Table 1.
Final list of projections.
| Technology | ID | Projection | Category |
|---|---|---|---|
| Big Data Analytics (BDA) | 1.1 | BDA have enabled de-centralization of decision-making processes in supply networks and have supported the growth of micro-retailing, such as “nanostores”. | Benefits of using the technology |
| 1.2 | The application of BDA has increased order frequency for B2B customers. | Impacts on stakeholders | |
| 1.3 | The market share of same day delivery services is higher due to more precise demand forecasting supported by BDA. | Impacts on stakeholders | |
| 1.4 | At an operational level, Big Data is used for supporting interaction between final customers and Logistics Service Providers (LSP) – e.g. Real time coordination with drivers-. | Benefits of using the technology | |
| Crowd Logistics | 2.1 | Acceptability by customer (trust, safety, and security) is one of the main barriers blocking the adoption of crowd logistics solutions. | Barriers to the implementation |
| 2.2 | For e-commerce home-deliveries, traditional delivery vans are still preferred to crowd-logistics due to their more efficient use of the vehicle (i.e. delivery vans have higher load factors). | Impacts on stakeholders | |
| 2.3 | Crowd logistics is better suited in nonstandard non-scheduled deliveries (groceries, flowers, etc.) and in less dense (i.e. rural) environments. | Benefits of using the technology | |
| 2.4 | Crowd logistic services are economically viable only in high demand areas. | Enabling factors | |
| 2.5 | Crowd logistics does not provide environmental benefits if associated with private cars. | Impacts on stakeholders | |
| 2.6 | Crowd-logistics services negatively impacts the level of salaries for last-mile professional drivers. | Impacts on stakeholders | |
| 2.7 | Crowd-logistics ensures the same level of service even though the carriers are, usually, not trained professionals. | Benefits of using the technology | |
| Drones | 3.1 | Urban drone deliveries are economically viable only if paired with centralized urban fullfilment and/or consolidation centres. | Enabling factors |
| 3.2 | To support the adoption of drone-based delivery, how important it has been to overcome the following issues: [Lack of dedicated regulation frameworks.] | Barriers to the implementation | |
| 3.3 | To support the adoption of drone-based delivery, how important it has been to overcome the following issues: [Social acceptance -e.g. privacy, surveillance concerns-] | Barriers to the implementation | |
| 3.4 | To support the adoption of drone-based delivery, how important it has been to overcome the following issues: [Technological issues -e.g.range, capacity, resistance to extreme weather, landing capabilities, safety, advanced navigation and coordination algorithms-] | Barriers to the implementation | |
| 3.5 | Drone-based deliveries are enabled by being integrated with delivery vans (both autonomous and manned) for the first leg of the journey (Outward journey). | Enabling factors | |
| 3.6 | Drone-based delivery are better suited in limited scenarios such as rural deliveries, medical deliveries or emergency relief. | Benefits of using the technology | |
| 3.7 | The adoption of drone-based delivery reduces the size of last-mile vehicle fleets and in turn the number of required drivers. | Benefits of using the technology | |
| Intelligent Transportation Systems (ITS) | 4.1 | The number of freight delivery bays have increased, and their locations and size are optimized. In addition, delivery bay monitoring and booking systems have been deployed and enforced (i.e. ensuring that illegal behaviors are fined). | Impacts on stakeholders |
| 4.2 | Public authorities are focusing their efforts on enforcing access restrictions such as Low Emission Zones and congestion charges through ITS systems (e.g. automated plate reading and electronic payments). | Impacts on stakeholders | |
| 4.3 | ITS implementations aim at gathering reliable, precise, deep and broad data on last-mile systems -e.g. number of vehicles, volumes transported, load factors, traffic flows etc.-. | Benefits of using the technology | |
| Low Emission Vehicles | 5.1 | Adoption of EVs is still related to the implementation of public policies such as: access restrictions and economic incentives. | Enabling factors |
| 5.2 | Only LSPs with high consumer density are able to use cargo bikes efficiently. | Enabling factors | |
| Parcel Lockers | 6.1 | Parcel Lockers diffusion has reached a plateau due to the investment costs needed to reach all customers. | Barriers to the implementation |
| 6.2 | Local administrations allow parcel lockers to be installed on public space only if they are accessible via public transportation. | Enabling factors | |
| 6.3 | Only LSPs with high consumer density are able to use parcel lockers efficiently. | Enabling factors | |
| 6.4 | Shared parcel lockers are supported by LSPs. | Impacts on stakeholders | |
| 6.5 | Parcel Locker systems have been associated with automobile dependent travel behavior. | Impacts on stakeholders | |
| 6.6 | Parcel Lockers are more likely to be installed in urban rather than suburban areas. | Impacts on stakeholders | |
| 6.7 | Parcel Lockers are more likely to be installed in high density (i.e. urban) rather than low density (i.e. rural) areas. | Impacts on stakeholders | |
| Internet of Things (IoT) and connected devices | 7.1 | The main barrier to the increase of communication and coordination mechanisms between carriers and customers is the customers' inertia to technology adoption. | Barriers to the implementation |
| 7.2 | Acceptability by customers (trust, safety, and security) is one of the main barriers blocking the adoption of IOT-based logistics services (e.g. smart locks, digital keys for in-car delivery etc.) | Barriers to the implementation | |
| 7.3 | Real-time data from multiple sources (e.g. traffic, road disruptions) are more available and thus enable a more widespread usage of dynamic vehicle routing algorithms | Enabling factors |