Studying the Inter-Relationship amongst the Barriers to Implementation of Analytics in Manufacturing Supply Chains

Abstract

With every economy becoming globalized , operations of global manufacturing and logistics teams are becoming complex and challenging. Delayed shipments, inefficient plants, inconsistent suppliers can stall and delay the shipments thereby increasing the company's supply chain costs. Managing demand volatility and cost fluctuations in supply chain and making it visible globally are some of the challenges which supply chain managers are facing. As per Accenture report , only up to 17 % of the supply chain managers are comfortable implementing analytics to supply chain functions which means despite being a need for these supply chain managers and despite being the fact that analytics can serve as their problem solver , it cannot , and still has a long way to go to prove itself in this domain. The required foundation is still in its nascent stage. This research work thus focuses on studying and exploring the barriers to implementation of analytics or big data analytics to manufacturing supply chains. After exploring , it further study the interrelationship amongst them with the help of Interpretive Structural Modelling (ISM) methodology .

Price sensitivity, government green interventions, and green product availability triggers intention toward buying green products

“…The present study thus is an endeavor to explore and establish factors triggering the intention of consumers toward buying green products through the lenses of the TPB and the TCV. It is designed to be done with a larger sample, reaching out to maximum groups across India, as compared to studies conducted mostly outside India or on a localized set of consumers in India (Aggarwal et al, 2018; Jaiswal & Kant, 2018; Kautish et al, 2019; Paul et al, 2016). The study intends to examine the moderating effect of external variables like price sensitivity (PS), green product availability (GPA), government green interventions (GGI), and demographic factors on the GBI of Indian consumers.…”