Data-Driven & Emerging Technologies


Due to global distributions of sourcing and production, changing customer purchasing patterns and increasing penetration of e-commerce, supply chain structures and processes complexify and are becoming increasingly diverse. The underlying technological developments are rapidly changing how we make decisions and perform logistics operations. Data-Driven & Emerging Technologies (DD&ET) such as Internet of Things (IoT), Big Data, advanced robotics, 3D printing, among others are shaping the future of several industries and their supply chains. However, emerging technologies and new supply chain strategies, especially in the Latin American context with its fragmentation typical of emerging markets, will not be easily adopted for a variety of interrelated challenges. We will address these challenges through three dimensions: the technical, the applicative, and the socio-technical. First, it is crucial to investigate what emerging technologies and data sources can be viably adopted in the Latin-American context given, for example, specific economic and infrastructure constraints. Second, to fully harness the inherent potentials of DD&ET, we need to understand what application areas hold the biggest potentials for overcoming the mentioned fragmentations allowing to create regionally transferable technologies and applications. And third, it will be essential taking into considerations technical characteristics and design strategies aware of existing socio-technical barriers toward the adoption of DD&ET.

Research Goal

This regional research track aims to build data-driven decision making tools and to investigate how to leverage the potentials of emerging technologies to promote faster, smarter logistics and business models that benefit all stakeholders within supply chains.

Research Questions

Given the social, economic and cultural context of Latin America it can be safely assumed that data-driven decision making tools and emerging technologies will not be embraced, adopted and utilized in the very same way such technologies will perform in already highly technologized markets in other parts of the world. We therefore frame our research questions along three dimensions.

1. The technological dimension

Considering a context of lower economical purchasing power, less incentives for technologization due to cheaper labour and lower levels of industrialization will inform the viability of emerging technologies to impact Latin America. We therefore need to ask:

What data-driven and emerging technologies promise viability to positively transform current SCM and logistics operations in Latin America?

2. The applicational dimension

To overcome the fragmentation of the Latin American industry and to best leverage intellectual and economic investments in technologies it is of strategic importance to identify data-driven tools and emerging technologies that can find wide use and provide a significant value. We therefore need to ask:

What SCM and logistics application areas will benefit the most from DD&ET and provide transferability across the region?

3. The socio-cultural dimension

The ways in technologies change the work responsibilities and interactions of people and the level to which the logical structure of a decision-making tool corresponds to decision-making strategies of people will directly impact the success of a technology. We therefore need to ask:

What design strategies and characteristics are fundamental for DD&ET to overcome socio-cultural barriers for their adoption?

In summary, we will investigate DD&ET for the Latin American context to provide assessments, theories, implementations and recommendations that promote viability, transferability and adoptability of DD&ET.