukhopadhyay ◽  

In this article, the author seeks to understand how any information society generates clusters of information that act to secure and reinforce ecologies of consumption for media conglomerates and its circle of consumers. Empirical case studies would show that news information may not be based in the larger realities of all the players involved. Societies may be described in such situations as desiring their ends by means of segmented branching, but more empirically, by imperatives of survival and growth. Pseudology comprise the only sustaining principle of discourse for such a world immersed and fragmented by its local interests and their recognizable patterns of behavior as they are retrospectively conditioned by media.


Author(s):  
Malek Sarhani ◽  
Abdellatif El Afia

Reliable prediction of future demand is needed to better manage and optimize supply chains. However, a difficulty of forecasting demand arises due to the fact that heterogeneous factors may affect it. Analyzing such data by using classical time series forecasting methods will fail to capture such dependency of factors. This chapter addresses these problems by examining the use of feature selection in forecasting using support vector regression while eliminating the calendar effect using X13-ARIMA-SEATS. The approach is investigated in three different case studies.


Author(s):  
Sumeet Gupta ◽  
Tushar Agrawal ◽  
Priyanka Jain ◽  
Dolly Jaisinghani ◽  
Ritika Rathi

This chapter presents several case studies of the multilayered system in India and shows how the prevalent distribution system preclude any means of cost reduction and making these supply chains efficient. Supply chains of perishable goods, electronic products, FMCG products and Pharmaceutical products are discussed in this chapter. Each of these supply chains present unique challenges and issues that need attention. The three main objectives in these studies are to understand the distribution systems as well as cost economics of the supply chains, identify potential conflicts and issues in their distribution system, and to study the effect of macro-environment on the distribution system. Apart from these objectives, these cases are also meant to prepare those venturing into such supply chains to come up with efficient solutions for improving these supply chains.


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